A novel use of the discrete templated notes within an electronic health record software to monitor resident supervision

Uses of Electronic Health Record Data to Measure the Clinical Learning Environment of Graduate Medical Education Trainees: A Systematic Review

PURPOSE

This study systematically reviews the uses of electronic health record (EHR) data to measure graduate medical education (GME) trainee competencies.

METHOD

In January 2022, the authors conducted a systematic review of original research in MEDLINE from database start to December 31, 2021. The authors searched for articles that used the EHR as their data source and in which the individual GME trainee was the unit of observation and/or unit of analysis. The database query was intentionally broad because an initial survey of pertinent articles identified no unifying Medical Subject Heading terms. Articles were coded and clustered by theme and Accreditation Council for Graduate Medical Education (ACGME) core competency.

RESULTS

The database search yielded 3,540 articles, of which 86 met the study inclusion criteria. Articles clustered into 16 themes, the largest of which were trainee condition experience (17 articles), work patterns (16 articles), and continuity of care (12 articles). Five of the ACGME core competencies were represented (patient care and procedural skills, practice-based learning and improvement, systems-based practice, medical knowledge, and professionalism). In addition, 25 articles assessed the clinical learning environment.

CONCLUSIONS

This review identified 86 articles that used EHR data to measure individual GME trainee competencies, spanning 16 themes and 6 competencies and revealing marked between-trainee variation. The authors propose a digital learning cycle framework that arranges sequentially the uses of EHR data within the cycle of clinical experiential learning central to GME. Three technical components necessary to unlock the potential of EHR data to improve GME are described: measures, attribution, and visualization. Partnerships between GME programs and informatics departments will be pivotal in realizing this opportunity.

Management and outcomes of flexor tendon repairs at a peripheral hospital: a New Zealand case series study

BACKGROUND

Current evidence for flexor tendon repair management and outcomes performed at peripheral centres is unclear. Most studies are based on evidence from specialist hand centres. This study evaluated a peripheral hospital in New Zealand; where all flexor tendon repairs were performed by a generalist Orthopaedic service. The purpose of the study was to benchmark management and outcomes from a peripheral hospital in comparison to international standards.

METHODS

A retrospective single-centre consecutive case series of Zones I and II flexor tendon repairs was extracted between 1 January 2014 and 1 January 2018. Medical records were used to evaluate management and outcomes of repairs. Hand therapy notes were used to evaluate rehabilitation protocols provided. The primary objective was to measure re-rupture and re-operation rates. Secondary objectives included auditing operative management and hand therapy compliance.

RESULTS

Forty-six patients (76 tendon repairs) were included in our final analysis. Mean follow up time to last clinical appointment was 11.8 weeks, and to last patient episode was 4.9 years. Most patients received timely surgery with a four-core repair using 3-0 or larger suture. All hand therapy followed a controlled active motion protocol. The re-operation rate was 19.6% (P = <0.05) and the re-rupture rate was 8.7% (P = 0.28).

CONCLUSIONS

Most flexor tendon injuries at this peripheral centre were managed according to international standards. However, high complication rates including re-operation and re-rupture occurred. Due to a lack of local comparison studies, confounding factors cannot be excluded as a contributor for these results.

Learning health systems and the future of clinical research

Pediatric surgeons are collectively passionate about prioritizing the healthcare needs of children. We contend that this passion is deeply ingrained in how we drive clinical care and influence scientific discovery. Thus, the future of clinical research in our field will be deeply embedded in our history as a "patient-centric" profession. Service to pediatric patients requires an understanding of their needs and expectations, and designing research that acknowledges both. In this article we detail how future pragmatic clinical research will look in the evolving and learning health system.

Efficacy and unintended consequences of hard-stop alerts in electronic health record systems: a systematic review

Objective

Clinical decision support (CDS) hard-stop alerts-those in which the user is either prevented from taking an action altogether or allowed to proceed only with the external override of a third party-are increasingly common but can be problematic. To understand their appropriate application, we asked 3 key questions: (1) To what extent are hard-stop alerts effective in improving patient health and healthcare delivery outcomes? (2) What are the adverse events and unintended consequences of hard-stop alerts? (3) How do hard-stop alerts compare to soft-stop alerts?

Methods and Materials

Studies evaluating computerized hard-stop alerts in healthcare settings were identified from biomedical and computer science databases, gray literature sites, reference lists, and reviews. Articles were extracted for process outcomes, health outcomes, unintended consequences, user experience, and technical details.

Results

Of 32 studies, 15 evaluated health outcomes, 16 process outcomes only, 10 user experience, and 4 compared hard and soft stops. Seventy-nine percent showed improvement in health outcomes and 88% in process outcomes. Studies reporting good user experience cited heavy user involvement and iterative design. Eleven studies reported on unintended consequences including avoidance of hard-stopped workflow, increased alert frequency, and delay to care. Hard stops were superior to soft stops in 3 of 4 studies.

Conclusions

Hard stops can be effective and powerful tools in the CDS armamentarium, but they must be implemented judiciously with continuous user feedback informing rapid, iterative design. Investigators must report on associated health outcomes and unintended consequences when implementing IT solutions to clinical problems.

Clinical Informatics Researcher's Desiderata for the Data Content of the Next Generation Electronic Health Record

OBJECTIVE

Clinical informatics researchers depend on the availability of high-quality data from the electronic health record (EHR) to design and implement new methods and systems for clinical practice and research. However, these data are frequently unavailable or present in a format that requires substantial revision. This article reports the results of a review of informatics literature published from 2010 to 2016 that addresses these issues by identifying categories of data content that might be included or revised in the EHR.

MATERIALS AND METHODS

We used an iterative review process on 1,215 biomedical informatics research articles. We placed them into generic categories, reviewed and refined the categories, and then assigned additional articles, for a total of three iterations.

RESULTS

Our process identified eight categories of data content issues: Adverse Events, Clinician Cognitive Processes, Data Standards Creation and Data Communication, Genomics, Medication List Data Capture, Patient Preferences, Patient-reported Data, and Phenotyping.

DISCUSSION

These categories summarize discussions in biomedical informatics literature that concern data content issues restricting clinical informatics research. These barriers to research result from data that are either absent from the EHR or are inadequate (e.g., in narrative text form) for the downstream applications of the data. In light of these categories, we discuss changes to EHR data storage that should be considered in the redesign of EHRs, to promote continued innovation in clinical informatics.

CONCLUSION

Based on published literature of clinical informaticians' reuse of EHR data, we characterize eight types of data content that, if included in the next generation of EHRs, would find immediate application in advanced informatics tools and techniques.