ArticleJAMIA open2024
"For the first time…I am seriously fighting burnout": clinician experiences with a challenging electronic health record transition.
Article in JAMIA open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Harnessing institutional knowledge: mixed methods evaluation of peer coaching in a multi-site EHR transition.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- "The emperor's new clothes": a qualitative study of end users' experiences from a failed large-scale implementation of an electronic health record system.BMC health services research · 2026Article
- Data in Diabetic Foot Care: From Current State to a Management Framework for Implementation.Journal of clinical medicine · 2025Review
- Tensions in large-scale electronic health record implementations: insights from a meta-synthesis.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Navigating artificial intelligence in home healthcare: challenges and opportunities in nursing wound care.BMC nursing · 2025Article
- From theory to practice - assessing translation of physical fitness research in the emergency department through machine learning and natural language processing.Journal of clinical and translational science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Objectives: The Department of Veterans Affairs (VA) is transitioning from its legacy electronic health record (EHR) to a new commercial EHR in a nationwide, rolling-wave transition. We evaluated clinician and staff experiences to identify strategies to improve future EHR rollouts. Materials and Methods: We completed a convergent mixed-methods formative evaluation collecting survey and interview data to measure and describe clinician and staff experiences. Survey responses were analyzed using descriptive statistics; interview transcripts were coded using a combination of a priori and emergent codes followed by qualitative content analysis. Qualitative and quantitative findings were compared to provide a more comprehensive understanding of participant experience. Employees of specialty and primary care teams at the first nationwide EHR transition site agreed to participate in our study. We distributed surveys at 1-month pre-transition, 2 months post-transition, and 10 months post-transition to each of the 68 identified team members and completed longitudinal interviews with 30 of these individuals totaling 122 semi-structured interviews. Results: Interview participants reported profoundly disruptive experiences during the EHR transition that persisted at 1-year post implementation. Survey responses indicated training difficulties throughout the transition, and sharp declines ( Discussion: Our findings highlight strategies to improve employee experiences during EHR transitions: (1) working with Oracle Cerner to resolve known issues and improve usability; (2) role-based training with opportunities for self-directed learning; (3) peer-led support systems and timely feedback on issues; (4) messaging that responds to challenges and successes; and (5) continuous efforts to support staff with issues and address clinician and staff stress and burnout. Conclusion: Our findings provide relevant strategies to navigate future EHR transitions while supporting clinical teams.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.