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dc.contributor.authorCutrona, Sarah L.
dc.contributor.authorFouayzi, Hassan
dc.contributor.authorBurns, Laura
dc.contributor.authorSadasivam, Rajani S.
dc.contributor.authorMazor, Kathleen M.
dc.contributor.authorGurwitz, Jerry H.
dc.contributor.authorGarber, Lawrence D.
dc.contributor.authorSundaresan, Devi
dc.contributor.authorHouston, Thomas K.
dc.contributor.authorField, Terry S.
dc.date2022-08-11T08:08:22.000
dc.date.accessioned2022-08-23T15:52:39Z
dc.date.available2022-08-23T15:52:39Z
dc.date.issued2017-11-01
dc.date.submitted2017-12-11
dc.identifier.citationJ Gen Intern Med. 2017 Nov;32(11):1210-1219. doi: 10.1007/s11606-017-4146-3. Epub 2017 Aug 14. <a href="https://doi.org/10.1007/s11606-017-4146-3">Link to article on publisher's site</a>
dc.identifier.issn0884-8734 (Linking)
dc.identifier.doi10.1007/s11606-017-4146-3
dc.identifier.pmid28808942
dc.identifier.urihttp://hdl.handle.net/20.500.14038/29188
dc.description.abstractBACKGROUND: 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.
dc.language.isoen_US
dc.relation<p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=28808942&dopt=Abstract">Link to Article in PubMed</a></p>
dc.relation.urlhttps://doi.org/10.1007/s11606-017-4146-3
dc.subjectelectronic health records
dc.subjecthealth information technology
dc.subjecthealth services research
dc.subjecthealthcare communication
dc.subjectHealth Information Technology
dc.subjectHealth Services Research
dc.subjectPrimary Care
dc.titlePrimary Care Providers' Opening of Time-Sensitive Alerts Sent to Commercial Electronic Health Record InBaskets
dc.typeJournal Article
dc.source.journaltitleJournal of general internal medicine
dc.source.volume32
dc.source.issue11
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/faculty_pubs/1413
dc.identifier.contextkey11228094
html.description.abstract<p>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.</p> <p>OBJECTIVE: To characterize factors associated with opening of non-interruptive time-sensitive alerts delivered into primary care provider (PCP) InBaskets.</p> <p>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.</p> <p>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.</p> <p>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]).</p> <p>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.</p>
dc.identifier.submissionpathfaculty_pubs/1413
dc.contributor.departmentDepartment of Medicine
dc.contributor.departmentMeyers Primary Care Institute
dc.contributor.departmentDepartment of Quantitative Health Sciences
dc.source.pages1210-1219


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