Primary Care Providers’ Opening of Time-Sensitive Alerts Sent to Commercial Electronic Health Record InBaskets
Open accessAbstract
Background Time-sensitive alerts are among the many types of clinical notifications delivered to physicians' secure InBaskets within commercial electronic health records (EHRs). A delayed alert review can impact patient safety and compromise care. Objective To characterize factors associated with opening of non-interruptive time-sensitive alerts delivered into primary care provider (PCP) InBaskets. Design and participants We analyzed data for 799 automated alerts. Alerts highlighted actionable medication concerns for older patients post-hospital discharge (2010-2011). These were study-generated alerts sent 3 days post-discharge to InBaskets for 75 PCPs across a multisite healthcare system, and represent a subset of all urgent InBasket notifications. Main measures Using EHR access and audit logs to track alert opening, we performed bivariate and multivariate analyses calculating associations between patient characteristics, provider characteristics, contextual factors at the time of alert delivery (number of InBasket notifications, weekday), and alert opening within 24 h. Key results At the time of alert delivery, the PCPs had a median of 69 InBasket notifications and had received a median of 379.8 notifications (IQR 295.0, 492.0) over the prior 7 days. Of the 799 alerts, 47.1% were opened within 24 h. Patients with longer hospital stays (>4 days) were marginally more likely to have alerts opened (OR 1.48 [95% CI 1.00-2.19]). Alerts delivered to PCPs whose InBaskets had a higher number of notifications at the time of alert delivery were significantly less likely to be opened within 24 h (top quartile >157 notifications: OR 0.34 [95% CI 0.18-0.61]; reference bottom quartile ≤42). Alerts delivered on Saturdays were also less likely to be opened within 24 h (OR 0.18 [CI 0.08-0.39]). Conclusions The number of total InBasket notifications and weekend delivery may impact the opening of time-sensitive EHR alerts. Further study is needed to support safe and effective approaches to care team management of InBasket notifications.
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Studies using raw audit logs fit into three broad categories: manual mapping, identification of networks, application of automatic methods.
“Studies using raw audit logs fit into three broad categories:”
From Electronic health record activity changes around new decision support implementation: monitoring using audit logs and topic modeling (2025) · cites this paper as [78]
The Discussion describes uses of EHR audit logs, and Dependent Variables explains how this study used them to track alert opening. Neither section classifies audit-log studies into manual mapping, network identification, and automatic methods; searches for those terms and the proposed three-category classification found no supporting passage in our copy. (LLM, conf=0.72)
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- Authors
- Cutrona, S. L., Fouayzi, H., Burns, L., Sadasivam, R. S., Mazor, K. M., Gurwitz, J. H., Garber, L., Sundaresan, D., Houston, T. K., & Field, T. S.
- Affiliations
- University of Massachusetts Chan Medical School (US)
- Corresponding author
- Cutrona, Sarah L.
- ORCID
- Venue
- Journal of General Internal Medicine
- Published
- 2017-08-14
- Volume
- 32
- Issue
- 11
- Pages
- 1210-1219
- ISSN
- 0884-8734 (ISSN-L)
- 1525-1497
- PMC
- PMC5653559
- OpenAlex
- W2748928483
- Cited by
- 24
- References
- 33
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 3 · 2023: 2 · 2022: 1 · 2021: 2 · 2020: 3 · 2019: 6 · 2018: 2
- FWCI
- 3.95
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of General Internal Medicine (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- The Journal of the American Medical Association (JAMA) Network (American Medical Association) (submittedVersion)
- Funders
- National Institutes of Health
- Agency for Healthcare Research and Quality
- National Cancer Institute (K07CA172677)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
- Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
- Keywords
- electronic health record alerts, primary care providers, clinical decision support, elderly patients, length of hospital stay, patient safety
- MeSH terms
- Aged, Aged, 80 and over, Continuity of Patient Care, Female, Humans, Male, Middle Aged, Patient Discharge, Primary Health Care, Time Factors, Reminder Systems, Electronic Health Records, Physicians, Primary Care
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