An Information Systems Model of the Determinants of Electronic Health Record Use

Objectives

The prominence given to universal implementation of electronic health record (EHR) systems in U.S. health care reform, underscores the importance of devising reliable measures of factors that predict medical care providers’ use of EHRs. This paper presents an easily administered provider survey instrument that includes measures corresponding to core dimensions of DeLone and McClean’s (D & M) model of information system success.

Methods

Study data came from self-administered surveys completed by 460 primary care providers, who had recently begun using an EHR.

Results

Based upon assessment of psychometric properties of survey items, a revised D&M causal model was formulated that included four measures of the determinants of EHR use (system quality, IT support, ease of use, user satisfaction) and five indicators of provider beliefs about the impact on an individual’s clinical practice. A structural equation model was estimated that demonstrated a high level of inter-correlation between the four scales measuring determinants of EHR use. All four variables had positive association with each of the five individual impact measures. Consistent with our revised D&M model, the association of system quality and IT support with the individual impact measures was entirely mediated by ease of use and user satisfaction.

Conclusions

Survey research provides important insights into provider experiences with EHR. Additional studies are in progress to investigate how the variables constructed for this study are related to direct measures of EHR use.     

Physician Specialty and Variations in Adoption of Electronic Health Records

Objective

Efforts to promote adoption of electronic health records (EHRs) have focused on primary care physicians, who are now expected to exchange data electronically with other providers, including specialists. However, the variation of EHR adoption among specialists is underexplored.

Methods

We conducted a retrospective cross-sectional study to determine the association between physician specialty and the prevalence of EHR adoption, and a retrospective serial cross-sectional study to determine the association of physician specialty and the rate of EHR adoption over time. We used the 2005–2009 National Ambulatory Medical Care Survey. We considered fourteen specialties, and four definitions of EHR adoption (any EHR, basic EHR, full EHR, and a novel definition of EHR sophistication). We used multivariable logistic regression, and adjusted for several covariates (geography, practice characteristics, revenue characteristics, physician degree).

Results

Physician specialty was significantly associated with EHR adoption, regardless of the EHR definition, after adjusting for covariates. Psychiatrists, dermatologists, pediatricians, ophthalmologists, and general surgeons were significantly less likely to adopt EHRs, compared to the reference group of family medicine / general practitioners. After adjustment for covariates, these specialties were 44 – 94% less likely to adopt EHRs than the reference group. EHR adoption increased in all specialties, by approximately 40% per year. The rate of EHR adoption over time did not significantly vary by specialty.

Conclusions

Although EHR adoption is increasing in all specialties, adoption varies widely by specialty. In order to insure each individual’s network of providers can electronically share data, widespread adoption of EHRs is needed across all specialties.     

Electronic Health Record Adoption – Maybe It’s not about the Money: Physician Super-Users,Electronic Health Records and Patient Care

Objective

The slow adoption of electronic health record (EHR) systems has been linked to physician resistance to change and the expense of EHR adoption. This qualitative study was conducted to evaluate benefits, and clarify limitations of two mature, robust, comprehensive EHR Systems by tech-savvy physicians where resistance and expense are not at issue.

Methods

Two EHR systems were examined – the paperless VistA / Computerized Patient Record System used at the Veterans’ Administration, and the General Electric Centricity Enterprise system used at an academic medical center. A series of interviews was conducted with 20 EHR-savvy multiinstitutional internal medicine (IM) faculty and house staff. Grounded theory was used to analyze the transcribed data and build themes. The relevance and importance of themes were constructed by examining their frequency, convergence, and intensity.

Results

Despite eliminating resistance to both adoption and technology as drivers of acceptance, these two robust EHR’s are still viewed as having an adverse impact on two aspects of patient care, physician workflow and team communication. Both EHR’s had perceived strengths but also significant limitations and neither were able to satisfactorily address all of the physicians’ needs.

Conclusion

Difficulties related to physician acceptance reflect real concerns about EHR impact on patient care. Physicians are optimistic about the future benefits of EHR systems, but are frustrated with the non-intuitive interfaces and cumbersome data searches of existing EHRs.     

Clinician Perceptions of Pediatric Growth Chart Use and Electronic Health Records in Kentucky

Background

Growth chart recording is a key component of pediatric care. EHR systems could provide several growth charting functionalities compared to paper methods. To our knowledge, there has been no U.S. study exploring clinicians’ perceptions and practices related to recording of growth parameters as they adapt to electronic methods.

Objectives

To explore clinician practices regarding recording growth parameters as they adapt to electronic health records (EHR) and to investigate clinician perceptions of electronic growth charting using EHR.

Methods

An online survey of pediatricians and family practitioners in Kentucky inquiring about EHR usage, specifically use of growth charting with EHR, was conducted.

Results

Forty-six percent of respondents utilized EHRs, with pediatricians lagging family practitioners, and academic pediatricians lagging non-academicians. There was no consensus on EHR platforms being used. Almost a third of those who used EHR did not utilize electronic growth charting. Clinicians using EHR reported that electronic growth charts would improve clinician satisfaction and clinical efficiency as well as parent satisfaction and parent education. Only 12% of respondents provided copies of growth charts to parents at the end of their visit and discussed growth parameters with parents, with clinicians using EHR more likely to engage in these activities than non-EHR users.

Conclusion

Although Kentucky clinicians continue to slowly adopt EHRs, clinician perceptions and practices reflect enduring barriers to widespread use of electronic growth charting in pediatric and family practice. However, our results suggest that electronic growth charting has important benefits for both clinicians and patients, and greater adoption is expected as EHRs become standard across health care systems.     

Searching the PDF Haystack: Automated Knowledge Discovery in Scanned EHR Documents

Background  Clinicians express concern that they may be unaware of important information contained in voluminous scanned and other outside documents contained in electronic health records (EHRs). An example is “unrecognized EHR risk factor information,” defined as risk factors for heritable cancer that exist within a patient''s EHR but are not known by current treating providers. In a related study using manual EHR chart review, we found that half of the women whose EHR contained risk factor information meet criteria for further genetic risk evaluation for heritable forms of breast and ovarian cancer. They were not referred for genetic counseling. Objectives  The purpose of this study was to compare the use of automated methods (optical character recognition with natural language processing) versus human review in their ability to identify risk factors for heritable breast and ovarian cancer within EHR scanned documents. Methods  We evaluated the accuracy of the chart review by comparing our criterion standard (physician chart review) versus an automated method involving Amazon''s Textract service (Amazon.com, Seattle, Washington, United States), a clinical language annotation modeling and processing toolkit (CLAMP) (Center for Computational Biomedicine at The University of Texas Health Science, Houston, Texas, United States), and a custom-written Java application. Results  We found that automated methods identified most cancer risk factor information that would otherwise require clinician manual review and therefore is at risk of being missed. Conclusion  The use of automated methods for identification of heritable risk factors within EHRs may provide an accurate yet rapid review of patients'' past medical histories. These methods could be further strengthened via improved analysis of handwritten notes, tables, and colloquial phrases.     

Motivations and barriers to implementing electronic health records and ED information systems in Japan

Background

Although electronic health record systems (EHRs) and emergency department information systems (EDISs) enable safe, efficient, and high-quality care, these systems have not yet been studied well. Here, we assessed (1) the prevalence of EHRs and EDISs, (2) changes in efficiency in emergency medical practices after introducing EHR and EDIS, and (3) barriers to and expectations from the EHR-EDIS transition in EDs of medical facilities with EHRs in Japan.

Materials and methods

A survey regarding EHR (basic or comprehensive) and EDIS implementation was mailed to 466 hospitals. We examined the efficiency after EHR implementation and perceived barriers and expectations regarding the use of EDIS with existing EHRs. The survey was completed anonymously.

Results

Totally, 215 hospitals completed the survey (response rate, 46.1%), of which, 76.3% had basic EHRs, 4.2% had comprehensive EHRs, and 1.9% had EDISs. After introducing EHRs and EDISs, a reduction in the time required to access previous patient information and share patient information was noted, but no change was observed in the time required to produce medical records and the overall time for each medical care. For hospitals with EHRs, the most commonly cited barriers to EDIS implementation were inadequate funding for adoption and maintenance and potential adverse effects on workflow. The most desired function in the EHR-EDIS transition was establishing appropriate clinical guidelines for residents within their system.

Conclusion

To attract EDs to EDIS from EHR, systems focusing on decreasing the time required to produce medical records and establishing appropriate clinical guidelines for residents are required.     

Lessons Learned for Collaborative Clinical Content Development

Background

Site-specific content configuration of vendor-based Electronic Health Records (EHRs) is a vital step in the development of standardized and interoperable content that can be used for clinical decision-support, reporting, care coordination, and information exchange. The multi-site, multi-stakeholder Acute Care Documentation (ACD) project at Partners Healthcare Systems (PHS) aimed to develop highly structured clinical content with adequate breadth and depth to meet the needs of all types of acute care clinicians at two academic medical centers. The Knowledge Management (KM) team at PHS led the informatics and knowledge management effort for the project.

Objectives

We aimed to evaluate the role, governance, and project management processes and resources for the KM team’s effort as part of the standardized clinical content creation.

Methods

We employed the Center for Disease Control’s six step Program Evaluation Framework to guide our evaluation steps. We administered a forty-four question, open-ended, semi-structured voluntary survey to gather focused, credible evidence from members of the KM team. Qualitative open-coding was performed to identify themes for lessons learned and concluding recommendations.

Results

Six surveys were completed. Qualitative data analysis informed five lessons learned and thirty specific recommendations associated with the lessons learned. The five lessons learned are: 1) Assess and meet knowledge needs and set expectations at the start of the project; 2) Define an accountable decision-making process; 3) Increase team meeting moderation skills; 4) Ensure adequate resources and competency training with online asynchronous collaboration tools; 5) Develop focused, goal-oriented teams and supportive, consultative service based teams.

Conclusions

Knowledge management requirements for the development of standardized clinical content within a vendor-based EHR among multi-stakeholder teams and sites include: 1) assessing and meeting informatics knowledge needs, 2) setting expectations and standardizing the process for decision-making, and 3) ensuring the availability of adequate resources and competency training.     

Use,Impact, Weaknesses,and Advanced Features of Search Functions for Clinical Use in Electronic Health Records: A Scoping Review

Objective  Although vast amounts of patient information are captured in electronic health records (EHRs), effective clinical use of this information is challenging due to inadequate and inefficient access to it at the point of care. The purpose of this study was to conduct a scoping review of the literature on the use of EHR search functions within a single patient''s record in clinical settings to characterize the current state of research on the topic and identify areas for future study. Methods  We conducted a literature search of four databases to identify articles on within-EHR search functions or the use of EHR search function in the context of clinical tasks. After reviewing titles and abstracts and performing a full-text review of selected articles, we included 17 articles in the analysis. We qualitatively identified themes in those articles and synthesized the literature for each theme. Results  Based on the 17 articles analyzed, we delineated four themes: (1) how clinicians use search functions, (2) impact of search functions on clinical workflow, (3) weaknesses of current search functions, and (4) advanced search features. Our review found that search functions generally facilitate patient information retrieval by clinicians and are positively received by users. However, existing search functions have weaknesses, such as yielding false negatives and false positives, which can decrease trust in the results, and requiring a high cognitive load to perform an inclusive search of a patient''s record. Conclusion  Despite the widespread adoption of EHRs, only a limited number of articles describe the use of EHR search functions in a clinical setting, despite evidence that they benefit clinician workflow and productivity. Some of the weaknesses of current search functions may be addressed by enhancing EHR search functions with collaborative filtering.     

Measuring Electronic Health Record Use in the Pediatric ICU Using Audit-Logs and Screen Recordings

Background  Time spent in the electronic health record (EHR) has been identified as an important unit of measure for health care provider clinical activity. The lack of validation of audit-log based inpatient EHR time may have resulted in underuse of this data in studies focusing on inpatient patient outcomes, provider efficiency, provider satisfaction, etc. This has also led to a dearth of clinically relevant EHR usage metrics consistent with inpatient provider clinical activity. Objective  The aim of our study was to validate audit-log based EHR times using observed EHR-times extracted from screen recordings of EHR usage in the inpatient setting. Methods  This study was conducted in a 36-bed pediatric intensive care unit (PICU) at Lucile Packard Children''s Hospital Stanford between June 11 and July 14, 2020. Attending physicians, fellow physicians, hospitalists, and advanced practice providers with ≥0.5 full-time equivalent (FTE) for the prior four consecutive weeks and at least one EHR session recording were included in the study. Citrix session recording player was used to retrospectively review EHR session recordings that were captured as the provider interacted with the EHR. Results  EHR use patterns varied by provider type. Audit-log based total EHR time correlated strongly with both observed total EHR time ( r  = 0.98, p  < 0.001) and observed active EHR time ( r  = 0.95, p  < 0.001). Each minute of audit-log based total EHR time corresponded to 0.95 (0.87–1.02) minutes of observed total EHR time and 0.75 (0.67–0.83) minutes of observed active EHR time. Results were similar when stratified by provider role. Conclusion  Our study found inpatient audit-log based EHR time to correlate strongly with observed EHR time among pediatric critical care providers. These findings support the use of audit-log based EHR-time as a surrogate measure for inpatient provider EHR use, providing an opportunity for researchers and other stakeholders to leverage EHR audit-log data in measuring clinical activity and tracking outcomes of workflow improvement efforts longitudinally and across provider groups.     

A Framework for Systematic Assessment of Clinical Trial Population Representativeness Using Electronic Health Records Data

Background  Clinical trials are the gold standard for generating robust medical evidence, but clinical trial results often raise generalizability concerns, which can be attributed to the lack of population representativeness. The electronic health records (EHRs) data are useful for estimating the population representativeness of clinical trial study population. Objectives  This research aims to estimate the population representativeness of clinical trials systematically using EHR data during the early design stage. Methods  We present an end-to-end analytical framework for transforming free-text clinical trial eligibility criteria into executable database queries conformant with the Observational Medical Outcomes Partnership Common Data Model and for systematically quantifying the population representativeness for each clinical trial. Results  We calculated the population representativeness of 782 novel coronavirus disease 2019 (COVID-19) trials and 3,827 type 2 diabetes mellitus (T2DM) trials in the United States respectively using this framework. With the use of overly restrictive eligibility criteria, 85.7% of the COVID-19 trials and 30.1% of T2DM trials had poor population representativeness. Conclusion  This research demonstrates the potential of using the EHR data to assess the clinical trials population representativeness, providing data-driven metrics to inform the selection and optimization of eligibility criteria.     

Clinical Summarization Capabilities of Commercially-available and Internally-developed Electronic Health Records

Objective

Clinical summarization, the process by which relevant patient information is electronically summarized and presented at the point of care, is of increasing importance given the increasing volume of clinical data in electronic health record systems (EHRs). There is a paucity of research on electronic clinical summarization, including the capabilities of currently available EHR systems.

Methods

We compared different aspects of general clinical summary screens used in twelve different EHR systems using a previously described conceptual model: AORTIS (Aggregation, Organization, Reduction, Interpretation and Synthesis).

Results

We found a wide variation in the EHRs’ summarization capabilities: all systems were capable of simple aggregation and organization of limited clinical content, but only one demonstrated an ability to synthesize information from the data.

Conclusion

Improvement of the clinical summary screen functionality for currently available EHRs is necessary. Further research should identify strategies and methods for creating easy to use, well-designed clinical summary screens that aggregate, organize and reduce all pertinent patient information as well as provide clinical interpretations and synthesis as required.     

Satisfaction after the transition between electronic health record systems at six ambulatory practices

Rationale, aims and objectives Early adopters of electronic health records (EHRs) are transitioning from older to newer EHRs to satisfy meaningful use requirements. Facilitators and barriers to satisfaction after transitioning are important to understand as provider satisfaction is linked with improvement in health care. Method We conducted a cross‐sectional survey of providers who transitioned from an older to a newer EHR at six academic, urban ambulatory medical practices. A novel survey was developed to assess: (1) satisfaction with the EHR implementation; (2) patterns of information technology use; (3) work perceptions; (4) methods for completing clinical tasks; and (5) demographic characteristics. We analysed the results using bivariate and multivariate analyses. Results The response rate was 64% (n = 197). A small majority were satisfied with the new EHR (64%, n = 120). Providers who reported satisfaction with overall quality of work life, their workload and the transition were more likely to be satisfied with the new EHR (P < 0.01). Providers who reported using the Internet at least daily were also more likely to be satisfied with the new EHR (P < 0.05). In a multivariate model, satisfaction with the transition was a strong predictor of satisfaction with the new EHR (P < 0.01). Barriers to satisfaction include dissatisfaction with: maintaining problem and medication lists, tracking health maintenance information, referring to clinical practice guidelines and ordering laboratory and radiology tests (P < 0.01). Conclusion This study provides groundwork for understanding the facilitators and barriers to provider satisfaction after the transition between EHRs and provides insight into areas requiring attention by entities undergoing similar transitions.     

Electronic Health Records: Upsides,Downsides, and Inside-Outsides on the Way Toward Their Use in Clinical Practice

Background: The author reviews his personal history learning to use Electronic Health Records (EHRs) and examination room computers. He asks key questions that pertain to the use of EHRs in practice and discusses the current state of knowledge regarding EHRs and doctor–patient communication. Summary: He notes that—regardless of the ubiquity of computers in our society and the recognition that they are a part of current medical practice—one cannot just plop down a computer in the examination room, click “on,” and anticipate that communication between doctors and patients will flow smoothly. Conclusions: He recommends the accompanying article by Duke, Frankel, and Reis (see p. 358 in this issue) as an excellent step-by-step guide for framing how to teach the basics of EHR use in clinical practice.     

A Work in Progress: Electronic Health Record Utilization in Residential Treatment

The use of Electronic Health Records (EHRs) has increased dramatically in the past few years, in part as a result of the 2009 Health Information Technology for Economic and Clinical Health Act (HITECH), and has significant potential benefit for youth residential treatment providers. Although use is widespread in the medical profession, youth residential treatment providers have only recently begun to use EHRs, and there is little information available to guide them in selection. Members of the Association of Children’s Residential Centers (ACRC) were invited via the association newsletter, and targeted email and phone call reminders, to participate in a 13-item on-line survey focused on use, satisfaction and concerns with EHRs. Eighty-seven percent of ACRC member organizations responded to the survey. Two thirds (66%) of the organizations reported using a wide variety of EHRs, and cited a range of strengths and challenges of the various systems; no single EHR product dominated the residential agency market. The authors discuss the need for further comparative EHR information and stress the importance of EHRs for data exchange and outcomes evaluation.     

Research Management Team (RMT): A Model for Research Support ‐Services at Duke University

Collecting and managing data for clinical and translational research presents significant challenges for clinical and translational researchers, many of whom lack needed access to data management expertise, methods, and tools. At many institutions, funding constraints result in differential levels of research informatics support among investigators. In addition, the lack of widely shared models and ontologies for clinical research informatics and health information technology hampers the accurate assessment of investigators’ needs and complicates the efficient allocation of crucial resources for research projects, ultimately affecting the quality and reliability of research. In this paper, we present a model for providing flexible, cost‐efficient institutional support for clinical and translational research data management and informatics, the research management team, and describe our initial experiences with deploying this model at our institution. Clin Trans Sci 2012; Volume 5: 464–469     

Electronic health records: use, barriers and satisfaction among physicians who care for black and Hispanic patients

Objectives  Electronic health records (EHRs) are a promising tool to improve the quality of health care, although it remains unclear who will benefit from this new technology. Given that a small group of providers care for most racial/ethnic minorities, we sought to determine whether minority-serving providers adopt EHR systems at comparable rates to other providers.
Methods  We used survey data from stratified random sample of all medical practices in Massachusetts in 2005. We determined rates of EHR adoption, perceived barriers to adoption, and satisfaction with EHR systems.
Results  Physicians who reported patient panels of more than 40% black or Hispanic had comparable levels of EHR adoption than other physicians (27.9% and 21.8%, respectively, P  = 0.46). Physicians from minority-serving practices identified financial and other barriers to implementing EHR systems at similar rates, although these physicians were less likely to be concerned with privacy and security concerns of EHRs (47.1% vs. 64.4%, P  = 0.01). Finally, physicians from high-minority practices had similar perceptions about the positive impact of EHRs on quality (73.7% vs. 76.6%, P  = 0.43) and costs (46.9% vs. 51.5%, P  = 0.17) of care.
Conclusions  In a state with a diverse minority population, we found no evidence that minority-serving providers had lower EHR adoption rates, faced different barriers to adoption or were less satisfied with EHRs. Given the importance of ensuring that minority-serving providers have equal access to EHR systems, we failed to find evidence of a new digital divide.     

Electronic health records: which practices have them,and how are clinicians using them?

Background Limited data exist to estimate the use of electronic health records (EHRs) in ambulatory care practices in the United States. Methods We surveyed a stratified random sample of 1829 office practices in Massachusetts in 2005. The one‐page survey measured use of health information technology, plans for EHR adoption and perceived barriers to adoption. Results A total of 847 surveys were returned, for a response rate of 46%. Overall, 18% of office practices reported having an EHR. Primary‐care‐only and mixed practices reported similar adoption rates (23% and 25%, respectively, P = 0.70). The adoption rate in specialty practices (14%) was lower compared with both primary‐care‐only (P < 0.01) and mixed (P < 0.05) practices. The number of clinicians in the practice strongly correlated with EHR adoption (P < 0.001), with fewer small practices adopting EHRs. Among practices that have EHRs with laboratory and radiology result retrieval capabilities, at least 87% of practices report that a majority of their clinicians actively use these functionalities, while 74% of practices with electronic decision support report that the majority of clinicians actively use it. Among the practices without an EHR, 13% plan to implement one within the next 12 months, 24% within the next 1–2 years, 11% within the next 3–5 years, and 52% reported having no plans to implement an EHR in the foreseeable future. The most frequently reported barrier to implementation was lack of adequate funding (42%). Conclusions Overall, fewer than 1 in 5 medical practices in Massachusetts have an EHR. Even among adopters, though, doctor usage of EHR functions varied considerably by functionality and across practices. Many clinicians are not actively using functionalities that are necessary to improve health care quality and patient safety. Furthermore, among practices that do not have EHRs, more than half have no plan for adoption. Inadequate funding remains an important barrier to EHR adoption in ambulatory care practices in the United States.