ArticleJournal of general internal medicine2023
Understanding Patients' Preferences and Experiences During an Electronic Health Record Transition.
Article in Journal of general internal medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Promising Patient-Engagement Practices Used by National Research Networks at the US Veterans Health Administration: Perspectives of Veterans, Staff, and Research Leaders.Learning health systems · 2026Article
- Patient Engagement Activities and Infrastructure Among US Veterans Affairs National Research Networks.Journal of general internal medicine · 2026Article
- Users' perspectives on a demonstration to increase shared access to older adults' patient portals.BMC health services research · 2025Article
- Improving diagnosis-based quality measures: an application of machine learning to the prediction of substance use disorder among outpatients.BMJ open quality · 2025Article
- Clinician and staff experiences with frustrated patients during an electronic health record transition: a qualitative case study.BMC health services research · 2024Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundThe Department of Veterans Affairs (VA) has embarked on the largest system-wide electronic health record (EHR) transition in history. To date, most research on EHR-to-EHR transitions has focused on employee and system transition-related needs, with limited focus on how patients experience transitions.
objective(1) Understand patients' preferences for information and support prior to an EHR transition, and (2) examine actual patient experiences that occurred at facilities that implemented a new EHR.
designWe used a two-step approach. We had discussions with geographically diverse patient advisory groups. Discussions informed semi-structured, qualitative interviews with patients.
participantsPatients affected by the EHR transition. MAIN MEASURES: We met with four patient advisory groups at sites that had not transitioned their EHR. Interviews were conducted with patients who received care at one of two facilities that recently transitioned to the new EHR. KEY
resultsPatient advisors identified key areas important to patients during an EHR transition. 1) Use a range of communication strategies to reach diverse populations, especially older, rural patients. 2) Information about the EHR transition should be clear and reinforce trustworthiness. 3) Patients will need guidance using the new patient portal. From the patient interviews, we learned if and how these key areas mapped onto patients' experiences. Patients at the sites that had transitioned learned about the new EHR through a variety of modalities, including letters and banners on the patient portal. However, their experiences varied in terms of information quality, leading to frustrations during and between healthcare encounters. Patient portal issues exacerbated frustrations. These raised concerns about the accuracy and security of the overall EHR.
conclusionsMaintaining clear communication across patients, local leadership, and providers throughout an EHR transition is essential for successful implementation. Patient-facing communications can set expectations, and help patients receive adequate support, particularly related to the patient portal.
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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.