Applied Clinical Informatics最新文献

{"title":"Special Topic Burnout: Analyzing Physician In Basket Burden and Efficiency Using K-Means Clustering.","authors":"Vincent Lattanze, Xinyue Lan, Drew Vander Leest, Jasper Sim, Melissa Fazzari, Xianhong Xie, Sunit Jariwala","doi":"10.1055/a-2562-1100","DOIUrl":"10.1055/a-2562-1100","url":null,"abstract":"<p><strong>Background: </strong>Electronic health record (EHR) systems are essential for modern healthcare but contribute to significant documentation burden, affecting physician workflow and well-being. While previous studies have identified differences in EHR usage across demographics, systematic methods for identifying high-burden physician groups remain limited. This study applies cluster analysis to uncover distinct EHR usage profiles and provide a framework to inform the development of targeted interventions.</p><p><strong>Objectives: </strong>This study investigated two research questions: (1) Can cluster analysis effectively identify distinct physician EHR usage profiles? (2) How do these profiles vary across physician demographics and practice characteristics? We hypothesized that (1) EHR usage clusters would emerge based on workload intensity, after-hours documentation, and In Basket management patterns, and (2) would be significantly associated with physician experience, sex, and specialty.</p><p><strong>Methods: </strong>We analyzed outpatient EHR usage data from 323 physicians at an academic health system using Epic Signal, an analytical tool for Epic EHR. Using k-means clustering, we examined six metrics representing EHR workload (after-hours and extended-day activities) and In Basket efficiency (message handling and management patterns). We assessed cluster differences and conducted subgroup analyses by physician sex and specialty.</p><p><strong>Results: </strong>Two distinct physician clusters emerged: one high-burden cluster, predominantly comprising experienced primary care physicians, and another lower-burden cluster, consisting mostly of younger specialists. Physicians in the high-burden cluster spent nearly three times as much time on after-hours documentation and In Basket management. While message response times remained similar, subgroup analyses revealed significant sex and specialty-based differences, particularly in the lower-burden cluster.</p><p><strong>Conclusions: </strong>Cluster analysis effectively identified distinct EHR usage patterns, highlighting disparities in workload by experience, sex, and specialty. This approach provides a scalable, data-driven method for health systems to identify at-risk groups and design targeted interventions to mitigate documentation burden and enhance EHR efficiency.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143664961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relationship between additional required nursing documentation and patient outcomes: A Scoping Review.","authors":"Rachel Lee, Jennifer A Thate, Jennifer Withall, Po-Yin Yen, Kenrick Cato, Sarah Collins Rossetti","doi":"10.1055/a-2561-3960","DOIUrl":"10.1055/a-2561-3960","url":null,"abstract":"<p><strong>Background: </strong>While many aspects of nursing documentation are considered an essential part of clinical communication and care coordination, other types of nursing documentation have been implemented to meet compliance and other secondary use needs. Adding required documentation without carefully assessing its association with patient outcomes adds excessive documentation burden on nurses. There is a gap in the evidence of the association between additional required nursing documentation and improvements in patient outcomes.</p><p><strong>Objectives: </strong>To synthesize and describe the state of the evidence on the relationship between adding required electronic nursing documentation and improved patient outcomes in inpatient hospital settings.</p><p><strong>Methods: </strong>Databases were searched using relevant terms for original studies examining the effects of additional required nursing documentation. Two authors screened titles, abstracts and full texts for eligibility criteria.</p><p><strong>Data sources: </strong>PubMed, CINAHL (EBSCO), Web of Science, and Embase from January 2011 to May 2023.</p><p><strong>Results: </strong>A total of 47 studies were included. Of the studies reviewed, 57.4% (n=27) focused only on process measures, primarily measuring documentation compliance and 42.6% (n=20) studies included patient outcome measures such as infection rates, length of stay, and falls. Of these studies 45% (n=9) reported statistically significant relationship between required nursing documentation and improved patient outcomes. Overall quality of evidence was generally low, with 72% (n=34) being quality improvement studies and only one study being a randomized controlled trial.</p><p><strong>Conclusion: </strong>The findings of this scoping review suggest an assumed, yet unverified, connection between added required nursing documentation and improved patient outcomes that is not substantiated by high quality empirical evidence. The paucity of studies with significant findings-and the methodological weaknesses of those that report them-suggest the need for critical examination of documentation practices that are truly beneficial to patient outcomes versus those documentation practices that are excessively burdensome.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143664960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Provider adoption of an online ADHD eHealth care application.","authors":"Jeff Epstein, Bill Brinkman, Froehlich Tanya, Constance A Mara, John Simon, Andrew Beck, Suzanne Emmer","doi":"10.1055/a-2562-1161","DOIUrl":"10.1055/a-2562-1161","url":null,"abstract":"<p><strong>Objectives: </strong>To assess what practice-, provider-, and patient population-level predictors predict adoption of an ADHD ehealth technology in community pediatric settings, pediatric providers nationwide were recruited and offered free use of an evidence-based mental-health-focused ehealth quality improvement intervention (mehealth for ADHD). Practice-, provider-, and patient population-level factors predicting provider's adoption of the intervention were studied. We hypothesized that providers who were younger, nearing re-credentialing, having more patients with ADHD, working at larger practices, serving socioeconomically deprived patient populations, and using an electronic health record (EHR) with mehealth integration would predict higher rates of adoption.</p><p><strong>Methods: </strong>A variety of recruitment strategies were attempted. Providers completed a baseline survey, were given free access to mehealth, and then had their software adoption recorded (i.e., account activation, rate of patients registered, completion of Plan-Do-Study-Act cycles). Multiple regressions examined what practice-, provider-, and patient population-level variables predicted provider's adoption of the software.</p><p><strong>Results: </strong>A total of 1,612 providers at 813 practices across 48 states and the District of Columbia consented to the study. The most common ways that providers heard about the research study was through word-of-mouth (37%), advertising (23%), and through professional affiliation (11%). 1,210 (75.1%) providers activated their mehealth provider account and 446 (36.8%) registered at least 1 patient. Over 4.5 years, 21,804 patients were registered on the platform. Being able to access mehealth within their EHR predicted provider account activation, provider rate of patients registered, and the practice's completion of Plan-Do-Study-Act cycles. In addition, having a lower proportion of Medicaid patients predicted higher rates of patients being registered on the software.</p><p><strong>Conclusions: </strong>Getting providers to consider, try, and adopt new evidence-based assistive technologies is challenging. Making ehealth software easier for providers' to access through EHR integration appears critical to adoption.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"User Actions Within a Clinical Decision Support Alert for the Management of Hypertension in Chronic Kidney Disease.","authors":"Lipika Samal, Sarah W Chen, Stuart Lipsitz, Heather J Baer, John L Kilgallon, Michael P Gannon, Ryan Dunk, Weng Ian Chay, Richard Fay, Michael Sainlaire, Chenxi Gao, Matthew Wien, Pamela Garabedian, Edward Wu, Hojjat Salmasian, David W Bates, Patricia Dykes, Adam Wright, Allison B McCoy","doi":"10.1055/a-2554-3969","DOIUrl":"10.1055/a-2554-3969","url":null,"abstract":"<p><strong>Objective: </strong>To examine user actions within a clinical decision support (CDS) alert addressing hypertension (HTN) in chronic kidney disease (CKD).</p><p><strong>Methods: </strong>A pragmatic randomized controlled trial of a CDS alert for primary care patients with CKD and uncontrolled blood pressure included pre-checked default orders for medication initiation or titration, basic metabolic panel (BMP), and nephrology electronic consult. We examined each type of action and calculated percentages of placed and signed orders for subgroups of firings.</p><p><strong>Results: </strong>There were firings for medication initiation (813) and medication titration (430), and every firing also included orders for nephrology electronic consult (1243) and BMP (1243). High rates of override (59.6%) and deferral (14.6%) were observed, and CDS-recommended orders were only signed about one-third of the time from within the alert. The percentage of orders that were signed after being placed within the alert was higher for medication initiation than for medication titration (33% vs 12.0% for angiotensin-converting enzyme inhibitors (ACEi), 38.8% vs 14% for angiotensin II receptor blockers (ARB).</p><p><strong>Discussion: </strong>Findings suggest that users are hesitant to commit to immediate action within the alert.</p><p><strong>Conclusion: </strong>Evaluating user interaction within alerts reveals nuances in physician preferences and workflow that should inform CDS alert design.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143651507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The STREAMLINE Pilot - Study on Time Reduction and Efficiency in AI-Mediated Logging for Improved Note-Taking Experience.","authors":"Roheet Kakaday, Elizabeth Zoe Herrera, Olivia Coskey, Andrew W Hertel, Paulina Kaiser","doi":"10.1055/a-2559-5791","DOIUrl":"10.1055/a-2559-5791","url":null,"abstract":"<p><strong>Objectives: </strong>This pilot study aimed to evaluate the impact of an ambient listening AI tool, DAX CoPilot (DAX), on clinical documentation efficiency among primary care providers in a community-based setting.</p><p><strong>Methods: </strong>We conducted a randomized controlled trial among volunteer clinicians (physicians, nurse practitioners, and physician assistants in family medicine, internal medicine, pediatrics, and urgent care), who were asked to use DAX with a standardized note template (N = 25) or to continue with traditional documentation methods (N = 20) over a three-month intervention period. We evaluated documentation efficiency with both standard and custom Epic metrics to evaluate impact on all visit types as well as specifically problem-focused visits.</p><p><strong>Results: </strong>Because of heterogeneity in DAX usage, we created post-hoc categories of Low (< 45% of all visits, N=12), Moderate (45-69.9% of all visits, N=6) and High Frequency (≥ 70% of all visits, N=7) DAX users. We observed the largest differences among High Frequency DAX users. For problem-focused visits with clinicians in this group, a median of 50% of note characters were written by DAX, and we observed a 1.4-minute decrease in time spent on notes per visit (p-value: 0.38) and a 35% decrease in the median number of characters per note (p-value: 0.38) from baseline to the end of the study period. The control group metrics were largely uncharged throughout the study.</p><p><strong>Conclusions: </strong>Our findings suggest that DAX can improve documentation efficiency, particularly among clinicians that use it frequently. Healthcare systems might benefit by using AL-AI tools like DAX but should consider implementation scope and note template features. Future investigations are needed to further explore these trends and their additional implications for outcomes such as burnout.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143651504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Special Issue on CDS Failures: A Case Study: Optimizing CDS for Pediatric Oncology Trials by Transitioning from Interruptive to Passive Alerts.","authors":"Renee Potashner, Karim Jessa, Natalie Meyer, Erica Patterson, Adam Paul Yan","doi":"10.1055/a-2555-2441","DOIUrl":"https://doi.org/10.1055/a-2555-2441","url":null,"abstract":"<p><strong>Background: </strong>Many children with cancer are treated as part of interventional clinical trials. Ensuring that the correct chemotherapy treatment plan is used is paramount.</p><p><strong>Objectives: </strong>The objectives of this report were to: (1) highlight the initial design of a clinical decision support (CDS) tool that was intended to help ensure the correct matching of research studies to research chemotherapy medications, (2) discuss the issues identified with the CDS tool, and (3) review the redesign of the tool that was done to overcome the issues identified.</p><p><strong>Methods: </strong>We previously utilized an interruptive alert developed by Epic Systems ® to identify mismatches between a patient's chemotherapy plan and research study. We identified an issue with the logic of the alert resulting in the alert firing inappropriately.</p><p><strong>Results: </strong>We estimate that the chemotherapy-research plan alert fired when 93.4% of treatment plans were applied (17.3 alerts/provider/year). A high number of misfiring alerts were identified due to the inclusion of our institution name as both (1) a \"tag\" in the research protocol, and (2) as an unallowed tag in the research study record. Since the tag was included in all protocols, but also unallowed in all research records the alert fired with the application of almost all treatment plans. We developed a new mechanism to provide CDS that did not involve an interruptive alert. Within the research study record we manually associate compatible treatment plans to that study record, then when an oncologist goes to order chemotherapy the system prioritizes display of compatible treatment plans to the oncologist. The goal of the redesigned CDS approach is to eliminate interruptive alerts, while ensuring the correct chemotherapy plan is selected.</p><p><strong>Conclusion: </strong>With end user engagement and creative approaches to CDS design, interruptive alerts can be transitioned into passive and effective CDS tools.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143617625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"User-centered Design in Real Time: Utilization of an Insider Position to Inform Design and Adoption.","authors":"Jessica Kanis, Emily C Webber, Rob Busch, Jason T Schaffer","doi":"10.1055/a-2556-4652","DOIUrl":"https://doi.org/10.1055/a-2556-4652","url":null,"abstract":"<p><strong>Background: </strong>Electronic Health Records (EHRs) have significantly impacted healthcare improving access to patient information and enhancing communication among the health care team. However, lack of usability and increased documentation burden has greatly contributed to clinician burnout. Improvements in EHR design that include physician input is critical to develop specific changes that make EHRs less cumbersome; however, it can be challenging to gather input from physicians with full clinical workloads.</p><p><strong>Objective: </strong>We sought to establish a practical, repeatable framework for soliciting and integrating user-centered design elements into our vendor EHR system utilizing meaningful clinician involvement and feedback.</p><p><strong>Methods: </strong>Over a one-year period, physician volunteers were given access to a position within the EHR where new features were available for testing before widespread deployment. Real-time feedback was obtained through a shared platform with institutional IS support leaders and vendor executive and used to impact design and broader implementation decisions. Physician feedback regarding the testing process was obtained via survey.</p><p><strong>Results: </strong>Thirteen physicians and 15 support staff were given access to a separate unique EHR position to test new features during real-world clinical work at their discretion. Feedback was given via a Teams chat function resulting in 1024 messages from 28 users over a one- year period peaking in accordance with new features made available. During two primary phases, 8 new EHR features were tested to elicit feedback prior to adoption. Six of the eight features were adopted after initial testing while 2 required additional changes to improve functionality prior to implementation. The majority found this method intuitive and effective in testing new EHR features.</p><p><strong>Discussion: </strong>Healthcare EHR workflows are effective and well adopted when informed and designed by the clinical users. The insider position was shown to be an effective method for testing new features to gain valuable insight without overburdening clinicians.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143617627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward a Provider Builder Maturity Model to Empower Clinicians to Actively Participate in Electronic Health Record Design.","authors":"Wayne H Liang, Jeffrey M Hoffman, Lia McNeely, Stephon Proctor, Evan W Orenstein","doi":"10.1055/a-2512-9647","DOIUrl":"10.1055/a-2512-9647","url":null,"abstract":"<p><strong>Background: </strong> Engagement of clinicians who understand clinical workflows and technology constraints can accelerate the development and implementation of better electronic health record (EHR) designs that improve quality and reduce burnout. Provider builder programs can accelerate clinical informatics education for a broader coalition of clinical specialties.</p><p><strong>Objectives: </strong> In this State of the Art/Best Practice paper, we aim to (1) propose a provider builder maturity model informed by the experience of three institutions using a single EHR vendor (Epic Systems) and (2) describe the program elements and relationships necessary to advance along this model to yield organizational benefits.</p><p><strong>Methods: </strong> We used a modified version of the Glaser State-of-the-Art approach, gathering consensus among a small group of experts at institutions with successful provider builder programs. The model was updated through meetings with a larger group of experts and then feedback from presentation at national conferences and the American Medical Informatics Association's Maturity Model Working Group.</p><p><strong>Results: </strong> The final maturity model describes the characteristics and suggested next steps beginning from Planting the Seed (Stage 0) and progressing through Lone Wolves (Stage 1), a Community of Builders (Stage 2), Organizational Structure (Stage 3), a Council of Builders (Stage 4), and Informatics in the Room Where it Happens (Stage 5). We also describe the journeys of three organizations through these stages.</p><p><strong>Conclusion: </strong> A provider builder maturity model can help guide organizations on their journey engaging clinicians in collaborative EHR design to promote quality and safety and reduce burnout.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"418-428"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12077985/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142957071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hospital Health Information Exchange Network Density and Predictors Across U.S. Hospital Referral Regions.","authors":"Sunny C Lin, Karen Joynt Maddox, Daphne Lew, Julia Adler-Milstein, Thomas Kannampallil","doi":"10.1055/a-2516-1692","DOIUrl":"10.1055/a-2516-1692","url":null,"abstract":"<p><strong>Objectives: </strong> This study aimed to develop a measure of health information exchange (HIE) for characterizing the density of inter-hospital HIE connections and identify regional characteristics associated with HIE network density.</p><p><strong>Methods: </strong> HIE network density was measured as the proportion of hospital pairs within a region that are connected through HIE. The 2022 American Hospital Association's Information Technology Supplement survey was used to calculate HIE network density for US hospital referral regions (HRRs). Bivariate tests and multivariable regression were used to characterize hospital, electronic health record (EHR) vendor, and resident characteristics associated with HIE network density.</p><p><strong>Results: </strong> Data on 2,509 hospitals across 274 HRRs were included in the study, with 92% of hospitals participating in at least one HIE. On average, hospitals participated in two HIEs and there were seven HIEs present in each region. HIE network density ranged from 0.0 to 1.0, with a median of 0.78 and an interquartile range (IQR) of 0.51-1.00. Hospital and vendor characteristics associated with greater HIE network density include: more HIEs per hospital, a higher proportion of non-profit hospitals, greater Epic market share, and more concentrated hospital and EHR vendor markets. Resident characteristics associated with greater HIE network density include: higher home values, more educated residents, and higher median household incomes.</p><p><strong>Conclusion: </strong> We found that, on average, 7 out of 10 hospital pairs within a given HRR are connected via at least one HIE, with lower HIE network density in regions with lower socioeconomic status. This measure can be used to track the impact of the Trusted Exchange Framework and Common Agreement on area-level interoperability.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"463-471"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12094861/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143013646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Facilitators and Barriers to Uptake of Drug-Drug Interaction Alerts: Perspectives of Australian End Users and Managers.","authors":"Kristian Stanceski, Bethany A Van Dort, Teresa Lee, Andrew J McLachlan, Richard O Day, Sarah N Hilmer, Ling Li, Johanna Westbrook, Wu Yi Zheng, Michael Barras, Karma Z S Mekhail, Melissa T Baysari","doi":"10.1055/a-2481-4221","DOIUrl":"10.1055/a-2481-4221","url":null,"abstract":"<p><strong>Background: </strong> Drug-drug interaction (DDI) alerts in electronic systems are frequently implemented to minimize the occurrence of preventable DDIs. While prescribers recognize the potential benefits of DDI alerts, a large proportion are overridden by users.</p><p><strong>Objectives: </strong> This study aimed to explore and compare prescribers' and managers' perspectives of DDI alerts.</p><p><strong>Methods: </strong> A qualitative descriptive study was conducted across six hospitals in Australia with end users (prescribers who receive alerts) [<i>n</i> = 14] and managers [<i>n</i> = 20] (senior staff in roles relevant to alert system implementation and management). End users were asked to reflect on alert usefulness, benefits, risks, and impacts. Managers were asked what they thought of alerts, and about any feedback they had received from frontline clinicians. Key themes were extracted via an inductive content analysis approach and deductively mapped to the Technology Acceptance Model (TAM3). Comparisons of the views held toward the alerts were made between the two participant groups.</p><p><strong>Results: </strong> End users predominantly reflected on the utility of the DDI alert system (i.e. how useful it was to their role), less on how easy the system was to use, and mainly focused on the negative consequences of alerts. Managers believed the benefits of DDI alerts are primarily experienced by junior doctors. While end users suggested that alerts should be tailored to the patient's clinical scenario, managers called for DDI alerts to be tailored to the prescriber (seniority and specialty).</p><p><strong>Conclusion: </strong> Interviews with end users and managers uncovered a number of perceived benefits and limitations of DDI alerts, primarily related to the system's usefulness. While largely consistent, some perceptions were different between end users and managers, particularly in the types of benefits, and how they conceptualized potential tailoring to improve DDI alerts. Our findings point to a need for user participation in the development, deployment, and improvement of alerts to promote consideration and effectiveness of DDI alerts.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 2","pages":"295-304"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11964717/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143773953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}