PEER REVIEW

MHI 583 Methods Medical-Electronic Health Record (EHR)

Student’s Name: S. H.

Department, University Affiliation

Course Number, Course Title

Professor’s Name

Date

Electronic Health Record (EHR)

ABSTRACT

This paper explores the adoption of electronic health record (EHR) systems, and ways it can benefits better care, and decreased healthcare costs, serious unintended consequences from the implementation of these systems have emerged. The articles, however, vary in similar, and different definitions that are used for Electronic health records that improve care delivery. This paper examines how to use electronic health record (EHR) systems in a meaningful way to their full potential, as well as improved system communication. Although professional organizations and federal agencies encourage widespread adoption, no national data are available regarding the penetration of electronic health records into primary care pediatric practices (KEMPER, UREN, CLARK, 2006). Electronic health records (EHRs) have the potential to advance the quality of care, but studies have shown mixed results. The authors sought to examine the extent of EHR usage and how the quality of care delivered in ambulatory care practices varied according to duration of EHR availability.

 

 

 

 

 

INTRODUCTION

EHRs are real-time, patient-centered records that make information available instantly and securely to authorized users. While an EHR does contain the medical and treatment histories of patients, an EHR system is built to go beyond standard clinical data collected in a provider’s office and can be inclusive of a broader view of a patient’s care (HEALTHIT, 2021). Electronic health records are concentrated in larger and networked pediatric practices (HEALTHIT, 2021). Smaller and independent pediatric practices, the most common types of practice, are unlikely to adopt electronic health records until the cost of implementing and maintaining the systems decreases, developing standards for interoperability are adopted, and electronic health records are widely perceived to improve quality of care by practicing general pediatricians (HEALTHIT, 2021). The lack of decision support in current electronic health records may limit the ability of these tools to improve care delivery (KEMPER, UREN, CLARK, 2006).

Electronic health records (EHRs) have the potential to advance the quality of health care by providing timely access to patients' health information, tracking patients over time to ensure that they receive guideline-recommended care, and offering decision-support mechanisms to reduce medical errors (ZHOU, SORAN,JENTER, VOLK, ORAV, BATES, SIMON, 2009).However, cross-sectional studies have failed to show a direct correlation between having an EHR and high levels of quality of care, suggesting that simply having an EHR may not be sufficient to improve quality and safety of health care (ZHOU, SORAN,JENTER, VOLK, ORAV, BATES, SIMON, 2009). Nonetheless, randomized controlled trials demonstrate clearly that quality improvement occurs when specific decision support is in place (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009). Other factors, such as presence of order entry and better training and implementation of EHR systems, are likely also needed to achieve higher levels of quality and safety. In addition, it is conceivable that quality and safety benefits of EHR adoption and use may be time-dependent, possibly taking some years after implementation to occur, as users become more facile with the applications (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009). As with other new technologies, there may be considerable lag in comprehensive usage and consequent delay in realizing the benefits attributable to EHR adoption (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009). Therefore, we undertook the present study to examine how the quality of care delivered in ambulatory care practices varied according to duration of EHR adoption and usage (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009).

Electronic medical records improve quality of care, patient outcomes, and safety through improved management, reduction in medication errors, reduction in unnecessary investigations, and improved communication and interactions among primary care providers, patients, and other providers involved in care (MANCA, 2015). Electronic medical records improve the work lives of family physicians despite some subjective concerns about implementation costs and time (MANCA, 2015). Electronic medical records have been demonstrated to improve efficiencies in workflow through reducing the time required to pull charts, improving access to comprehensive patient data, helping to manage prescriptions, improving scheduling of patient appointments, and providing remote access to patients’ charts (MANCA, 2015). Electronic medical records capture point-of-care data that inform and improve practice through quality improvement projects, practice-level interventions, and informative research (MANCA, 2015). Healthcare leaders are enrapt by EHR investments. Hospitals and health systems shell out millions — sometimes billions — of dollars to implement EHR systems, and people want to know who is spending what (BECKER, 2016). Boston-based Partners HealthCare and Rochester, Minn.-based Mayo Clinic turned heads when both said their Epic EHR implementation projects would exceed $1 billion. EHR price tags elicit some to scoff at vendors and criticize them for overpricing software systems, especially when reported costs reach billions, but vendor costs make up only a fraction of an implementation budget (BECKER, 2016). EHR system vendors often add functionalities to assist with documentation, such as copy and paste, templates, use of standard phrases and paragraphs, and automatic object insertion (e.g., clinical values brought in from other parts of the electronic record) (BOWMAN, 2013). Benefits of these features include improved efficiency of data capture, timeliness and legibility, and consistency and completeness of documentation (BOWMAN, 2013). However, when used inappropriately, without proper education and controls, these features can lead to inaccurate documentation and potentially result in medical errors or allegations of fraud (BOWMAN, 2013).  Errors related to copy/paste functionality and templates, described in further detail below, represent two of the most common EHR risks associated with inappropriate documentation capture (BOWMAN, 2013).

METHODS

The study linked two data sources: a statewide survey of physicians' adoption and use of EHR and claims data reflecting quality of care as indicated by physicians' performance on widely used quality measures (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009). Using four years of measurement, we combined 18 quality measures into 6 clinical condition categories (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009). While the survey of physicians was cross-sectional, respondents indicated the year in which they adopted EHR. In an analysis accounting for duration of EHR use, we examined the relationship between EHR adoption and quality of care (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009).

EHR systems offer opportunities to transform healthcare, but only if the systems are properly designed and used and the data in the systems are accurate (BOWMAN, 2013). Although HIT-associated risks have been reported in the literature for at least a decade and research over the past several decades supports HIT usability guidelines and principles to improve safety, these guidelines and principles have not been put into widespread practice. Nor has little other action been taken to address these risks (BOWMAN, 2013).

A 2008 study noted that a few reports had documented the potential of EHRs to contribute to healthcare system flaws and patient harm, but few EHR risk management strategies had been published (BOWMAN, 2013). A dynamic tension exists between the need for design standards and vendors’ competitive differentiation, resulting in restraint of the dissemination of best practices for EHR design (BOWMAN, 2013). Safer implementation and use of HIT are a complex, dynamic process requiring a shared responsibility between vendors and healthcare organizations (BOWMAN, 2013). Policy makers, EHR vendors, and healthcare providers must all work together to ensure that EHR systems prevent, rather than cause, medical errors, and lead to better patient care (BOWMAN, 2013). To achieve the high-level quality of care and improved patient safety anticipated from the use of HIT, the problems with EHR design and use that hinder achievement of these benefits need to be addressed (BOWMAN, 2013). The need for more rigorous data quality governance, stewardship, management, and measurement is greater than ever (BOWMAN, 2013).

To prevent medical errors (including errors that stem from flawed or erroneous information), it is not merely the design of the EHR system that is important, but also its implementation, or how it is incorporated into clinical processes and workflow and how users actually use it in routine clinical care (BOWMAN, 2013).The risk of patient harm associated with a specific application should be systematically assessed, and quality and safety procedures that are proportional in stringency to the identified clinical risk should be adopted (BOWMAN, 2013). The current approach to EHR standardization and certification does not address system implementation, usability by clinicians (including integration with workflows), or information integrity (BOWMAN, 2013). Certification criteria used to establish eligibility for use in the Centers for Medicare and Medicaid Services EHR Incentive Program, while slowly starting to address EHR safety and usability issues, are not yet sufficient to ensure EHR-related safety and improve information integrity (BOWMAN, 2013). 

STATEWIDE SURVEY OF PHYSICIANS' USE OF ELECTRONIC HEALTH RECORDS

In 2005, we surveyed a representative sample of physicians in Massachusetts regarding adoption and use of EHRs (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009). The methods for sampling, questionnaire development, survey administration and data collection have been described elsewhere. The following presents a summary of the methods. The survey and research protocol were approved by the Human Studies Committee of Partners Healthcare (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009)..

PARTICIPANTS

Out of 6,174 active medical and surgical practices in Massachusetts, we drew a stratified random sample of 1977 practices and then randomly selected one physician per practice (BOWMAN, 2013). After excluding ineligible practices and physicians, the remaining sample included 1884 physicians, of whom 1,345 (71%) responded to the survey (BOWMAN, 2013). We further excluded respondents who indicated that they do not see any outpatients or who did not complete the principal questions on EHR prevalence, resulting in 1,181 respondents for subsequent analysis. Demographic characteristics of respondents and non-respondents were similar (BOWMAN, 2013).

EHR ADOPTION AND USE

An eight-page questionnaire collected demographic and practice information, as well as measures of health information technology (HIT) adoption and usage. For this analysis, we used the reported date of EHR adoption, use of EHR features, demographics, and practice information (BOWMAN, 2013). Respondents indicated how long they had been associated with their main practice and if their main practice had an HER (ZHOU, SORAN,JENTER, VOLK, ORAV, BATES, SIMON, 2009).If a practice was currently using an EHR, respondents indicated when their practice first began using it and noted which EHR features were available and, if available, the extent to which they used each feature (most or all of the time; some of the time; do not use). The EHR features are listed in. Because we hypothesized that certain essential EHR functions would be more likely than others to be associated with quality of care, we took the following approach to define these key features (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009). Starting with the Institute of Medicine's eight core EHR functions, a government advisory panel identified four functions essential to a functioning EHR “health information and data”, “result management”, “order entry management” and “decision support”; we added “electronic communication and connectivity” and mapped use of the ten features included in our survey to these five core EHR functions, as shown in (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009).

Table 1(ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009).

Table 1 Core EHR Functions and Associated Features that were Studied in the Survey.

Core EHR Functions ∗	Features in Statewide Survey
Health information and data ∗	Electronic visit notes
(access to key information, such as patients' diagnoses, allergies, and medications)	Medication list
	Problem list
Result management ∗	Laboratory test results viewing
(ability to manage results of all types electronically)	Radiology test result viewing
Order entry and management ∗	Laboratory order entry
(ability to enter and store orders for prescriptions, tests, and other services into a computer)	Radiology order entry
	Electronic transmission or faxing of prescriptions
Decision Support ∗	Reminders for care activities (e.g., overdue health maintenance)
(computer reminders, alerts, prompts and computerized decision support systems to improve prevention, diagnosis and management of patient disease)
Electronic communication and connectivity ∗	E-referrals or clinical messages
(efficient, secure, and readily accessible electronic communication between providers and patients)	(e.g., via e-mail) between providers

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∗ Health information and data, result management, order entry and management, and decision support were defined as core EHR functions by an Institute of Medicine Panel. 16 The authors added electronic communication and connectivity as an additional core function.

EHR = electronic health record.

In addition, to assess financial considerations, respondents were asked to indicate whether their practice's income or their personal earnings were eligible for incentive payments for quality of care, patient satisfaction, adoption of HIT, or actual use of HIT.

Statewide Data on Physicians' Quality of Care (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009).

DATA SOURCE AND MEASURES

The quality-of-care measures in this study were based on the National Committee for Quality Assurance (NCQA)—Healthcare Effectiveness Data and Information Set (HEDIS®). The Massachusetts Health Quality Partners (MHQP) has aggregated HEDIS® data for commercially insured members from five major health plans in Massachusetts, accounting for approximately 75% of the state's population, and provided annual physician-level data for survey respondents for 2001–2004. After removing specialists and other survey respondents who did not have any HEDIS® data, the resulting analytic sample included 506 physicians (42.8% of the survey respondents) with at least 1 year of HEDIS® data, of whom 445 (87.9%) had 4 years of data (FRISSE,&MISULIS,2019). From a set of 18 available quality measures, we aggregated measures based on six previously defined clinical categories of quality, as shown in (ZHOU, SORAN,JENTER, VOLK, ORAV, BATES, SIMON, 2009).

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Table 2

Table 2 HEDIS® Quality Measures Aggregated into Six Clinical Categories ∗

Clinical Category	Measures
Asthma care	Appropriate asthma medications for children
	Appropriate asthma medications for adults ages 18–56 yrs
Behavioral and mental health	Effective acute phase treatment
	Effective continuation phase treatment
	Optimal practitioner contacts during acute phase
Cancer screening	Breast cancer screening
	Cervical cancer screening
Diabetes care	LDL-C screening
	LDL-C controlled (less than 130 mg/dL)
	Eye examinations
	HbA1c testing
	Poor HbA1c control
	Monitoring diabetic nephropathy
Well child and adolescent visit†	Well-child visits first 15 mo of life
	Well-child visits ages 3–6
	Well care visits for adolescents
Women's health	Chlamydia screening in women ages 16–20
	Chlamydia screening in women ages 21–25

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∗ Not all physicians were eligible for each clinical category, as inclusion depended on having at least five eligible patients for each HEDIS® measure group. The clinical categories were adopted from prior study. 17

† Only applied to physicians who practiced in pediatrics and family medicine.

HEDIS = Healthcare Effectiveness Data and Information Set.

DEFINITIONS OF PERFORMANCE ON QUALITY MEASURES

Each physician's performance on individual HEDIS® measures was defined as the proportion of patients receiving the required care among the eligible patients for that measure (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009). We created an annual score for each physician for each of the six clinical categories for which they were eligible by summing the numerators for each of the component HEDIS® measures and dividing by the sum of the denominators (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009). For example, considering the cancer screening category, if a physician had 15 of 20 eligible patients completing mammography and 22 of 25 patients completing cervical cancer screening, the score for that category would be (15 + 22)/(20 + 25) = 0.82, or 82%. For each category we excluded physicians who had less than 5 eligible patients, i.e., the sum of the denominators was less than 5, because estimates based on such small samples may not be statistically valid (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009).

RESULT

The percent of physicians reporting adoption of EHR and availability of EHR core functions more than doubled between 2000 and 2005 (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009). Among EHR users in 2005, the average duration of EHR use was 4.8 year (FRISSE, &MISULIS,2019). For all 6 clinical conditions, there was no difference in performance between EHR users and non-users (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009). In addition, for these 6 clinical conditions, there was no consistent pattern between length of time using an EHR and physician’s performance on quality measures in both bivariate and multivariate analyses (ZHOU, SORAN, JENTER, VOLK, ORAV, BATES, SIMON, 2009).

DISCUSSION

EHR systems can transform the way healthcare is delivered when these technologies are designed, implemented, and used appropriately (BOWMAN, 2013). Designed and used inappropriately, EHRs add a layer of complexity to the already complex delivery of healthcare, leading to unintended adverse consequences such as dosing errors, failure to detect serious illnesses, and delays in treatment due to poor human-computer interactions or loss of data (BOWMAN, 2013).While much has been written about EHR-associated risks impacting information integrity, and the subsequent actual and potential impacts on quality of care and safety over at least the past decade, little has been done to systematically measure and analyze these risks, identify the root causes, and universally implement strategies (such as system design modifications and adoption of usability principles) to reduce risks (BOWMAN, 2013). However, attention to the potential unintended consequences of electronic documentation is growing. In addition to the risks to the quality and safety of patient care, apprehension about EHR-associated errors may be a barrier to EHR adoption and use (BOWMAN, 2013).

CONCLUSION

In closing, Electronic health records (EHRs) were generally developed with adult inpatient or ambulatory care as the principal focus. Therefore, the design, functionality, and anticipated workflow serve those arenas well, but serve many other specialties less well (FRISSE,&MISULIS,2019). Although many system developers and policy makers believe that the risks of EHRs are minor and easily manageable, that is not the case (BOWMAN, 2013). Patient safety and quality of care are seriously compromised by flawed EHR system design or functionality or improper use (BOWMAN, 2013). Failure to address information integrity issues in EHR systems will lead to spiraling, rather than declining, healthcare costs and medical errors because of the proliferation of new types of patient safety hazards (BOWMAN, 2013).

A combination of federal government oversight and industry action is necessary to avert unintended consequences from EHR use (BOWMAN, 2013). Federal leadership, in the form of regulation and oversight (and legislation if appropriate), is needed to ensure the development, implementation, and enforcement of comprehensive national standards for the design, performance, and use of EHR systems that reduce serious EHR-related errors (BOWMAN, 2013). However, federal oversight alone is insufficient to eliminate EHR-related adverse events. EHR system vendors should adopt design and usability standards that optimize system safety and information integrity (BOWMAN, 2013). Healthcare providers should implement policies and procedures that address proper EHR training and use, to prevent errors related to system use (rather than system design) and identify errors in the EHR before patient care is affected (BOWMAN, 2013).

 

REFERENCES

Do electronic medical records improve quality of care?: Yes. (n.d.). PubMed Central (PMC).  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4607324/

Impact of electronic health record systems on information integrity: Quality and safety implications. (n.d.). PubMed Central (PMC).  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3797550/

The relationship between electronic health record use and quality of care over time. (2009). PubMed Central (PMC).  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2705247/

Unpacking hospitals' EHR implementation costs: What's behind the million-dollar price tags?. Numbers are meaningless without context, but those in health IT can often get trapped in a numbers game. When dollar signs related to EHR implementations are ablaze in headlines, it's easy to take those numbers at face value. (n.d.). Becker's Hospital Review - Healthcare News.  https://www.beckershospitalreview.com/healthcare-information-technology/unpacking-hospitals-ehr-implementation-costs-what-s-behind-the-million-dollar-price-tags.html

What is an electronic health record (EHR)? | HealthIT.gov. (n.d.). ONC | Office of the National Coordinator for Health Information Technology.  What is an electronic health record (EHR)? | HealthIT.gov

Frisse & Misulis. (2019). Essentials of clinical informatics. Oxford University Press. New York, NY. ISBN: 978019085574.

 

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