RUA: Evidence-Based Practice Change Group Project

Fuller_Andrew_201909_MSc1.pdf

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Electronic Medication Administration Records and Barcode Medication Administration to Support Safe Medication Practices in Long-term Care Facilities

Andrew Fuller

A thesis submitted in partial fulfillment of the requirements for the degree of

Master of Science

in Pharmacy Practice

Faculty of Pharmacy and Pharmaceutical Sciences University of Alberta

ãAndrew Fuller, 2019

Abstract

Medication incidents are common in long-term care facilities (LTCF). While few contribute to

permanent disability or death, a significant proportion lead to resident harm. Technology

solutions have been proposed to improve medication safety in long-term care environments, with

electronic medication administration records (eMAR) and barcode assisted medication

administration (BCMA) being a main focus of adoption. However, the impacts of eMAR-

BCMA on medication incidents and medication administration incidents (MAIs) within LTCF

have not been well defined. The overall objective of this research project was to explore the

influence of stand-alone eMAR-BCMA systems on safe medication practices in LTCF.

In the first study of this thesis, we conducted a scoping review to map the extent, range and

nature of research on the effectiveness, level of use, and perceptions of eMAR-BCMA in LTCF.

We identified limited direct evidence linking eMAR-BCMA use and reduction in medication

incidents and MAIs; in addition to, evidence of new types of medication incidents resulting from

nursing staff workarounds, inconsistent influence on nursing time spent during medication

administration and an array of perceived benefits and challenges.

In our second study, we conducted a retrospective review of medication incident reports

submitted voluntarily by nursing staff within a single LTCF two years post adoption of eMAR-

BCMA, in order to explore the frequency, type and severity of medication incidents; as well as,

the characteristics of residents who experience them. We determined that despite eMAR-BCMA

implementation, medication incidents and MAIs continued to be reported. The majority of

medication incidents were related to improper medication administration practices,

communication issues, and pharmacy dispensing errors.

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Our results suggest that more rigorous, prospective research in LTCF and community

pharmacies is required to demonstrate the impact that stand-alone eMAR-BCMA systems have

on medication safety in LTCF. It also highlights that opportunities remain to optimize use of

eMAR-BCMA and improve medication incident reporting in the LTCF setting.

PREFACE

This thesis is an original work by Andrew Fuller. Chapter 3 of this research project, of which

this thesis is a part, received ethics approval from the University of Alberta Ethics Board,

“Electronic Medication Administration Records in Long-term Care Facilities,” No. Pro0007992,

April 30, 2018.

Chapter 2 of this thesis has been published as AEC Fuller, LM Guirguis, CA Sadowski, MJ

Makowsky, “Electronic Medication Administration Records in Long-Term Care Facilities: A

Scoping Review,” Journal of the American Geriatrics Society. 2018;66(7):1428-1436. I was

responsible for concept, design, data analysis and interpretation and manuscript compostion. LM

Guirguis contributed to the concept and design, data interpretation and manuscript composition.

CA Sadowski contributed to data interpretation and manuscript composition. MJ Makowsky

was the supervisory author and assisted with concept and design, data analysis and interpretation,

and manuscript composition.

DEDICATION

I would like to dedicate this Thesis to my beautiful wife Michele Fuller whose love and support

throughout my pharmacy career inspired me to take this journey and helped make this work

possible.

ACKNOWLEDGEMENTS

I am thankful for being given the opportunity to be a graduate student within the Faculty of

Pharmacy and Pharmaceutical Sciences. This has been such a great experience and I would not

have been able to achieve what I have done without the endless support from my supervisory

committee and many other faculty members. I also want to send thanks to my family and friends

who have provided encouragement over the course of my Masters.

More specifically, I would like to thank Dr. Mark Makowsky who took the leap of faith and

joined me on this journey. We learned a lot of throughout the course of this project, and I thank

him for the support, guidance, patience and passion towards research which helped us achieve

this goal. I would also like to extend gratitude and thanks to my supervisory committee

members, Dr. Lisa Guirguis and Dr. Cheryl Sadowski, who provided further support, direction

and perspective in the development and completion of this project.

Ms. Trish Chatterly and Ms. Janice Kung for providing guidance regarding literature search

strategies for our scoping review and Ms. Lily Yushko who provided support in developing our

data collection templates.

I would also like to thank the Faculty of Pharmacy and Pharmaceutical Sciences for providing

financial support to allow me to present my research findings at the Canadian Pharmacists

Association Conference in 2017.

Lastly, I want to thank the management and nursing staff at Villa Marguerite who provided me

an avenue to develop my skills as a pharmacist practitioner and as a researcher.

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Table of Contents CHAPTER 1.............................................................................................................................. 1 INTRODUCTION .................................................................................................................... 1

1.1 Introduction ....................................................................................................................... 1 1.1.1 Background: ................................................................................................................ 1 1.1.2 Medication Safety ........................................................................................................ 2 1.1.3 Medication Incidents .................................................................................................... 2 1.1.4 Medication Incident Reporting ..................................................................................... 3 1.1.5 Health Information Technology ................................................................................... 5

1.2 Objectives: ......................................................................................................................... 7 1.3 References ......................................................................................................................... 9

CHAPTER 2............................................................................................................................ 17 Electronic Medication Administration Records in Long-Term Care Facilities: A Scoping Review ..................................................................................................................................... 17

2.1 Background ..................................................................................................................... 20 2.2 Methods ........................................................................................................................... 21

2.2.1 Inclusion and Exclusion Criteria ................................................................................ 22 2.2.2 Screening and Data Abstraction ................................................................................. 22

2.3 Results ............................................................................................................................. 23 2.3.1 Main Outcomes.......................................................................................................... 24 2.3.2 Medication and Administration Error Rates ............................................................... 24 2.3.3 Benefits and Challenges ............................................................................................. 25 2.3.4 eMAR Prevalence and Uptake in LTCFs.................................................................... 28

2.4 Discussion ....................................................................................................................... 28 2.4.1 Comparison with Other Research ............................................................................... 29 2.4.2 Main Gaps and Priority Areas for Future Research in LTCFs ..................................... 30 2.4.3 Strengths and Limitations .......................................................................................... 31

2.5 Conclusion ....................................................................................................................... 31 2.6 References ....................................................................................................................... 43

CHAPTER 3............................................................................................................................ 51 Evaluation of Medication Incidents in a Long-Term Care Facility Utilizing Electronic Medication Administration Records and Barcode Technology ............................................ 51

3.1 Background ..................................................................................................................... 54

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3.2 Methods ........................................................................................................................... 56 3.2.1 Facility Background ................................................................................................... 56 3.2.2 Inclusion/Exclusion Criteria & Data Access ............................................................... 58 3.2.3 Data Abstraction ........................................................................................................ 59 3.2.4 Data Analysis............................................................................................................. 61

3.3 Results ............................................................................................................................. 62 3.3.1 Medication Incident Reports ...................................................................................... 62 3.3.2 Resident Characteristics ............................................................................................. 63 3.3.3 Medication Incident Report Characteristics ................................................................ 63 3.3.4 Medications Involved with Medication Incident Reports ............................................ 64 3.3.5 Primary Personnel Involved & Incident Follow-up..................................................... 64 3.3.6 Content Analysis: Factors Leading to MAIs and Dispensing Errors ........................... 64 3.3.7 Characteristics of Residents with Multiple Medication Incidents ................................ 65 3.3.8 Severity of Medication Incidents ................................................................................ 65

3.4 Discussion ....................................................................................................................... 66 3.4.1 Strengths .................................................................................................................... 72 3.4.2 Limitations ................................................................................................................ 72

3.5 Conclusion ....................................................................................................................... 73 3.6 Glossary of Terms ............................................................................................................ 75 3.7 References ....................................................................................................................... 86

CHAPTER 4............................................................................................................................ 93 GENERAL DISCUSSION AND CONCLUSIONS ............................................................... 93

4.1 General discussion ........................................................................................................... 93 4.1.1 Electronic Medication Administration Records in Long-Term Care Facilities: A Scoping Review.................................................................................................................. 93 4.1.2 Evaluation of Medication Incidents in a Long-Term Care Facility Utilizing Electronic Medication Administration Records and Barcode Technology ............................................ 96

4.2 Implications and Future Directions................................................................................. 100 4.2.1 for clinical practice: ................................................................................................. 100 4.2.2 for research .............................................................................................................. 103 4.2.3 for policy ................................................................................................................. 105

4.3 Conclusion ..................................................................................................................... 105 4.4 References ..................................................................................................................... 106

BIBLIOGRAPHY ................................................................................................................. 112

LIST OF TABLES

Table 2.1 Descriptive Characteristics of Included Studies 27

Table S2.1 Summary of Published Studies Included in Scoping Review 29

Table S2.2. Summary of Grey Literature Included in Scoping Review 32

Table 3.1. Resident Characteristics 69

Table 3.2. Medication Incident Characteristics 70

Table 3.3. Factors Involved in Medication Administration Incidents and Dispensing Errors 75

Table 3.4. Characteristics of Residents by Number of Reported Medication Incidents and Number of Medication Administration Phase Incidents

Table 3.5. Comparison of Severity of Medication Incidents 77

LIST OF FIGURES

Figure 2.1. Search decision flow chart for Scoping Review of eMAR in LTCF 25

Figure 2.2. Map of main outcomes measured by number of studies in Scoping Review of eMAR 26

Figure 3.1. Number of medication incidents and medication administration incidents reported over a 29-month period. 68

CHAPTER 1

INTRODUCTION

1.1 Introduction

1.1.1 Background: Medication incidents are a concern in long-term care facilities (LTCF) and occur at any stage of

the medication use process, such as the prescribing, transcribing, dispensing, administration,

communication/documentation and monitoring of a medication.1-3 A recent systematic review

suggests they impact up to 27% of LTCF residents and can lead to significant resident harm.4 A

medication incident, also referred to as a medication error, is any preventable event that may

cause or lead to inappropriate medication use or resident harm while the medication is in the

control of the health care professional, resident, or consumer.1, 5 With over 300,000 Canadians

6, 7 and 2.2 million Americans8 residing in LTCF in 2011-2014, upholding medication safety in

these facilities is a key priority.

Residents of LTCF require a higher level of care due to chronic illness, injury, functional and

cognitive impairments, disability, and other health related conditions8 which may prevent

maintaining the activities of daily living, such as personal self-care and health-related

responsibilities. In Canada, the majority of LTCF residents are seniors, where the average age is

86, 70% are female, 98% have a cognitive and/or functional impairment and 67% have a

diagnosis of dementia.9 LTCF may contain secure units for individuals with moderate to severe

dementia, who may have a high risk of wandering and unpredictable behaviors.10 In Alberta,

long-term care is available depending on the level of services and support that is required,11

where the majority is provided within long-term care and other assisted living facilities that

include on-site supervised care, 24 hours a day, 7 days a week.12

Due to the complexities of the healthcare needs and medical conditions of LTCF residents,

polypharmacy is a concern as almost half of LTCF residents are prescribed nine or more

medications daily13 increasing the risk of medication incidents14, 15 and adverse drug events

(ADE).16 An ADE is an injury from a medicine or lack of an intended medicine and also

includes adverse drug reactions and harm from medication incidents.17 ADEs can occur when

medications are managed safely and appropriately but can be amplified due to age-related

changes to the metabolism and response to medications18 or when the medication is used in error.

1.1.2 Medication Safety Several approaches have been adopted to reduce the risk of ADEs and medication incidents.

Deprescribing strategies address potentially inappropriate medications (PIM);19, 20 however, up to

75% of LTCF residents are still prescribed at least one PIM.21 Guidance for prescribing

medications in individuals with multiple medical conditions, including dementia has been

endorsed22, 23 even though there is little research on how to appropriately treat co-morbidities in

those living with dementia.24 Strategies have been used to reduce medication incidents due to

misinterpreted medication orders25 and to increase healthcare provider awareness to medications

known to instigate significant ADEs and harm to LTCF residents if used in error 26, 27 Other

approaches to improving patient safety focus on building a culture of safety, teamwork, quality

improvement strategies, education and training.28

1.1.3 Medication Incidents While there are different approaches to improve medication safety, medication incidents still

occur within LTCF. The majority of medication incidents are medication administration

incidents (MAI; also known as medication administration errors [MAE]) and order

communication issues which account for up to 53% 3, 13, 29-34 and 51%2, 4, 35-38 of medication

incidents respectively. In a 2017 systematic review of the prevalence of medication incidents in

LTCF residents by Ferrah et al., medication administration was involved in up to 53% of

medication incidents.4 Similarly, an evaluation of web-based medication incident reporting data

from 25 LTCF within North Carolina, found that 47% of medication incidents involved

administration.32 The most common medication error type associated with MAIs include

medication administration at an incorrect time, the medication was missed, or the wrong dose or

wrong medication was adminsiterd.2, 29, 31, 32, 39

Inappropriate medication management can lead to negative outcomes. For example, 12.6% of

medication incidents have been reported to lead to resident harm.2, 32, 36, 38 Typically medication

administration was the most common medication-use phase in which an incident led to harm in

LTCF.32, 36, 38 For example, using retrospective web-based medication incident reporting data

from 393 LTCF, Greene et al. found that over 56% of medication incidents that caused serious

harm was due to medication administration. Resident harm can range from temporary harm

requiring intervention to permanent disability or death.40 Even though harm can occur, the

systematic review by Ferrah et al. found that a small proportion of medication incidents

actually led to permanent disability or death within LTCF.4

1.1.4 Medication Incident Reporting Effective medication incident reporting and analysis is a key element in establishing a safe

medication use system.41 These systems depend on the willingness of individual providers to

report incidents and therefore health care organizations strive to facilitate a just culture where

providers, feel safe, encouraged, and enabled to discuss quality and safety concerns.42 It is

well recognized that disciplining employees for honest mistakes does little to improve overall

system safety, while mishaps accompanied by malicious behavior present valid objections to

calls for blame-free error reporting.42 When incidents occur, the system approach concentrates

on the conditions under which individuals work, rather than focusing on the failings on the part

of the individuals providers.43 Rather than focus on punishment or remediation, the systems

approach seeks to identify situations or factors likely to give risk to human error and change

the underlying systems of care to reduce the occurrence of errors or minimize their impact on

patients.44

The majority of data that is used to assess medication incident and MAI frequency, medication

error type and resident harm in hospital and LTCF are based on the voluntary submission of

medication incident reports by nursing staff. Medication incident reports are used for LTCF

quality improvement and assurance initiatives; as well as, as a requirement by governing

bodies.45 However, despite efforts to create a culture of patient safety medication incidents are

under-reported and are not considered to reflect the actual number of medication incidents that

may have occurred in a particular facility.46-52 Previous studies examined the perception of

medication incident report submissions by nursing staff and under-reporting can be related to

nursing staff interpreting the medication incident as not serious enough to report46, 47 or a fear

of disciplinary action when a medication incident occurs.49, 51 In addition, the process of

completing an medication incident report may be too complicated or time consuming.52

Furthermore to under-reporting, medication incident reports are known to be incomplete,

missing relevant information.53 Additional methods can be used to evaluate medication

incidents including manual chart reviews,54 direct observation of the nursing staff

administering medications,55 or utilizing reporting data available from health information

technologies designed to prevent medication incidents from occurring, such as barcode assisted

medication administration (BCMA).56, 57

1.1.5 Health Information Technology To address resident safety issues, health care systems have adopted various health information

technologies to decrease medication incidents and improve the accuracy of medication

administration. This includes electronic heath records (EHR), electronic medical records (EMR),

computer physician order entry (CPOE), drug distribution/dispensing systems, smart

(computerized) intravenous infusion pumps, electronic medication administration records

(eMAR) and BCMA.58 An eMAR is a software program that provides access to a resident’s

profile, including the residents’ photo, medical conditions, allergies, vitals and the most current

medication list and administration directions. Nursing staff refer to the eMAR to confirm the

medications required to be administered and then electronically sign off the medication as

administered once completed. An eMAR can be used as a stand-alone program for medication

administration or it can be integrated with a BCMA system. BCMA utilizes a handheld device

which scans resident specific packaged medications and presents the residents profile on the

eMAR. Barcode scanning adds an additional safety check prior to administration confirming

appropriateness. When a medication is scanned in error (i.e. wrong time or wrong medication), a

safety alert or a warning prompt is generated in order to correct the error prior to administration.

Again, once medication administration is complete, the medications are signed off on the eMAR.

A 2014 national survey suggested that eMAR-BCMA systems are found in over 93% of hospital

settings in the U.S.59 Information on uptake in LTCF is more sparse with a 2008 survey of

nursing homes in the state of Minnesota suggesting that 50% of LTCF in this jurisdiction utilize

this technology.60

The majority of evidence regarding the effectiveness of eMAR-BCMA systems in medication

administration and safety comes from hospital environments. In a systematic review to

determine whether implementation of the eMAR-BCMA is associated with declines in MAI rate

in acute care settings by Young et al., eMAR-BCMA inconsistently decreased the overall

incidence of MAIs.61 For example, Franklin et al. documented a 39% reduction in MAIs

reported post implementation,62 while Morriss et al. found an increase in medication error rates

of 69.5 medication incidents per 1000 doses pre-implementation to 79.7 per 1000 doses post

implementation (p<0.001).63 More recently, an integrative review to understand the effect of

barcode medication administration technology on medication incidents, by Strudwick et al.

concluded that most of the 11 studies reviewed had significant decreases in medication incidents

after eMAR-BCMA implementation.64 For example, in the study by Poon et al.,65 there was a

decrease in non-timing MAIs from 11.5% to 6.8% (p<0.001), in the study by DeYoung et al. the

medication incident rate decreased from 19.7% pre- implementation to 8.7% post

implementation (p<0.001),66 while Ching et al. found a reduction from 5.9 errors/100 doses pre-

implementation to 3.0 errors/100 doses post implementation, an absolute risk reduction of 2.9

errors per 100 doses (95%CI: 2.2, 3.6, p<0.001).67 In addition, an eMAR-BCMA pretest-posttest

direct observation non-equivalent comparison group study within several hospital settings found

the accuracy rate of medication administration increased and the number of medication incidents

consistently declined.58

Typically, hospitals have implemented integrated eMAR-BCMA systems in the context of other

health information solutions (i.e. EHR, EMR, CPOE), whereas in LTCF, the use of health

technology lags, and stand-alone eMAR or eMAR-BCMA are more common. eMAR-BCMA

systems designed for use in LTCF are commercially available and are promoted as being more

efficient and accurate than paper-based processes and capable of improving the safety of

medication administration.68, 69 As a manager and clinical pharmacist with a practice in a LTCF

environment, I was directly involved in the implementation of eMAR-BCMA systems in LTCF

across Alberta and the assessment and interventions around medication incidents in individual

residents. This involvement sparked my interest in how eMAR-BMCA systems influence

medication safety for the residents I directly or indirectly cared for. However, the existing

literature exploring effects of eMAR-BCMA on medication administration and MAIs within

LTCF had not been summarized and it is unknown if these systems can deliver similar gains in

medication safety to those seen in hospital environments. Further, while studies completed

within acute care settings and LTCF have used medication incident report data to establish the

frequency, type and outcome of medication incidents, limited research has been found reviewing

medication incident reports in LTCF that utilize eMAR-BCMA.

1.2 Objectives:

The overall objective of this thesis is to explore the influence of stand-alone eMAR-BCMA

systems on safe medication practices in LTCF. Two projects were conducted. The first project

was a scoping literature review to map the extent, range, and nature of research on the

effectiveness, level of use, and perceptions of eMAR and BCMA in LTCF, to identify gaps in

current knowledge and prioritize areas for future research. Utilizing methodologies described by

Arksey and O’Malley,70 relevant peer-reviewed literature and grey literature was identified using

a two-phase approach search strategy. The second project was a retrospective review of

voluntarily submitted medication incident reports within a single 239-bed designated assisted

living facility which implemented eMAR-BCMA to support medication administration

approximately two years prior to the review. In addition to characterizing the frequency, type

and severity of reported medication incidents and MAIs, we evaluated if medication incidents

were more commonly reported on secure or non-secure units, investigated characteristics of

residents that experienced multiple medication incidents, and explored factors that influence

medication incident severity.

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CHAPTER 2

Electronic Medication Administration Records in Long-Term Care Facilities: A Scoping Review

Andrew E.C. Fuller, BSc. Pharm1

Lisa M. Guirguis, BSc. Pharm, MSc. PhD1

Cheryl A. Sadowski, BSc. (Pharm), PharmD1

Mark J. Makowsky, BSP, PharmD1

Author Affiliations 1 Faculty of Pharmacy & Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta,

Canada T6G 1C9

Corresponding Author:

Mark J. Makowsky, BSP, PharmD

Associate Professor

Faculty of Pharmacy and Pharmaceutical Sciences,

3-171 Edmonton Clinic Health Academy, University of Alberta

11405 87 Avenue, Edmonton, Alberta, T6G 1C9, Canada.

Tel.: 780 492 1735; fax: 780 492 1217; e-mail: [email protected]

Abstract Word count: 264

Text Word Count: 3562

Figures: 2

Tables: 1

Appendices: 1

Supplemental Tables: 2

References: 80

ABSTRACT

Objectives: To map the extent, range, and nature of research on the effectiveness, level of use,

and perceptions about electronic medication administration records (eMAR) in long-term care

facilities (LTCF), and identify gaps in current knowledge and priority areas for future research.

Design: Scoping review of quantitative and qualitative literature.

Setting: Literature Review

Participants: Original research relating to eMAR in LTCF was eligible for inclusion.

Measurements: We systematically searched MEDLINE, CINAHL, Scopus, ProQuest, and the

Cochrane Library, and performed general and advanced searches of Google to identify grey

literature. Two authors independently screened for eligibility of studies. Independent reviewers

extracted data regarding country of origin, design, study methods, outcomes studied, and main

results.

Results: We identified 694 articles of which 34 met inclusion criteria. Studies were published

between 2007 and 2016 and were mostly from the United States (n=25). Twenty studies (59%)

used quantitative methods including surveys or analysis of eMAR data; seven (21%) used

qualitative methods including interviews/focus groups, document review, and observation, and

seven (21%) used mixed methods. Three major research areas were explored: medication

error/medication administration error rates (n=11); eMAR benefits and challenges (n=19); and

eMAR prevalence and uptake (n=15). Evidence linking eMAR use and reductions in medication

errors is weak because of suboptimal study design and reporting. The majority of studies were

descriptive and documented inconsistent benefits and challenges and low levels of eMAR

implementation.

Conclusion: Further investigation is required to rigorously evaluate the effect of standalone

eMAR systems on medication administration errors and patient safety, the extent of eMAR

implementation, pharmacists’ perceptions, and cost effectiveness of eMAR systems in LTCF.

Key Words: Electronic medication administration records; Long-term care; Medication Safety;

Scoping review

2.1 Background Long-term care includes a broad range of health, personal care, and supportive services that meet

the needs of individuals whose capacity for self-care is limited due to chronic illness, injury,

disabilities, or other health-related conditions.1 While individuals may receive long-term care in

a variety of settings, most receive care in nursing homes or other assisted living facilities. An

estimated 300,000 Canadians and 2.2 million Americans resided in nursing homes or other

assisted living facilities in 2013/2014.1,2

Because of the complexity of medication regimens and physical, functional, or cognitive

impairments, residents of long-term care facilities (LTCF) require nursing assistance for

medication management and administration. Almost half of residents are prescribed nine or

more medication therapies daily,3 which increases the risk for medication errors4,5 and adverse

drug events (ADE).6 Medication errors, which are any preventable event that may cause or lead

to inappropriate medication use or patient harm,7 can occur at any stage in the medication-use

process including prescribing, dispensing, documentation, monitoring and administration.8,9 A

recent systematic review found that medication errors occur in 16-27% of nursing home

residents. In five of the reviewed studies, the majority of errors (between 20-60%) occurred in

the administration and order communication phase.10 Other studies in LTCF have reported

medication administration error (MAE) rates between 3% and 50%.3,9,11-16 Wrong time errors

(71%), wrong dose (13%), and omitted doses (11%) are most commonly documented.13

Extensive medication regimens put increased pressure on nursing staff and increase the risk of

errors as approximately one-third of nursing time in LTCF is spent on medication

administration.17

Standalone eMAR systems targeted to LTCF are available and are promoted as having the ability

to improve the efficiency and safety of medication administration.28,29 While facilities

implementing these systems strive to achieve safer medication administration, it is not known

whether LTCF can expect similar benefits as hospitals. Typically, hospitals have implemented

integrated systems in the context of other health information solutions, while LTCF are generally

understaffed and the majority of care is provided by unregulated healthcare or nursing staff.30

These factors, in addition to differences in levels of patient acuity and private and public funding

models may further complicate translation of these findings to LTCF. To our knowledge, the

literature exploring the outcomes associated with eMAR implementation in LTCF has not been

comprehensively summarized. Therefore, our objective was to map the extent, range and nature

of research on the effectiveness, level of use, and perceptions about eMAR and BCMA in LTCF

in order to identify gaps in current knowledge and prioritize areas for future research.

2.2 Methods Relevant literature was identified using a 2-phase search strategy. First MEDLINE, CINAHL,

Cochrane Library, Scopus, ProQuest Dissertations, and Theses Global databases were searched

from 2000 to July 2016. Terms used included “electronic medication administration record,”

“bar-code medication administration,” “medication management information technology,”

“health information technology,” “medical informatics,” “nursing informatics,” “electronic

health records,” and “medication therapy management.” Second, to identify relevant grey

literature, we conducted advanced and basic searches of Google. Four search terms were used:

“electronic medication administration records,” “eMAR,” “health information technology,” and

“bar-code medication administration.” Each search term was combined with “long-term care,

nursing home, supportive living, assisted living, and skilled nursing facility.” All searches were

conducted with the assistance of a medical librarian. The full set of search terms is shown in

Appendix 2.1. Reference lists of all relevant articles were manually searched.

2.2.1 Inclusion and Exclusion Criteria We included English-language original literature, regardless of design, related to eMARs and

BCMA in LTCF. We defined eMAR systems as electronic point-of-care systems that allow an

electronic version of the resident’s medication administration record to be displayed on a digital

device and on which the nursing staff or pharmacist updates records using a web interface and

nursing staff document when medications are administered. We defined BCMA systems as

electronic point-of-care systems designed to scan resident-specific barcodes using a hand-held

device to confirm resident identification and medication administration. We defined LTCFs as

nursing homes, residential aged-care facilities, assisted living facilities, and care homes. Long-

term care wards located in hospitals were not considered to be LTCFs. We defined grey

literature as literature that government, academics, business, and industry produce in print and

electronic formats (e.g., theses, conference proceedings, technical reports) and not controlled by

commercial publishers.31 We excluded systematic reviews or other narrative reviews of the

literature, but when these were found, the original studies were located. News reports, news

article interviews, personal opinion pieces, unstructured interviews, and advertisements from

eMAR vendors and community pharmacies were excluded.

2.2.2 Screening and Data Abstraction Two reviewers (AF, MM) independently screened titles and abstracts of all literature identified

in the Phase 1 search, obtaining full articles to assess relevance when necessary. Given the large

number of results in the general Google-based grey literature search (n=450,940), both reviewers

independently completed a review of the website title for the top 50 results for each of the 4

searches and actual website content when necessary. The two reviewers reviewed the reference

lists of included studies from both searches. Disagreements were resolved by consensus. Three

authors were contacted (two to provide more information to determine eligibility, one to

determine year of publication), but none responded to our requests.

Quantitative and qualitative data were extracted using a standardized template and included

author, publication year, country of origin, design, study methods, study environment,

population, technology studied, main outcomes studied, main results, and conclusion. Study

designs were categorized as analytic or descriptive, with analytical studies further categorized as

experimental or observational according to a previously published classification system.32 The

method of data collection was characterized as survey, qualitative, observation, document

review, analysis of eMAR administrative data, or mixed methods. We documented whether an

eMAR or BCMA was implemented in isolation or in the context of other health information

solutions (e.g., electronic medical record, computerized physician order entry (CPOE), electronic

health record (EHR)). Studies were grouped according to the main outcomes reported. Given

that this review did not directly use health information, approval from the health research ethics

board was not sought.

2.3 Results The initial search yielded 771 abstracts, of which 34 articles were included in this review (Figure

2.1). Of the included studies, eleven were identified through the medical database search,15,25,33–

41 eight from reference lists of included studies,42–49 and 15 from the grey literature search.50–64

Fifty percent (n=17) of articles were published in the peer-reviewed literature (Table 2.1).

Included studies were published between 2006 and 2016, 74% (n=25) were completed in the

United States and 88% in nursing homes or residential aged care facilities (n=30). We found 28

descriptive reports and six analytical studies. Of the descriptive reports, 14 (50%) were surveys,

12 were qualitative investigations, and one each was implementation and document review. All

of the analytical studies were observational (two cohort, four cross-sectional). Overall, 20 used

quantitative methodology, seven used qualitative methodology, and seven used mixed methods.

Qualitative data collection methods included individual interviews, focus groups, document

review, direct observation, process mapping, nominal group technique, and informal

conversations. Participants in included studies were primarily nursing home staff or

administrators, but some were pharmacists and physicians. Standalone eMAR systems were

evaluated in six studies, and combinations of eMAR with BCMA, electronic medical records,

EHR, or CPOE were studied in 13 studies.

2.3.1 Main Outcomes The outcomes investigated in the included studies fell into three main categories: medication and

medication administration error rates (11 studies),25,36–39,41,50,52,56,58,59 benefits and challenges (19

studies),15,34,36–41,44,45,50,51,54,56,58–60,62,63 and eMAR prevalence and uptake (15 studies) 33,35,41–43,45–

49,53,55,57,61,64 (Figure 2.2.) Studies that included multiple outcomes were counted in each

respective category; detailed summaries may be found in Supplementary Tables S2.1 and S2.2.

2.3.2 Medication and Administration Error Rates Four articles reported medication error rates in relation to eMAR implementation.25,52,58,59 Two

studies were grey literature descriptive case reports that reported error rates before and after

implementation of an eMAR.58,59 After implementation of an eMAR, one study noted that the

incidence of medication errors dropped from 192 to 31 per year59 and another that the rate

dropped from 212 per year before implementation to 20 and 17 in the two years after

implementation.58 Neither described the type of medication errors that decreased. The other two

reports were from a cohort study that used a BCMA system to measure the incidence of MAEs

after implementation only and found that 1.2% of all medications administered (2,289/188,249

administration attempts over 3 months) were potential MAEs that the BCMA averted.25,52 Of

these, 86% were administering medications at an incorrect time, 10% were attempts to give a

medication to the wrong resident, and 4% were attempts to give a discontinued medication.

Neither the clinical significance or severity of MAEs was adjudicated in these reports.

Nine reports (six peer-reviewed,25,37–39,41,50 three grey literature36,52,56) described other outcomes

related to medication errors. Three studies used questionnaires of nursing staff to assess

perceptions of stress and risk of medication errors,38 awareness of medication errors or near

misses,50 and awareness of MAEs.25,52 (Supplementary Tables S2.1 and S2.2). One reported

statistically significantly lower perceived risk of MAEs with implementation of an eMAR than

with paper records.38 In the grey literature, a questionnaire to understand the costs and benefits

of eMAR noted a perceived medication error rate of zero after eMAR implementation.56 Other

studies used qualitative or mixed methods to explore the medication administration process and

errors. Specifically, these studies reported outcomes related to eMAR prevention of MAEs,37

identification of medication order discrepancies ordered through an eMAR that led to a MAE,39

and perceptions and concerns regarding medication administration and MAEs.36 Nursing staff

with access to an eMAR reported lower stress levels about making MAEs, a positive perception

of medication administration,50 and the perception that the eMAR decreased medication errors.36

Lastly, registered nurses felt that, when physicians used an eMAR system that integrated CPOE,

medication errors were avoided.41

2.3.3 Benefits and Challenges Twelve studies reported benefits of eMAR beyond MAEs.15,36,37,41,44,54,56,58– 60,62,63

2.3.3.1 Improved Efficiency Outcomes Ten studies (four peer-reviewed,15,37,41,44 six grey literature36,56,58–60,62) reported on efficiencies

with eMARs, which were described as improving workflow, resulting in time savings for the

medication administration pass,44,56,58,62 whereas in two studies, no differences were reported.36,37

Several studies addressed how eMARs provided easier access to complete, real-time resident

information regarding active medication orders.15,36,60 Two grey literature case studies56,59

documented a reduction in monthly medication reconciliation time with eMAR. In the peer-

reviewed literature, when an eMAR was combined with CPOE41 or an EHR,15 medication order

processing was reported to be streamlined, reducing the numbers of steps and documentation

points. One grey literature report identified monetary savings resulting from the ability to update

the eMAR immediately with changed medications orders.56 Lastly, adoption of an eMAR

created a more complete EHR59 and, when combined with a CPOE, gave physicians the ability to

modify the eMAR remotely, avoiding delays or additional site visits.41

2.3.3.2 Safety and Quality Nine studies (five peer-reviewed,15,37,41,44,63 four grey literature 56,59,60,62) reported on

improvements to safety and quality of care as a result of eMAR. Some linked these

improvements to medication administration, and others linked them to other features in the

eMAR. For example, eMAR alerts and signaling functionalities were reported to have alerted

staff to potential medication safety problems such as when a medication was due or past due,

when a medication needed follow-up, or when a new medication was ordered.15 Others reported

that care was felt to be safer with an eMAR but provided no further elaboration.44 One case

study claimed improvements to patient safety and better health outcomes because of eMAR

alerts, mandatory documentation of administration, and effectiveness of as-needed medications,

and resident photographs for identification.60 Kramer reported that built-in accountability

features in the eMAR contributed to a safer, more reliable workflow.56 eMAR integrated

decision support systems resulted in improvements in staff adherence to medication monitoring

and reduced missed lab tests and other orders.56 Finally, one report identified eMAR as a high

priority for implementation to improve quality.63

2.3.3.3 Administrative Reporting Quality Improvement Five studies37,54,58–60 addressed the effect of eMARs on quality improvement and adherence to

organizational and regulatory policies. The only peer-reviewed study acknowledged that eMAR

eliminated documentation practices that did not adhere to organizational policy such as nursing

staff administering medications before signing their charts.37 eMARs also permitted ease in

demonstrating that care was being provided in accordance with regulatory requirements set forth

by state legislation59 and improved the ability to monitor drug use and evaluate quality measures,

which includes as needed medication frequency and documentation of effectiveness.58 Other

perceived administrative benefits included eMAR reporting functions, mitigation of drug

diversion, and staff login with unique credentials.59

2.3.3.4 Challenges Seven studies (five peer-reviewed,15,34,37,40,41 two grey literature 36,51) reported challenges with

eMARs related to the design or instability of the Internet or eMAR system. Other examples

included limited interactivity between facility and pharmacy, inadequate flexibility because

profiles were “read only,” minimal decision support tools, and poor resident information

layout.40 Physicians and nurses noted lack of training and information technology support.41

Lastly, eMAR implementation could not resolve chronic structure and process problems that

predated implementation and led to new safety concerns. For example, nursing staff would work

around intentional blocks that prevented excessive medication ordering, dual documentation of

medication administration, and documentation of assessment before administration.15,34

Workarounds were also noted with unintentional blocks resulting from ineffective technology

design related to medication orders, Internet connectivity, and organizational processes.15,34

2.3.4 eMAR Prevalence and Uptake in LTCFs Twelve cross-sectional surveys (five peer-reviewed,33,42,43,49,57 seven grey literature reports45–

47,53,55,61,64) between 2006 and 2015 evaluated the prevalence of eMAR uptake in U.S. LTCFs.

Depending on the timeframe and location, 18% to 49% of facilities surveyed had implemented

an eMAR. Two additional cross-sectional surveys of LTCF pharmacy providers reported that

18%48 and 23.3%35 of pharmacies used an eMAR. Three investigated predictors of adoption of

eMARs in LTCFs using multivariate regression analysis.33,42,53 Census region; level of

administrator experience, education, and accreditation; and overall number of services delivered

were independent predictors of electronic information systems for medication administration

records,33 whereas profit status did not influence eMAR uptake.42 Lastly, one study explored

physician uptake of an eMAR system with CPOE functionality.41

2.4 Discussion In this scoping review, we identified 34 reports related to the use of eMARs in LTCFs. The most

studied outcomes were the benefits and challenges of eMARs, mainly explored using qualitative

or mixed methods. eMAR prevalence and uptake were determined using cross-sectional surveys,

and MAEs were determined according to objective review of eMAR data, staff surveys, or focus

groups regarding perceptions of risk of medication errors. Although most studies were

descriptive and provided consistent data that nursing staff act on warnings that eMAR systems

generate, we did not find any robust experimental trials evaluating the effect of eMARs on

MAEs in the peer-reviewed literature, although we identified two case reports that compared

medication error rates before and after eMAR implementation which showed a substantial

decrease in medication errors. Unfortunately, these provided weak evidence of benefit because

of weaknesses in study design and reporting. Small published studies suggest that eMARs can

increase nursing staff awareness and decrease anxiety associated with medication administration.

Other benefits identified in qualitative studies included greater efficiency, safety, and

administrative processes, and problems with eMAR design, reliability, information technology,

and staff workarounds were the main challenges. The influence of eMARs on nursing time spent

during medication administration rounds was inconsistent. Finally, surveys suggest that up to

49% of LTCFs in certain U.S. jurisdictions have implemented eMAR.

2.4.1 Comparison with Other Research In contrast to the long-term care literature, many studies have addressed the effect of eMARs and

BCMA on MAEs in the hospital setting. A 2010 systematic review27 concluded that BCMA

systems, which incorporate eMAR technology, had varied influence on the 5 rights of

medication administration (i.e., right drug, right time, right patient, right dose, right route) and

did not consistently decrease overall incidence of MAEs but were able to identify additional

MAE categories beyond the five rights. Since this review, additional well-designed hospital-

based comparative studies have demonstrated significant reductions in MAE rates with eMARs

and BCMA ranging from 41.4% to 80.7%.65–69 Similarly, other studies have shown that

medication error rates decreased after BCMA70,71 and eMAR implementation,72 although the

most recent study73 illustrates the inconsistent effect of BCMA and eMARs on MAEs, finding no

significant change in MAE rates. The major methodological differences between the studies we

identified and those exploring eMARs in institutional settings make further comparisons

regarding MAE rates challenging.

There are several similarities in the benefits and challenges of implementing eMARs in LTCFs

and hospital settings, including improved communication between team members;

interdisciplinary relationships; immediate access to resident-specific information and medication

orders; and positive nursing perceptions about ease of documentation, drug information

accuracy, and patient safety.65,74–76 Hospital pharmacists had positive perceptions in terms of

ability to interpret prescription orders through eMARs with CPOE functionality.76 As for

challenges, hospital nursing staff perceived that communication between nursing staff and

pharmacy did not improve,75 the medication administration process was slower,72 nursing staff

workload increased, and eMARs were inflexible and user-unfriendly and was slow to reflect

updated medication information.74 Pharmacists perceived medication dispensing to be slower

and inefficient in the dispensary and difficult to use and not useful for improving patient care and

reported low satisfaction with the system.76 At a system level, the high financial cost associated

with implementing and operating this technology has been perceived as a significant barrier.77

Several hospital based studies have also documented workarounds, whereby nursing staff bypass

the safety alerts of eMAR or rely on the technology too much, possibly increasing the risk of

errors not seen before implementation of eMARs.66,78,79 Finally, rates of eMAR implementation

in LTCFs seem to lag those in hospital settings, which had an uptake in U.S. hospitals in 2014 of

93.3% for eMAR and 88.4% for BCMA.24

2.4.2 Main Gaps and Priority Areas for Future Research in LTCFs Evaluation of the existing literature in LTCFs revealed several research gaps. First, there has

been no rigorous MAE prevention study, and a trial similar to two previous trials66,72 is

important, because eMAR systems typically implemented in LTCFs are vastly different from the

large integrated health information systems implemented in hospital settings. Second, although a

large proportion of articles included in our review investigated uptake of eMARs in LTCFs,

these studies were outdated and do not reflect uptake in Canada. Third, there was little research

on the effect of eMARs on pharmacy practice, given community pharmacists’ role in the

processing, assessing, dispensing, and distributing of medications for LTCFs and in altering the

medication profile in the eMAR. The studies that included pharmacist or pharmacy views

consisted of the perceptions of two pharmacists,41 one pharmacist’s experience with eMAR,40

prevalence of eMAR uptake by LTCF pharmacy providers,35,48 and the pharmacist perspective of

how eMARs could improve current care processes.63 Further study is required on the effect of

eMARs from the community pharmacist perspective. Finally, there are no data evaluating the

economic effect of eMARs in LTCFs. It is unclear whether providing more efficient delivery of

resident care or preventing emergency department visits or hospitalizations because of a

reduction in MAEs and the adverse drug reactions associated with them offset the financial costs

of implementation, training, and maintenance of the system.

2.4.3 Strengths and Limitations To our knowledge, this is the first scoping review of the topic, and it has several strengths. First,

our search was comprehensive and included peer-reviewed and grey literature. Second, our

methodology was robust, following the methodology of Arksey and O’Malley.80 Nevertheless,

this review has several limitations. First, results from the grey literature should be used with

caution because the reporting, methodologies, and resulting claims are not as robust as those

found in the peer-reviewed literature. This reinforces the need for more published literature on

eMARs in LTCFs. Second, we may have missed important grey literature because of the large

number of results from the general Google search and Google’s search algorithms, which

incorporate an individual user’s previous search history. Third, only a small number of

identified studies focused on standalone eMAR implementation.

2.5 Conclusion We mapped the available evidence related to eMAR and BCMA technology in LTCFs. The

research on eMARs in LTCFs was focused on medication errors, benefits, challenges, and

eMAR uptake. The majority of studies were descriptive, and there is a lack of rigorously

designed research to inform administrators and clinicians about the effect of eMARs and BCMA

on medication errors in LTCFs. Further investigation is required to evaluate the effect of

contemporary eMAR and BCMA systems on MAEs and patient safety, levels of uptake of

eMARs in LTCFs, the factors influencing uptake of these technologies, clinical pharmacists’

perceptions of eMAR systems, and the cost effectiveness of eMAR implementation.

Figure 2.1. Search decision flow chart for Scoping Review of eMAR in LTCF

Figure 2.2. Map of main outcomes measured by number of studies in Scoping Review of eMAR.

*Some studies examined outcomes in more than one category

Table 2.1. Descriptive Characteristics of Included Studies Characteristic N=34 Publication Status

Peer-Reviewed Literature 17 (50%) Grey Literature 17 (50%)

Publication Year Unknown 1 (3%) 2005-2009 11 (32%) 2010-2014 14 (41%) 2015-2016 8 (24%)

Country USA 25 (74%) Australia 4 (12%) UK 3 (9%) Sweden 1 (3%) Canada 1 (3%)

Study Design Descriptive 28 (82%)

Survey 14 (41%) Qualitative 12 (35%) Implementation 1 (3%) Document Review 1 (3%)

Analytic 6 (16%) Experimental 0 (0%) Observational Analytic 6 (16%)

Cohort 2 (6%) Cross-sectional 4 (12%) Case Control 0 (0%)

Study Design Quantitative 20 (59%) Qualitative 7 (21%) Mixed 7 (21%)

Method of Data Collection Survey 18 (53%) Interview 12 (35%) Document Review 9 (26%) Direct Observation 7 (21%) Focus Groups 7 (21%) Analysis of eMAR Data 5 (15%) Field notes 3 (9%) Time motion-based observation 1 (3%) Process mapping 1 (3%) Nominal Group Technique 1 (3%) Informal conversation 1 (3%)

Setting

Long-term Care 30 (88%) Assisted/Supportive Living 5 (15%) Pharmacy 3 (9%) Home Health Agencies 1 (3%)

Population/Participants Long-term Care Facilities 18 (53%) Nursing Staff 15 (44%) Pharmacists 5 (15%) Physician 3 (9%) Site Manager 4 (12%)

Health Information Technology Studied eMAR and EHR/EMR 7 (21%) eMAR only 6 (18%) eMAR and BCMA 3 (9%) eMAR and CPOE 1 (3%) eMAR, BCMA, and EHR 1 (3%) eMAR, EMR and CPOE 1 (3%) N/A 15 (44%)

Main Outcomes Medication Error/Medication Administration Errors 11 (32%) Benefits/Challenges of eMAR 19 (56%) Prevalence/Uptake of eMAR 15 (44%)

Legend: eMAR: Electronic Medication Administration Record, BCMA: Bar-code Medication Administration, EHR: Electronic Health Record, EMR: Electronic Medical Record, CPOE: Computer Physician Order Entry

Supplementary Table S2.1. Summary of Published Studies Included in Scoping Review (n=17)

Research Outcomes Authors Type of

Study Country Setting Purpose Relevant Measured Outcomes `Methods Results/Relevant Findings Source

Medication Administration Errors

Szczepura et al. 25 2011

Cohort Study Cross-sectional Survey

United Kingdom

Nursing Homes and Residential Homes (BCMA)

To measure the incidence of MAEs in nursing and residential homes using a BCMA system

Comparison 2 settings using BCMA (nursing home and residential home)

• The incidence of potential MAEs using BCMA

• Staff awareness of MAEs prior to BCMA implementation.

Disguised observation technique

Disguised observation of n=9 residential homes and n=4 nursing homes

Cross-sectional pre-study

survey Survey of n=45 staff members

• 1.2% of all medication administrations were potential MAEs prevented by BCMA.

• The frequency of averted MAEs with BCMA was significantly higher in NH vs. RH (p<0.01)

• MAE risk was higher in the nursing homes (IR 1.43; 95% CI 1.32 to 1.56)

Medical Database Search

Medication Administration Errors; Benefits/ Challenges

Elliot et al. 39 2016

Retrospective Cohort

Australia RACF (eMMS)

To investigate the discrepancies between GP paper medication orders and pharmacy-prepared eMAR (eMMS) charts and delays between prescribing, charting and administration.

• Number and type of discrepancies between medication orders and eMAR (eMMS)

• The number of discrepancies and delays that led to a MAE.

Cross-sectional audit of medication orders and medication charts

Audit of n = 88 resident

medication records

• 125 discrepancies noted where 47 (37.6%) led to MAE. • Of these, 42.6% (20) were due to discrepancies

between GP-signed medication chart and eMAR (eMMS)

Medical Database Search

Perceived MAEs; Benefits/ Challenges

Qian et al. 37 2015

Mixed Methods

Australia RACF (eMAR)

To compare eMAR and paper MAR with the nursing time spent on various activities in a medication round and medication administration process.

To identity the benefits and

unintended adverse consequences of eMAR

Comparison 2 units within an RACF (control/intervention)

• The impact eMAR has on nursing time spent on activities

• The benefits and consequences of eMAR

Time-motion observation Direct observation of n=7

nursing staff members Field notes Informal conversation Document review

• No difference in nursing time spent on medication administration or other various activities during the medication round.

eMAR Benefits: • Improved nurses' compliance with documentation. • Freedom from the error of signing twice. • Reduces the possibility of forgetting medication

administration or to sign medication charts. • Facilitates the time of medication administration. • Increase documentation space. Challenges of eMAR: • Inadequate information about residents. • Late addition of a new residents' provide in eMAR. • Nurses forgetting to medicate a resident due to power

outage.

Medical Database Search

Perceived MAEs; Benefits/ Challenges

Alenius and Graf. 38 2016

Prospective Case-control

Sweden Nursing Home (MCSS)

To investigate the impact of eMAR on perceived stress among health personnel and the risk of MAEs in the Nursing Home setting.

Comparison 2 nursing home settings (control/intervention)

• Perceived stress among health personnel and perceived risk of MAEs before and after eMAR implementation.

Pre-post eMAR implementation questionnaire

Questionnaire of n=66 (pre) and

n=59 (post) nursing personnel

• Fewer personnel who were worried or anxious about MAEs in the intervention group at follow up (P<0.001)

• Statistically significant reduction in perceived risk of making MAEs in the intervention group at follow up while the risk stayed the same or was increased in control group.

• Perceived stress in general daily work was lower in the intervention group both at baseline (P=0.020) and follow up (P<0.001)

• Perception of medication administration improved and more positive in intervention group

• Perceived stress with the medication administration process decreased from baseline to follow-up in the intervention group while it was similar in the control group at both time points.(P=0.001).

• The perception of the medication administration process improved in the intervention group at follow up (P=0.002), while there was no change in the control group.

Medical Database Search

Perceived MAEs; Benefits/ Challenges

Wild et al. 50 2001

Qualitative United Kingdom

Residential Homes and Nursing Homes (BCMA)

To evaluate the effects of a pharmacy led BCMA in care homes.

• Staff awareness of 'near misses' Survey n=49 pre, n=39 post nursing

staff Interview n=unknown

• Staff Awareness of near misses: • RH pre/post implementation~40%/74%. • NH pre/post implementation~0%/83%

• Staff were more aware of 'near misses with BCMA. • Less and stress and pressure post-BCMA

Grey Literature Search

Perceived MAEs; Benefits/ Challenges; Prevalence/ Uptake

Elliot et al. 41 2016

Mixed: Retrospective Audit and Qualitative

Australia RACF (ePMMS)

Explore the uptake of the ePMMS by GPs and the experiences and perceptions of GPs, RACF Nurses and Pharmacists with the ePMMS.

• The uptake of ePMMS by GPs • Perceptions and the experiences of

GPs, Nurses and Pharmacists with ePMMS

Interviews n=2 pharmacists Focus Groups n=5 GPs, n=12 nurses Retrospective audit of medication

orders

• 3 of 7 GPs used the ePMMS. • 83% of medication orders through ePMMS were by 1

GP. Benefits: • Patient safety (updated MARs, avoided errors and

delays and easier to interpret orders • Workforce efficiencies (quicker to modify MAR,

decreased GP visits, time saved for new orders) Limitations and Barriers: • Inefficiencies • Poor uptake prevented full benefit of system being

realized

Medical Database Search

Research Outcomes Authors Type of

Study Country Setting Purpose Relevant Measured Outcomes `Methods Results/Relevant Findings Source

• Low training/support Benefits/ Challenges

Scott- Cawiezell et al. 15 2009

Implementation

United States

Nursing Home (eMAR)

To explore the impact of technology and a focused Quality Improvement team on medication safety practices and medication errors with an eMAR implementation.

• The impact of eMAR in the medication administration process and Quality Improvement.

Detailed Observation Focus Group n=5 Midwestern nursing homes

eMAR Benefits: • Provides new structures and processes to resolve

challenges related to each individual medication, the medication pass and management of medications over time.

• Provides real time information on active orders. • Allows the administrator to focus only on the

medications that were due. • Provides alerts and signaling features to prompt staff of

medication safety issues. • Streamlines medication order processing. • Provides critical safety issue reports. • Brings Nursing Home and Pharmacy staff together to

solve problems. eMAR Limitations: • Did not provide an independent and sufficient solution

to the challenges of medication safety • Safety practice concerns noted with staff workarounds • Could not solve chronic structure and process issues on

site Could not resolve omitted and missing medication information between GP, Pharmacist and administration.

Medical Database Search

Benefits/ Challenges

Vogelsmeier et al. 34 2008

Implementation United States

Nursing Home (eMAR)

To explore the relationship of workarounds related to the implementation of eMAR and medication safety practices.

• To identify workarounds associated with the implementation of eMAR.

• Identify the potential risks of workarounds on medication safety.

Direct observation n=43 (pre) and n=45 (post)

nursing staff Key informant interviews n=unknown Process mapping Review of field notes

Workarounds related to technology implementation: • Intentional blocks designed to enhance resident safety • Unintentional blocks resulting from ineffective design Workarounds related to organizational processes not re- engineered to effectively integrate the new technology

Medical Database Search

Benefits/ Challenges

Tariq et al. 40 2014

Formative Evaluation

Australia RACF

Pharmacy (eMAR)

To conduct an in-practice evaluation of eMAR being piloted in one RACF before its rollout to other sites, and to provide recommendations for system improvements

• The challenges associated with the design and use of the eMAR system.

• Recommendations to improve the design before rollout.

Workflow observation n=1 Pharmacy n=1 RACF Semi-structured interviews n=4 RACF staff, n=1 RACF

manager and n=1 pharmacist

Design Challenges of eMAR system: • Limited interactivity • Inadequate flexibility • Issues in information layout and semantics: • Minimal decision support System maintenance issues

Medical Database Search

Benefits/ Challenges

Rantz et al. 44 2011

Qualitative United States

Nursing Homes (eMAR)

To determine if quality of care provided is improved through the use of EMR and if care is improved, what elements improved?

• Quality of care with the use of eMAR • Benefits of eMAR

Observation n=4 Nursing Homes Interview n=unknown Focus Groups n=22 focus groups

Benefits: ● Care was safer (no specifics provided) ● Facilitated faster and safer medication pass.

Reference List

Benefits/ Challenges

Degenholtz et al. 63 2016

Qualitative United States

Nursing Homes (eMAR)

To develop an empirical framework for understanding the intersection between specific uses of HIT and clinical care processes

● Identify key care processes that domain areas that can benefit from health information technology.

Focus Groups (Nominal Group Technique)

Physicians and Pharmacists identified eMAR implementation among the top 3 care processes Physicians: ● Nurses record when they have given medication

using eMAR ● Maximum dosing’s should not have to be written

explicitly. ● There should be an automatic check for drug

interactions Pharmacists: ● Document when residents refuse medications and

automatically transmit information to RN or Physician for drug

● Identify ADR or side effects ● Automate pain management protocol

Capture actionable information not just “5 Rights”

Grey Literature Search

Prevalence/ Uptake

Chan33 2008

Cross-sectional Survey Retrospective Secondary Analysis

United States

Nursing Home (eMAR)

To test whether the percentage of occupancy and metropolitan location are associated with the likelihood of NH using EIS for clinical care support.

• Hypothesis 1: Higher occupancy rate in NH will lead to more medication administration EIS use.

• Hypothesis 2: Being within a metropolitan area will lead to more medication administration EIS use.

Survey n=1174 nursing homes

eMAR implementation in Nursing Homes • Implemented: 38.1% • NHs in metropolitan areas are less likely than those in

rural to have medication administration EIS. • NHs with occupancy rate of 70-79% are less likely than

those with <70% to have medication administration EIS.

• NHs with administrators <5years are less likely than those with at least 20 years to have medication administration EIS.

Medical Database Search

Research Outcomes Authors Type of

Study Country Setting Purpose Relevant Measured Outcomes `Methods Results/Relevant Findings Source

NHs offering more services are more likely to have medication administration EIS.

Prevalence/ Uptake

Martin35 2011

Cross-sectional Survey

United States

Pharmacy (eMAR)

To determine industry standards for LTCF pharmacy operations, consultant pharmacist practice, and the use of HIT in LTCF.

• Prevalence of eMAR in LTCF and AL Pharmacy providers

Survey n=unknown Pharmacy providers

eMAR implementation in Pharmacy • Implemented (LTCF/AL): 23.3%/19.5% • Pharmacies with larger staff numbers are more likely to

have HIT.

Medical Database Search

Prevalence/ Uptake

Hamann et al. 42 2013

Cross-sectional Survey

United States

Nursing Homes (eMAR)

To examine the ownership differences in the use of technology in NHs

• The mean percentage of adoption of eMAR in non-profit and for-profit Nursing Homes

Cross-sectional Survey n=1174 Nursing Homes

Prevalence: 38% for profit, 38% non-profit NHs have medication administration information via health IT

Reference List

Prevalence/ Uptake

Abramson et al. 57 2014

Cross-sectional Survey

United States

Nursing Homes To determine rates of electronic health record (EHR) adoption and health information exchange (HIE) among New York State (NYS) nursing homes

• The extent of eMAR uptake in those nursing homes with EHR.

Cross-sectional Survey n=375 nursing homes

• 45.5% of those nursing homes with full or partial EHRs had eMAR,

• 8.1% of nursing homes without EHRs had eMAR

Grey Literature Search

Prevalence/ Uptake

Resnick et al. 49 2009

Cross-sectional Survey

United States

Nursing Home (EIS/eMAR)

To define the extent of utilization of 12 types EIS function in U.S. Nursing homes.

Relate EIS utilization to selected facility characteristics

Contrast these findings to previous estimates of EIS use in NH

• Medication Administration EIS use in U.S. nursing homes

Survey n=1174 nursing homes

eMAR implementation in Nursing Homes • Implemented: 38.1% • Larger facilities and those that were part of a larger

chain used more EIS.

Reference List

Prevalence/ Uptake

Abramson et al. 43 2015

Cross-sectional Survey

United States

Nursing Homes (eMAR)

To assess the pace of EHR adoption, changes in computerized function adoption and participation in HIE by NY state nursing homes over time

● Prevalence of eMAR

Cross-sectional Survey n=472 Nursing Homes

Prevalence: • 47.6% of NHs that are EHR adopters had eMAR (2012) • 51.0% of NHs that are EHR adopters had eMAR (2013)

Reference List

Legend: eMAR: Electronic Medication Administration Record, BCMA: Bar-code Medication Administration, eMMS: Electronic Medication Management System [This intervention includes electronic medication administration chart]; EIS: Electronic information systems [This term has 12 functional areas which includes Electronic Medication Administration information], ePMMS: Electronic Prescribing and Medication Management System [This intervention consists of electronic prescribing which directly populates Electronic Medication Administration Records], MCSS: Medication and Care Support System [This term is synonymous to eMAR], GP: General Practitioner, RN: Registered Nurse; MAE: Medication Administration Error, LTCF: Long-term Care Facility, HIT: Health Information Technology, AL: Assisted Living Facilities, SNF: Skilled Nursing Facilities, IT: Information Technology, RACF: Residential Aged Care Facility, NH: Nursing homes, HHA: Home Health Agencies, HIE: Health Information Exchange, EHR: Electronic Health Record

Supplementary Table S2.2. Summary of Grey Literature Included in Scoping Review (n=17) Research Outcomes Authors Type of

Study Country Setting Purpose Relevant Measured Outcomes Methods Results/Relevant Findings Source

Medication Administration Errors

Szczepura et al. 52 2013

Prospective Cohort

United Kingdom

Long-term Care and Assisted Living (BCMA)

To evaluate BCMA management system designed to improve drug administrations in residential and nursing homes, including comparison of error rates and staff awareness in both settings.

Comparison 2 settings (nursing home and

residential home)

• MAE rates • Staff Awareness of MAEs

Cross-sectional pre-study survey Survey of n=45 staff members Chart Review

• 1.2% of medication administrations demonstrated a potential MAE error that was averted

• Residential home staff were more aware of near misses compared to Nursing home staff.

Grey Literature Search

Medication Administration Errors; Benefits/ Challenges

Dibert et al. 58 2012

Case Study United States

Assisted Living (eMAR)

To demonstrate the implementation of eMAR and the reasons and implications of introducing the system

• The impact of eMAR in assisted living

Observation n=11 Assisted Living Facilities

• Medication error rates decreased 212/year pre- implementation (2010) to 20/year (2011) and 17/year (2012) post-implementation

• Improved ability to track and monitor medication use • Improved quality measures:

• PRN medication use and documentation of effectiveness

• Timeliness of medication delivery at passes • Documentation of parameters.

Grey Literature Search

Medication Administration Errors; Benefits/ Challenges

Pratt59 2014

Case Study

United States

Assisted Living (eMAR)

To report on the goals established in an eMAR implementation project.

• Reduced medication error rate • Achievement of a more complete

EHR • Workflow efficiencies • Regulatory compliance. • Caregiver accountability • Resident/workforce safety • Mitigation of drug diversion

Observation n=1 Assisted Living Facility

• Error rate decreased to 0.011% (2014) from 0.072% (2013) Med errors before eMAR 192/yr vs. 31/yr after eMAR

• EHR is more complete with eMAR • 10 less nursing hours required per month for medication

reconciliation at month end. • 1 hour less per day reviewing paper MARs not signed

off or resolving paper MAR discrepancies. • Permits ease in demonstrating regulatory compliance. • Built in accountability feature increases patient safety. • eMAR can detect and mitigate diversion. • Staff login with unique credentials. Dashboard alerts that are outside required practice.

Grey Literature Search

Perceived MAEs; Benefits/ Challenges

Potter36 2014

Qualitative United States

SNF (eMAR)

To explore perceptions and concerns of RNs regarding safe medication administration in SNFs

Nurse satisfaction with current medication administration systems.

• Perceptions and concerns of RNs regarding safe medication administration in SNFs

• RN satisfaction with current medication administration systems

Interviews n=6 Registered Nurses

(experience with eMAR)

eMAR Benefits: • eMAR was safer than paper MAR • Provided better information regarding medications and

administration times • Convenience • Decreased medication errors and improved residents'

safety Challenges: • “Time management” was the same. • Difficulties adjusting to eMAR. • Lack of IT reliability

Medical Database Search

Perceived MAEs; Benefits/ Challenges;

Kramer et al. 56 2009

Case Study United States

Nursing Homes and Home Health Agencies (eMAR)

Understand how HIT tools are being used in NH and HHA. Identify the costs and benefits associated with HIT. Develop data collection and analysis plan to assess the costs and benefits.

• Benefits and negatives of eMAR

Interview n=unknown

Benefits: • Improved workflow resulting in time saving in

medication administration. Reduced from 9 hours per 12 hour shift, to 6 hours per 12 hours shift

• Monthly medication reconciliation time was reduced from several days per month, to less than an hour.

• Updating the eMAR immediately saved money and improved safety by reducing discontinued medications being ordered or administered.

• Improvements to error rates. • Improvement in staff compliance with medication

monitoring and helped reduce missed labs and other orders.

Negatives: • eMAR hard to navigate

Grey Literature Search

Benefits/ Challenges

Mohamoud et al. 51 2009

Report United States

Nursing Homes (eMAR)

A report summarizing the key challenges noted, solutions identified, and lessons learned by AHRQ funded projects implementing health IT in LTCF.

Project InfoCare

• BCMA implementation barriers, lessons learned and best practices emerging from Project InfoCare

Unknown Barriers: • Resident identification wristbands were an issue due to

dignity and skin integrity. • Little incentive of pharmacies to participate.

Grey Literature Search

Research Outcomes Authors Type of

Study Country Setting Purpose Relevant Measured Outcomes Methods Results/Relevant Findings Source

Benefits/ Challenges

Klinger et al. 54 2010

Case Study United States

Nursing Homes (HIT/eMAR)

To establish the lessons learned from HIT demonstration in New York Nursing homes.

• On time administration of medications uptake of ePMMS by GPs

Survey n=unknown Interview n=unknown

• 99% of medication and treatments administered on time

Grey Literature Search

Benefits/ Challenges

Campbell et al. 60 Unknown Date

Case Study Canada Nursing Home (eMAR)

To demonstrate the implementation of eMAR

• Does eMAR minimize errors, improve documentation and enhance communication?

Observation n=1 Nursing Home Interview n=unknown Chart Review

Benefits: • User friendly; “Quick & easy to use” • Easier information access • Complete documentation • Enhanced communication • Error prevention and safe care: “Harder to make

mistakes” “Easier to identify residents” Report functions

Grey Literature Search

Benefits/ Challenges

Ko et al. 62 2016

Qualitative United States

Nursing Homes (eMAR)

To characterize the effect of HIT on workforce perceptions and care processes, the training needs associated with HIT implementation and the infrastructure needed for the workforce to effectively use HIT.

• Benefits of eMAR Interview n=15 nursing home staff where

HIT was present Focus Groups n=2 focus groups (6 nursing

home staff)

Benefits: • HIT Shortened the time to complete medication

administration. (No specifics on type of HIT) • Easier to see medications and treatments (no specifics

on type of HIT)

Grey Literature Search

Benefits/ Challenges; Prevalence/ Uptake

Hudak et al. 45 2007

Mixed Methods

United States

SNF and AL (eMAR)

To determine the current state of HIT planning and adoption in LTCF in California.

What are the perceived benefits and barriers?

What should providers, policymakers, and community stakeholders know and do to support HIT adoption and successful se in LTCF?

• Prevalence of eMAR in LTCF • Barriers of HIT implementation • Drivers of HIT adoption

Literature Review Focus Groups/Interviews n=unknown Survey n=80 SNF, n=18 AL

eMAR implementation within SNF/AF: • Implemented: 18%/ 22% Barriers to HIT implementation • Lack of capital resources, difficulty in finding HIT that

meet their need, lack of evidence of HIT and quality of care and operational efficiencies, risk of new state/federal requirements, lack of hardware and IT staff.

Reference List

Prevalence/ Uptake

Maestro46 2007

Cross-sectional Survey

United States

Nursing Home (eMAR)

To cover information technologies’ impact on organizational strategy, address how LTCF organizations are planning for and managing IT, define level of capital and operating budgets dedicated to IT, and explore various operating models of IT

• Prevalence of eMAR in LTCF Survey n=36 AHCA multi-facility members

eMAR implementation in Nursing Homes • Implemented: ~22%

Reference List

Prevalence/ Uptake

Stratis Health47 2008

Cross-sectional Survey

United States

Nursing Home (eMAR)

To determine the level of HIT use in Minnesota nursing homes

• Prevalence of eMAR in LTCF Survey n=297 nursing homes

eMAR implementation in Nursing Homes • Implemented: 49% • Rural homes: 55.9% • Urban homes: 41.7% • Not for profit: 53.4%, for profit: 36% Part of a chain: 59%

Reference List

Prevalence/ Uptake

ASCP48 2009

Cross-sectional Survey

United States

Pharmacy (eMAR)

To provide insight into the senior care pharmacy marketplace

• Prevalence of eMAR in LTCF Pharmacy providers

Survey n=unknown Pharmacy providers

eMAR implementation within Pharmacy providers: Implemented: 18%

Reference List

Prevalence/ Uptake

Murray53 2015

Correlational United States

Nursing Homes (eMAR) (BCMA)

To examine the relationship between NH quality of care as measured by CMS Quality Rating Scores and adoption of HIT in Minnesota NHs

• Prevalence of eMAR and BCMA Cross-sectional Survey n=217 Nursing Homes which

have EHR

Prevalence: • 36% of NHs have eMAR, 48% • 6% BCMA have eMAR • Significant correlation with small effect size for

medication administration (among other outcomes) and CMS quality rating.

Grey Literature Search

Prevalence/ Uptake

Oregon Office of Health Information Technology 55 2011

Cross-sectional Survey

United States

Long-term Care (eMAR)

To determine the technology integration currently existing in Oregon LTCF and to identify what challenges exist to expanding the use of HIT in LTCF.

• The extent of eMAR uptake in Oregon LTCF.

Cross-sectional Survey n=116 LTCF

● 22% of facilities have eMAR. ● 41.9% of facilities with EHR have eMAR.

Grey Literature Search

Research Outcomes Authors Type of

Study Country Setting Purpose Relevant Measured Outcomes Methods Results/Relevant Findings Source

Prevalence/ Uptake

Bergstrom et al. 61 2012

Cross-sectional Survey

United States

Nursing Homes (eMAR and BCMA)

To assess adoption, use and exchange of HIT

• Prevalence of eMAR and BCMA Cross-sectional Survey n=217 Nursing Homes which

have EHR

Prevalence: • 36% of NHs have eMAR, • 6% of NHs have eMAR

Grey Literature Search

Prevalence/ Uptake

CCLC64 2006

Cross-sectional Survey

United States

Long-term Care (HIT/eMAR)

To understand the current state of HIT efforts in LTCF including successes and challenges, and determine current and future HIT priorities in LTCF

• Prevalence of eMAR

Cross-sectional Survey n=34 LTCF organizations

Prevalence: 21% of LTCF have eMAR

Grey Literature Search

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CHAPTER 3

Evaluation of Medication Incidents in a Long-Term Care Facility Utilizing Electronic Medication Administration Records and Barcode Technology

Andrew E.C. Fuller BSc.Pharm1

Lisa M. Guirguis, PhD1

Cheryl A. Sadowski, B.Sc. (Pharm), Pharm.D., BCGP, CSHP1

Mark J. Makowsky, BSP, PharmD1

Author Affiliations

1 Faculty of Pharmacy & Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta,

Canada T6G 1C9

Corresponding Author:

Mark J. Makowsky, BSP, PharmD

Associate Professor

Faculty of Pharmacy and Pharmaceutical Sciences,

3-171 Edmonton Clinic Health Academy, University of Alberta

11405 87 Avenue, Edmonton, Alberta, T6G 1C9, Canada.

Tel.: 780 492 1735; fax: 780 492 1217; e-mail: [email protected]

Disclosures: Andrew Fuller: At the time of writing, is Manager of Health Benefits,

Pharmaceutical and Health Benefits Branch, Alberta Health. He was employed by the contracted

community pharmacy for the participating site between 2014 and 2019, holding positions as staff

pharmacist from 2014 to Nov 2017, Clinical Operations Manager from Nov 2017 to December

2018, and staff pharmacist until January 31st, 2019.

Abstract Word Count: 343; Text Word Count: 5,645; Tables: 5; Figures: 1; Appendices: 3;

References: 63

ABSTRACT

Background: Electronic medication administration records (eMAR) with barcode scanning

(BCMA) may increase the safety of medication administration in long-term care facilities

(LTCF), but supportive evidence is lacking.

Objectives: To evaluate the frequency, type, and severity of reported medication incidents within a

LTCF that utilizes eMAR-BCMA and further explore the characteristics of medication incidents and

the residents who experience them.

Methods: Retrospective review of paper-based, medication incident reports submitted

voluntarily between June 2015 and October 2017 at a 239-bed designated assisted living facility,

in Edmonton, AB, Canada. Using a standardized template, a single reviewer abstracted data from

each medication incident report and classified incidents according to medication-use phase, error

type, severity and medications involved based on established definitions. Content analysis was

used to summarize reported factors that led to a medication administration incident (MAI).

Results: A total of 270 medication incidents reports involving 154 residents were reviewed.

There was a total of 175 (66.3%) MAIs, where missed medication (46.3%) and incorrect time

(24.6%) were the most common error types. Temporary harm occurred in five (2.9%) MAIs, and

83 (47%) reached the resident and required intervention. Opioids, antihistamines, insulin, and

anxiolytics were involved in incidents that caused temporary harm and high-alert medications

were involved in 17.7% (n=31) of all MAIs. Suboptimal medication administration processes

(54.9%; n=96) and communication within the facility or with the community pharmacy (18.9%;

n=33) were the most common factors that led to MAIs. Residents experiencing multiple MAIs

were younger (61.6±13.3 vs. 74.6±17.4 years) than those experiencing one MAI and were more

likely to reside on non-secure than secure units (55.7% vs. 14.6%; RR: 3.81; 95% CI: 1.89, 7.73;

p<0.001). Medication incidents reported with multiple medication error types were more severe

than those with a single error type.

Conclusion: Our study illustrates that MAIs still occur despite implementation of an eMAR-

BCMA system. The frequency and types of MAI were similar to LTCF not utilizing eMAR-

BCMA; however, few incidents led to patient harm. A prospective, pre-post implementation

study is required to robustly assess the impact of eMAR-BCMA on medication administration

incidents in LTCF.

3.1 Background Long-term care involves a variety of services designed to help people live as independently and

safely as possible when they can no longer perform everyday activities on their own.1 The

majority of long-term care is provided within nursing homes and other assisted living facilities

offering on-site personal care and services.2 Over 300,000 Canadians and 2.2 million Americans

resided in nursing homes or other assisted living facilities in 2011–14.3-5

A medication incident, also defined as a medication error, is any preventable event that may

cause or lead to inappropriate medication use or resident harm while the medication is in the

control of the health care professional, resident, or consumer.6, 7 Medication incidents can

occur at any stage in the medication use process such as prescribing, transcribing, dispensing,

administration, communication/documentation and monitoring.6, 8, 9 Effective medication

incident reporting and analysis is a key element in establishing safe medication use systems.10

The systems approach views most errors as predictable human failings in the context of poorly

designed systems, rather than treat errors as failings on the part of individual providers.11

However, optimizing safety through effective learning systems requires a just culture of patient

safety, which finds a balance between a punitive culture which disciplines all deviations from

standard operating procedure and a blame-free culture where all behavioral choices are

forgiven. Providers must feel safe, encouraged, and enabled to discuss quality and safety

concerns in order to learn from everyday errors and allow for systems to be designed to be less

error prone and more error tolerant.12

Despite ongoing efforts to improve patient safety in LTCF, a recent systematic review found that

medication incidents occur in 16% to 27% of LTCF residents.13 Additional studies have

reported medication administration incident (MAI) rates of 3% to 53%.9, 14-21 Up to 12.6% of

medication incidents cause harm,8, 18, 22, 23 where the majority are due to medication

administration.18, 22, 23

LTCF have adopted electronic medication administration records (eMAR) and barcode assisted

medication administration (BCMA) technology to address MAIs, where close to 50% of LTCF

in some American jurisdictions utilize this technology.24 Pharmacies that service LTCF have a

reported uptake of 18%25 to 23.3%.26 In contrast, hospital environments in the U.S. have eMAR

and BCMA uptake of more than 88%27 where it has demonstrated to reduce the overall incidence

of MAIs, improve medication administration, and improve the detection of medication

incidents.28, 29

We recently completed a scoping review on the effectiveness, use and perceptions of eMAR-

BCMA in LTCF. We found limited evidence linking eMAR-BCMA use and reduction in

medication incidents; in addition to, evidence of new types of medication incidents resulting

from nursing staff workarounds, inconsistent influence on nursing time spent during medication

administration and an array of perceived benefits and challenges.30

In order to explore medication safety issues that occur despite the use of eMAR-BCMA

technology and facilitate learning and quality improvement around the medication use process,

we conducted a small-scale evaluation within a 239-bed designated assisted living facility in

Edmonton, AB, Canada which implemented an eMAR-BCMA system in 2013. The main

purpose of this study was to characterize the frequency, type and severity of reported medication

incidents and MAIs. Additionally, we determined if medication incidents were more commonly

reported on secure or non-secure units, investigated characteristics of residents that experienced

multiple medication incidents, and explored factors that influence medication incident severity.

3.2 Methods A retrospective review of voluntarily submitted, paper-based, medication incident reports within

the LTCF was completed. The medication incident report is an internal document completed by

nursing staff and is used as per facility policy for quality improvement/assurance and for external

reporting to the LTCF governing body. In Alberta, LTCF that are supported by Alberta Health

Services, are required to report medication incidents that could or do result in an unintended

injury to a resident.31 This anonymous data is used to identify risks to resident safety for the

purpose of organizational learning. The medication incident report utilized within the study

LTCF includes the date, time and the person(s) involved, medication error type, injuries/adverse

reactions, the description of the medication incident, and team leader/resident care manager

follow-up (See Appendix 3.1 for the full Medication Incident Report form).

3.2.1 Facility Background The study site is affiliated with a large conglomerate that consists of over 30 LTCFs throughout

the provinces of Alberta and British Columbia. It contains five residential units, of which two

are secure units for residents with significant cognitive impairments including dementia. The

majority of residents live within the three non-secure units. All medications are administrated by

Healthcare Aids (HCA) and Licensed Practical Nurses (LPN) within four designated medication

administration times (0800/1200/1700/2100) where nursing staff have a 2-hour window to

administer the medication.

During the study period, the site utilized a single outside pharmacy provider for the dispensing

and distribution of all prescription and non-prescription medications. The pharmacy was an

affiliate within a nationwide pharmacy chain with multiple retail centers across Canada that

offers medication distribution and clinical services to patients, customers, and private care

facilities. The implementation of the eMAR-BCMA system was financially supported by the

dispensing pharmacy and was introduced to the LTCF as a value-added service in 2013.

Ongoing maintenance and nursing staff training was also provided by the dispensing pharmacy.

One member of the investigator team (AF) was employed by the contracted dispensing pharmacy

as a staff pharmacist and acted as the onsite clinical pharmacist at the study LTCF two days a

week from August 2014 to November 2017. The onsite clinical pharmacist roles and

responsibilities consisted of conducting medication reconciliation and reviews, participating in

multidisciplinary care conferences, acting as a drug information resource for LTCF staff and

residents, and providing support in the assessment of medication incidents and associated

interventions if they occurred while the pharmacist was onsite. AF acted as the Clinical

Operations Manager of the pharmacy chain from Nov 1st, 2017 to Dec 1st 2018, and was

involved in implementation of eMAR-BCMA systems with LTCF across Alberta during this

time, but had no role in the implementation of the eMAR-BCMA system at the participating site

The eMAR-BCMA system in use is oneMAR (Catalyst Healthcare, Kelowna, BC) and consists

of an online resident medication profile and resident specific barcoded medication packaging.

Data management and packaging is completed centrally by an outside community pharmacy. All

documentation outside of medication administration is found within paper medical charts and the

site does not use an electronic medical record (EMR) or computerized physician order entry

(CPOE). The eMAR provides access to a residents’ profile, including medical conditions,

allergies, vitals and the most current medication list. During medication administration, the

nursing staff member scans the residents’ mediation using a hand-held device (BCMA) which

presents the resident profile on the eMAR. This visually confirms the identification of the

resident. HCAs confirm the number and visual description of each unit dosed oral medication

within the packaging and review the specific administration directions for topical therapies.

LPNs confirm the same; however, they must review the administration directions regardless of

formulation and are responsible for administering all high-risk medications. Warnings within the

eMAR-BCMA inform nursing staff of an incorrect resident profile or incorrect administration

processes if the wrong barcode is scanned or if it is scanned outside of any parameter. Using a

unique username and password, nursing staff sign off on medication administration using the

eMAR system. After each designated medication administration time, the lead nurse generates

an eMAR shift audit report which informs nursing staff which medications for that designated

time were not signed off as administered on the eMAR. Nursing staff can then complete the

administration of the missed medications, or the medication can be signed off as administered in

instances when the nursing staff administered the medication but failed to sign it off as

administered.

3.2.2 Inclusion/Exclusion Criteria & Data Access All medication incident reports submitted between June 2015 to October 2017 were eligible for

review. As per facility policy, medication incidents reports are maintained for 2 years, and

reports submitted at the study site prior to June 2015 were no longer available, while a new

community pharmacy was contracted to provide pharmacy dispensing services starting

November 1, 2017. Medication incidents that were discovered and documented at the dispensing

pharmacy or outside of the LTCF were not studied. A research agreement was created with the

LTCF to allow access to the medication incident reports. The study was approved by the

University of Alberta Research Ethics Board.

3.2.3 Data Abstraction A single investigator who is a registered clinical pharmacist (AF) reviewed all original

medication incidents reports submitted within the LTCF onsite in June 2018 and January 2019

and extracted relevant information into two standardized data collection forms hosted on the

REDCap secure web-based database platform at the University of Alberta. Medication error

type and injuries/adverse reactions were abstracted based on self-reported data from the nursing

staff at the time the incident occurred. Options for error type included incorrect resident,

incorrect medication, incorrect time, incorrect dose, incorrect route, missed medication,

medication expired, pharmacy error, documentation error/omission, or other and injuries/adverse

reactions were recorded as yes, no, or unknown (i.e., missing). (Appendix 3.1)

The investigators adjudicated each medication incident report and categorized them according to

medication-use phase(s) and severity/perceived harm to the resident. Medication-use phases

included: prescription, transcription, dispensing, administration, communication/documentation

and monitoring.6 Resident self-prescribing and self-administration were defined as prescribing

and administration medication-use phases respectively.32 To support categorization of the

severity of each medication incident report, the NCC MERP Index for Categorizing Medication

Errors and associated Algorithm33, 34 were utilized. This categorization method has been

employed in previous studies evaluating medication incident report severity.21, 22, 35-39 (see

Appendix 3.2) For instances where the investigator (AF) was uncertain of the medication-use

phase or NCC MERP severity, a second clinical pharmacist investigator (MM) independently

reviewed the medication incident report and final categorizations were achieved by consensus.

Each medication incident report may have involved more than one medication error type or

medication-use phase.

Narrative free-text descriptions of each incident were reviewed to categorize each according to

the medication involved, the primary personnel involved, and the LPN Team Leader and

Resident Care Manager follow-up. Medications were categorized according to the ISMP List of

High Alert Medications in Long-term Care40 and the Anatomical Therapeutic Chemical and

Metabolism/Defined Daily Dose (ATC/DDD) Index.41 Primary personnel involved in the

incident were categorized as nursing staff, pharmacy, eMAR-BCMA, prescriber, and resident.

Two investigators (AF, MJM) conducted content analysis as described by Schreier to

systematically categorize the reported factors that led to MAIs and dispensing errors.42 Initially

we planned to use a concept-driven approach based on Reason’s model of accident causation,

however, because the descriptions of the medication incident were reviewed retrospectively it

was difficult to categorize the reported factors as being related to latent conditions or active

failures11, 43 Therefore we employed a data-driven approach to create a list of categories that

related to the factors interpreted as being influential to MAIs and dispensing errors. An iterative

approach was utilized to create and assign each individual medication incident report into

categories and associated sub-categories based on what was reported within the description of

each medication incident report. Categories were first developed by reading the description of a

medication incident report until a relevant concept was encountered. If the concept and related

category was not yet developed or was not found previously, a new category was created and the

medication incident report was assigned to it. If the concept and related category was already

created or found in a previous medication incident report, the medication incident report was

assigned to that category. This process was repeated for the development of respective sub-

categories for each main category. Category and sub-category definitions were created which

included a description, definition, indicators and examples to support appropriate categorization

for each medication incident report. To ensure that sub-categories within one main category

were mutually exclusive and to prevent uncertainty in categorization for sub-categories that

could potentially overlap, decision rules were added. Once the categories and sub-categories

were finalized, both investigators independently reviewed the description of each medication

incident report again and re-assigned each medication incident into its respective category and

sub-category. Final categorizations were achieved by consensus. (See Appendix 3.3 and 3.4.)

The investigators did not have access to the eMAR system itself, number of medications

administered, the occupancy rate, or the total number of residents who lived within the LTCF

during the study period.

3.2.4 Data Analysis The data collected is presented into two categories, data from all medication incident reports

(which includes each medication-use phase) and data from MAIs only. STATA (version 15,

Statcorp LLC, College Station Texas) was used for all statistics. Descriptive statistics were

recorded as means and proportions as appropriate. Post-hoc analyses were conducted to explore

differences in medication incident and MAI occurrence per month between non-secure and

secure units and between shifts (0700-1500, 1500-2300, 2300-0700). Due to differences in

resident capacity between non-secure and secure units, we further explored the differences in the

mean proportion of residents involved in a medication incident and MAI between units. This

was based on the residents’ first reported medication incident of the month. We investigated

differences in resident characteristics (age, gender and unit) for those who experienced one

medication incident vs. multiple incidents and for those who experienced a non-MAI vs. one-

MAI vs. multiple-MAIs. Lastly, we explored differences in medication incident severity using

both mean severity score and a dichotomized severity grouping (Did not reach resident [NCC

MERP severity 1-2] and did reach resident ([NCC MERP severity 3-9]) for medication incidents

that contained one vs. multiple medication error types, one vs. multiple medication-use phases,

that were reported within vs. after 24 hours of occurrence, and that were reported between

nursing shifts.

Student t-tests and one-way ANOVA tests were used to determine differences in means.

Shapiro-Wilk tests and analysis of Q-Q plots were used to ensure that mean scores in each group

were sufficiently distributed to allow the use of parametric tests. Chi-squared tests were used for

categorical cross-tabulation tests, and Fisher’s exact was used when sample sizes were small.

Significance was set at a = 0.05. The Bonferroni Correction was applied to correct for multiple

statistical calculations for post-hoc tests across multiple groups, where a statistical significance

of a = 0.017 was used for three group comparisons.

3.3 Results

3.3.1 Medication Incident Reports Over the 29-month study period, 270 medication incidents were reported and all were analyzed

in this study. None were excluded. Six were non-resident specific and included incorrect

narcotic counts (n=4) and eMAR-BCMA software issues (n=2). These are not further included

in the descriptive nor the post-hoc data analysis. A longitudinal breakdown of the number of

medication incidents and MAIs reported per month is shown in Figure 3.1.

3.3.2 Resident Characteristics The 264-resident specific medication incident reports impacted 154 residents and on average

each of these 154 residents experienced 1.71 medication incidents. The majority of residents

with medication incidents were women (63.0%) and most residents experiencing medication

incidents resided on the non-secure units (68.8%). The mean proportion of residents involved in

a medication incident per month based on unit capacity (4.49%±1.68 vs. 2.05±1.53, p<.001) and

a MAI per month (2.93%±1.35 vs. 1.50%±1.49, p<.001) was statistically higher in non-secure

than secure units. (Table 3.1)

3.3.3 Medication Incident Report Characteristics The characteristics of the 264 reported medication incidents are shown in Table 3.2. The

majority of medication incidents were reported on the non-secure units (n=207; 78.4%). The

medication administration-use phase was involved in 66.3% (n=175) of all medication incidents.

On average, 9.10±3.54 medication incidents were reported at the facility per month, of which

6.03±2.83 were MAIs. The most common medication error types reported by the nursing staff

included missed medications (32.6%, n=86) and pharmacy dispensing error (23.5%, n=62).

Missed medication (46.3%, n=81) and incorrect time (23.4%, n=41) were the most common

MAIs. The majority of medication incidents were reported within 24 hours of occurrence

(81.4%, n=215). The nursing staff reported that an injury or adverse event occurred in six

(2.3%) medication incidents (n=5 were due to medication administration and two of these were

resident self-administration medication incidents) and this was consistent with the categorization

of severity done by the investigator. The investigators determined that 160 medication incidents

(60.6%) reached the resident (NCC-MERP 3-9) and intervention was required for 55.6% (n=89)

of them. Similarly, 145 MAIs (82.3%) reached the resident and 57.2% (n=83) required

intervention. No permanent harm or deaths as a result of medication incidents were reported.

3.3.4 Medications Involved with Medication Incident Reports Over 28% of medication incident reports did not specify which medications were involved.

However, ISMP high alert medications were involved in 48 medication incidents (18.2%) and 31

MAIs (17.7%), where opioids (9.5%; 8.0%) and anticoagulants (4.2%; 4.6%) were the most

common medications documented within medication incidents and MAI reports respectively.

Antipsychotics (9.1%; 10.3%) and anti-infectives (7.6%; 8.6%) were the most common non-

ISMP medications. Opioids (n=2), antihistamines (n=1), insulin (n=1), and anxiolytics (n=1),

were involved in the medication incidents that caused resident harm and in one case the

medication involved was missing.

3.3.5 Primary Personnel Involved & Incident Follow-up Nursing staff were involved in the majority of medication incidents (68.2%; n=180), followed by

the dispensing pharmacy (28.4%; n=75). The most common response by the LPN Team Leaders

or Resident Care Managers post medication incident was providing education to those involved

(58.3%; n=154). (Table 3.2.)

3.3.6 Content Analysis: Factors Leading to MAIs and Dispensing Errors As shown in Table 3.3., content analysis for the factors that led to MAIs resulted in the creation

of five main categories, with 15 associated sub-categories. The main categories consisted of

medication administration processes with eMAR-BCMA, medication packaging, environmental

issues and internal/external factors, communication, and other/not available. Content analysis for

the factors involved in dispensing errors resulted in the creation of two main categories and five

sub-categories. The main categories included pharmacy packaging and delivery, and other/

unknown. The full description of the categories and sub-categories can be found in Appendix

3.4. The most commonly reported factors that led to MAIs included nursing staff not reviewing

the eMAR and/or the medication prior to administration, signing off medications as administered

but not actually being administered, problems with providing leave of absence (LOA)

medications, and issues with order communication. The reported factors that led to MAIs that

caused harm included resident self-administration issues (n=2), medications administered but not

signed off (n=1), distracted during medication administration (n=1), and issues with order

communication within facility or between facility and pharmacy (n=1). Issues with packaging,

delivery or eMAR-BCMA barcodes, were the most common factors involved in dispensing

errors. The medication incident involving pharmacy dispensing that caused harm was

categorized as medication packaging error (n=1).

3.3.7 Characteristics of Residents with Multiple Medication Incidents Of the 154 residents, 66 (43.4%) experienced multiple medication incidents and 37 (24.0%)

experienced multiple MAIs. (Table 3.4.) Residents with multiple medication incidents were

significantly younger vs. those with a single medication incident, (61.6±13.3 vs. 74.6±17.4,

p<.001) and a similar pattern was seen for residents with multiple MAIs vs. a single MAI

(59.9±15.8 vs. 73.2±16.2 p<.001). A larger proportion of residents with multiple medication

incidents (55.7% vs. 14.6%, p<.001) and MAIs (20.8% vs. 10.4%, p=0.013) lived in non-secure

units. Residents residing on non-secure units were 3.81 times (95%CI: 1.89, 7.73) more likely to

have multiple medication incidents reported than those on secure units.

3.3.8 Severity of Medication Incidents Compared to medication incidents coded with a single error, those that involved multiple error

types had a greater mean severity score (3.28±1.28 vs. 2.66±1.15 out of 9; p<.001), where a

medication incident with a severity score of three reached the resident but did not cause harm.

Similarly, incidents coded with multiple error types were more likely to have reached the

resident (76.1% vs. 57.3%, p=0.02; RR: 1.33; 95% CI: 1.09, 1.62). (Table 3.5.) There was no

difference in severity scores for medication-use phase, shift, or time to error report.

3.4 Discussion This study retrospectively explored 29 months of medication incident reports from a single

LTCF to explore medication safety issues that occur despite the use of eMAR-BCMA for

medication administration and identify opportunities for quality improvement in medication

safety. On average there were approximately nine medication incidents reported per month and

the majority were from the three non-secure units. Once we accounted for the difference of

resident capacity between the units, there was a greater mean proportion of non-secure residents

exposed to a medication incident and MAI per month. Medication administration, dispensing,

and communication/documentation were the most common medication-use phases involved.

Missed medications and incorrect time were the most commonly reported medication error types

by nursing staff for MAIs. There were six mediation incidents that led to an injury and over half

of MAIs reached the resident and were determined by the investigator to require monitoring to

confirm no harm or interventions to preclude harm. The medications involved were poorly

documented with almost 30% of medication incidents being unknown. The medications

involved in the six cases which the residents were harmed include opioids, insulin, antihistamine,

anxiolytic, and in one case, unknown medications. Nursing staff and the dispensing pharmacy

were the primary personnel involved in medication incidents. Medication order communication

and inadequate medication administration processes, such as not reviewing the eMAR or

medication prior to administration, signing off medications but not administering them, and

issues with LOA medications, were the most commonly reported factors leading to MAIs. The

residents who experienced multiple medication incidents or multiple MAIs were younger and

more likely to reside on non-secure units. Finally, while there were no delays in reporting more

severe incidents and incident severity did not differ between AM and PM designated medication

administration times, medication incidents coded with multiple error types were rated by

investigators as being more severe.

Despite data that suggests high levels of uptake of eMAR and BCMA in LTCF in some

American jurisdictions24 and evaluations of potential MAIs in LTCF using a BCMA system in

the United Kingdom,44 there is a paucity of published reviews of medication incidents in LTCF

using eMAR- BCMA. In contrast, the review of medication incident reports and eMAR-BCMA

data within hospital environments has been studied extensively.28, 29, 37, 45-47 Notably, several

published papers exploring medication incidents using data from state wide web-based incident

reporting system for nursing homes are available but they are limited in that the proportion of

facilities that use eMAR-BCMA in these reports is unclear.8, 22, 23, 48, 49 Even though medication

incidents can occur at any stage of the medication use process, previous studies found that

medication administration was involved in the majority of medication incidents.8, 18, 22, 48-50

Missed medications, incorrect time, incorrect dose, documentation and dispensing errors were

the most common error types described by nursing staff and found in earlier studies.8, 18, 22, 23, 35,

50 While these studies are comparable to ours in that they rely on voluntarily reported data and

evaluated medication-use phases and error types within LTCF, again the proportion using

eMAR-BCMA is not reported. Using disguised observation and analysis of BCMA records

within multiple LTCF, Szczepura et al. determined that incorrect time was the most common

potential medication error type for MAIs.44 eMAR shift audit was only documented twice as a

medication error type by nursing staff. The eMAR shift audit report is generated after each

designated medication administration time to prevent missed medications; however, in our study

missed medications were still documented in 46.3% of MAIs.

We determined that 47% of MAIs reported in our facility reached the resident and required

monitoring or intervention by the nursing staff, which is considerably greater than that reported

by others.18, 23 We found a low incidence of medication incidents that led to resident harm

(2.2%), whereas previous studies report up to 12.6%.8, 22 For example, through a web-based

medication incident reporting tool in North Carolina, Greene et al. found 11% of medication

incidents were serious (as described as NCC MERP 4-9).23 Additionally, Baril et al. determined

that the number of medication accidents (as described as NCC MERP 4-9) decreased

significantly after medication distribution technology (not eMAR or BMCA) was implemented

in six Quebec nursing homes.35

Similar to our findings, high alert medications, such as opioids and insulin have been

documented as common medications that cause serious resident harm in LTCF when

administered in error.18, 23, 49, 51 Additionally, antipsychotics have been reported to be associated

with a high incidence of ADEs in LTCF.49, 51 Hansen et al.52 report a similar frequency of

medication incidents causing resident harm based on the Beers Criteria medication list.53

Review of the narrative descriptions of medication incidents suggested that improper medication

administration processes were a common factor leading to MAIs, the dispensing pharmacy

played a significant role in the number of medication incidents, and the distribution of leave of

absence (LOA) medications to a resident was also a common factor that led to medication

incidents in our study. When analyzing these factors, it is important to fully consider them in the

context of the systems approach where issues such as the environment, working conditions,

distractions, management decisions, and limitations in the drug distribution systems may result in

the manifestation of these incidents.54, 55 While many of the descriptions of reported factors that

follow appear to focus on shortcomings on the part of individual providers, because of the

retrospective nature of our study, we were not able to evaluate the causative factors in depth and

differentiate those occurring as a result of flaws in the underlying system or as a result of

behavioral choices.56 For example, there were many instances where LPNs and HCAs were

scanning and signing off a medication as administered; however, the medication was not actually

given. Additionally, reports indicated that the LPNs were not reviewing the eMAR to confirm

when the last as needed (PRN) dose was administered or the specific PRN directions, therefore

preventing either an early dose or administering an incorrect order. In our study, there were also

examples of MAIs where nursing staff administered medications prior to scanning the barcode,

thus not confirming medication correctness or allowing the safety warning prompt to appear.

Similar workarounds with eMAR-BCMA technology in LTCF have been reported by others.16, 57

Communication issues within the LTCF and between the LTCF and the pharmacy contributed to

MAIs, which has also been reported previously.8, 44

The dispensing pharmacy played a significant role in the number of medication incidents, where

the majority were related to medication packaging errors, such as missing or extra medications,

eMAR-BCMA operational issues and delivery problems. There were several medication

incidents where the medication was delivered to the LTCF, but the pharmacy did not include or

update specific barcodes or upload the medication orders into the eMAR, consequently

preventing the ability for the nursing staff to confirm correctness prior and during medication

administration. Further evaluation of the pharmacy’s operational challenges with eMAR-BCMA

could also be an area of future research and no published data exists on this topic.

The distribution of leave of absence (LOA) medications to a resident was also a common factor

that led to medication incidents in our study. Examples include providing an incorrect duration

of medication, either too short or too long, residents incorrectly self-administering the

medications when off site or non-routine medications being missed completely. LOAs are a

period of transition for both the resident and nursing staff, and could be similar to a hospital

discharge or a residents’ transition into a LTCF where residents are at a greater risk of

medication incidents.22, 48

Nursing staff and the dispensing pharmacy were reported to be the primary personnel involved in

the reviewed medication incidents and this information can help focus quality improvement

efforts aimed at preventing future medication incidents on the administration and dispensing

phases of the medication use process. LPNs have been previously documented to be involved in

59% to 69% of medication incidents,8, 18, 22, 23, 48 HCAs up to 12%8, 18, 23 and the

pharmacy/pharmacist up to 6% of incidents.8, 18, 23, 48

Post hoc, we explored medication incident and MAI frequency based on resident characteristics;

as well as, resident harm based on medication incident report characteristics. Non-secure unit

residents and younger residents were exposed to multiple medication incidents and MAIs more

frequently. The impact of repeat medication incidents has been studied previously where older,

cognitively impaired residents were more at risk.8 The reasons for this discrepancy are not clear,

but the study by Crespin et al. may be more generalizable as it included medication incident

report data from 294 LTCF, rather than a single site as in our study. We did not assess the

severity of repeat medication incidents in this study; however, studies have shown that repeat

medication incidents are more likely to cause resident harm versus non-repeat medication

incidents8, 48 Medication incidents with multiple error types (as defined by nursing staff) had a

greater mean severity score and a higher proportion reached the resident. The medication

incidents may have been more thoroughly documented as the medication incident reached the

resident and required an assessment or intervention.

Lastly, while it is difficult to make comparisons to other studies, we expected that the frequency

of MAIs may have been lower and the corresponding medication error types may be different

than those reported in previous studies that did not include eMAR-BCMA. In theory, the

prompts and safety alerts when the medication is scanned in error should warn nursing staff prior

to administration to prevent incorrect time, incorrect dose and incorrect resident medication error

types and the eMAR shift audit report should prevent missed medications. That being said, this

specific eMAR-BCMA software, does not have a safety warning for PRN medications when they

are administered early or too frequently. The LPN has to review the last documented

administration time within the eMAR in addition to the directions to ensure appropriateness.

Even though we did not assess the preventability of medication incidents as done in other

studies,21, 36, 44, 47, 58 it appeared that a significant proportion of medication incidents may have

been prevented, especially if more established procedures for administration were in place, as

illustrated by the failure to scan a medication prior to administration confirming the date and

time of each medication as indicated on the packaging or the number of LOA medication

incidents. There are many factors that influence medication administration processes, including

nursing staff workarounds with the eMAR-BCMA, which may be inhibiting the full optimization

of this technology.

3.4.1 Strengths Our study has two strengths. First, our methodology was robust as it was consistent with those

employed by others reporting descriptive statistics and severity categorization of medication

incident reports within LTCF and acute care settings. Second, few other studies have explored

differences in resident and mediation incident report characteristics and NCC MERP severity

classification.

3.4.2 Limitations However, our study has several limitations. First, medication incidents are universally

underreported by nursing staff in both LTCF and acute institutions.59-63 Thus the collected data

may not be reflective of the actual number of medication incidents that occurred during the study

period. Second, the medication incident reports showed signs of poor/inadequate reporting for

certain characteristics, particularly, the medication involved and injury/adverse reactions. Third,

medication incidents that are electronically tracked within the eMAR-BCMA software were not

collected. Review of a residents’ eMAR, could facilitate determination of the true number of

medication incidents including those that were administered outside of the 2-hour administration

window (i.e. incorrect time) and resident refusals (i.e. missed medication), which were not found

within the medication incident reports, or uncover new medication incidents that may not have

been reported, such as missed medications or early/inappropriate PRN administrations. That

being said, medication incidents detected by the eMAR-BCMA that were not documented, are

most likely to be of low clinical significance and pose minimal safety risks to a resident.47

Fourth, we did not have access to the number of medications dispensed and administered and the

exact number of residents living within the LTCF during the study period. This prevented us

determining the medication incident rate. Fifth, we were unable to determine if medication

incidents occurred during times of transition beyond LOAs, such as new admissions and hospital

discharges, where residents are known to be at a greater incident risk.22, 48 Sixth, previous

studies included medication incident report data from multiple facilities or state-wide, while our

study focused only on one LTCF which is likely not generalizable to other settings. Seventh,

unlike other studies, the small number of incidents and limited patient demographic information

precluded us from performing multivariate logistic regression to explore certain characteristics

related to an increased likelihood of a medication incident or resident harm.8, 22, 48 Eighth, we

only used retrospective data within the medication incident reports and we did not conduct

formal root cause analyses for reported medication incidents. Lastly, we cannot conclude that

eMAR BCMA technology influences medication safety due to the lack of medication incident

report data prior to eMAR-BCMA implementation.

3.5 Conclusion This analysis of medication incident reports adds to our knowledge concerning medication

incidents that occur despite implementation of eMAR-BCMA in a single LTCF. While it is

difficult to compare across institutions and contexts, MAIs appeared to be reported with similar

frequency rates when compared to other LTCF without eMAR-BCMA. However, the MAIs

were mostly of low severity. We identified several opportunities to optimize the use of eMAR-

BCMA and improve medication incident reporting at the participating facility. The majority of

medication incidents were related to improper medication administration practices and

dispensing errors and potential solutions should focus on how the eMAR supports medication

administration and processes around medication distribution and resident self-administration

during leaves of absence. A prospective study to address the most common factors identified in

both the LTCF and pharmacy would provide further understanding of optimal use of this

technology. Future study of eMAR data relating to MAIs could further assist in characterizing

un-reported and poorly reported medication incidents at the participating facility.

3.6 Glossary of Terms High Alert Medications – drugs that bear a heightened risk of causing significant patient or resident harm when they are used in error. Workaround – a method to overcome or bypass a problem or limitation in a program or system. As needed – the medication is requested according to need by the resident or patient (i.e. PRN as written in prescriptions)

Figure 3.1. Number of medication incidents and medication administration incidents reported over a 29-month period.

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Medication Incidents (Total) Medication Administration Incidents

Table 3.1. Resident Characteristics Number of Residents

with Medication Incidents

Number of Residents with Medication Administration Incidents

Resident Characteristics Number (%) Number (%) Total number of residents 154 (100.0%) 114 (74.0%) Age at time of first reported Medication Incident [years]

69.18 ± 16.91 68.88 ±17.15

Gender Female 97 (63.0%) 70 (61.4%) Male 57 (37.0%) 44 (38.6%)

Location of first reported Medication Incident Non-Secure Units a 106 (68.8%) 78 (68.4%) Secure Unitsb 48 (31.2%) 36 (31.6%) Age of resident at first reported Medication Incident [years]

Non-Secure Unitsa 61.76 ± 14.67 61.42 ± 14.62 Secure Unitsb 85.02 ± 9.02 85.03 ± 9.34 p-value P<.001 P<.001

Date of residents’ first reported Medication Incident June 2015 – September 2015 26 (16.9%) 22 (19.3%) October 2015 – January 2016 27 (17.5%) 17 (14.9%) February 2016 – May 2016 26 (16.9%) 22 (19.3%) June 2016 – September 2016 27 (17.5%) 19 (16.7%) October 2016 – January 2017 22 (14.3%) 16 (14.0%) February 2017 – May 2017 15 (9.7%) 12 (10.5%) June 2017 – October 2017 11 (7.1%) 6 (5.3%)

Mean number of residents involved in a Medication Incident per month Non-Secure Unitsa 6.52 ± 2.43 4.24 ± 1.96 Secure Unitsb 1.93 ± 1.44 1.41 ± 1.40 Mean proportion of residents involved in a Medication Incident per month (based on LTCF unit resident capacity)

Non-Secure Unitsa 4.49% ± 1.68 2.93% ± 1.35 Secure Unitsb 2.05% ± 1.53 1.50% ± 1.49 p-value P<.001 P<.001

Number of residents with repeat Mediation Incidents 6 Medication Incidents 2 2 5 Medication Incidents 4 4 4 Medication Incidents 4 4 3 Medication Incidents 16 15 2 Medication Incidents 40 31 1 Medication Incident 88 58

a Non-secure unit capacity (n=145) b Secure unit capacity (n=94)

Table 3.2. Medication Incident Characteristics Number of

Medication Incidents Number of Medication Administration Incidents

Medication Incident Report Characteristics Number (%) Number (%) Total number of Medication Incidents 264 (100.0%) 175 (66.3%) Location of Medication Incidents Non-Secure Unitsa 207 (78.4%) 134 (76.6%) Secure Unitsb 57 (21.6%) 41 (23.4%) Date of Medication Incidents

June 2015 – September 2015 31 (11.7%) 21 (12.0%) October 2015 – January 2016 40 (15.2%) 23 (13.1%) February 2016 – May 2016 43 (16.3%) 29 (16.6%) June 2016 – September 2016 44 (16.7%) 30 (17.1%) October 2016 – January 2017 39 (14.8%) 25 (14.3%) February 2017 – May 2017 32 (12.1%) 24 (13.7%) June 2017 – October 2017 35 (13.3%) 23 (13.1%)

Mean number of Medication Incidents per month LTCF 9.10 (+/-3.54) 6.03 (+/-2.83)

Mean number of Medication Incidents per month by LTCF unit Non-Secure Unitsa 7.14 (+/-2.96) 4.62 (+/-2.29) Secure Unitsb 1.97 (+/-1.50) 1.41 (+/-1.40) p-value P<.001 P<.001

Shift of Medication Incidents Shift 1 (0700-1500) 132 (50.0%) 80 (45.7%) Shift 2 (1500-2300) 120 (45.5%) 85 (48.6%) Shift 3 (2300-0700) 12 (4.5%) 10 (5.7%)

Mean number of Medication Incidents per month by shift Shift 1 (0700-1500) 4.55 (+/-2.37) 2.76 (+/-1.68) Shift 2 (1500-2300) 4.14 (+/-2.30) 2.93 (+/-2.10) Shift 3 (2300-0700) 0.41 (+/-0.63) 0.34 (+/-0.55) p-value (Shift 1 vs. Shift 2) P =.50 P=.47 p-value (Shift 1 vs. Shift 3) P<.001 P<.001 p-value (Shift 2 vs. Shift 3) P<.001 P<.001

Medication-use phases Prescription 4 (1.5%) - Transcription 2 (0.8%) - Dispensing 59 (22.3%) - Dispensing & Documentation/Communication 1 (0.4%) - Administration 153 (58.0%) 153 (87.4%) Administration & Prescription 1 (0.4%) 1 (0.6%) Administration & Dispensing 7 (2.7%) 7 (4.0% Administration & Documentation/Communication 13 (4.9%) 13 (7.4%)

Administration, Dispensing & Documentation/Communication 1 (0.4%) 1 (0.6%)

Monitoring 1 (0.4%) - Documentation/Communication 22 (8.3%) -

Number of medication-use phases within Medication Incidents One Medication-use phase 241 (91.3%) 153 (87.4%) Two Medication-use phases 22 (8.3%) 21 (11.9%) Three Medication-use phases 1 (0.4%) 1 (0.6%)

Medication Error Types within Medication Incidents (as documented by nursing staff) Incorrect Resident 2 (0.8%) 2 (1.1%) Incorrect Medication 7 (2.7%) 7 (4.0%) Incorrect Time 32 (12.1%) 31 (17.6%) Missed Medication 69 (26.1%) 65 (36.9%) Incorrect Dose 12 (4.5%) 11 (6.3%) Incorrect Route 1 (0.4%) 1 (0.6%) Expired Medication 1 (0.4%) 1 (0.6%) Pharmacy Dispensing Error 51 (19.3%) 2 (1.1%) Documentation Error 21 (8.0%) 9 (5.1%) eMAR Shift Audit - - Other (*this was not further defined) 21 (8.0%) 7 (4.0%) Missed Medication & Documentation Error 11 (4.2%) 11 (6.3%) Missed Medication & Pharmacy Dispensing Error 4 (1.5%) 3 (1.7%) Missed Medication & Other 1 (0.4%) 1 (0.6%) Incorrect Medication & Resident 4 (1.5%) 4 (2.3%) Incorrect Medication & Pharmacy Dispensing Error

1 (0.4%) -

Incorrect Dose & Resident 1 (0.4%) 1 (0.6%) Incorrect Dose & Documentation Error 2 (0.8%) 2 (1.1%) Incorrect Dose & Pharmacy Dispensing Error 2 (0.8%) 2 (1.1%) Incorrect Time & Pharmacy Dispensing Error 1 (0.4%) - Incorrect Time & Documentation Error 1 (0.4%) 1 (0.6%) Incorrect Time & Medication 3 (1.1%) 3 (1.7%) Documentation Error & eMAR Shift Audit 6 (2.3%) 2 (1.1%) Documentation Error & Pharmacy Dispensing Error

1 (0.4%) 1 (0.6%)

Other & Pharmacy Dispensing Error Dispensing Error

1 (0.4%) 1 (0.6%)

Incorrect Time, Medication & Dose 5 (1.9%) 5 (2.8%) Missed Medication & Incorrect Time & Medication

1 (0.4%) 1 (0.6%)

Incorrect Dose, Resident, & Medication 1 (0.4%) 1 (0.6%) Incorrect Time & Dose & Pharmacy Dispensing Error

1 (0.4%) -

Number of medication error types within Medication Incidents One Medication Error Type 217 (82.2%) 136 (77.7%)

Two Medication Error Types 39 (14.8%) 32 (18.2%) Three Medication Error Types 8 (3.0%) 7 (4.0%)

Time to error report Less than 24 hours 215 (81.4%) 140 (80.0%) Greater than 24 hours 49 (18.6%) 35 (20.0%)

Medication Incident severity (Nursing Staff) ADE – No 239 (90.5%) 156 (89.1%) ADE – Yes 6 (2.3%) 5 (2.9%) ADE – Unknown 19 (7.2%) 14 (8.0%)

Medication Incident severity (Investigators) NCC MERP 1-4: No Harm 258 (97.7%) 170 (97.1%) NCC MERP 5-9: Harm 6 (2.3%) 5 (2.9%)

Medication Incident severity (NCC MERP Classification) 1 – Circumstances or events that have the capacity

to cause error 55 (20.8%) 23 (13.1%)

2 – An error occurred but the error did not reach the resident 49 (18.6%) 7 (4.0%)

3 – An error occurred that reached the resident but did not cause resident harm 71 (26.9%) 62 (35.4%)

4 – An error occurred that reached the resident and required monitoring to confirm that it resulted in no harm to the resident and/or required intervention to preclude harm.

83 (31.4%) 78 (44.6%)

5 – An error occurred that may have contributed to or resulted in temporary harm to the resident and required intervention

3 (1.1%) 2 (1.1%)

6 – An error occurred that may have contributed to or resulted in temporary harm to the resident and required initial or prolonged hospitalization

3 (1.1%) 3 (1.7%)

7 – An error occurred that may have contributed to or resulted in permanent resident harm - -

8 – An error occurred that required intervention necessary to sustain life - -

9 – An error occurred that may have contributed to or resulted in the residents’ death - -

Medications involved in Medication Incidents ISMP High Alert Medications

Opioids 25 (9.5%) 14 (8.0%) Anticoagulant 11 (4.2%) 8 (4.6%) Hypoglycemics 7 (2.7%) 6 (3.4%) Insulin Preparations 5 (1.9%) 3 (1.7%)

Non-ISMP Medications Analgesic 15 (5.7%) 12 (6.9%) Antidepressant 13 (4.9%) 10 (5.7%)

Antiepileptic 7 (2.7%) 4 (2.3%) Anti-infective 20 (7.6%) 15 (8.6%) Antipsychotic 24 (9.1%) 18 (10.3%) Anxiolytic 20 (7.6%) 13 (7.4%) Hypertension 6 (2.3%) 6 (3.4%) Hypnotic and Sedative 5 (1.9%) 3 (1.7%) Vitamin/Mineral/Supplement 17 (6.4%) 11 6.3%) Unknown 76 (28.8%) 46 (26.3%) Antihistamine 1 (0.4%) 1 (0.6%) Miscellaneous 45 (17.0%) 33 (18.9%)

Number of medications involved in Medication Incidents One Medication 165 (62.5%) 109 (62.3%) Two Medications 18 (6.8%) 16 (9.1%) Three Medications 4 (1.5%) 4 (2.3%) Four Medications - - Five Medications 1 (0.4%) 1 (0.6%) Unknown 76 (17.0%) 45 (25.7%)

Primary contributing influences in Medication Incidents Nursing Staff 168 (63.6%) 148 (84.6%) Pharmacy 65 (24.6%) 1 (0.6%) eMAR-BCMA 2 (0.8%) 2 (1.1%) Prescriber 2 (0.8%) - Resident 15 (5.7%) 13 (7.4%) Nursing Staff and Pharmacy 9 (3.0%) 8 (4.6%) Nursing Staff and eMAR-BCMA 1 (0.4%) 1 (0.6%) Nursing Staff and Prescriber 1 (0.4%) 1 (0.6%) Nursing Staff, Pharmacy and eMAR-BCMA 1 (0.4%) 1 (0.6%)

Number of primary contributing influences in Medication Incidents One 252 (95.5%) 164 (93.7%) Two 11 (4.2%) 10 (5.7%) Three 1 (0.4%) 1 (0.6%)

Team Leader/Resident Care Manager follow-up to Medication Incident Education to Staff 102 (38.6%) 91 (52.0%) Education to HCA 9 (3.4%) 8 (4.5%) Education to HCAs 1 (0.4%) 1 (0.6%) Education to LPN 29 (11.0%) 22 (12.6%) Education to LPN and Physician 2 (0.8%) 1 (0.6%) Education to Staff and Pharmacy Notified 5 (1.9%) 5 (2.9%) Education to Resident 6 (2.3%) 5 (2.9%) Pharmacy informed/notified 80 (30.3%) 17 (9.7%) Pharmacy and LPN Informed 1 (0.4%) 1 (0.6%) Pharmacy informed to update directions 1 (0.4%) - Pharmacy Error 1 (0.4%) - Moved medications from HCA to LPN cart 1 (0.4%) 1 (0.6%) Moved medications to LPN cart 2 (0.8%) 2 (1.1%)

LPN to monitor Room frequently 1 (0.4%) 1 (0.6%) Regular Room Checks 1 (0.4%) 1 (0.6%) Reviewed with Family and LPN 1 (0.4%) 1 (0.6%) Education to Family to not provide medications to resident

1 (0.4%) 1 (0.6%)

Discussion with Family 1 (0.4%) 1 (0.6%) Update Residents file to only give pass meds to family

1 (0.4%) 1 (0.6%)

Unknown 18 (6.8%) 15 (8.6%) a Non-secure unit capacity (n=145) b Secure unit capacity (n=94)

Table 3.3. Factors Involved in Medication Administration Incidents and Dispensing Errors Factors Involved in a Medication Administration Incidents n=175 Categories and Sub-categories Number (%) Medication Administration Processes with eMAR-BCMA

Not reviewing eMAR and/or medication prior to administration 28 (16.0%) Medications signed off, but not administered 20 (11.4%) Issue with LOA medications 20 (11.4%) Medications administered, but not signed off (refusals not signed off) 14 (8.0%) Administered next interval medication dose in error 13 (7.4%) Medication not administered, not signed off as administered on eMAR

1 (0.6%)

Medication Packaging Incidents involving non-pouch medication packaging 8 (4.6%) Packaging/Dispensing issue 3 (1.7%)

Environmental Issues and Internal/External Factors Distracted During Medication Administration 9 (5.4%) Medication Supply or Storage Issues 10 (5.7%) Resident Self Administration Issues and Medication Refusals 6 (3.4%) Warfarin Issue or Restricted Medication Issue 7 (4.0%)

Communication Manual Documentation on the eMAR 10 (5.7%) Issues with order communication within facility or between facility and pharmacy

23 (13.1%)

Other and Not Available Other and Not Available 3 (1.7%)

Factors Involved in Dispensing Errors n=67 Categories and Sub-categories Number (%) Pharmacy Packaging and Delivery

Medication Packaging Error 34 (50.8%) Delivery Error 7 (10.4%) Errors in eMAR-BMCA Barcodes 7 (10.4%)

Other and Unknown MIR already defined 8 (11.9%) Other and Unknown 11 (16.4%)

Table 3.4. Characteristics of Residents by Number of Reported Medication Incidents and Number of Medication Administration Phase Incidents

Medication Incidents Medication Administration-use Phase Incidents (MAI) p-value 0.017 (Bonferroni Correction)

One Medication Incident (n=88 residents) (88 MIRs)

Multiple Medication Incidents (n=66 residents) (176 MIRs)

No MAI

(n=40 residents)

One MAI

(n=77 residents)

Multiple MAIs

(n=37

residents)

p values (no vs. one vs. multiple)

p value (no MAI vs. one MAI)

p value (no MAI vs. multiple MAIs)

p value (one MAI vs. multiple MAIs)

Age [years] 74.6 +/-

17.4

61.6 +/-

13.3 P<.001

69.4 +/-

16.8

73.3 +/-

16.2

59.9 +/-

15.8 P<.001 P=.24 P=.013 P<.001

Gender RR (CI) 0.80 (0.56 to 1.15) P =0.23 P=.048 1.02 (0.77-1.36) 0.64 (0.40-1.01) 0.53 (0.32-0.90)

Female 59 (60.2%) 38 (39.8%) 97 (100%)

27 (27.8%)

53 (54.6%)

17 (17.5%)

97 (100%) P=.88 P=.056 P=.019

Male 29 (50.9%) 28 (49.1%) 57 (100%)

13 (22.8%)

24 (42.1%)

20 (35.1%)

57 (100%)

88 (57.1%) 66 (42.9%) 154 (100%)

40 (26.0%)

77 (50.0%)

37 (24.0%)

154 (100%)

Unit RR (CI) 3.81 (1.89 to 7.73) P<.001 P=.013* 0.86 (0.67-1.12) 1.81 (0.84-3.93) 2.95 (1.26-6.95)

Non-Secure 47 (44.3% 59 (55.7%) 106 (100%)

28 (26.4%)

46 (43.4%)

32 (30.2%)

106 (100%) P=.32 P=.10* P=.005

Secure 41 (85.4%) 7 (14.6%) 48 (100%)

12 (25.0%)

31 (64.6%)

5 (10.4%)

48 (100%)

88 (57.1%) 66 (42.9%) 154 (100%)

40 (26.0%) 77 (50%) 37

(24.0%) 154

(100%) y p-value 0.017 (Bonferroni Correction) (p-value= 0.05/number of comparisons (i.e. 3) = 0.017) *Fishers Exact Test (Note: Age at time of first reported incident)

Table 3.5. Comparison of Severity of Medication Incidents (n=264)

*Fishers Exact Test

Mean

Severity Score (SD)

Did Not Reach

Resident (Categories

1-2) (n=104)

Reached Resident

(Categories 3-9) (n=160)

p value

Medication error Type P=.001 RR (CI) 1.33 (1.09 to 1.62)

P=.02*

Multiple Error Types (n=46) 3.28±1.28 11 (23.9%) 35 (76.1%) 46 (100%)

One Error Type (n=218) 2.66± 1.15 93 (42.7%) 125 (57.3%) 218 (100%)

104 (39.4%) 160 (60.6%) 264 (100%)

Medication Use Phase P=.33 RR (CI) 1.25 (0.96 to 1.62)

P=.19*

>1 Medication use phase involved (n=23) 3.00± 1.28 6 (26.1%) 17 (73.9%) 23

(100%) One Medication use phase involved (n=241) 2.75±1.19 98 (40.7%) 143 (59.3%) 241

(100% 104 (39.4%) 160 (60.6%) 264

(100%) Time to error report P=.77 RR (CI) 1.15 (0.92 to

1.45) P=.32*

Reported after 24 hours (n=47) 2.72± 1.10 15 (31.9%) 32 (68.1%) 47 (100%)

Reported within 24 hours (n=217) 2.78±1.22 89 (41.0%) 128 (59.0%) 217 (100%

104 (39.4%) 160 (60.6%) 264 (100%)

Shifts P=.19 P=.46* (1) 0700-1500 (n=132) 2.63±1.17 57 (43.2%) 75 (56.8%) 132

(100%) (2) 1500-2300 (n=120) 2.91±1.22 43 (35.8%) 77 (64.2%) 120

(100%) (3) 2300-0700 (n=12) 2.83±1.11 4 (33.3%) 8 (66.7%) 12

(100%) 104 (39.4%) 160 (60.6%) 264

(100%)

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CHAPTER 4

GENERAL DISCUSSION AND CONCLUSIONS

4.1 General discussion

Medication incidents are common in long-term care facilities (LTCF) and while few contribute

to permanent disability or death, a small but significant proportion lead to resident harm.

Technology solutions have been proposed to improve medication safety in LTCF, with electronic

medication administration records (eMAR) and barcode assisted medication administration

(BCMA) being a main focus of adoption. However, the impacts of eMAR-BCMA on

medication administration and medication administration incidents (MAIs) within LTCF have

not been well defined. Within this thesis, different methodologies were used in two projects (a

scoping review of the literature and a retrospective review of medication incident report data) to

expand our understanding of eMAR-BCMA use within LTCF and how the technology influences

medication administration and safety.

4.1.1 Electronic Medication Administration Records in Long-Term Care Facilities: A

Scoping Review

The first study was a scoping literature review that aimed to map the extent, range, and nature of

research on the effectiveness, level of use, and perceptions of eMAR and BCMA in LTCF. In

addition, we identified gaps in current knowledge and prioritized areas for future research.

Using methodologies developed by Arksey and O’Malley,1 we summarized 34 studies, of which

17 were published in the peer-reviewed literature and 17 in the grey literature. The included

studies fell into three main categories: medication and medication administration error (MAE)

rates, benefits and challenges and eMAR prevalence/uptake. We found two descriptive case

reports in the grey literature that claimed a positive impact of eMAR on MAE rates after eMAR

implementation; however, these reports provided weak evidence of benefit because of

weaknesses in study design and reporting. Two additional prospective studies utilized BCMA

reporting functions to determine the incidence of potential MAEs averted by BCMA, suggesting

that MAEs, such as incorrect time, wrong resident or attempting to administer a discontinued

medication, are prevented by the safety warnings/prompts of BCMA technology. Several studies

reported nursing staff perceptions of eMAR which includes decreased medication errors or the

elimination of errors, a lowered the risk of MAEs, lowered stress levels and positivity towards

the medication administration process.

Twelve studies reported benefits of eMAR and BCMA, which included improved medication

reconciliation and real-time access to resident information, while evidence of efficient

medication administration was inconsistent. Improvement to safety and quality, mostly related

to the warning prompts and alerts, resident photographs and mandatory documentation of

administration, and quality improvement and compliance to organization and regulatory policies,

such as documentation practices and ability to monitor drug use were reported. Seven studies

reported challenges with eMAR and BCMA, such as unreliability of the internet or eMAR

system, lack of training or IT support and nursing staff workarounds. Lastly, 12 studies

evaluated the prevalence of eMAR and BCMA in LTCF. Depending on the timeframe and

location, uptake in LTCF ranged from 18% to 49%, while pharmacy uptake was reported to be

up to 23.3%.

Due to the lack of evidence-based reports on the impact of eMAR-BCMA on MAEs within

LTCF, we can only compare our observations from the scoping review to hospital environments

where several studies have demonstrated positive but inconsistent results on MAE rates. For

example, in a 2010 systematic review evaluating barcode medication administration systems and

MAE rate in acute care settings by Young et al., the authors concluded that eMAR-BCMA

inconsistently decreased the overall incidence of MAEs.2 A subsequent before-and-after quasi

experimental study in an academic medical center implementing eMAR-BCMA published in

2010 by Poon et al., found the medication error rate in order transcription and medication

administration; as well as, ADEs were substantially reduced post eMAR-BCMA implementation.

However, they concluded that the system did not eliminate errors entirely.3 Most recently, a

survey and evaluation of MAEs before and after BCMA implementation in a Taiwanese medical

center published by Lin et al., demonstrated a MAE rate decrease of 22.5%, from 405 MAIs at

pre-implementation to 314 post-implementation (p<0.001).4

There are similarities in the benefits and challenges of eMAR-BCMA reported in the hospital

and long-term care literature, such as immediate access to patient information5 and positive

nursing perceptions about patient safety;6 as well as, nursing staff workarounds to the safety

alerts of the eMAR-BCMA system7 and the perception that medication administration was

slower.8

In contrast to LTCF, it appears that eMAR and BCMA adoption is higher in acute care facilities

where a 2014 U.S. national survey found that hospitals have an eMAR-BCMA adoption rate of

93%.9

The observations from our scoping review provide the most up to date summary of the literature

on eMAR-BCMA in LTCFs, focusing on medication errors, benefits, challenges and eMAR-

BCMA uptake. We noted a lack of rigorously designed studies to inform LTCF administrators

and clinicians about the impact eMAR-BCMA has on MAEs and resident safety in LTCF. Even

though LTCF have adopted eMAR-BCMA for medication administration without direct

supporting evidence of an improvement to medication administration practices, reductions in

medication incidents and increases to resident safety, we believe that there is sufficient

opportunity to further investigate standalone eMAR-BCMA systems and the influence on

medication management and LTCF resident safety.

4.1.2 Evaluation of Medication Incidents in a Long-Term Care Facility Utilizing Electronic

Medication Administration Records and Barcode Technology

The second study of this thesis was a retrospective review of medication incidents reports

submitted voluntarily by nursing staff within a 239-bed LTCF that has been utilizing eMAR-

BCMA since 2013. The aim of the study was to characterize the frequency, type and severity

(i.e. resident harm) of reported medication incidents and medication administration incidents

(MAI). Ideally, we wanted to compare medication incidents before and after eMAR-BCMA

implementation, but because the medication incident reports prior to implementation were no

longer available at the LTCF, we focused on post-implementation medication incidents only.

Furthermore, we determined if medication incidents were more commonly reported on secure

units (where residents with moderate to severe dementia who may have a high risk of wandering

and unpredictable behaviors reside), or non-secure units, investigated characteristics of residents

that experienced multiple medication incidents, and explored factors that influence medication

incident severity.

An average of nine medication incidents were reported each month at the study LTCF, with the

majority coming from the three non-secure units. Medication administration, dispensing, and

communication/documentation were the most common medication use-phases involved in

medication incidents. Missed medications and incorrect time were the most frequently reported

medication error types for MAIs. Six mediation incidents led to resident harm and over half of

MAIs reached the resident. Close to 30% of medication incidents reports did not have a

documented medication involved, while, opioids, insulin, antihistamine, and anxiolytic

medications were involved in medication incidents where residents were harmed. Inadequate

medication administration processes with eMAR-BCMA and medication order communication

issues were the most common factors reported to lead to MAIs. Younger residents and those

residing on the non-secure units were more likely to experience multiple medication incidents or

multiple MAIs. The residents experiencing multiple events were approximately 13 years

younger than those experiencing one event (i.e., 61.6±13.3 vs. 74.6±17.4, p<.001 for medication

incidents and 59.9±15.8 vs. 73.3±16.2 p<.001 for MAIs). Those residing on the non-secure units

were almost four times more likely to experience multiple medication incidents (55.7% vs.

14.6%, RR: 3.81; 95% CI: 1.89, 7.73; p<.001). Medication incidents coded with multiple error

types were rated by investigators as being more severe. Based on our findings, we determined

that several influential factors lead to MAIs despite the presence of an eMAR-BCMA. These

factors prevent an eMAR-BCMA from entirely mitigating the risk of medication incidents and

associated harm within LTCF.

Comparisons with other published data are difficult as there is limited information exploring

eMAR-BCMA in LTCF in Canada.10 Even though American data from specific states suggests

high levels of uptake of eMAR-BCMA in LTCF in some areas, there is limited published

evaluation data in LTCF that utilize eMAR-BCMA. This is in contrast to the body of literature

of medication incident report data and direct observations of medication administration available

from hospital environments2, 4, 11-14 or from LTCF that do not use eMAR-BCMA.15-19 Our study

findings are consistent with a 2017 systematic review of the prevalence of medication incidents

in LTCF residents by Ferrah et al.15 This review did not include studies that used eMAR-

BCMA. Studies within this review were primarily based on medication incident report data, and

the authors found that the majority of medication incidents occurred in the medication

administration and communication phases (20%-53%). Additionally, missed medications and

wrong dose error types were most commonly associated with MAIs. Opioids, anticoagulants,

and antidiabetics were a few of the most common medications involved in medication incidents.

Similarly, opioids and insulin had a greater risk of causing serious adverse drug events (ADE) or

harm.

In contrast to our study, Ferrah et al. found that older age and cognitive impairment were

associated with greater risk of repeat medication incidents. This discrepancy may be explained

by the fact that we included only a single LTCF, while Ferrah et al. reviewed multiple sites and

included statewide data from North Carolina. Ultimately, our study site may not be reflective of

a typical LTCF and generalizability to other settings may be limited. Ferrah et al., concluded

that human error and nursing staff distractions accounted for a significant number of medications

incidents within their systematic review. We found evidence of these within our study as well,

although in situations where staff were reportedly not following proper medication

administration processes or employing workarounds to eMAR-BCMA technology we were not

able to conclusively differentiate if this was a result of flaws in the underlying medication use

process or as a result of behavioral choices by individual providers. Similar to Ferrah et al., we

suggest that the narrative descriptions we reviewed may indicate a lack of recognition of the role

of systemic or latent factors by those reporting the medication incident. Two studies within the

systematic review address that during periods of LTCF resident transition (i.e. new admissions or

hospital discharges) missed medications and incorrect doses were reported,20, 21 which is

comparable to the transitions that we found within our study for LTCF residents leaving or

returning from a leave of absence. While medication incidents were almost twice as likely to be

repeated within seven days of a transition as reported by Crespin et al.,22 our study only

evaluated resident characteristics (i.e. age, gender and unit) that could impact repeat medication

incident and MAIs. We were unable to find comparative data on the impact of medication

incident severity based on specific medication incident report characteristics.

Overall, while it is difficult to compare incident rates across LTCF or institutions, we noted

several similarities in reported medication incidents at our study site in comparison to LTCF that

do not utilize eMAR-BCMA. Unfortunately, our method is not robust enough to determine if the

eMAR-BCMA implementation affected medication incident rate at our study LTCF. However,

it is clear that the use of eMAR-BCMA has not entirely eliminated medication incidents

including those associated with harm. Our study provides further understanding of the ongoing

100

medication safety issues that occur despite the ongoing use of an eMAR-BCMA in a large

LTCF.

4.2 Implications and Future Directions

4.2.1 for clinical practice:

Our work has several potential implications on improving the medication safety in practice at

the participating site as well as other similar facilities where voluntary paper-based medication

incident reporting is the norm. First, the use of paper-based medication incident report forms

that lack critical data elements such as medication involved and contributing factors found in

modern online medication incident reporting forms such as those from the Canadian Medication

Incident Reporting System, may not facilitate optimal documentation of a medication incident

and limits their ability to be used for quality improvement purposes. Literature suggests that

medication incidents are under-reported for many reasons23-29 and medication incident reports

tend to be incomplete.30 Almost 30% of the medication incidents reports reviewed in our second

study did not specify which medications were involved.

There are two potential strategies to improve the quality of submitted medication incident

reports; implementing electronic medication incident reporting or revising existing paper-based

processes to ensure they are consistent with reporting best practices. Electronic medication

incident reporting is used in many jurisdictions and may represent a strategy for a large

coordinated approach to improving medication safety. For example, the Medication Error

Quality Initiative (MEQI) in North Carolina USA, could be used as an example where all nursing

homes licensed by the state were required by law to report all medication incidents and potential

medication incidents through web-based reporting.31 The purpose was for each nursing home to

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oversee each medication incident and evaluate their cause to reduce subsequent error and

enhance resident safety and the pooled data from this initiative resulted in several academic

publications. 21, 22, 32, 33 In a benefits evaluation study of an electronic clinical safety reporting

system in Newfoundland and Labrador by Elliot et al., electronic reporting contributed to

improved clinical safety and was preferred over the paper-based incident reporting system.34

Electronic incident reporting is recommended by ISMP Canada and the Canadian Society of

Hospital Pharmacists (CSHP) to improve the ability to analyze medication incident data, and to

facilitate the development of recommendations on how to adapt and update processes and

practices that may impact patient safety.35, 36 On a national level, Canadian healthcare facilities

can participate in anonymous electronic incident reporting through the National System for

Incident Reporting (NSIR)37 where data is used to inform quality improvement activities to

foster improvements in healthcare delivery.

Notably, the eMAR/BCMA system in place within the study facility does have medication

incident reporting functionality and while it is not currently used, it represents a potentially

feasible way to move toward electronic reporting at the study LTCF. If electronic reporting is

not feasible, we recommend that the facility implement an updated paper-medication incident

report template with associated reporting processes as promoted by the Canadian Patient Safety

Institute38 and ISMP Canada.39

We noted several factors that contributed to reported medication incidents and we suggest

focusing on the root causes of these common incidents. There are opportunities to reduce the

number MAIs associated with the improper use of the eMAR-BCMA system. This would

102

include addressing inappropriate medication administration processes (such as nursing staff not

checking the medication or the eMAR prior to administration) and the incorrect distribution of

LOA medications. Nursing staff workarounds to eMAR-BCMA are also noted as a factor that

can lead to MAIs; however, workarounds are multifaceted and could be related to the culture of

the LTCF, the individual nursing staff member, the medication administration processes or the

technology itself for example. Ultimately, workarounds occur to overcome or bypass a problem

or process. Actively engaging nursing staff in prospectively evaluating and addressing identified

suboptimal practices, problems and processes could be an area of prioritization in tackling

medication safety issues at the study facility. In addition, communication between nursing staff

and the communication of new medication orders between the LTCF and the dispensing

pharmacy were also recognized as influential factors that led to MAIs and medication incidents.

Empowering nursing staff and the dispensing pharmacy to re-evaluate current communication

practices could assist in establishing new policies and procedures to address this issue. These

engagement activities could be tied to an evaluation around the culture of safety at both the

facility and dispensing pharmacy which would further inform optimal ways to address the

identified process and communication issues. The Nursing Home and Community Pharmacy

versions of the Survey on Patient Safety (SOPS) from the Agency for Healthcare Research and

Quality could be used for this purpose.40, 41

While the participating LTCF has processes in place to address medication incidents as they

occur, we hope that our scoping review and the summary data from our formal evaluation will

lead to greater awareness of the literature around eMAR-BCMA use and common medication

incidents, and lead to further opportunities to adapt and improve medication administration

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processes at the participating site. Hopefully, in turn this will ultimately improve medication

safety for all those residing at the facility.

4.2.2 for research

Our two studies identified opportunities to further understand the impact of eMAR-BCMA on

medication administration practices in LTCF. Our scoping review determined that there was

very limited published research on the use of eMAR-BCMA in LTCF. There remains

opportunity for a rigorously designed before and after implementation study to directly evaluate

the impact of eMAR-BCMA on MAIs in LTCF, similar to those conducted in hospital

environments. In this regard, formal partnerships between LTCF and community pharmacies

who want to implement eMAR-BCMA with academics who have expertise in technology

implementation could partner to allow a more robust evaluation of eMAR-BCMA. Additionally,

family members of LTCF residents or residents themselves should be engaged as partners in

research teams and help in governance, priority setting, and development of further research

questions to ensure relevance of the research output.

Future research should also explore medication safety in LTCF using data sources beyond

medication incident reports. Other methodologies, such as manual chart reviews,30 direct

observation42 or utilizing data generated by reporting functions within some BCMA systems43,

44 can provide further understanding of medication incidents within LTCF.

Further exploration of medication safety with eMAR-BCMA in LTCF from a community

pharmacy perspective should occur. The dispensing pharmacy is a vital component of

medication management and was involved in a significant number of medication incidents within

104

our study from failing to include necessary operational requirements such as medication

barcodes, or updating new medication orders within the eMAR. Relatively little is known about

the impact of eMAR-BCMA from a pharmacy workflow and pharmacist perspective. Our

scoping review included two cross-sectional survey studies of LTCF pharmacy providers on the

uptake of eMAR-BCMA, one study that completed in-depth interviews to determine the

perceptions of eMAR-BCMA by two pharmacists and one study that used a semi-structured

interview to determine one pharmacists’ experience with eMAR. The perception of hospital

pharmacists towards eMAR-BCMA has been studied previously, where the ease of eMAR-

BCMA use was low and it was not useful for improving either personal job performance or

patient care.45 We suggest exploring ways to optimize communication between the LTCF and

pharmacy, as nurses and pharmacists are not co-located like they are in hospital settings. The

majority of communication between the LTCF and dispensing pharmacy is through phone and

fax. However, the eMAR-BCMA system utilized within the study LTCF consists of a one-way

communication function, similar to direct messaging, where nursing staff can request real-time

medication refills or updates to a resident profile to the dispensing pharmacy. Two-way

electronic communication may improve efficiency; as well as, provide a secure method to track

and document communications.

Lastly, access to grants or subsidies promoting standardized, large-scale (e.g., province wide)

incident reporting systems in LTCF, similar to the MEQI in North Carolina, could be a focus for

building capacity to study the impact of safety and quality improvement initiatives in long-term

care.

105

4.2.3 for policy LTCF in Alberta that are supported by Alberta Health Services (AHS) have to adopt and adhere

to established policies and procedures (as a minimum standard) for medication administration to

ensure consistency and awareness of safe medication administration practices.46 Even though

eMAR-BCMA is being utilized within Alberta LTCF, the AHS medication administration

policy, which was updated in September 2018, makes no reference to the use of eMAR or

eMAR-BCMA systems for medication administration. As the provincial leader in establishing

and approving safe and appropriate clinical practices, AHS has not addressed or provided

direction for the use of eMAR-BCMA to LTCF, leaving individual LTCF or organizations to

establish such protocols and procedures on their own. As evidence regarding eMAR-BCMA

systems in LTCF emerges, the gap in medication administration policy should be addressed to

support the introduction of new health information technologies in LTCF by establishing

appropriate guidelines and procedures that will uphold nursing staff and LTCF resident safety.

4.3 Conclusion This thesis examined the use of eMAR-BCMA in supporting medication administration practices

in LTCF. The findings from our two studies, a scoping review and a retrospective audit of

medication incident reports, identified limited direct evidence linking eMAR-BCMA use and

reduction in medication incidents and MAIs and suggests that more rigorous, prospective

research in LTCF and community pharmacies is required to demonstrate the impact of stand-

alone eMAR-BCMA systems on medication safety. It also highlights that opportunities remain

to optimize use of eMAR-BCMA and improve medication incident reporting in the LTCF

setting.

106

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Appendices Appendix 2.1. Search Strategy Pubmed eMAR Search Strategy (((((((((long-term care/ OR nursing care/ OR home nursing/ OR respite care/)) OR (residential facilities/ OR assisted living facilities/ OR group homes/ OR halfway houses/ OR homes for the aged/ OR nursing homes/ OR intermediate care facilities/ OR skilled nursing facilities/)) OR Housing for the Elderly/) OR ((nursing home* OR extended care* OR care home*) AND .mp.)) OR (((senior* OR continuing care OR disabled OR old age OR geriatric* OR elder care* OR rehabilitat* OR long term care) AND adj2 AND (lodge* OR facility* OR home* OR residence* OR centre* OR center*)) AND .mp.)) OR supportive living.mp.) OR ((assisted living OR residential facilit* OR group home*) AND .mp.))) AND (((((((Medication Management Information Technology.mp.) OR Bar-Code* AND Medication Administration.mp.) OR BarCode* AND Medication Administration.mp.) OR electronic medication administration.mp.) OR electronic treatment administration.mp.)) AND ((((Medication Therapy Management/) OR ((medication administration OR medication management OR medication therapy management OR drug therapy management OR medication reconciliation*) AND .mp.))) AND ((((((exp medical informatics/ OR nursing informatics/)) OR systems integration/) OR (automatic data processing/ OR computer systems/ OR computer communication networks/)) OR Electronic Health Records/) OR ((health information technolog* OR barcode* OR computer system* OR electronic health record* OR electronic medical record*) AND .mp.))))

CINAHL eMAR Search Strategy 1.) (MH "Medical Informatics") OR (MH "Nursing Informatics") OR (MH "Systems Integration") OR (MH "Computer Systems+") OR (MH "Computer Communication Networks+") OR (MH "Computerized Patient Record") OR ("health information technolog*" or barcode* or "computer system*" or "electronic health record*" or "electronic medical record*") 2.) "medication administration" or "medication management" or "medication therapy management" or "drug therapy management" or "medication reconciliation*" 3.) 1 and 2 4.) (MH "Long Term Care") OR (MH "Nursing Care+") OR (MH "Home Nursing") OR (MH "Respite Care") OR (MH "Residential Facilities+") OR (MH "Assisted Living") OR (MH "Halfway Houses") OR (MH "Housing for the Elderly") OR (MH "Nursing Homes+") OR (MH "Skilled Nursing Facilities") OR ("nursing home*" or "extended care*" or "care home*" OR "supportive living" OR "assisted living" or "residential facilit*" or "group home*") OR ((senior* or "continuing care" or disabled or "old age" or geriatric* or "elder care*" or rehabilitat* or "long term care") N2 (lodge* or facility* or home* or residence* or centre* or center*)) 5.) 3 and 4

142

Cochrane Library search: "medication administration" or "medication therapy" or "medication reconciliation" or "medication management":ti,ab,kw and electronic or computer* or technolog*:ti,ab,kw and "long term care" or "nursing homes" or "assisted living" or "supportive living":ti,ab,kw SCOPUS eMAR Search Strategy (medication management information technology ) OR ( barode* medication administratio n ) OR ( barcode* medication administration ) OR ( electronic medication administration ) OR ( electronic treatment administration ) OR ( medical informatics OR nursing infor matics ) OR ( systems integration ) OR ( automatic data processing OR computer system s OR computer communication networks ) OR ( electronic health records ) OR ( health information technolog* OR barcode* OR computer system* OR electronic health record * OR electronic medical record* ) AND (medication therapy management ) OR ( medication administration OR medication mana gement OR medication therapy management OR drug therapy management OR medication reconciliation* ) AND (longterm care OR nursing care OR home nursing OR respite care) OR ( residential fa cilities OR assisted living facilities OR grouphomes OR halfway houses OR homes for the aged OR nursing homes OR intermediate care facilities OR skilled nursing facilitie s ) OR ( housing for the elderly ) OR ( nursing home* OR extended care* OR care ho me* ) OR ( ( senior* OR continuing care OR disabled OR old age OR geriatric* OR e lder care* OR rehabilitat* OR long term care ) n/2 ( lodge* OR facility* OR home* O R residence* OR centre* OR center* ) ) OR ( supportive living ) OR ( assisted living O R residential facilit* OR group home* ) )

ProQuest Dissertations and Theses search: ("medication management" OR "medication administration" OR "medication therapy" OR "medication reconciliation") AND (electronic OR computer* OR technolog*) AND ("long term care" OR "nursing home*" OR "assisted living" OR "supportive living")

143

GREY LITERATURE SEARCH

Google Search Terms

emar AND (“long term care” OR “nursing home” or “Assisted living” or “skilled nursing

facility”)

“electronic medication administration record” AND (“long term care” OR “nursing home” or

“Assisted living” or “skilled nursing facility”)

“barcode medication administration” AND (“long term care” OR “nursing home” or “Assisted

living” or “skilled nursing facility”)

“health information technology” AND (“long term care” OR “nursing home” or “Assisted

living” or “skilled nursing facility”)

144

Appendix 3.1. Study LTCF Medication Incident Report Template MEDICATION INCIDENT REPORT

Facility: □ VM □ SP Report Date: _____________________ Report Time: __________________ Reporting Team Member(s): (print) _________________________ Signature: ___________________________ Incident Date: ____________ Incident Time: ____________ Person Responsible for Error: (print) __________ Resident Suite: _______________________________ Resident Name: _______________________________ Type of Medication Error/Omission: Injuries/Adverse Reaction as a Result of Medication Error: (check as appropriate) □ Yes □ No □ Incorrect Resident □ Incorrect Medication If Yes, please describe: □ Incorrect Time □ Incorrect Dose □ Incorrect Route □ Medication Expired □ Medication Omission (Attach Med Pouch) □ Pharmacy Error □ Documentation Error/Omission □ OneMAR Shift Audit □ Other: Description of Incident _________________________________________________________________________________

_________________________________________________________________________________

145

LPN Team Leader Follow Up (specify Nursing Interventions/Assessment) _________________________________________________________________________________

_________________________________________________________________________________

Action Taken RCM Notified: □ Yes Name of RCM: (print) ______________Date: ____________Time: _________ □ No, by Incident Report as per Policy

Resident Own Personal Decision Maker? □ Yes □ No (if No, complete next two lines) Guardian Notified: □ Yes Name: (print) Date: Time: If unable to reach Guardian, why? Follow up: Pharmacy Notified □ Phone □ Fax Name: Date: Time: If no, why?

_________________________________________________________________________________

HCA Progress Notes □ Yes □ No

LPN Progress Notes □ Yes □ No (Include pain, behaviour, VS, NVS, BGM) Shift Report LPN/HCA □ Yes □ No

RCM Follow Up Reportable Incident: □ Yes □ No CM Verbally Notified? □ Yes □ No

146

Name of CM: Date: Time: _________________________________________________________________________________

_________________________________________________________________________________

Administration Signature of LPN Team Member Date Signature of Resident Care Manager Date Signature of Director of Care (if applicable) Date

147

Appendix 3.2.1 NCC MERP Index for Categorizing Medication Errors

PSF030G

Category A: Circumstances or events that have the capacity to cause error

Category B: An error occurred but the error did not reach the patient (An "error of omission" does reach the patient)

Category C: An error occurred that

reached the patient but did not cause patient harm

Category D: An error occurred that reached the patient and required monitoring to

confirm that it resulted in no harm to the patient and/or required intervention to preclude harm

Category E: An error occurred that may have contributed to or resulted in

temporary harm to the patient and required intervention

Category F: An error occurred that may have contributed to or

resulted in temporary harm to the patient and required initial or prolonged hospitalization

Category G: An error occurred that

may have contributed to or resulted in permanent patient harm

Category H: An error occurred that required intervention necessary to sustain life

Category I: An error occurred that may have contributed to or resulted in the patient’s death

NCC MERP Index for Categorizing Medication Errors

Definitions

Harm Impairment of the physical, emotional, or psychological function or structure of the body and/or pain resulting therefrom.

Monitoring To observe or record relevant physiological or psychological signs.

Intervention May include change in therapy or active medical/surgical treatment.

Intervention Necessary to Sustain Life Includes cardiovascular and respiratory support (e.g., CPR, defibrillation, intubation, etc.)

No Error

Error, No Harm

Error, Harm

Error, Death

*Permission is hereby granted to reproduce information contained herein provided that such reproduction shall not modify the text and shall include the copyright notice appearing on the pages from which it was copied.

148

Appendix 3.2.2 NCC MERP Index for Categorizing Medication Errors Algorithm

Was the harm temporary?

Harm Impairment of the physical, emotional, or psychological function or structure of the body and/or pain resulting therefrom.

Monitoring To observe or record relevant physiological or psychological signs.

Intervention May include change in therapy or active medical/surgical treatment.

Intervention Necessary to Sustain Life Includes cardiovascular and respiratory support (e.g., CPR, defibrillation, intubation, etc.)

*An error of omission does reach the patient.

Category A

Category B

Category C

Category D

Category E Category F

Category G

Category H

Category I

Circumstances or events that have the capacity to cause error

Did an actual error occur?

Did the error reach the patient? *

Did the error contribute to or result in patient death?

Was the patient harmed?

Was intervention to

preclude harm or extra monitoring required?

Did the error require an intervention necessary to sustain life?

Was the harm permanent?

YES

YES YES

YES

NO NO

YES

NCC MERP Index for Categorizing Medication Errors Algorithm

Did the error require initial or prolonged hospitalization?

YES

PSF030G

149

Appendix 3.3. Medication Administration Incident Review Factors Definitions Content Analysis: Medication Administration Categories and Definitions CATEGORY 1: Medication Administration Processes with eMAR-BCMA Sub-Categories: 1.) Not reviewing eMAR and/or medication prior to administration Description:

Definition: This category applies if the MIR descriptions states that the correct medication was barcode scanned and administered, but was given at the wrong time or administered incorrectly. The nurse failed to follow specific medication orders regarding administration (e.g., PRN frequency/indication, crushing/not crushing a medication, etc.). The nurse failed to confirm the right medication prior to administration. Indicators: The HCA or LPN “didn’t look at the directions on the eMAR” “wrong dose given” Example: “LPN did not look at the eMAR prior to administering PRN Ativan. Dose was given early.” “LPN did not confirm medication dose. 3mg was given instead of 1mg”

2.) Medications signed off, but not administered

Definition: This category applies if the MIR description states that the medications were signed off as administered in the eMAR-BCMA, but some or none were actually administered to the resident. Indicators: Medications were found in the medication cart at the next medication pass, but was signed off as administered during the earlier pass. Example: “Medication was administered as per eMAR at 1200, but medication was found in cart at 1700” “HCA signed off on medication, but did not provide 7of7 pouch”

3.) Issue with LOA medications Definition: This category applies if the MIR description states that the MI relates to medication administration prior to or while the resident was on a leave of absence or pass from the facility. Indicators: “LOA” Leave of Absence, Pass Medications Example: “Resident was provided LOA medications but he did not take all of them upon return.” “Resident went on a LOA and was provided 1200 medications. LPN signed off 1200 and 1700 as given for LOA”

4.) Medications administered, but not signed off (refusals not signed off) Definition: This category applies if the MIR description states that the medication(s) were administered, but not signed off. It includes situations where refusals to take meds were not signed off as ‘refusals.’ Indicators: Medications flashing overdue, but medications not found, resident not home for administration Example: “LPN administered Insulin at 1640, but did not sign off admin on eMAR, 2nd LPN didn't know that insulin was already administered and administered the insulin again” “HCA did not sign off medication after administration”

150

5.) Administered next interval medication dose in error

Definition: This category applies if the MIR description states that the correct medications were scanned and signed off, but additional medications from the next or subsequent medication pouches were administered as well in error. Indicators: 1 of 2 pouch for 1200 missing, medications for the 5th and 6th were given together. Example: “HCA scanned 2100 medications, but grabbed 2100 and 0800 medication pouches. Gave both at 2100”

6.) Medication not administered, not signed off as administered on eMAR Definition: This category applies if the MIR description states the medication was not administered and was not scanned and signed off. The medication was missed all together Indicators: Medication still in cart and eMAR is flashing that medication requires administration Example: “Medication was not administered. Was not signed off on eMAR”

CATEGORY 2: Medication Packaging Sub-categories: 1.) Incidents involving non-pouch medication packaging

Definition: This category applies if the MIR description states that the MI involved a medication that was dispensed in a pre-filled, single-use or multidose packaging (i.e., not medication pouch unit dose). Indicators: Inhaler, Cream, Insulin, Pre-filled syringes, Ampoule Example: “Risperidone liquid in AM and PM. Different doses. Staff were using AM doses for PM” “LPN scanned Depo-Provera but grabbed the Clopixol instead and administered the wrong medication.” “LPN used only one ampoule, when 2 should have been used”

2.) Packaging/Dispensing issue

Definition: This category applies if the MIR description states that the MI occurred because of the way that the medications were packaged/dispensed or delivered from the pharmacy. This includes missing or extra medications in a blister, incorrect labelling of medications, packaged medication does not match prescription, etc. Indicators: pouch medications, narcotics not in lock box, incorrect labelling Example: “Extra tablet in pouch” “Dispensing and labelling”

CATEGORY 3: Environmental Issues and Internal/External Factors

Sub-categories: 1.) Distracted During Medication Administration

Definition: This category applies if the MIR description uses the word distracted. Indicators: “distracted” “in a hurry” Example: “HCA was distracted during the pass and handed another residents' medication to this resident who was speaking with her.”

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2.) Medication Supply or Storage Issues Definition: This category applies if the MIR description states that the medications could not be found or were in the wrong location or the lead nurse did not ‘receive’ new medications. Indicators: Back order, pharmacy did not send injection, wrong porter, wrong room, not received Example: “0800 meds could not be found. Replace pouch given instead.” “Missing medication” “HCA found medication in the wrong med porter for a different resident” “Medication not received on to eMAR by LPN. Medications not administered.”

3.) Resident Self Administration Issues and Medication Refusals Definition: This category applies if the MIR description relates to resident self- administration, self-harm or administration refusal within the LTCF Indicators: Medication compliance, self-administration Example: “Resident did not come for medications,” “Self-harm” Rules: If the issue relates to self-administration/medication refusals while on LOA or pass (outside the facility), it should be assigned to the LOA category.

4.) Warfarin Issue or Restricted Medication Issue Definition: This category applies if the MIR description relates to procedures for use of warfarin were not followed or when other policies regarding the use of restricted medications were not followed. Indicators: Warfarin Example: “HCA administered LPN only medication” Rules: If the issue relates to incorrect/up to date Warfarin orders, it should be assigned to the Communication category.

CATEGORY 4: Communication Sub-categories: 1.) Manual Documentation on the eMAR

Definition: This category applies if the MIR description relates to staff manually signing off on the eMAR rather than barcode scanning or documenting/not documenting administration on a paper MAR. Category also includes manual documentation of medication orders on eMAR for medications not dispensed by the pharmacy. Indicators: “manually signed off” “paper MAR” “non-pharmacy supply” Example: “IM injection was manually signed off by HCA. Should be signed off and given by LPN. Med was never administered” “Staff were using Green MAR to document admin but did not communicate at shift change. Resident missed dose.” “LPN did not put medication as non-pharmacy supplied (got from hospital)”

2.) Issues with order communication within facility or between facility and pharmacy

Definition: This category applies if the MIR description relates to issues in order/reorder communication between nursing staff at the facility or between the facility staff and the pharmacy. This includes MI caused by waiting for Special authorization for medication coverage. Indicators: Communication

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Example: “Clozapine not ordered, delay of 3 days until Pharmacy was aware and sent” “LPN did not know that resident had new meds” “HCA did not inform LPN to reorder nitropatch” “The active Warfarin Rx did not match what was dispensed.” Rules: If the issue relates to communication at shift change regarding paper/green MARs, it should be assigned to the Manual Documentation category.

CATEGORY 5: Other and Not Available 1.) Other and Not Available

Definition: This category applies to the MIR description when none of the above categories/subcategories apply or there was insufficient information to allow categorization. Indicators: Unknown, no information Example: Description of incident left blank.

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Appendix 3.4. Pharmacy Dispensing Errors Factors Codebook Definitions CATEGORY 1: Pharmacy Packaging and Delivery 1.) Medication Packaging Error

Definition: This category applies if the MIR description relates to errors with how the medications were packaged or labeled by the Pharmacy. This includes the pharmacy packaging incorrect medications, providing incorrect directions/information, packaging, and labeling, or packaging discontinued medications. Indicators: Extra tablet, missing tablet, wrong tablet, incorrect label Example: “Missing tablet in pouch” “Pharmacy labeled Narcotic Blister with wrong resident info” “Medication missing from strip” “Medication in strip was D/C”

2.) Delivery Error Definition: This category applies if the MIR description relates to errors in the delivery of the medication to the LTCF. Indicators: Medication not delivered, delivered to wrong location, wrong medication delivered. Example: “Pharmacy did not send full Rx that was Rx'd” “Pharmacy sent 2 medications strip” Rules: If the pharmacy delivered a different medication then what was ordered, place in Medication Packaging Error sub-category.

3.) Errors in eMAR-BMCA Barcodes Definition: This category applies if the MIR description relates to the pharmacy not following proper processes relating to eMAR-BCMA requirements. Indicators: Barcode for medication was not provided, wrong barcode, eMAR not updated Examples: “Updated barcodes with insulin change not provided” “Barcode not sent for eyedrops”

CATEGORY 2: Other and Unknown 1.) MIR already defined

Definition: This category applies if the MIR description involves both the medication administration-use phase (which has already been defined previously) and dispensing-use phase. Indicators: Medications dispensed incorrectly and was administered by nursing staff. MIR already assigned to a MAE category and sub-category Example: “Medication directions error and staff administered incorrect dose”

2.) Other and Unknown Definition: This category applies to the MIR description when none of the above categories/subcategories apply or there was insufficient information to allow categorization. Indicators: Unknown, no or minimal information Examples: Dispensing Error, pharmacy dispensing, pharmacy error