Understanding differences in electronic health record (EHR) use: linking individual physicians’ perceptions of uncertainty and EHR use patterns in ambulatory care

Objective

Electronic health records (EHR) hold great promise for managing patient information in ways that improve healthcare delivery. Physicians differ, however, in their use of this health information technology (IT), and these differences are not well understood. The authors study the differences in individual physicians'' EHR use patterns and identify perceptions of uncertainty as an important new variable in understanding EHR use.

Design

Qualitative study using semi-structured interviews and direct observation of physicians (n=28) working in a multispecialty outpatient care organization.

Measurements

We identified physicians'' perceptions of uncertainty as an important variable in understanding differences in EHR use patterns. Drawing on theories from the medical and organizational literatures, we identified three categories of perceptions of uncertainty: reduction, absorption, and hybrid. We used an existing model of EHR use to categorize physician EHR use patterns as high, medium, and low based on degree of feature use, level of EHR-enabled communication, and frequency that EHR use patterns change.

Results

Physicians'' perceptions of uncertainty were distinctly associated with their EHR use patterns. Uncertainty reductionists tended to exhibit high levels of EHR use, uncertainty absorbers tended to exhibit low levels of EHR use, and physicians demonstrating both perspectives of uncertainty (hybrids) tended to exhibit medium levels of EHR use.

Conclusions

We find evidence linking physicians'' perceptions of uncertainty with EHR use patterns. Study findings have implications for health IT research, practice, and policy, particularly in terms of impacting health IT design and implementation efforts in ways that consider differences in physicians'' perceptions of uncertainty.     

Brief communication: Facility characteristics associated with the use of electronic health records in residential care facilities

The integration of electronic health records (EHRs) across care settings including residential care facilities (RCFs) promises to reduce medical errors and improve coordination of services. Using data from the 2010 National Survey of Residential Care Facilities (n=2302), this study examines the association between facility structural characteristics and the use of EHRs in RCFs. Findings indicate that in 2010, only 3% of RCFs nationwide were using an EHR. However, 55% of RCFs reported using a computerized system for one or more (but not all) of the functionalities defined by a basic EHR. Ownership, chain membership, staffing levels, and facility size were significantly associated with the use of one or more core EHR functionalities. These findings suggest that facility characteristics may play an important role in the adoption of EHRs in RCFs.     

Area-level factors associated with electronic health record adoption and meaningful use in the Regional Extension Center Program

Objective

To identify area-level correlates of electronic health record (EHR) adoption and meaningful use (MU) among primary care providers (PCPs) enrolled in the Regional Extension Center (REC) Program.

Materials and methods

County-level data on 2013 EHR adoption and MU among REC-enrolled PCPs were obtained from the Office of the National Coordinator for Health Information Technology and linked with other county-level data sources including the Area Resource File, American Community Survey, and Federal Communications Commission''s broadband availability database. Hierarchical models with random intercepts for RECs were employed to assess associations between a broad set of area-level factors and county-level rates of EHR adoption and MU.

Results

Among the 2715 counties examined, the average county-level EHR adoption and MU rates for REC-enrolled PCPs were 87.5% and 54.2%, respectively. Community health center presence and Medicaid enrollment concentration were positively associated with EHR adoption, while metropolitan status and Medicare Advantage enrollment concentration were positively associated with MU. Health professional shortage area status and minority concentration were negatively associated with EHR adoption and MU.

Discussion

Increased financial incentives in areas with greater concentrations of Medicaid and Medicare enrollees may be encouraging EHR adoption and MU among REC-enrolled PCPs. Disparities in EHR adoption and MU in some low-resource and underserved areas remain a concern.

Conclusions

Federal efforts to spur EHR adoption and MU have demonstrated some early success; however, some geographic variations in EHR diffusion indicate that greater attention needs to be paid to ensuring equitable uptake and use of EHRs throughout the US.     

Effects of electronic health record use on the exam room communication skills of resident physicians: a randomized within-subjects study

Background The effects of electronic health records (EHRs) on doctor–patient communication are unclear.Objective To evaluate the effects of EHR use compared with paper chart use, on novice physicians’ communication skills.Design Within-subjects randomized controlled trial using observed structured clinical examination methods to assess the impact of use of an EHR on communication.Setting A large academic internal medicine training program.Population First-year internal medicine residents.Intervention Residents interviewed, diagnosed, and initiated treatment of simulated patients using a paper chart or an EHR on a laptop computer. Video recordings of interviews were rated by three trained observers using the Four Habits scale.Results Thirty-two residents completed the study and had data available for review (61.5% of those enrolled in the residency program). In most skill areas in the Four Habits model, residents performed at least as well using the EHR and were statistically better in six of 23 skills areas (p<0.05). The overall average communication score was better when using an EHR: mean difference 0.254 (95% CI 0.05 to 0.45), p = 0.012, Cohen''s d of 0.47 (a moderate effect). Residents scoring poorly (>3 average score) with paper methods (n = 8) had clinically important improvement when using the EHR.Limitations This study was conducted in first-year residents in a training environment using simulated patients at a single institution.Conclusions Use of an EHR on a laptop computer appears to improve the ability of first-year residents to communicate with patients relative to using a paper chart.     

Openness of patients' reporting with use of electronic records: psychiatric clinicians' views

Objectives

Improvements in electronic health record (EHR) system development will require an understanding of psychiatric clinicians'' views on EHR system acceptability, including effects on psychotherapy communications, data-recording behaviors, data accessibility versus security and privacy, data quality and clarity, communications with medical colleagues, and stigma.

Design

Multidisciplinary development of a survey instrument targeting psychiatric clinicians who recently switched to EHR system use, focus group testing, data analysis, and data reliability testing.

Measurements

Survey of 120 university-based, outpatient mental health clinicians, with 56 (47%) responding, conducted 18 months after transition from a paper to an EHR system.

Results

Factor analysis gave nine item groupings that overlapped strongly with five a priori domains. Respondents both praised and criticized the EHR system. A strong majority (81%) felt that open therapeutic communications were preserved. Regarding data quality, content, and privacy, clinicians (63%) were less willing to record highly confidential information and disagreed (83%) with including their own psychiatric records among routinely accessed EHR systems.

Limitations

single time point; single academic medical center clinic setting; modest sample size; lack of prior instrument validation; survey conducted in 2005.

Conclusions

In an academic medical center clinic, the presence of electronic records was not seen as a dramatic impediment to therapeutic communications. Concerns regarding privacy and data security were significant, and may contribute to reluctances to adopt electronic records in other settings. Further study of clinicians'' views and use patterns may be helpful in guiding development and deployment of electronic records systems.     

Exploring the relationship between electronic health records and provider burnout: A systematic review

ObjectiveStress and burnout due to electronic health record (EHR) technology has become a focus for burnout intervention. The aim of this study is to systematically review the relationship between EHR use and provider burnout.Materials and MethodsA systematic literature search was performed on PubMed, EMBASE, PsychInfo, ACM Digital Library in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. Inclusion criterion was original research investigating the association between EHR and provider burnout. Studies that did not measure the association objectively were excluded. Study quality was assessed using the Medical Education Research Study Quality Instrument. Qualitative synthesis was also performed.ResultsTwenty-six studies met inclusion criteria. The median sample size of providers was 810 (total 20 885; 44% male; mean age 53 [range, 34-56] years). Twenty-three (88%) studies were cross-sectional studies and 3 were single-arm cohort studies measuring pre- and postintervention burnout prevalence. Burnout was assessed objectively with various validated instruments. Insufficient time for documentation (odds ratio [OR], 1.40-5.83), high inbox or patient call message volumes (OR, 2.06-6.17), and negative perceptions of EHR by providers (OR, 2.17-2.44) were the 3 most cited EHR-related factors associated with higher rates of provider burnout that was assessed objectively.ConclusionsThe included studies were mostly observational studies; thus, we were not able to determine a causal relationship. Currently, there are few studies that objectively assessed the relationship between EHR use and provider burnout. The 3 most cited EHR factors associated with burnout were confirmed and should be the focus of efforts to improve EHR-related provider burnout.     

Implementation and Use of an Electronic Health Record within the Indian Health Service

Objectives

There are limited data regarding implementing electronic health records (EHR) in underserved settings. We evaluated the implementation of an EHR within the Indian Health Service (IHS), a federally funded health system for Native Americans.

Design

We surveyed 223 primary care clinicians practicing at 26 IHS health centers that implemented an EHR between 2003 and 2005.

Methods

The survey instrument assessed clinician attitudes regarding EHR implementation, current utilization of individual EHR functions, and attitudes regarding the use of information technology to improve quality of care in underserved settings. We fit a multivariable logistic regression model to identify correlates of increased utilization of the EHR.

Results

The overall response rate was 56%. Of responding clinicians, 66% felt that the EHR implementation process was positive. One-third (35%) believed that the EHR improved overall quality of care, with many (39%) feeling that it decreased the quality of the patient–doctor interaction. One-third of clinicians (34%) reported consistent use of electronic reminders, and self-report that EHRs improve quality was strongly associated with increased utilization of the EHR (odds ratio 3.03, 95% confidence interval 1.05–8.8). The majority (87%) of clinicians felt that information technology could potentially improve quality of care in rural and underserved settings through the use of tools such as online information sources, telemedicine programs, and electronic health records.

Conclusions

Clinicians support the use of information technology to improve quality in underserved settings, but many felt that it was not currently fulfilling its potential in the IHS, potentially due to limited use of key functions within the EHR.     

Research and applications: Primary care practitioners’ views on test result management in EHR-enabled health systems: a national survey

Context

Failure to notify patients of test results is common even when electronic health records (EHRs) are used to report results to practitioners. We sought to understand the broad range of social and technical factors that affect test result management in an integrated EHR-based health system.

Methods

Between June and November 2010, we conducted a cross-sectional, web-based survey of all primary care practitioners (PCPs) within the Department of Veterans Affairs nationwide. Survey development was guided by a socio-technical model describing multiple inter-related dimensions of EHR use.

Findings

Of 5001 PCPs invited, 2590 (51.8%) responded. 55.5% believed that the EHRs did not have convenient features for notifying patients of test results. Over a third (37.9%) reported having staff support needed for notifying patients of test results. Many relied on the patient''s next visit to notify them for normal (46.1%) and abnormal results (20.1%). Only 45.7% reported receiving adequate training on using the EHR notification system and 35.1% reported having an assigned contact for technical assistance with the EHR; most received help from colleagues (60.4%). A majority (85.6%) stayed after hours or came in on weekends to address notifications; less than a third reported receiving protected time (30.1%). PCPs strongly endorsed several new features to improve test result management, including better tracking and visualization of result notifications.

Conclusions

Despite an advanced EHR, both social and technical challenges exist in ensuring notification of test results to practitioners and patients. Current EHR technology requires significant improvement in order to avoid similar challenges elsewhere.     

Electronic health records and clinician burnout: A story of three eras

ObjectiveThe study sought to provide physicians, informaticians, and institutional policymakers with an introductory tutorial about the history of medical documentation, sources of clinician burnout, and opportunities to improve electronic health records (EHRs). We now have unprecedented opportunities in health care, with the promise of new cures, improved equity, greater sensitivity to social and behavioral determinants of health, and data-driven precision medicine all on the horizon. EHRs have succeeded in making many aspects of care safer and more reliable. Unfortunately, current limitations in EHR usability and problems with clinician burnout distract from these successes. A complex interplay of technology, policy, and healthcare delivery has contributed to our current frustrations with EHRs. Fortunately, there are opportunities to improve the EHR and health system. A stronger emphasis on improving the clinician’s experience through close collaboration by informaticians, clinicians, and vendors can combine with specific policy changes to address the causes of burnout.Target audienceThis tutorial is intended for clinicians, informaticians, policymakers, and regulators, who are essential participants in discussions focused on improving clinician burnout. Learners in biomedicine, regardless of clinical discipline, also may benefit from this primer and review.ScopeWe include (1) an overview of medical documentation from a historical perspective; (2) a summary of the forces converging over the past 20 years to develop and disseminate the modern EHR; and (3) future opportunities to improve EHR structure, function, user base, and time required to collect and extract information.     

Graphical display of diagnostic test results in electronic health Records: a comparison of 8 systems

Accurate display and interpretation of clinical laboratory test results is essential for safe and effective diagnosis and treatment. In an attempt to ascertain how well current electronic health records (EHRs) facilitated these processes, we evaluated the graphical displays of laboratory test results in eight EHRs using objective criteria for optimal graphs based on literature and expert opinion. None of the EHRs met all 11 criteria; the magnitude of deficiency ranged from one EHR meeting 10 of 11 criteria to three EHRs meeting only 5 of 11 criteria. One criterion (i.e., the EHR has a graph with y-axis labels that display both the name of the measured variable and the units of measure) was absent from all EHRs. One EHR system graphed results in reverse chronological order. One EHR system plotted data collected at unequally-spaced points in time using equally-spaced data points, which had the effect of erroneously depicting the visual slope perception between data points. This deficiency could have a significant, negative impact on patient safety. Only two EHR systems allowed users to see, hover-over, or click on a data point to see the precise values of the x–y coordinates. Our study suggests that many current EHR-generated graphs do not meet evidence-based criteria aimed at improving laboratory data comprehension.     

Enhancing the use of EHR systems for pragmatic embedded research: lessons from the NIH Health Care Systems Research Collaboratory

ObjectiveWe identified challenges and solutions to using electronic health record (EHR) systems for the design and conduct of pragmatic research.Materials and MethodsSince 2012, the Health Care Systems Research Collaboratory has served as the resource coordinating center for 21 pragmatic clinical trial demonstration projects. The EHR Core working group invited these demonstration projects to complete a written semistructured survey and used an inductive approach to review responses and identify EHR-related challenges and suggested EHR enhancements.ResultsWe received survey responses from 20 projects and identified 21 challenges that fell into 6 broad themes: (1) inadequate collection of patient-reported outcome data, (2) lack of structured data collection, (3) data standardization, (4) resources to support customization of EHRs, (5) difficulties aggregating data across sites, and (6) accessing EHR data.DiscussionBased on these findings, we formulated 6 prerequisites for PCTs that would enable the conduct of pragmatic research: (1) integrate the collection of patient-centered data into EHR systems, (2) facilitate structured research data collection by leveraging standard EHR functions, usable interfaces, and standard workflows, (3) support the creation of high-quality research data by using standards, (4) ensure adequate IT staff to support embedded research, (5) create aggregate, multidata type resources for multisite trials, and (6) create re-usable and automated queries.ConclusionWe are hopeful our collection of specific EHR challenges and research needs will drive health system leaders, policymakers, and EHR designers to support these suggestions to improve our national capacity for generating real-world evidence.     

Feeling and thinking: can theories of human motivation explain how EHR design impacts clinician burnout?

The psychology of motivation can help us understand the impact of electronic health records (EHRs) on clinician burnout both directly and indirectly. Informatics approaches to EHR usability tend to focus on the extrinsic motivation associated with successful completion of clearly defined tasks in clinical workflows. Intrinsic motivation, which includes the need for autonomy, sense-making, creativity, connectedness, and mastery is not well supported by current designs and workflows. This piece examines existing research on the importance of 3 psychological drives in relation to healthcare technology: goal-based decision-making, sense-making, and agency/autonomy. Because these motives are ubiquitous, foundational to human functioning, automatic, and unconscious, they may be overlooked in technological interventions. The results are increased cognitive load, emotional distress, and unfulfilling workplace environments. Ultimately, we hope to stimulate new research on EHR design focused on expanding functionality to support intrinsic motivation, which, in turn, would decrease burnout and improve care.     

The marginal value of pre-visit paper reminders when added to a multifaceted electronic health record based quality improvement system

Objective

We have reported that implementation of an electronic health record (EHR) based quality improvement system that included point-of-care electronic reminders accelerated improvement in performance for multiple measures of chronic disease care and preventive care during a 1-year period. This study examined whether providing pre-visit paper quality reminders could further improve performance, especially for physicians whose performance had not improved much during the first year.

Design

Time-series analysis at a large internal medicine practice using a commercial EHR. All patients eligible for each measure were included (range approximately 100–7500).

Measurements

The proportion of eligible patients in the practice who satisfied each of 15 quality measures after removing those with exceptions from the denominator. To analyze changes in performance for individual physicians, two composite measures were used: prescribing seven essential medications and completion of five preventive services.

Results

During the year after implementing pre-encounter reminders, performance continued to improve for eight measures, remained stable for four, and declined for three. Physicians with the worst performance at the start of the pre-encounter reminders showed little absolute improvement over the next year, and most remained below the median performance for physicians in the practice.

Conclusions

Paper pre-encounter reminders did not appear to improve performance beyond electronic point-of-care reminders in the EHR alone. Lagging performance is likely not due to providers'' EHR workflow alone, and trying to step backwards and use paper reminders in addition to point-of-care reminders in the EHR may not be an effective strategy for engaging slow adopters.     

Mining tasks and task characteristics from electronic health record audit logs with unsupervised machine learning

ObjectiveThe characteristics of clinician activities while interacting with electronic health record (EHR) systems can influence the time spent in EHRs and workload. This study aims to characterize EHR activities as tasks and define novel, data-driven metrics.Materials and MethodsWe leveraged unsupervised learning approaches to learn tasks from sequences of events in EHR audit logs. We developed metrics characterizing the prevalence of unique events and event repetition and applied them to categorize tasks into 4 complexity profiles. Between these profiles, Mann-Whitney U tests were applied to measure the differences in performance time, event type, and clinician prevalence, or the number of unique clinicians who were observed performing these tasks. In addition, we apply process mining frameworks paired with clinical annotations to support the validity of a sample of our identified tasks. We apply our approaches to learn tasks performed by nurses in the Vanderbilt University Medical Center neonatal intensive care unit.ResultsWe examined EHR audit logs generated by 33 neonatal intensive care unit nurses resulting in 57 234 sessions and 81 tasks. Our results indicated significant differences in performance time for each observed task complexity profile. There were no significant differences in clinician prevalence or in the frequency of viewing and modifying event types between tasks of different complexities. We presented a sample of expert-reviewed, annotated task workflows supporting the interpretation of their clinical meaningfulness.ConclusionsThe use of the audit log provides an opportunity to assist hospitals in further investigating clinician activities to optimize EHR workflows.     

Human-centered development of an electronic health record-embedded,interactive information visualization in the emergency department using fast healthcare interoperability resources

ObjectiveDevelop and evaluate an interactive information visualization embedded within the electronic health record (EHR) by following human-centered design (HCD) processes and leveraging modern health information exchange standards.Materials and MethodsWe applied an HCD process to develop a Fast Healthcare Interoperability Resources (FHIR) application that displays a patient’s asthma history to clinicians in a pediatric emergency department. We performed a preimplementation comparative system evaluation to measure time on task, number of screens, information retrieval accuracy, cognitive load, user satisfaction, and perceived utility and usefulness. Application usage and system functionality were assessed using application logs and a postimplementation survey of end users.ResultsUsability testing of the Asthma Timeline Application demonstrated a statistically significant reduction in time on task (P < .001), number of screens (P < .001), and cognitive load (P < .001) for clinicians when compared to base EHR functionality. Postimplementation evaluation demonstrated reliable functionality and high user satisfaction.DiscussionFollowing HCD processes to develop an application in the context of clinical operations/quality improvement is feasible. Our work also highlights the potential benefits and challenges associated with using internationally recognized data exchange standards as currently implemented.ConclusionCompared to standard EHR functionality, our visualization increased clinician efficiency when reviewing the charts of pediatric asthma patients. Application development efforts in an operational context should leverage existing health information exchange standards, such as FHIR, and evidence-based mixed methods approaches.     

Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data

ObjectiveIn applying machine learning (ML) to electronic health record (EHR) data, many decisions must be made before any ML is applied; such preprocessing requires substantial effort and can be labor-intensive. As the role of ML in health care grows, there is an increasing need for systematic and reproducible preprocessing techniques for EHR data. Thus, we developed FIDDLE (Flexible Data-Driven Pipeline), an open-source framework that streamlines the preprocessing of data extracted from the EHR.Materials and MethodsLargely data-driven, FIDDLE systematically transforms structured EHR data into feature vectors, limiting the number of decisions a user must make while incorporating good practices from the literature. To demonstrate its utility and flexibility, we conducted a proof-of-concept experiment in which we applied FIDDLE to 2 publicly available EHR data sets collected from intensive care units: MIMIC-III and the eICU Collaborative Research Database. We trained different ML models to predict 3 clinically important outcomes: in-hospital mortality, acute respiratory failure, and shock. We evaluated models using the area under the receiver operating characteristics curve (AUROC), and compared it to several baselines.ResultsAcross tasks, FIDDLE extracted 2,528 to 7,403 features from MIMIC-III and eICU, respectively. On all tasks, FIDDLE-based models achieved good discriminative performance, with AUROCs of 0.757–0.886, comparable to the performance of MIMIC-Extract, a preprocessing pipeline designed specifically for MIMIC-III. Furthermore, our results showed that FIDDLE is generalizable across different prediction times, ML algorithms, and data sets, while being relatively robust to different settings of user-defined arguments.ConclusionsFIDDLE, an open-source preprocessing pipeline, facilitates applying ML to structured EHR data. By accelerating and standardizing labor-intensive preprocessing, FIDDLE can help stimulate progress in building clinically useful ML tools for EHR data.     

Electronic health records and support for primary care teamwork

Objective Consensus that enhanced teamwork is necessary for efficient and effective primary care delivery is growing. We sought to identify how electronic health records (EHRs) facilitate and pose challenges to primary care teams as well as how practices are overcoming these challenges.Methods Practices in this qualitative study were selected from those recognized as patient-centered medical homes via the National Committee for Quality Assurance 2011 tool, which included a section on practice teamwork. We interviewed 63 respondents, ranging from physicians to front-desk staff, from 27 primary care practices ranging in size, type, geography, and population size.Results EHRs were found to facilitate communication and task delegation in primary care teams through instant messaging, task management software, and the ability to create evidence-based templates for symptom-specific data collection from patients by medical assistants and nurses (which can offload work from physicians). Areas where respondents felt that electronic medical record EHR functionalities were weakest and posed challenges to teamwork included the lack of integrated care manager software and care plans in EHRs, poor practice registry functionality and interoperability, and inadequate ease of tracking patient data in the EHR over time.Discussion Practices developed solutions for some of the challenges they faced when attempting to use EHRs to support teamwork but wanted more permanent vendor and policy solutions for other challenges.Conclusions EHR vendors in the United States need to work alongside practicing primary care teams to create more clinically useful EHRs that support dynamic care plans, integrated care management software, more functional and interoperable practice registries, and greater ease of data tracking over time.     

Factors associated with nurse well-being in relation to electronic health record use: A systematic review

ObjectiveAlthough nurses comprise the largest group of health professionals and electronic health record (EHR) user base, it is unclear how EHR use has affected nurse well-being. This systematic review assesses the multivariable (ie, organizational, nurse, and health information technology [IT]) factors associated with EHR-related nurse well-being and identifies potential improvements recommended by frontline nurses.Materials and MethodsWe searched MEDLINE, Embase, CINAHL, PsycINFO, ProQuest, and Web of Science for literature reporting on EHR use, nurses, and well-being. A quality appraisal was conducted using a previously developed tool.ResultsOf 4583 articles, 12 met inclusion criteria. Two-thirds of the studies were deemed to have a moderate or low risk of bias. Overall, the studies primarily focused on nurse- and IT-level factors, with 1 study examining organizational characteristics. That study found worse nurse well-being was associated with EHRs compared with paper charts. Studies on nurse-level factors suggest that personal digital literacy is one modifiable factor to improving well-being. Additionally, EHRs with integrated displays were associated with improved well-being. Recommendations for improving EHRs suggested IT-, organization-, and policy-level solutions to address the complex nature of EHR-related nurse well-being.ConclusionsThe overarching finding from this synthesis reveals a critical need for multifaceted interventions that better organize, manage, and display information for clinicians to facilitate decision making. Our study also suggests that nurses have valuable insight into ways to reduce EHR-related burden. Future research is needed to test multicomponent interventions that address these complex factors and use participatory approaches to engage nurses in intervention development.     

Correlates of Electronic Health Record Adoption in Office Practices: A Statewide Survey

Objective

Despite emerging evidence that electronic health records (EHRs) can improve the efficiency and quality of medical care, most physicians in office practice in the United States do not currently use an EHR. We sought to measure the correlates of EHR adoption.

Design

Mailed survey to a stratified random sample of all medical practices in Massachusetts in 2005, with one physician per practice randomly selected for survey.

Measurements

EHR adoption rates.

Results

The response rate was 71% (1345/1884). Overall, while 45% of physicians were using an EHR, EHRs were present in only 23% of practices. In multivariate analysis, practice size was strongly correlated with EHR adoption; 52% of practices with 7 or more physicians had an EHR, as compared with 14% of solo practices (adjusted odds ratio, 3.66; 95% confidence interval, 2.28–5.87). Hospital-based practices (adjusted odds ratio, 2.44; 95% confidence interval, 1.53–3.91) and practices that teach medical students or residents (adjusted odds ratio, 2.30; 95% confidence interval, 1.60–3.31) were more likely to have an EHR. The most frequently cited barriers to adoption were start-up financial costs (84%), ongoing financial costs (82%), and loss of productivity (81%).

Conclusions

While almost half of physicians in Massachusetts are using an EHR, fewer than one in four practices in Massachusetts have adopted EHRs. Adoption rates are lower in smaller practices, those not affiliated with hospitals, and those that do not teach medical students or residents. Interventions to expand EHR use must address both financial and non-financial barriers, especially among smaller practices.     

Harmonized patient-reported data elements in the electronic health record: supporting meaningful use by primary care action on health behaviors and key psychosocial factors

Background

Electronic health records (EHR) have the potential to improve patient care through efficient access to complete patient health information. This potential may not be reached because many of the most important determinants of health outcome are rarely included. Successful health promotion and disease prevention requires patient-reported data reflecting health behaviors and psychosocial issues. Furthermore, there is a need to harmonize this information across different EHR systems.

Methods

To fill this gap a three-phased process was used to conceptualize, identify and recommend patient-reported data elements on health behaviors and psychosocial factors for the EHR. Expert panels (n=13) identified candidate measures (phase 1) that were reviewed and rated by a wide range of health professionals (n=93) using the grid-enabled measures wiki social media platform (phase 2). Recommendations were finalized through a town hall meeting with key stakeholders including patients, providers, researchers, policy makers, and representatives from healthcare settings (phase 3).

Results

Nine key elements from three areas emerged as the initial critical patient-reported elements to incorporate systematically into EHR—health behaviors (eg, exercise), psychosocial issues (eg, distress), and patient-centered factors (eg, demographics). Recommendations were also made regarding the frequency of collection ranging from a single assessment (eg, demographic characteristics), to annual assessment (eg, health behaviors), or more frequent (eg, patient goals).

Conclusions

There was strong stakeholder support for this initiative reflecting the perceived value of incorporating patient-reported elements into EHR. The next steps will include testing the feasibility of incorporating these elements into the EHR across diverse primary care settings.