Applied Clinical Informatics最新文献

{"title":"A Systematic Approach to Screen, Identify, and Correct Malfunctioning Interruptive Alerts.","authors":"EzzAddin Al Wahsh, Justin Juskewitch, Carol Eichenlaub, Courtney Holbrook, Pedro J Caraballo","doi":"10.1055/a-2646-6297","DOIUrl":"https://doi.org/10.1055/a-2646-6297","url":null,"abstract":"<p><p>Interruptive alerts can negatively impact clinical workflows and contribute to alert fatigue, provider frustration, and burnout. Given that interruptive alert overriding is a heterogeneous and recurring phenomenon, occurring across different organizational contexts with varying characteristics and circumstances, we hypothesize a pragmatic approach with multimodal interventions to address malfunctioning alert populations and maintain those contributing to better patient care.This study aimed to develop a systematic approach to screen, identify, and correct malfunctioning interruptive alerts within a tertiary healthcare system.We performed screening by assessing the alert population, exploring available resources, and defining alert population inclusion and exclusion criteria. We identified interruptive alerts and then conducted an exploratory analysis. We shared insights from discussions with our expert panel to validate our findings and find gaps in current alert monitoring. We then performed focus groups and interviews as part of a root cause analysis. To address the findings of these investigations, we prioritized which alerts to improve, evaluated solutions, and recommended steps to improve our governance structure.We developed an approach to assess around 1,500 unique alerts in a tertiary center from January to June 2023. We introduced two approaches to visually analyze alert populations: alert-focused analysis and people- and systems-focused analysis. We utilized an expert panel to further enhance the power and speed of alert evaluation and then investigated one emerging alert with focus groups, identifying root causes for its malfunction. This alert demonstrated how enterprise practice changes, coupled with design and cultural issues, can trigger significant alert malfunctions.A multi-modal intervention approach is needed to evaluate interruptive alerts and act quickly on findings. Utilizing both analytical and nonanalytical methods can work in synergy to facilitate this framework. Such approaches may reduce time and be valuable tools for optimally allocating resources to tackle institutional alert challenges.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 4","pages":"863-871"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12367368/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144975357","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":"Suicidality Screening: Ensuring Providers Do Not Miss Adolescents at High Risk through Clinical Decision Support.","authors":"Shravani Vundavalli, Aarti Chandawarkar, Kristen Beck, Emily Decker, Stefanie Bester, Juan D Chaparro, Alysha J Taxter","doi":"10.1055/a-2591-4071","DOIUrl":"https://doi.org/10.1055/a-2591-4071","url":null,"abstract":"<p><p>Major depression in adolescents is recognized as a serious psychiatric illness and a risk factor for suicide. It is important for providers to screen for depression and suicidality and have clinical decision support (CDS) for evaluation, risk assessment, and initial management. Our efforts focused on leveraging the electronic health record (EHR) to ensure that high-risk adolescents received appropriate interventions before leaving the office.This study aims to improve notification of positive adolescent depression and suicide risk screening results. Subaims include (1) designing and optimizing CDS alerts for severe depression and/or acute lethality; and (2) increasing visibility for different EHR users to avoid the near misses.We implemented several iterations of an interruptive alert after a positive mental health screening for patients aged 12 to 20 years seen in primary care and subspecialty rheumatology clinics between 2016 and 2023. Screening started with the Patient Health Questionnaire (PHQ) and Ask Suicide-Screening Questions (ASQ) on paper, and later via tablets.There were 76,919 visits during the study period, of which 50,502 (66%) completed PHQ screening. Rates of PHQ screening increased throughout the study period. Of the ASQ screenings completed, alerts were fired for 2,355 nonacute positive and 411 acute positive. In most cases, all alerts fired were more than once. Providers and clinicians receiving alerts (physicians, nurse practitioners, social workers, and psychologists) acknowledged 63 to 96% of alerts and cancelled 6 to 70% of alerts. We revised the initial alert identifying lethality to include separate alerts for major depressive symptoms and suicide risk. Iterations also included an icon on the clinic schedule and incorporated guidance on appropriate actions.By creating multiple types of alerting within different workflows, we improved notification and increased next-step visibility, leveraging decision support for patients screening positive for depression and suicidality.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 4","pages":"816-824"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12373463/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144975540","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":"Opportunities and Challenges Associated with the Pilot Implementation of Clinical Decision Support Systems in a Rural Hospital: A Qualitative Study.","authors":"Nicki Newton, Adeola Bamgboje-Ayodele, Rowena Forsyth, Lenert Bruce, Steven M McPhail, Tim Shaw, Sundresan Naicker, Amina Tariq, Melissa T Baysari","doi":"10.1055/a-2581-6236","DOIUrl":"10.1055/a-2581-6236","url":null,"abstract":"<p><p>Despite their potential, Clinical Decision Support (CDS) systems often lack alignment with clinicians' needs and are underutilized in practice. Pilot implementations can help to improve the fit between systems and local needs by engaging users in real-world testing and refinement. Although pilot implementations of CDS have been reported, limited evidence has explored the factors contributing to pilot success.This study aimed to explore the opportunities and challenges associated with the pilot implementation of a CDS system that ultimately did not progress to full-scale implementation.We conducted interviews with clinicians, health service managers, and vendors involved in the pilot implementation and use of a mobile application-based CDS, and a dashboard-based CDS in two departments (Emergency and Patient Flow) of a rural Australian hospital. A semistructured interview guide was developed using the Non-adoption, Abandonment, Sustainability, Scale-up, and Spread (NASSS) framework. Interviews were audio-recorded, transcribed, and thematically analyzed.Analysis revealed four major themes: system performance and design, implementation processes, organizational support and resources, and perceived benefits of the CDS. The pilot implementation allowed for greater user input into the iterative design of CDS in practice, particularly in the Emergency Department (ED), where clinicians had both the capacity and willingness to engage. However, technical issues encountered early in the pilot deterred many users who did not re-engage even after issues were resolved. Although some users remained engaged, they became frustrated as organizational resource constraints meant that critical issues impacting the CDS's clinical utility went unresolved.Successful CDS pilots depend on the readiness of organizations, departments, and users to engage in pilot activities. Pilot implementations should be pursued in settings where users have both the capacity and willingness to participate in iterative feedback processes and where organizations have sufficient resources to address emerging needs.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"777-785"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12352988/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144020528","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":"Qualitative Verification of Machine Learning-Based Burnout Predictors in Primary Care Physicians: An Exploratory Study.","authors":"Daniel Tawfik, Stefanie S Sebok-Syer, Cassandra Bragdon, Cati Brown-Johnson, Marcy Winget, Mohsen Bayati, Tait Shanafelt, Jochen Profit","doi":"10.1055/a-2595-0415","DOIUrl":"10.1055/a-2595-0415","url":null,"abstract":"<p><p>Electronic health record (EHR) usage measures may quantify physician activity at scale and predict practice settings with a high risk for physician burnout, but their relation to experiences is poorly understood.This study aimed to explore the EHR-related experiences and well-being of primary care physicians in comparison to EHR usage measures identified as important for predicting burnout from a machine learning model.Exploratory qualitative study with semi-structured interviews of primary care physicians and clinic managers from a large academic health system and its community physician partners. We included primary care clinics with high burnout scores, low burnout scores, or large changes in burnout scores between 2020 and 2022, relative to all primary care clinics in the health system. We conducted inductive and deductive coding of interview responses using a priori themes related to the machine learning model categories of patient load, documentation burden, messaging burden, orders, and physician distress and fulfillment.Interviews with 16 physicians and 4 clinic managers identified burdens related to three dominant themes: (1) messaging and documentation burdens are high and require more time than most physicians have available during standard working hours. (2) While EHR-related burdens are high they also provide patient-care benefits. (3) Turnover and insufficient staffing exacerbate time demands associated with patient load. Dimensions that are difficult to quantify, such as a perceived imbalance between job demands and individual resources, also contribute to burnout and were consistent across all themes.EHR-related work burden, largely quantifiable through EHR usage measures, are major source of distress among primary care physicians. Organizational recognition of this work as well as staffing and support to predict associated work burden may increase professional fulfillment and reduce burnout among primary care physicians.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"1031-1040"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12413275/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144041460","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":"Development and Evaluation of Clinical Decision Support for Immigrant Child Health Screening in Primary Care.","authors":"Jeremy J Michel, Dean Karavite, Daniel White, Nadège Mudenge, Elizabeth Dawson-Hahn, Katherine Yun","doi":"10.1055/a-2594-3633","DOIUrl":"10.1055/a-2594-3633","url":null,"abstract":"<p><p>While electronic health record (EHR)-based tools for refugee health screening exist, support for other immigrant children has lagged. Reasons include lack of time, difficulty determining screening eligibility, and lack of awareness of screening recommendations. EHR-based tools to promote immigrant child health screening (ICHS) can address these challenges, but guidance is needed for tools that are usable by clinicians and acceptable to immigrant families.Develop useful EHR-based tools to support ICHS while incorporating evaluation of acceptability, usability, and implementation effort.We followed a five-step human-centered design approach to develop EHR-based tools for ICHS. This included: (1) representative users completing semi-structured interviews. (2) Health professionals and community advisory groups providing ongoing guidance. (3) Developing a functional prototype. (4) Usability testing of the prototype. And (5) an assessment of the implementation effort involving a second site installation coupled with expert implementation time estimations.Sixteen interviewees discussed screening barriers and how EHR-based tools could support discussing nativity (country of birth). From the interview findings and in consultation with advisory group members, we developed an EHR-based toolkit including noninterruptive alerts, an order set, and a documentation prompt. Ten clinicians completed usability testing. All recognized the alert and asked country of birth. Most (9) were satisfied with the system. All felt it was easy to use, helpful, and would not hinder patient care. Content experts (<i>n</i> = 8) estimated installation times (range: 4-20 hours, median 10) with high levels of confidence (range: 1-5, median 4). A second-site test installation required 7.25 hours.Our EHR-based tools designed with the guidance of experts were highly rated on usability and can help clinicians identify patients eligible for ICHS in a sensitive manner. Installation testing demonstrated that this content could be implemented in a reasonable timeframe at external sites.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"961-973"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12396900/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144041859","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":"Redesigning Clinical Decision Support for Retinopathy of Prematurity Screening After Alert Failure.","authors":"Mikael C Guzman-Karlsson, Lauren M Hess, Amy L Jeppesen, Regine M Fortunov","doi":"10.1055/a-2594-3571","DOIUrl":"10.1055/a-2594-3571","url":null,"abstract":"<p><p>Retinopathy of prematurity (ROP) is the leading cause of preventable childhood blindness. Guidelines recommend screening for infants with gestational age at birth <31 weeks or birth weight ≤1,500 g. However, ensuring timely screening during readmissions after birth is challenging.To analyze the performance of an interruptive alert at a large academic pediatric hospital for identifying premature infants needing ROP screening upon hospital readmission and to describe how data informed the transition to a non-interruptive dashboard.The alert appeared for patients 1 to 365 days of age hospitalized in acute care or pediatric intensive care and instructed providers to order an ophthalmology consult from within the alert and to call ophthalmology for at-risk patients. For quality improvement, the clinical decision support (CDS) advisory group evaluated the effectiveness and efficiency of the alert. We extracted alert metrics from the hospital's enterprise data warehouse, including the user response and feedback, patient characteristics (age, birth gestational age, and birth weight), and any ophthalmology consultations. We analyzed the percentage of encounters seen by ophthalmology using a statistical process control chart during alert implementation and 6 months before and after.The alert appeared 3,309 times during 2,194 patient encounters usually. Users chose \"Accept and place order\" for 43% (943/2,194) of encounters, but only 11% (102/943) had an ophthalmology consult; 34% (53/155) of ophthalmology consultations occurred in encounters with a final response other than \"Accept and place order.\" The intervention was redesigned using a non-interruptive surveillance dashboard with greater specificity, and the alert was de-implemented.Analysis of a failed interruptive alert for identifying patients at risk for ROP led to a transition to targeted surveillance using a dashboard. This case emphasizes the importance of aligning the CDS modality to the clinical workflow, information availability, and user decision-making needs and should be supported by governance.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"1024-1030"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12413272/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055135","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":"Clinical Implementation of Artificial Intelligence Scribes in Health Care: A Systematic Review.","authors":"Hadeel Hassan, Amy R Zipursky, Naveed Rabbani, Jacqueline G You, Gabe Tse, Evan Orenstein, Mondira Ray, Chase Parsons, Stella Shin, Gregory Lawton, Karim Jessa, Lillian Sung, Adam P Yan","doi":"10.1055/a-2597-2017","DOIUrl":"10.1055/a-2597-2017","url":null,"abstract":"<p><p>Artificial intelligence (AI) scribes use advanced speech recognition and natural language processing to automate clinical documentation and ease administrative burden. However, little is known about the effect of AI scribes on clinicians, patients, and organizations.This study aimed to (1) propose an evaluation framework to guide future AI scribe implementations, (2) describe the effect of AI scribes along the domains proposed in the developed evaluation framework, and (3) identify gaps in the AI scribe implementation literature to be evaluated in future studies.Databases including Embase, Embase Classic, and Ovid Medline were searched, and a manual review was conducted of the New England Journal of Medicine AI. Studies published after 2021 that reported on the implementation of AI scribes in health care were included. Descriptive analysis was undertaken. Quality assessment was undertaken using the Newcastle-Ottawa Scale. The nominal group technique was used to develop an evaluation framework.Eleven studies met the inclusion criteria, with 10 published in 2024. The most frequently used AI scribe was Dragon Ambient eXperience (<i>n</i> = 7, 64%). While clinicians often reported improved documentation quality, AI scribe accuracy varied, frequently requiring manual edits and raising occasional concerns about errors. Nine of 10 studies reported improvements in at least one efficiency metric, and seven of ten studies highlighted positive effects on clinician wellness and burnout. Patient experience was assessed in three studies, all reporting favorable outcomes.AI scribes represent a promising tool for improving clinical efficiency and alleviating documentation burden. This systematic review highlights the potential benefits of AI scribes, including reduced documentation time and enhanced clinician satisfaction, while also identifying critical challenges such as variable adoption, performance limitations, and gaps in evaluation.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"1121-1135"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12449105/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143991867","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":"Evaluating Cost Savings Associated with a Patient-Facing Asthma Mobile Health Intervention.","authors":"Julia Nadelmann, Milin Patel, Sarah Lane, James Hammock, Allison Stark, Sunit P Jariwala","doi":"10.1055/a-2595-3329","DOIUrl":"10.1055/a-2595-3329","url":null,"abstract":"<p><p>The patient-facing ASTHMAXcel mobile platform has been linked to improved asthma knowledge decreased asthma-related health care utilization (emergency department [ED] visits, hospitalizations), and reduced prednisone use among adult and pediatric patient populations.Given the upfront costs associated with developing mobile health platforms, this paper seeks to estimate the savings attributable to pediatric and adult users of the ASTHMAXcel platform through decreased hospitalizations, ED visits, and prednisone use.Forty adult patients and 39 pediatric patients with asthma completed studies evaluating the effectiveness of the ASTHMAXcel mobile platform at Montefiore Medical Center. Study participants received the mobile intervention for 6 months and questionnaires were administered at baseline and follow-up visits. Using internal cost data from Montefiore and information on insurance coverage, we estimated the average costs saved by the decreases in ED visits, hospitalizations, and prednisone usage throughout the study time period.Throughout the study time period, participant exposure to ASTHMAXcel and ASTHMAXcel adventures was estimated to save a total of $367,280 with $270,732 in savings from adults' decreased asthma-related health care utilization and $96,548 from pediatric decreases in asthma-related health care utilization. The bulk of these savings estimates are driven by decreases in hospitalizations among both pediatric and adult participants during the study time frame.Given the significant economic burden of asthma treatment and management and its disproportionate impact on those who are economically disadvantaged, it is critical that asthma interventions are assessed not only for their clinical effectiveness but also for their cost-effectiveness.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"1086-1094"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12431811/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055245","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":"\"I worry we'll blow right by it:\" Barriers to Uptake of the STRATIFY-CDS for Acute Heart Failure.","authors":"Matthew A Christensen, Carrie Reale, Shilo Anders, Tim Coffman, Hala Alaw, Janos L Mathe, Dan Albert, Anna Sachs, Allison B McCoy, Dandan Liu, Alan B Storrow, Sunil Kripalani, Laurie L Novak","doi":"10.1055/a-2594-3770","DOIUrl":"10.1055/a-2594-3770","url":null,"abstract":"<p><p>Clinical decision support (CDS) tools in electronic health records (EHRs) often face low uptake due to limited usability, workflow integration, and other implementation issues. We recently designed and implemented the STRATIFY-CDS tool, which calculates a validated risk-prediction model and recommends disposition for emergency department (ED) patients with acute heart failure. Despite applying human-centered design and implementation science strategies, initial utilization in the first 3 months of the STRATIFY-CDS tool was just 3%.To identify usability issues and contextual barriers to uptake of STRATIFY-CDS tool among ED clinicians.We performed an exploratory qualitative and simulation study with ED clinicians at Vanderbilt University Medical Center who had used the STRATIFY-CDS tool at least once. Semi-structured interviews with interactive simulation (summative usability) were conducted via videoconference. Two authors performed thematic analysis informed by the Technology Acceptance Model.Of 13 invited ED clinicians, 10 participated (7 attending and 3 resident physicians) with 1 to 11 prior tool uses. Although the main user interface had high perceived usability, participants struggled to find the launch button. The <i>perceived utility</i> was low-to-moderate and varied based on whether the recommendation matched the participant's clinical gestalt. When there was mismatch, perceived utility was lower, and participants needed more information about the risk model and supporting evidence, which were not readily available. Despite educational implementation strategies and ED leadership approval, there was not a strong social norm to use the tool.Although the main user interface had high usability, poor visibility of the launch button coupled with low familiarity with the underlying evidence and lack of a social norm impaired uptake of the STRATIFY-CDS tool. Future work on CDS design should test novel non-interruptive launch mechanisms and evaluate training with simulation as an implementation strategy to bolster initial confidence and excitement around the CDS.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 4","pages":"1014-1023"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12413277/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145006665","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":"Achieving ACGME Clinical Informatics Fellowship Accreditation: A Chronicle of Our Institution's Journey.","authors":"Srikar Chamala, Matthew S Keefer, Troy McGuire, Leticia Diaz, Anthony A Luberti, Christoph U Lehmann, Ryan J Schmidt","doi":"10.1055/a-2680-5920","DOIUrl":"10.1055/a-2680-5920","url":null,"abstract":"<p><p>Clinical informatics (CI) is a dynamic field at the intersection of health care, technology, and information science, aimed at enhancing health care delivery and patient outcomes. CI fellowship programs prepare physicians to lead and apply health information technologies that drive improvements in clinical care, system efficiency, and innovation. Achieving Accreditation Council for Graduate Medical Education (ACGME) accreditation for such programs is crucial for standardizing training and ensuring the development of a competent workforce.This study aims to share our institution's experience at Children's Hospital Los Angeles in obtaining ACGME accreditation for a CI fellowship program, highlighting key steps and strategies.A multidisciplinary steering committee, including institutional leaders and CI experts, was formed. Key activities included a needs assessment, curriculum development, securing institutional support, and engaging with external advisors from accredited CI programs. The curriculum was designed to align with ACGME core competencies and the American Board of Preventive Medicine's CI subspecialty requirements. Extensive documentation, including rotation schedules and evaluation forms, was prepared for submission.Our CI fellowship program received ACGME accreditation. Essential components that contributed to our success included strong institutional support, a well-defined curriculum integrating clinical and non-clinical rotations, and strategic faculty involvement across various informatics domains. Guidance from experienced directors at established CI programs was instrumental in expediting our application process and ensuring program readiness. The development of detailed documentation, such as a block diagram and competency-based evaluations, was crucial in demonstrating compliance with ACGME requirements.Our experience of achieving ACGME accreditation underscores the importance of assembling a diverse steering committee, engaging external expertise, and securing robust faculty participation. The strategies and insights gained from our accreditation journey can serve as a roadmap for other institutions aiming to establish CI fellowship programs, which are vital for training future leaders in CI and advancing health care innovation.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"1171-1183"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12473513/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144838316","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}