The value of EHR-based assessment of physician competency: An investigative effort with internal medicine physicians

Community perspectives on the use of electronic health data to support reflective practice by health professionals

BACKGROUND

Electronic health records and other clinical information systems have crucial roles in health service delivery and are often utilised for patient care as well as health promotion and research. Government agencies and healthcare bodies are gradually shifting the focus on how these data systems can be harnessed for secondary uses such as reflective practice, professional learning and continuing professional development. Whilst there has been a presence in research around the attitudes of health professionals in employing clinical information systems to support their reflective practice, there has been very little research into consumer attitudes towards these data systems and how they would like to interact with such structures. The study described in this article aimed to address this gap in the literature by exploring community perspectives on the secondary use of Electronic Health Data for health professional learning and practice reflection.

METHODS

A qualitative methodology was used, with data being collected via semi-structured interviews. Interviews were conducted via phone and audio recordings, before being transcribed into text for analysis. Reflective thematic analysis was undertaken to analyse the data.

RESULTS

Fifteen Australians consented to participate in an interview. Analysis of interview data generated five themes: (1) Knowledge about health professional registration and professional learning; (2) Secondary uses of Electronic Health Data; (3) Factors that enable the use of Electronic Health Data for health professional learning; (4) Challenges using Electronic Health Data for health professional learning and (5) Expectations around consent to use Electronic Health Data for health professional learning.

CONCLUSIONS

Australians are generally supportive of health professionals using Electronic Health Data to support reflective practice and learning but identify several challenges for data being used in this way.

Using eHealth Data to Inform CPD for Medical Practitioners: A Scoping Review with a Consultation Exercise with International Experts

INTRODUCTION

eHealth data analytics is widely used in health care research. However, there is limited knowledge on the role of eHealth data analysis to inform continuing professional development (CPD). The aim of this study was to collate available research evidence on the use of eHealth data for the development of CPD programs and plans for medical practitioners.

METHODS

A scoping review was conducted using the six-stage Arksey and O'Malley Framework. A consultation exercise (stage 6) was performed with 15 international experts in the fields of learning and practice analytics to deepen the insights.

RESULTS

Scoping review. The literature searches identified 9876 articles published from January 2010 to May 2022. After screening and full-text review, a total of nine articles were deemed relevant for inclusion. The results provide varied-and at times partial or diverging-answers to the scoping review research questions. Consultation exercise. Research rigor, field of investigation, and developing the field were the three themes emerged from analysis. Participants validated the scoping review methodology and confirmed its results. Moreover, they provided a meta-analysis of the literature, a description of the current CPD ecosystem, and clear indications of what is and should be next for the field.

DISCUSSION

This study shows that there is no formal or well-established correlation between eHealth data and CPD planning and programming. Overall findings fill a gap in the literature and provide a basis for further investigation. More foundational work, multidisciplinary collaborations, and stakeholders' engagement are necessary to advance the use of eHealth data analysis for CPD purposes.

A Step Toward Identifying Sources of Medical Errors: Modeling Standards of Care Deviations for Different Disease States

Objective

To examine the feasibility of utilizing electronic health records (EHR) to determine a metric for identifying physician diagnostic and treatment deviations in standards of care for different disease states.

Methods

A Boolean-rule-based model compared deviations in standards of care across four disease states: diabetes, cardiovascular disease, asthma, and rheumatoid arthritis. This metric was used to identify the relationship between physician deviations in standards of care procedures, before and after diagnosis, for 76 internal medicine physicians.

Results

The Boolean-rule-based model identified patterns of standards of care deviation for the physicians before diagnosis and during treatment. The deviations identified for each of the four disease states were then related to Continuing Medical Education courses that could support further training. The rule-based model was extended and improved by including system and process aspects of medical care that are not specifically related to the physician, yet potentially have an impact on the physician's decision to deviate from the standards of care.

Conclusion

The Boolean-rule-based approach provided a means to systematically mine EHRs and use these data to assess deviations in standards of care that could identify quality of care issues stemming from system processes or the need for specific CME for a physician.

Impact of a tailored training on advanced electronic medical records use for providers in a Veterans Health Administration Medical System

This quality improvement project evaluated the impact of a tailored, evidence-based training strategy on advanced electronic medical record (EMR) use for Veterans Administration (VA) clinicians experienced in using the EMR. After developing the curriculum, an online needs assessment tool evaluated 20 clinicians' competency gaps. Responses were used to prioritize clinicians' training needs. Clinician informaticists then provided 2-4 h of tailored training to groups of 1-5 clinicians. Compared with baseline scores (M = 3.59), scores on EMR Task Comfort showed a large improvement in the week following training (M = 4.60; t = 5.41; P <.000, r = 0.58) regardless of baseline level of computer anxiety. Assessment and tailored training methods can help maximize the benefits of resources for EMR training. This formative evaluation suggests that tailored, hands-on training led by clinician informaticists effectively improved clinicians' EMR comfort and confidence in only 2-4 h.