Presentation 4
a. Setting the Stage
The U.S. healthcare system faces the enormous challenge of improving the
quality of care while simultaneously controlling costs. EHRs were proposed as one
solution to achieve this goal (Institute of Medicine [IOM], 2001). In January 2004,
President George W. Bush raised the profile of EHRs in his State of the Union address
by outlining a plan to ensure that most Americans have an EHR by 2014. He stated
that “by computerizing health records we can avoid dangerous medical mistakes,
reduce costs, and improve care” (Bush, 2004). This proclamation generated an
increased demand for understanding EHRs and promoting their adoption, but
relatively few healthcare organizations were motivated at that time to pursue adoption
of EHRs. The Healthcare Information and Management Systems Society (HIMSS)
has been tracking EHR adoption since 2005 through its “Stage 7” award, and in 2013
reported that most U.S. healthcare organizations (77%) were in Stage 3, reflecting
only implementation of the basic EHR components of laboratory, radiology, and
pharmacy ancillaries; a clinical data repository, including a controlled medical
vocabulary; and simple nursing documentation and clinical decision support (HIMSS,
2013).
Higher stages of the electronic medical record adoption model include more
sophisticated use of clinical decision support systems (CDSSs) and medication
administration tools, with HIMSS Stage 7—the highest level—consisting of EHRs
that have data sharing and warehousing capabilities and that are completely interfaced
with emergency and outpatient facilities (HIMSS Analytics, 2013). Real progress is
being made on the adoption of more robust EHRs. HIMSS Analytics (2015) reports
that 1,313 hospitals in the United States have achieved Stage 6 with full physician
documentation, a robust CDSS, and electronic access to medical images.
Healthcare IT News (2015) reported that, to date, over 200 hospitals have
achieved Stage 7, indicating that they have become completely paperless. This
milestone signifies a major transformation in the way these hospitals manage and
process patient information, clinical records, and administrative data. By reaching
Stage 7, these hospitals have fully implemented advanced electronic health record
(EHR) systems that facilitate seamless, real-time access to patient data for healthcare
providers across various departments and locations.
The transition to a paperless environment has numerous benefits, including
improved patient care, increased efficiency, and reduced operational costs. Hospitals
at Stage 7 are able to leverage the latest in health information technology to enhance
clinical workflows, support decision-making processes, and ensure the highest
standards of data security and privacy. Moreover, these institutions are better
equipped to engage in data analytics and population health management, allowing
them to identify trends, monitor outcomes, and implement evidence-based
interventions.
The adoption of paperless systems also plays a crucial role in promoting
interoperability, enabling different healthcare entities to share information more
effectively and coordinate care for patients. This capability is especially important in
the context of complex care networks and integrated delivery systems, where timely
and accurate information exchange is essential for optimizing patient outcomes.
The report also highlights that more organizations are achieving this goal
every day, reflecting a broader industry trend towards digital transformation and the
widespread recognition of the value of health information technology. As more
hospitals reach Stage 7, the collective impact on the healthcare system becomes
increasingly significant, driving improvements in quality of care, operational
efficiency, and overall patient satisfaction.
In summary, the move towards Stage 7 and a paperless environment represents
a key advancement in healthcare delivery, positioning hospitals to better meet the
demands of modern medical practice and the expectations of patients in an
increasingly digital world.
In President Barack Obama’s first term in office, Congress passed the
American Recovery and Reinvestment Act of 2009 (ARRA). This legislation included
the HITECH Act, which specifically sought to incentivize health organizations and
providers to become meaningful users of EHRs. These incentives came in the form of
increased reimbursement rates from the Centers for Medicare and Medicaid Services
(CMS); ultimately, the HITECH Act resulted in payment of a penalty by any
healthcare organization that had not adopted an EHR by January 2015. The final rule
was published by the Department of Health and Human Services (USDHHS) in July
2010 for the first phase of implementation.
Stage 1 meaningful use criteria, as outlined by the United States Department
of Health and Human Services (USDHHS) in 2010, primarily focused on the
fundamental aspects of data capture and sharing. The initial stage aimed to ensure that
healthcare providers were capable of electronically capturing and storing essential
patient information, such as demographics, vital signs, and medical histories. It also
emphasized the need for maintaining problem lists, medication lists, and allergy lists.
Additionally, Stage 1 promoted the use of electronic prescribing (e-prescribing) and
the ability to provide patients with electronic copies of their health information upon
request. This foundational stage was crucial for setting the groundwork for more
advanced health information technology (HIT) initiatives.
Moving forward, Stage 2 criteria, which were implemented in 2014, built upon
the foundation established by Stage 1. This stage advanced several critical clinical
processes and placed a stronger emphasis on health information exchange (HIE) and
patient engagement. Stage 2 required healthcare providers to demonstrate the use of
electronic health records (EHRs) in ways that supported care coordination, improved
quality, and increased efficiency. Key objectives included the electronic transmission
of care summaries during transitions of care, enhanced clinical decision support
systems, and the capability to provide patients with secure online access to their
health information. Furthermore, Stage 2 encouraged more robust patient control over
personal data, empowering individuals to actively participate in their healthcare
management. This stage aimed to foster greater communication between patients and
providers, thereby improving the overall patient experience and care outcomes.
Stage 3, which had a target implementation date of 2016, represented a
significant progression towards achieving improved health outcomes for both
individuals and populations. This stage focused on the utilization of advanced EHR
functionalities to enhance clinical effectiveness and patient safety. Stage 3 objectives
included the incorporation of decision support for national high-priority conditions,
more comprehensive quality measurement and reporting, and the implementation of
advanced directives. Additionally, Stage 3 introduced patient self-management tools,
which are designed to engage patients more actively in their own healthcare. These
tools facilitate better chronic disease management, medication adherence, and
lifestyle modifications by providing patients with resources such as personalized
health plans, interactive educational materials, and remote monitoring capabilities.
Overall, the meaningful use criteria set forth in these stages are part of a
broader federal effort to modernize the American healthcare system through the
widespread adoption of EHRs and HIT. By progressing through these stages,
healthcare providers are expected to achieve higher levels of care quality, safety, and
efficiency, ultimately leading to better health outcomes and a more effective
healthcare delivery system.
b. Components of Electronic Health Records
Before enactment of the ARRA, several variants of EHRs existed, each with
its own terminology and each developed with a different audience in mind. The
sources of these records included, for example, the federal government (Certification
Commission for Healthcare Information Technology, 2007), the IOM (2003), the
HIMSS (2007), and the National Institutes of Health (2006; Robert Wood Johnson
Foundation [RWJF], 2006). Under ARRA, there is now an explicit requirement for
providers and hospitals to use a certified EHR that meets a set of standard functional
definitions to be eligible for the increased reimbursement incentive. Initially,
USDHHS granted two organizations the authority to accredit EHRs: the Drummond
Group and the Certification Commission for Healthcare Information Technology. In
2015, there were five recognized bodies for testing and certifying EHRs
(HealthIT.gov, 2015a). These bodies are authorized to test and certify EHR vendors
against the standards and test procedures developed by the National Institute of
Standards and Technology (NIST) and endorsed by the Office of the National
Coordinator for Health Information Technology for EHRs.
The initial NIST test procedure included 45 certification criteria, ranging from
the basic ability to record patient demographics, document vital signs, and maintain
an up-to-date problem list, to more complex functions, such as electronic exchange of
clinical information and patient summary records (Jansen & Grance, 2011; NIST,
2010). These criteria have been updated several times since 2010, with the 2015
version developed after going out for public comment (HealthIT.gov, 2015b). Each
iteration of certification criteria and testing procedures seeks to make the EHR more
robust, interoperable, and functional to meet the needs of patients and users.
Despite the points articulated in the ARRA, the IOM definition of an EHR also
remains a valid reference point. This definition is useful because it has distilled all the
possible features of an EHR into eight essential components with an emphasis on
functions that promote patient safety—a universal denominator that everyone in
health care can accept. The eight components are (1) health information and data, (2)
results management, (3) order entry management, (4) decision support, (5) electronic
communication and connectivity, (6) patient support, (7) administrative processes, and
(8) reporting and population health management (IOM, 2003). These initial core
components, as well as more recent modifications described by the Health Resources
and Services Administration (HRSA, n.d.) and the components of a comprehensive
EHR identified by HealthIT.gov (Charles, Gabriel, & Searcy, 2015), are described in
more detail here. With the exception of EHR infrastructure functions, such as security
and privacy management, controlled medical vocabularies, and interoperability
standards, the 45 initial NIST standards easily map into the IOM categories.
Health information and data comprise the patient data required to make sound
clinical decisions, including demographics, medical and nursing diagnoses,
medication lists, allergies, and test results (IOM, 2003). This component of the EHR
also includes care management data regarding details of patient visits and interactions
with patients, medication reconciliation, consents, and directives (HRSA, n.d.). A
comprehensive EHR will also contain nursing assessments and problem lists.
NIST has not provided an exhaustive list of all possible features and functions
of an EHR. Consequently, different vendor EHR systems combine different
components in their offerings, and often a single set of EHR components may not
meet the needs of all clinicians and patient populations. For example, a pediatric
setting may demand functions for immunization management, growth tracking, and
more robust order entry features to include weight-based dosing. These types of
features may not be provided by all EHR systems, and it is important to consider EHR
certification to be a minimum standard.
Another group that focuses on EHR standards and functionality is Health
Level Seven International (HL7). Founded in 1987, “Health Level Seven International
(HL7) is a not-for-profit, ANSI-accredited standards developing organization
dedicated to providing a comprehensive framework and related standards for the
exchange, integration, sharing, and retrieval of electronic health information that
supports clinical practice and the management, delivery and evaluation of health
services” (Health level Seven International, n.d., para. 1). This group concentrates on
developing the behind-the-scenes programming standards (Level Seven is the
application level of the Open Systems Interconnection model) for interfaces to ensure
interoperability and connectivity among systems.
c. Advantages of Electronic Health Records
Measuring the benefits of EHRs can be challenging. Possible methods to
estimate EHR benefits include using vendor-supplied data that have been retrieved
from their customers’ systems, synthesizing and applying studies of overall EHR
value, creating logical engineering models of EHR value, summarizing focused
studies of elements of EHR value, and conducting and applying information from site
visits.
Early on, the four most common benefits cited for EHRs were (1) increased
delivery of guidelines-based care, (2) enhanced capacity to perform surveillance and
monitoring for disease conditions, (3) reduction in medication errors, and (4)
decreased use of care. These findings were echoed by two similar literature reviews.
The first review (Dorr et al., 2007) focused on the use of informatics systems for
managing patients with chronic illness. It found that the processes of care most
positively impacted were guidelines adherence, visit frequency (i.e., a decrease in
emergency department visits), provider documentation, patient treatment adherence,
and screening and testing.
The AHRQ study highlighted the common findings already described, but also
noted that most of the data available for review came from six leading healthcare
organizations in the United States, underscoring the challenge of generalizing these
results to the broader healthcare industry. As noted previously by the HIMSS Stage 7
Awards, the challenge to generalize results persists in the hospital arena, with fewer
than 1% of U.S. hospitals or eight leading organizations providing most of the
experience with comprehensive EHRs (HIMSS, 2010a). Finally, the literature reviews
cited here indicated that there are a limited number of hypothesis- testing studies of
EHRs and even fewer that have reported cost data.
The descriptive studies do have value, however, and should not be hastily
dismissed. Although not as rigorous in their design, they do describe the advantages
of EHRs well and often include useful implementation recommendations learned from
practical experience. As identified in these types of reviews, EHR advantages include
simple benefits, such as no longer having to interpret poor handwriting and
handwritten orders, reduced turnaround time for laboratory results in an emergency
department, and decreased time to administration of the first dose of antibiotics in an
inpatient nursing unit. In the ambulatory care setting, improved management of
cardiac-related risk factors in patients with diabetes and effective patient notification
of medication recalls have been demonstrated to be benefits of the EHR. Two other
unique advantages that have great potential are the ability to use the EHR and
decision support functions to identify patients who qualify for research studies or who
qualify for prescription drug benefits offered by pharmaceutical companies at safety-
net clinics and hospitals.
The HIMSS Davies Award may be the best resource for combined quantitative
and qualitative results of successful EHR implementation. The Davies Award
recognizes healthcare organizations that have achieved both excellence in
implementation and value from health information technology (HIMSS, 2010a). One
winner demonstrated a significant avoidance of medication errors because of bar-code
scanning alerts, a $3 million decrease in medical records expenses as a result of going
paperless, and a 5% reduction of duplicate laboratory orders by using computerized
provider order entry alerting (HIMSS, 2010b). Another winner noted a 13% decrease
in adverse drug reactions through the use of computerized physician order entry; it
also achieved a decrease in methicillinresistant Staphylococcus aureus (MRSA)
nosocomial infections from 9.8 per 10,000 discharges to 6.4 per 10,000 discharges in
less than a year using an EHR flagging function, which made clinicians immediately
aware that contact precautions were required for MRSA-positive patients (HIMSS,
2009). At both organizations, there was qualitative and quantitative evidence of high
rates of end user adoption and satisfaction with use of the EHR.
A 2011 study of the effects of EHR adoption on nurse perceptions of quality of
care, communication, and patient safety documented that nurses report better care
outcomes and fewer concerns with care coordination and patient safety in hospitals
with a basic EHR. In this study, nurses perceived that in hospitals with a functioning
EHR, there was better communication among staff, especially during patient transfers,
and fewer medication errors. Bayliss et al. (2015) demonstrated that an integrated care
system utilizing an EHR resulted in fewer hospital readmissions and emergency room
visits for over 12,000 seniors with multiple health challenges.
A CIS is a technology-based system applied at the point of care and designed
to support care by providing instant access to information for clinicians. Early CISs
implemented prior to the advent of EHRs were limited in scope and provided such
information as interpretation of laboratory results or a medication formulary and drug
interaction information. With the implementation of EHRs, the goal of many
organizations is to expand the scope of the early CISs to become comprehensive
systems that provide clinical decision support, an electronic patient record, and in
some instances professional development and training tools. Benefits of such a
comprehensive system include easy access to patient data at the point of care;
structured and legible information that can be searched easily and lends itself to data
mining and analysis; and improved patient safety, especially the prevention of adverse
drug reactions and the identification of health risk factors, such as falls.
The ability to measure outcomes can be enhanced or impeded by the way an
information system is designed and used. Although many practitioners can paint a
very good picture of the patient by using a narrative (free text), employing this mode
of expression in a clinical system without the use of a coded entry makes it difficult to
analyze the care given or the patient’s response. Free-text reporting also leads to
inconsistencies of reporting from clinician to clinician and patient information that is
fragmented or disorganized. This can limit the usefulness of patient data to other
clinicians and interfere with the ability to create reports from the data for quality
assurance and measurement purposes. Moreover, not all clinicians are equally skilled
at the free-text form of communication, yielding inconsistent quality of
documentation. Integrating standardized nursing terminologies into computerized
nursing documentation systems enhances the ability to use the data for reporting and
further research.
According to the IOM (2012), “Payers, healthcare delivery organizations and
medical product companies should contribute data to research and analytic consortia
to support expanded use of care data to generate new insights” (para. 2). McLaughlin
and Halilovic (2006) described the use of clinical analytics to promote medical care
outcomes research. The use of a CIS in conjunction with standardized codes for
patient clinical issues helps to support the rigorous analysis of clinical data. Outcomes
data produced as part of these analyses may include length of stay, mortality,
readmissions, and complications. Future goals include the ability to compare data and
outcomes across various institutions as a means of developing clinical guidelines or
best practices guidelines. With the implementation of a comprehensive CIS, similar
analyses of nursing outcomes could also be performed and shared. Likewise, such a
system could aid nurse administrators in crossunit comparisons and staffing decisions,
especially when coupled with acuity systems data. In addition, clinical analytics can
support required data reporting functions, especially those required by accreditation
bodies.
Evidence-based practice (EBP) can be thought of as the integration of clinical
expertise and best practices based on systematic research to enhance decision making
and improve patient care. References supporting EBP, such as clinical guidelines, are
available for review at the click of a mouse or the press of a few keystrokes. The
CIS’s prompting capabilities can also reinforce the practice of looking for evidence to
support nursing interventions rather than relying on how things have been done
historically. This approach enhances processing and understanding of the information
and allows the nurse to apply the information to other areas, increasing the knowledge
obtained about why certain conditions or responses result in prompts for additional
questions or actions.
To incorporate EBP into the practice of clinical nursing, the information needs
to be embedded in the computerized documentation system so that it is part of the
workflow. The most typical way of embedding this timely information is through
clinical practice guidelines. The resulting interventions and clinical outcomes need to
be measurable and reportable for further research. The supporting documentation for
the EBP needs to be easily retrievable and meaningful. Links, reminders, and prompts
can all be used as vehicles for transmission of this information. The format needs to
allow for rapid scanning, with the ability to expand the amount of information when
more detail is required or desired. Balancing a consistency in formatting with
creativity can be difficult but is worth the effort to stimulate an atmosphere for
learning.
Joy Hilty, a registered nurse from Kaweah Delta, came up with a creative way
to provide staff development or education without taking staff away from the bedside
to a classroom setting. She created pop-up boxes on the opening charting screens for
all staff who chart on the computer. These pop-ups vary in color and content and
include a short piece of clinical information, along with a question. Staff can earn
vacations from these pop-ups for as long as 14 days by emailing the correct answer to
the question. This medium has provided information, stimulation, and a definite
benefit: the vacation from the pop-up boxes. The pop-up box education format has
also encouraged staff to share their answers, thereby creating interaction, knowledge
dissemination, and reinforcement of the education provided.
Embedding EBP into nursing documentation can also increase the compliance
with Joint Commission core measures, such as providing information on influenza
and pneumococcal vaccinations to at-risk patients. In the author’s experience at
Kaweah Delta, educating staff via classes, flyers, and storyboards was not successful
in improving compliance with the documentation of immunization status or offering
education on these vaccinations to atrisk patients. Embedding the prompts,
information, and related questions in the nursing documentation with a link to the
protocol and educational material, however, improved the compliance to 96% for
pneumococcal vaccinations and to 95% for influenza vaccinations.
As more information is stored electronically, nurse informaticists must
translate the technology so that the input and retrieval of information are developed in
a manner that is easy for clinicians to learn and use. A highly usable product should
decrease errors and improve information entry and retrieval. Nurse informaticists
must be able to work with staff and expert users to design systems that meet the needs
of the staff who will actually use the systems. The work is not done after the system is
installed; the system must continue to be developed and improved, because as staff
use the system, they will be able to suggest changes to improve it. This ongoing
revision should result in a system that is mature and meets the needs of the users.
In an ideal world, all clinical documentation will be shared through a national
database, in a standard language, to enable evaluation of nursing care, increase the
body of evidence, and improve patient outcomes. With minimal effort, the
information will be translated into new research that can be analyzed and linked to
new evidence that will be intuitively applied to the CIS. Alerts will be meaningful and
will be patient and provider specific. The steps required of the clinician to find
current, reliable information will be almost transparent, and the information will be
presented in a personalized manner based on user preferences stored in the CIS.
d. Standardized Terminology and the HER
As we inch closer to interoperable EHRs that provide for seamless health
information exchange among providers and healthcare institutions, the need for
standardizing terminologies becomes ever clearer. Consider also the trend toward
value-based care reimbursements, in which healthcare data are mined “to demonstrate
nursing’s contributions to improving the cost, quality, and efficiency of care, key
elements of the value equation” (Adams, Ponte, & Somerville, 2016, p. 127). EHR
data must be formatted in a machine-readable manner in order to support
interoperable exchange of information and data mining. An important distinction that
needs to be made here is the difference between interface terminologies (NANDA,
NIC, or NOC) and reference terminologies.
While interface terminologies play an important role in promoting direct entry
of categorical data by health care providers, both terminology developers and the
standards community historically have focused on other types of terminologies,
including reference and administrative (rather than on interface) terminologies. Such
terminologies are generally designed to provide exact and complete representations of
a given domain’s knowledge, including its entities and ideas and their
interrelationships. For example, reference terminologies can support the storage,
retrieval, and classification of clinical data; their contents correspond to the internal
system representation storage formats to which interface terminologies are typically
mapped.
The various interface terminologies and their subsets are coded in the EHR
and typically presented to the user in dropdown menus. Users may also be able to use
a search function in the EHR to identify the most appropriate term that represents the
patient’s condition(s). Bronnert, Masarie, Naeymi-Rad, Rose, and Aldin (2012)
described the value of an interface terminology for clinician workflow: Clinicians
interact with interface terminology when documenting diagnoses and procedures in
the patient’s electronic record. The physician performs searches using the search
functionality in designated locations in the EHR, which returns terms to the provider
to select the appropriate problem or procedure. The physician [nurse] selects the
appropriate term to capture the clinical intent. The term(s) populate predetermined
fields in the electronic record. The selected term contains mappings to one or more
industry standard terminologies, such as ICD or SNOMED CT. The “behind-
thescenes” mappings allow the physician to focus on patient care while at the same
time capturing the necessary administrative and reference codes.
Because no single model of standardized terminology for health care or
nursing can represent all of the contributions to the health of a patient, work is
ongoing to map terminologies to one another. For example, Kim, Hardiker, and
Coenen (2014) studied the degree of similarity between the International
Classification for Nursing Practice (ICNP) and the Systematized Nomenclature of
Medicine–Clinical Terms (SNOMED– CT); while they identified some areas of
overlap, they cautioned that there is still more work to be done to truly represent
nursing concepts in the EHR. Adams et al. (2016) issued a call to action to Chief
Nursing Officers (CNOs): “CNOs must begin partnering with and influencing EHR
developers and vendors to ensure the EHRs implemented in their organizations
capture nursing content using a standardized taxonomy that is evidence based and
mapped to SNOMED-CT and LOINC”
Ongoing efforts to map nursing problem lists to SNOMED-CT are evident in
the work of Matney and colleagues (2011) and on the National Library of Medicine
website (www.nlm.nih.gov/hit_interoperability.html). It is probably safe to say that
the number of different types of EHRs and the variability of EHRs are likely to
contract and converge as the demand for robust systems supporting interoperability
expands. Nurse informatics specialists and CNOs participating in the selection and
implementation of EHRs must ask a critical question: To what extent are nursing care
contributions visible, retrievable, and accurately represented in this EHR?
e. Ownership of Electronic Health Records
The implementation of an EHR has the potential to affect every member of a
healthcare organization. The process of becoming a successful owner of an EHR has
multiple steps and requires integrating the EHR into the organization’s day-to-day
operations and longterm vision, as well as into the clinician’s day-to-day practice. All
members of the healthcare organization— from the executive level to the clinician at
the point of care—must feel a sense of ownership to make the implementation
successful for themselves, their colleagues, and their patients. Successful ownership
of an EHR may be defined in part by the level of clinician adoption of the tool, and
this section reviews key steps and strategies for the selection, implementation and
evaluation, and optimization of an EHR in pursuit of that goal.
Historically, many systems were developed locally by the information
technology department of a healthcare organization. It was not unusual for software
developers to be employed by the organization to create needed systems and
interfaces between them. As commercial offerings were introduced and matured, it
became less and less common to see homegrown or locally developed systems. As
this history suggests, the first step of ownership is typically a vendor selection process
for a commercially available EHR. During this step, it is important to survey the
organization’s level of interest, identify possible barriers to participation, document
desired functions of an EHR, and assess the willingness to fund the implementation
(Holbrook, Keshavjee, Troyan, Pray, & Ford, 2003). Although clinicians, as the
primary end users, should drive the project, the assessment should also include the
needs and readiness of the executive leadership, information technology, and project
management teams. It is essential that leadership understands that this type of project
is as much about redesigning clinical work as it is about technically automating it and
that they agree to.
The second step of the selection process is to select a system based on the
organization’s current and predicted needs. It is common during this phase to see a
demonstration of several vendors’ EHR products. Based on the completed needs
assessment, the organization should establish key evaluation criteria to compare the
different vendors and products. These criteria should include both subjective and
objective items that cover such topics as common clinical workflows, decision
support, reporting, usability, technical build, and maintenance of the system.
Providing the vendor with these guidelines will ensure that the process meets the
organization’s needs; however, it is also essential to let the vendor demonstrate a
proposed future state from its own perspective. This activity is critical to ensuring that
the vendor’s vision and the organization’s vision are well aligned (Konschak &
Shiple, n.d.). It also helps spark dialogue about the possible future state of clinical
work at the organization and the change required in obtaining it. Such demonstrations
not only enable the organization to compare and contrast the features and functions of
different systems, but also are a good way to engage the organization’s members in
being a part of this strategic decision.
Implementation planning should occur concurrently with the selection process,
particularly the assessment of the scope of the work, initial sequencing of the EHR
components to be implemented, and resources required. However, this step begins in
earnest once a vendor and a product have been selected. In addition to further refining
the implementation plan, this is the time to identify key metrics by which to measure
the EHR’s success. An organization may realize numerous benefits from
implementing an EHR. It should choose metrics that match its overall strategy and
goals in the coming years and may include expected improvements in financial,
quality, and clinical outcomes. Commonly used metrics focus on reductions in the
number of duplicate laboratory tests through duplicate orders alerting, reductions in
the number of adverse drug events through the use of bar-code medication
administration, meaningful use objectives and measures, and the EHR advantages. To
ensure that the desired benefits are realized, it is important to avoid choosing so many
that they become meaningless or unobtainable, to carefully and practically define
those that are chosen, to measure before and after the implementation, and to assign
accountability to a member of the organization to ensure the work is completed.
End-user adoption of the EHR is also essential to realizing its benefits.
Clinicians must be engaged to use the EHR successfully in their practice and daily
workflows so that data may be captured to drive the decision support that underlies so
many of the advantages and metrics described. To promote adoption, a change
management plan must be developed in conjunction with the EHR implementation
plan. The most effective change management plans offer end users several exposures
to the system and relevant workflows in advance of its use and continue through the
go-live and post-live time periods. Successful pre-live strategies include end-user
involvement as subject-matter experts to validate the EHR workflow design and
content build, hosting enduser usability testing sessions, shadowing end users in their
current daily work in parallel with the new system, and formal training activities. The
goal of these pre-live activities is not only to ensure that the EHR implementation will
meet end user needs, but also to assess the impact of the new EHR on current
workflow and process. The larger the impact, the more change management is
required above and beyond system training. For example, simulation laboratory
experiences may be offered to more thoroughly dress rehearse a significant workflow
change, executive leadership may need to convey their support and expectations of
clinicians about a new way of working, and generally more anticipatory guidance is
required to communicate to those impacted by the changes.
Training may be delivered in a variety of media. Often a combination of
approaches works best, including classroom time, electronic learning, independent
exercises, and peer-to-peer, at-the-elbow support. Training must be workflow based
and reflect real clinical processes. It must also be planned and budgeted for through
the post-live period to ensure that competency with the system is assessed at the go-
live point and that any necessary retraining or reinforcements are made in the 30 to 60
days post-live. This not only promotes reliability and safe use of the system as it was
designed but also can have a positive impact on end users’ morale: Users will feel that
they are being supported beyond the initial go-live period and have an opportunity to
move from basic skills to advanced proficiency with the system.
Finally, the implementation plan should account for the long-term
optimization of the EHR. This step is commonly overlooked and often results in
benefits falling short of expectations because the resources are not available to realize
them permanently. It also often means the difference between end users of EHRs
merely surviving the change versus becoming savvy about how to adopt the EHR as
another powerful clinical tool, much as clinicians have embraced such technologies as
the stethoscope (HealthIT.gov, 2012). Optimization activities of the EHR should be
considered a routine part of the organization’s operations, should be resourced
accordingly, and should emphasize the continued involvement of clinician users to
identify ways that the EHR can enable the organization to achieve its overall mission.
Many organizations start an implementation of EHRs with the goal of transforming
their care delivery and operations. An endeavor that differs from simply automating a
previously manual or fragmented process, transformation often includes steps to
improve the process so as to realize better patient care outcomes or added efficiency.
Although some transformation is experienced with the initial use of the system, most
of this work is done postimplementation and relies on widespread clinician adoption
of the EHR. As such, it makes optimization a critical component to successful
ownership of an EHR.
f. What Is a Culture of Safety?
The 2000 Institute of Medicine report To Err Is Human is widely credited for
launching the current focus on patient safety in health care. This report was followed
in 2001 by the Institute of Medicine’s Crossing the Quality Chasm report, which
brought to national attention healthcare quality and safety. This national attention
resulted in a $50 million grant by Congress to the Agency for Healthcare Research
and Quality (AHRQ) to launch initiatives focused on safety research for patients.
Other initiatives prompted by these seminal reports were the Joint Commission’s
National Patient Safety Goals (2002); the National Quality Forum’s adverse events
and “never events” list (2002); the creation of the Office of National Coordinator for
Health Information Technology (HIT) to computerize health care (2004); the
formation of the World Health Organization’s Alliance for Patient Safety (2004); the
Institute for Healthcare Improvement’s (IHI) 100,000 Lives campaign (2005) and 5
Million Lives campaign (2008); Congressional authorization of patient safety
organizations created by the Patient Safety and Quality Improvement Act to promote
blameless error reporting and shared learning (2005); the “no pay for errors” initiative
launched by Medicare (2008); and the $19 billion Congressional appropriation to
support electronic health records (EHRs) and patient safety (Wachter, 2010). In 2013,
the Patient Safety Movement Foundation launched the Open Data Pledge, and later
announced three new patient safety challenges in 2016 (Patient Safety Movement,
2016). The most pressing challenges they identified—venous thromboembolism,
mental health, and pediatric adverse drug events—reflect those where patient death
could be prevented with the proper protocols in place during the provision of patient
care (Patient Safety Movement).
An important part of the safety culture is cultivating a blame-free
environment. Errors and near misses must always be reported so that they can be
thoroughly analyzed. All organizations can learn from mistakes and change their
organizational processes or culture to ensure patient safety. The Patient Safety and
Quality Improvement Act of 2005 mandated the creation of a national database of
medical errors and funded several organizations to analyze these data with the goal of
developing shared learning to prevent medical errors. Organizations themselves can
engage in root-cause analysis or failure modes and effects analysis (FMEA) to
examine medical errors closely and to determine the system processes that need to be
changed to prevent similar future errors (Harrison & Daly, 2009). A tool for
implementing root-cause analysis developed by the U.S. Department of Veteran’s
Affairs National Center for Patient Safety (2015) had three goals: to determine “what
happened, why did it happen and how to prevent it from happening again” (para. 4).
Everyone is encouraged to submit actual medical errors and/or patient safety issues to
the Patient Safety Network (PSNet, 2016a). Similarly, the IHI has a website dedicated
to FMEA. “Failure Modes and Effects Analysis (FMEA) is a systematic, proactive
method for evaluating a process to identify where and how it might fail, and to assess
the relative impact of different failures in order to identify the parts of the process that
are most in need of change” (IHI, 2016b, para. 1).
If one embraces a blame-free environment to encourage error reporting, then
where does individual accountability fit in? This question highlights the delicate
balance between fostering an open, non-punitive culture that promotes transparency
and learning from mistakes, and maintaining a level of accountability that ensures
high standards of professional conduct and patient safety. According to the Agency for
Healthcare Research and Quality (AHRQ), one effective way to reconcile these
seemingly competing cultural values—blamelessness versus accountability—is to
establish a "just culture."
A "just culture" is a framework that seeks to create an environment where
system or process issues that lead to unsafe behaviors and errors are identified and
addressed by changing practices or workflow processes. This approach recognizes
that most errors result from flaws in system design or organizational processes rather
than individual negligence. By focusing on the underlying causes of errors,
organizations can implement changes that improve safety and reduce the likelihood of
future mistakes. However, the "just culture" approach also communicates a clear
message that certain behaviors, particularly reckless ones, are not tolerated.
These are inadvertent actions that occur despite the individual's best
intentions. Human errors are seen as inevitable aspects of the human condition and are
often addressed through system redesign, additional training, or improved support
mechanisms. The focus is on preventing recurrence by understanding why the error
happened and what can be done to prevent it in the future. These occur when
individuals take shortcuts or engage in unsafe practices to accomplish a task. While
these behaviors are not inherently malicious, they represent a conscious deviation
from established protocols that can compromise safety. Addressing risky behaviors
involves understanding why the individual chose the workaround and finding ways to
make the safer, correct behavior the path of least resistance. Interventions might
include modifying workflows, improving communication, or providing better tools
and resources.
This is the most serious category, involving a conscious disregard for
substantial and unjustifiable risk. Reckless behaviors are not tolerated within a "just
culture." Individuals who engage in such behavior are held accountable through
disciplinary actions. The goal is to reinforce the importance of adhering to established
safety protocols and to deter others from similar conduct.
By implementing a "just culture," healthcare organizations can promote a
more balanced approach where learning from mistakes is prioritized, but
accountability for actions is also maintained. This balance ensures that individuals
feel safe to report errors without fear of unjust punishment, while also understanding
that they are responsible for their actions, especially when those actions involve risky
or reckless behavior. This cultural shift requires strong leadership, clear
communication, and ongoing education to be effective. Leaders must model just
culture principles, provide the necessary resources to support safe practices, and
consistently apply fair and transparent processes for evaluating errors and behaviors.
Ultimately, the "just culture" approach helps create a safer healthcare
environment by addressing the root causes of errors and fostering a culture of
continuous improvement, while still upholding professional accountability. This
nuanced strategy not only improves patient safety but also enhances trust and morale
among healthcare staff, as they are supported in their efforts to provide high-quality
care in a system that values both learning and responsibility.
g. Strategies for Developing a Safety Culture
Strategies for achieving a safety culture have been addressed frequently in the
literature. The focus here is limited to those strategies described by two key
organizations, the AHRQ and the IHI. The AHRQ (2016), based on data from the
Hospital Survey on Patient Safety Culture, suggested that teamwork training,
executive walk-arounds, and unit-based safety teams have improved safety culture
perceptions but have not led to a significant reduction in error rates. The AHRQ
recommended seven steps of action planning: “1. Understand your survey results. 2.
Communicate and discuss survey results. 3. Develop focused action plans. 4.
Communicate action plans and deliverables. 5. Implement action plans. 6. Track
progress and evaluate impact. 7. Share what works” (p. 61). Informatics can assist
with the analysis, trending, synthesis, and dissemination of the action plan results.
The IHI (2016a) stressed that organizational leaders must drive the culture
change by making a visible commitment to safety and by enabling staff to share safety
information openly. Some of the strategies suggested by the IHI include appointing a
safety champion for every unit, creating an adverse event response team, and
reenacting or simulating adverse events to better understand the organizational or
procedural processes that failed. Barnet (2016) reported that 49 companies had signed
the open data pledge with Patient Safety Movement. Radick (2016) believed that
senior leaders must be involved in order to sustain patient safety improvements.
Leadership oversight and support is critical to ongoing sharing and, most importantly,
collaborative solution development to provide safe care and achieve quality outcomes
for all patients.
A systems engineering approach to patient safety, in which technology
manufacturers partner with organizations to identify risks to patient safety and
promote safe technology integration, has been advocated by Ebben, Gieras, and
Gosbee (2008). They noted that human factors engineering is “[t]he discipline of
applying what is known about human capabilities and limitations to the design of
products, processes, systems, and work environments,” and its application to system
design improves “ease of use, system performance and reliability, and user
satisfaction, while reducing operational errors, operator stress, training requirements,
user fatigue, and product liability” (p. 327). For example, Ebben et al. described the
feel of an oxygen control knob that rotated smoothly between settings, suggesting to
the user that oxygen flows at all points on the knob, when in fact oxygen flowed only
at specifically designated liter flow settings. Human factors engineering testing would
most likely reveal this design flaw, and the setting knob could be improved to include
discrete audio or tactile feedback (click into place) to the user to indicate a point on
the dial where oxygen flows. Ebben et al. also emphasized that testing human use
factors provides more objective safety data than the subjective responses gained from
user preference testing. “Understanding how the equipment shapes human
performance is as important as evaluating reliability or other technical criteria”.
Organizations that are purchasing medical technology devices should avail themselves
of shared safety data on equipment maintained by several key organizations, including
the Joint Commission, the Food and Drug Administration, and the Medical Product
Safety Network. Many healthcare practitioners feel that we have not made great
strides in either sharing our data or accessing the available data to enhance patient
safety interests.
According to the WISH Patient Safety Forum (2015), the patient safety
premises that harms are inevitable, data silos are natural, and heroism is the norm
"have inadvertently provided excuses for not addressing patient safety
comprehensively." These entrenched beliefs have shaped the healthcare industry's
approach to patient safety in ways that may hinder rather than help efforts to create a
safer healthcare environment.
The premise that harms are inevitable suggests an acceptance of adverse
events as an unavoidable part of medical care. This fatalistic attitude can lead to
complacency and a lack of urgency in implementing systemic changes aimed at
preventing errors. Instead of striving for zero harm, this mindset may cause healthcare
providers and administrators to view patient safety incidents as regrettable but
expected outcomes, thereby diminishing the drive for continuous improvement and
innovation in safety practices.
Data silos, the second premise, refer to the isolated pockets of information that
exist within and between healthcare organizations. These silos prevent the seamless
sharing and integration of critical patient data, which is essential for comprehensive
care coordination and safety monitoring. When data is not shared effectively,
healthcare providers may lack access to complete patient histories, which can lead to
gaps in care, redundant tests, and potential medication errors. The normalization of
data silos as a natural state of affairs can result in missed opportunities to leverage
health information technology for improving patient outcomes and safety.
The third premise, that heroism is the norm, glorifies the idea that individual
healthcare providers, through extraordinary effort and personal sacrifice, can
overcome systemic deficiencies to ensure patient safety. While recognizing the
dedication and commitment of healthcare workers is important, this belief can obscure
the need for robust systems and processes that support safe care. Reliance on heroism
can create an unsustainable work environment where staff are expected to consistently
go above and beyond to mitigate risks, rather than working within a well-designed
system that inherently promotes safety. This can lead to burnout and increased risk of
errors, as overworked staff may not always be able to perform at heroic levels.
Together, these premises have inadvertently provided excuses for not
addressing patient safety comprehensively. By accepting harm as inevitable, data silos
as natural, and heroism as the norm, the healthcare industry may overlook the
fundamental changes needed to enhance patient safety. A comprehensive approach to
patient safety requires acknowledging that preventable harm can and should be
eliminated, breaking down data silos to ensure the free flow of information, and
designing systems that support and sustain safe practices without relying on
extraordinary individual efforts.
The WISH Patient Safety Forum advocates for a paradigm shift in how patient
safety is approached. This includes fostering a culture that prioritizes safety at all
levels, investing in interoperable health information systems, and developing
processes that support consistent and reliable care delivery. By challenging the
outdated premises and embracing a more holistic and proactive approach, healthcare
organizations can make significant strides in reducing harm and improving patient
outcomes.
In summary, the entrenched beliefs that harms are inevitable, data silos are
natural, and heroism is the norm have inadvertently allowed the healthcare industry to
avoid addressing patient safety in a comprehensive manner. To create a safer
healthcare environment, it is essential to reject these premises and adopt a more
integrated and systemic approach to patient safety. This involves recognizing that
preventable harm is unacceptable, ensuring seamless data integration and sharing, and
designing robust systems that promote safety without relying on individual heroics.
Once the technology is integrated into the organization, biomedical engineers
can become valuable partners in promoting patient safety through appropriate use of
these technologies. For example, in one organization, the biomedical engineers helped
to revamp processes associated with the new technology alarm systems after they
discovered several key issues: slow response times to legitimate alarms and multiple
false alarms (promoting alarm fatigue) created by alarm parameters that were too
sensitive. Strategies for addressing these issues included improving the nurse call
system by adding Voice over Internet Protocol telephones that wirelessly receive
alarms directly from technology equipment carried by all nurses, thus reducing
response times to alarms; feeding alarm data into a reporting database for further
analysis; and encouraging nurses to round with physicians to provide input into alarm
parameters that were too sensitive and were generating multiple false alarms (Joint
Commission, 2013; Williams, 2009).
Research Brief 1 describes three investigations spanning from 2009 to 2016: a
study of intelligent agent (IA) technology to improve the specificity of physiologic
alarms, an integrative review of alarms, and default alarm setting changes coupled
with in-service education. The Case Scenario, Well-Intentioned Providers,
demonstrates how well-intentioned healthcare providers can cause harm. An audit
conducted at one of their customer sites by Philips Healthcare (2013) revealed that a
Telemetry Charge Nurse was found to be receiving and responding to an average of
3.7 alarms per minute over the duration of the audit. Even allowing for minimal time
to respond to each alarm, it is clear that this situation was problematic. A majority of
that nurse’s time was spent responding to alarms, and inevitably some were missed.
Clearly, there is more work to be done to create safety cultures in complex
healthcare organizations and to reduce the incidence of errors. Many organizations are
looking to informatics technology to help manage these complex safety issues by
using smart technologies that provide knowledge access to users, provide automated
safety checks, and improve communication processes. Harrison (2016) stated that “as
nurse leaders in a clinical setting where smart tools are leveraged to increase the
quality and safety of patient care, we have certain responsibilities to ensure safe
implementation, training, and monitoring. To best utilize the available technology,
nurse leaders and administrators must be able to use data. More and more graduate
programs for nursing administrators are realizing the need for these emerging nursing
leaders to be skilled in nursing informatics. These leaders must be able to use data,
information, and knowledge efficiently and effectively to assess and manage their
clinical settings and ultimately apply these informatics skills to improve patient
outcomes and the quality of patient care.
The GAO interviewed patient safety experts and the related literature to
identify three key gaps where better information could help guide hospital officials in
their continued efforts to implement patient safety practices. These gaps involve a
lack of “(1) information about the effect of contextual factors on implementation of
patient safety practices, (2) sufficiently detailed information on the experience of
hospitals that have previously used specific patient safety implementation strategies,
and (3) valid and accurate measurement of how frequently certain adverse events
occur” (p. 22). Once again, implementing solid nursing informatics practices, skills,
and knowledge can close these gaps.
h. Informatics Technologies for Patient Safety
Healthcare technologies are frequently designed to improve patient safety,
streamline work processes, and improve the quality and outcomes of healthcare
delivery. However, technology is not always the answer to patient safety; as the Joint
Commission (2008) cautioned, “the overall safety and effectiveness of technology in
health care ultimately depends on its human users, and . . . any form of technology
can have a negative impact on the quality and safety of care if it is designed or
implemented improperly or is misinterpreted” (para. 2). As we continue to look to
HIT to advance patient safety initiatives, we must realize that integrating HIT presents
other challenges and can add to the patient safety issues. For example, Singh and
Sittig (2016) stated that HIT has the “potential to improve patient safety but its
implementation and use has led to unintended consequences and new safety concerns.
A key challenge to improving safety in health IT–enabled healthcare systems is to
develop valid, feasible strategies to measure safety concerns at the intersection of
health IT and patient safety”
Although technology may certainly help to prevent or reduce errors, one must
always remember that technology is not a substitution for safety vigilance by the
healthcare team in a safety culture. Harrison (2016) stated that “[p]atient safety should
always be at the center of the design and adoption of any technology introduced into
patient care settings. Technology that’s designed to improve patient safety is only as
good as the person using the device. It doesn’t replace critical thinking, solid nursing
practice, and careful patient monitoring”
The Wired for Health Care Quality Act of 2005 began a series of funding
streams to promote HIT, promote sharing of best practices in HIT, and help
organizations implement HIT (Harrison & Daly, 2009). Many early adopters opted to
focus technology and safety initiatives on medication ordering and administration
processes. Medication errors are the most frequent and the most visible errors because
the medication administration cycle has many poorly designed work processes with
several opportunities for human error. Thus computerized physician order entry
(CPOE), automated dispensing machines, smart pump technologies for IV drug
administration, and bar-code medication administration (BCMA) frequently preceded
the adoption of the EHR in many institutions because of the costs associated with
implementing these technologies. In an ideal world, the EHR would be adopted
concurrently as part of an interoperable HIT system. In the early EHR systems,
clinicians were prompted by electronic alerts reminding them of important
interventions that should be part of the standard of care, but these alerts tended to be
generalized and not patient specific—for example, “Did you check the allergy
profile?” or “Has the patient received a pneumonia immunization?” These early alert
and care reminders are now evolving into more sophisticated clinical decision support
(CDS) systems to promote accurate medical diagnoses and suggest appropriate
medical and nursing interventions based on patient data.
With the addition of triggers to detect adverse events, diagnostic errors,
adverse drug events, hospitalacquired infections, and delays in diagnoses have been
identified. “Trigger algorithms are frequently applied to EMRs for automated
surveillance, and increasingly to prospectively identify patients at risk” The National
Patient Safety Foundation (2016) listed the top patient safety issues as wrong-site
surgery, hospital-acquired infections, falls, hospital readmissions, diagnostic errors,
and medication errors. Many of these issues can be prevented or detected in their
early stages using informatics technologies, although we still continue to struggle with
these same safety issues. Other technologies designed to promote patient safety
include wireless technologies for patient monitoring, clinician alerts, point-of-care
applications, apps, and radiofrequency identification applications. Each of these is
reviewed here, concludes with a section discussing future technologies for patient
safety.
The steps in the medication administration cycle (assessment of need,
ordering, dispensing, distribution, administration, and evaluation) have been relatively
stable for many years. Each of the steps depends on vigilant humans to ensure patient
safety, resulting in the five rights of medication administration: (1) the right patient,
(2) the right time and frequency of administration, (3) the right dose, (4) the right
route, and (5) the right drug. Human error can be related to many aspects of this cycle.
Distractions, unclear thinking, lack of knowledge, short staffing, and fatigue are a few
of the factors that cause humans to deviate from accepted safety practices and commit
medication errors. Integration of technology into the medication administration cycle
promises to reduce the potential for human errors in the cycle by performing
electronic checks and providing alerts to draw attention to potential errors. Research
Brief 2 describes high-risk and preventable drug-related complications.
CPOE is an electronic prescribing system designed to support physicians and
nurse practitioners in writing complete and appropriate medication and care orders for
patients. When CPOE is part of an EHR with a CDS system, the medication order is
electronically checked against specific data in the patient record to prevent errors,
such as ordering a drug that might interact with a drug the patient is already taking,
ordering a dose that is too large for the patient’s weight, or ordering a drug that is
contraindicated by the patient’s allergy profile or renal function. Because it is
impossible for, and unreasonable to expect, a clinician to remember each of the more
than 600 drugs that require a dose adjustment in the case of renal dysfunction, for
example, safe dosing parameters are provided by the CPOE (Bates & Gawande,
2003). In a stand-alone CPOE system without a CDS system, the medication orders
are simply checked by the computer against the drug database to ensure that the dose
and route specified in the order are appropriate for the medication chosen.
CPOE solves the safety issues associated with poor handwriting and unclear or
incomplete medication orders. Orders can be entered in seconds and from remote
sites, eliminating the use of verbal orders that are especially subject to interpretation
errors. Orders are then transmitted electronically to the pharmacy, reducing the
potential for the transcription errors commonly encountered in the paper-based
system, such as lost or misplaced orders, delayed dosing, or unreadable faxes. Thus
CPOE changes workflows for all clinical staff and physicians as well as health team
communication patterns (Doshi, 2015). As with any technology integration,
introduction of CPOE is associated with a resistance to change and a learning curve to
gain proficiency, and users must learn to trust the system. Manor (2010) urges careful
planning and training during implementation with plenty of staff support. Manor also
reports on the need for a paperbased backup system in the case of network or
electrical outages or system maintenance.
The verification and dispensing functions of the pharmacy can also be assisted
by technology. The pharmacist begins by verifying the allergy status of the patient and
the medication reconciliation information to ensure that the new medication is
compatible with other medication in the care regimen. This verification function is
computer based, and the medication order is electronically checked via the knowledge
database. If the order is verified as safe and appropriate, the pharmacist proceeds to
the dispensing process. Barcode medication labeling at a unit dose level was
mandated by the Food and Drug Administration in 2004, with targeted compliance to
be achieved by 2006. A bar code is a series of alternating bars and spaces that
represents a unique code that can be read by a special bar-code reader. Bar-code
technology spans both the medication dispensing and administration steps in the
medication administration cycle. In the pharmacy, the bar code helps to ensure that
the right drug and the right dose are dispensed by the pharmacy. Medications that are
labeled with bar codes can also be dispensed by robots capable of reading the codes or
by automated dispensing machines. In this way, bar-code technology helps with the
processes of procurement, inventory, storage, preparation, and dispensing.
The processes of drug storage, dispensing, controlling, and tracking are easily
carried out via automated dispensing machines (also known as automated dispensing
cabinets, unit-based cabinets, automated dispensing devices, and automated
distribution cabinets). These devices have benefits for both the user and the
organization, specifically in the areas of access security (especially with narcotics
administration tracking), safety, supply chain, and charge functions.
BCMA systems help to ensure adherence to the five rights of medication
administration. Whether BCMA is part of the larger EHR or a free-standing electronic
medication administration system (eMAR), bar-code technology provides a system of
checks and balances to ensure medication safety. The nurse begins by scanning his or
her name badge, thereby logging in as the person responsible for medication
administration. Next, the bar code on the patient’s identification bracelet is scanned,
prompting the electronic system to pull up the medication orders. Next, the bar code
on each of the medications to be administered is scanned. This technology check
ensures that the five rights of medication administration are met. If there is a
discrepancy between the order and the medication that was scanned or a
contraindication for administration, an alert is generated by the system. For example,
in an EHR system with CDS, the nurse may be prompted to check the most recent
laboratory results for electrolytes before administering a potassium supplement. In a
free-standing eMAR without CDS or EHR links, if the medication orders have
recently been changed, the nurse is alerted to the change. When an alert is generated,
the nurse must chart the action taken in response to that alert. For example, an early
dose might need to be given if the patient is leaving the unit for a diagnostic test.
Smart pump technologies are designed for safe administration of high-hazard
drugs and to reduce adverse drug events during IV medication administration. Smart
pumps have software that is programmed to reflect the facility’s infusion parameters
and a drug library that compares normal dosing rates with those programmed into the
pump. Discrepancies generate an alarm alerting the clinician to a safety issue. A soft
alarm can typically be overridden by a clinician at the bedside, but a hard alarm
requires the clinician to reprogram the pump so that the dosing falls within the
facility’s IV administration guidelines for the drug to be infused. All alarms generated
by the smart pump are tracked along with the clinician’s responses to them
(Cummings & McGowan, 2015; Dulak, 2005; University of Alabama at Birmingham,
2013). Smart pumps can be seamlessly integrated into BCMA systems, and data can
be fed directly into the EHR.
A CDS can enhance the medication administration cycle by promoting safety
and improving patient outcomes. The CDS is guided by targeted information delivery,
ensuring that the five rights of CDSs are implemented: the right information provided
to the right person in the right format through the right channel at the right time in
workflow. For example, during medication selection, a CDS helps a clinician select an
appropriate medication based on client data, such as clinical condition, weight, renal
function, concurrent medications, and cost. This system ensures that the order is
complete by performing checks for drug interactions, duplications, or allergy
contraindications and ensures the right dose and right route are specified. During the
verification and dispensing phase of the medication administration cycle, the CDS
provides double checks for interactions, allergies, and appropriate dose orders.
Consideration is also given to potential infusion pump programming issues,
incompatibilities during infusion, and proper notation and dispensing when portions
of a dose must be wasted. During the administration phase, the CDS assists with
patient identification and current assessment parameters (i.e., blood pressure, glucose
level) that may contraindicate the use of the medication at that point in time. In
addition, checks for interactions with foods or other medications and timing and
monitoring guidelines are provided to the clinician administering the medication. The
CDS has patient education guidelines and printable handouts to assist clinicians in
educating patients about their medications. The monitoring functions of the CDS
provide a structured data reporting system to track side effects and adverse events
across the population.
