Applied Clinical Informatics最新文献

{"title":"A Clinical Decision Support System to Optimize Antimicrobial Dosing in Patients with Renal Impairment.","authors":"Ana Garcia-Souto, Sara Ibáñez-García, Beatriz Torroba-Sanz, Gonzalo Domínguez-Chaparro, Maria Nuñez-Nuñez, Maria Eugenia Velasco-García, Jose Luis de la Rosa-Triviño, Ana Herranz-Alonso, Maria Sanjurjo-Sáez","doi":"10.1055/a-2893-7843","DOIUrl":"10.1055/a-2893-7843","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to develop and validate a targeted set of clinical rules embedded within a clinical decision support system to support safer antimicrobial dosing in patients with impaired renal function and to assist antimicrobial stewardship activities.</p><p><strong>Methods: </strong>Clinical rules for renal dose adjustment were developed through a structured literature review and consensus by a multidisciplinary team. The rules were implemented within a clinical decision support system integrated with electronic prescribing, electronic health records, and laboratory data, through HL7 messaging and supported by a NoSQL database architecture. A 9-week pilot validation study was conducted in a tertiary care hospital, during which alerts were reviewed by pharmacists. System effectiveness was assessed by alert review rates, pharmacist interventions, physician acceptance, and positive predictive value.</p><p><strong>Results: </strong>A total of 58 clinical rules were implemented. During the validation period, 409 alerts were generated for 249 patients, of which 352 alerts (86%) were reviewed by pharmacists. Pharmacist interventions were performed for 190 alerts (54%). Among 156 assessable interventions, 111 (71%) were accepted by physicians, resulting in antimicrobial dose modifications. The overall positive predictive value of the clinical rule set was 0.32. Acceptance rates varied across clinical settings, ranging from 57% in surgical units to 80% in the emergency department.</p><p><strong>Conclusion: </strong>Implementation of a consensus-based bundle of clinical rules within a clinical decision support system generated actionable renal dosing alerts and supported pharmacist-led interventions with high prescriber acceptance. This informatics-enabled approach supports safer antimicrobial dosing decisions in patients with renal impairment and may help reduce the risk of medication-related harm.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"502-509"},"PeriodicalIF":2.7,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13293636/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148228872","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":"Co-designing an Outpatient Clinical Decision Support Prototype for Managing Social Risks in Patients Living with Dementia.","authors":"Miad Ahemd Alfaqih, Philipp Haessner, Jennifer H LeLaurin, Jingchuan Guo, Nicole C Hammer, Onyekachi Ike-Okpe, Michael J Pappa, Xing He, Ramzi G Salloum, Jiang Bian, Megan E Gregory","doi":"10.1055/a-2917-6503","DOIUrl":"10.1055/a-2917-6503","url":null,"abstract":"<p><strong>Background: </strong>Patients living with dementia (PLWD) require attention to social determinants of health (SDoH), but social information is often unavailable or incomplete during care encounters, and clinicians report uncertainty about how to act on this information.</p><p><strong>Objective: </strong>This study aimed to co-design the Intelligent Social Risk Management in Alzheimer's Disease and Alzheimer's Disease-Related Dementias Patients (iSMART) clinical decision support (CDS) prototype, which integrates an AI-driven individualized polysocial risk score (iPsRS) to identify PLWD at high social risk for hospitalization.</p><p><strong>Methods: </strong>We conducted a qualitative user-centered design study with nine outpatient providers and clinical staff who care for PLWD at a large academic health system. Participants completed semi-structured interviews to explore perceived social risks in dementia care, gather feedback on the iSMART prototype and its features, and identify implementation considerations. Interview transcripts were coded and analyzed via rapid qualitative and thematic analysis.</p><p><strong>Results: </strong>Nine participants (six providers, two nurses, and one social worker) were interviewed. Lack of caregiver or family support was identified as the most important social factor to consider for PLWD, followed by financial strain and transportation issues. Participants described the iSMART prototype as helpful for identifying social risks among PLWD, summarizing and prioritizing factors contributing to hospitalization risk, and connecting patients to relevant social resources. Participants suggested primary care providers and social workers should be the primary users. Recommended improvements included auto-populated (as opposed to manual entry) but editable SDoH fields for model input, incorporating caregiver presence as a model input, and providing clearer visual representations of risk.</p><p><strong>Conclusion: </strong>Outpatient providers and staff viewed the iSMART prototype as a promising approach to support social risk screening, resource connection, and referral support in dementia care. These findings inform practical strategies for integrating iPsRS-informed CDS tools into routine workflows in dementia clinics.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 3","pages":"659-667"},"PeriodicalIF":2.7,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13423536/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148632345","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":"From Pandemic Response to Kill the Clipboard: Patient-Controlled Sharing of Health Data Using International Patient Summary (IPS) and QR codes.","authors":"John D D'Amore, Estar Rani Vallapu, Lipika Samal, Bryant T Karras, William B Lober","doi":"10.1055/a-2902-8515","DOIUrl":"10.1055/a-2902-8515","url":null,"abstract":"<p><strong>Background: </strong>Despite advances in interoperability, patient-supplied medical histories commonly use paper-based forms. Dissatisfaction with this inefficiency has led to the \"Kill the Clipboard\" initiative from the Centers for Medicare & Medicaid Services to advance digital alternatives. During the coronavirus disease 2019 (COVID-19) pandemic, patient-controlled vaccination record sharing demonstrated that Quick Response (QR) codes and digital data standards provide an effective option. Building on this, several nations are using three standards to securely view and exchange medical data: Fast Healthcare Interoperability Resources, the International Patient Summary, and SMART Health Links.</p><p><strong>Objectives: </strong>This case report explores the use of QR codes and medical data standards in patient-mediated workflows to share medical histories, describing implementation experiences from four such implementations.</p><p><strong>Methods: </strong>We describe standards and developer community experience with global initiatives and implementations across the United States, Canada, and the Hajj pilgrimage, which all support the use of QR codes in patient-mediated data exchange.</p><p><strong>Results: </strong>We report on technical readiness, patient adoption, and reported improvements to emergency preparedness using QR codes to share patient summaries.</p><p><strong>Conclusion: </strong>Advancing patient-mediated exchange with these technologies aligns with initiatives to \"Kill the Clipboard.\" Preliminary evidence suggests this novel approach can better inform care. These four case studies demonstrate the viability of this approach and the lessons learned from this digital transition.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"559-567"},"PeriodicalIF":2.7,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13354518/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148354573","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":"Improving Data Segmentation Accuracy Through Clinician-Informed Contextual Reasoning.","authors":"Mengyi Wei, Anita Murcko, Patricia Bayless, Preston Lee, Maria Adela Grando","doi":"10.1055/a-2880-9069","DOIUrl":"10.1055/a-2880-9069","url":null,"abstract":"<p><strong>Background: </strong>A potential limitation of current data segmentation technologies is that pertinent contextual information accessible via the patient's electronic health records (EHRs) is not used to make segmentation inferences.</p><p><strong>Objective: </strong>Learn how physicians apply contextual reasoning when classifying potentially sensitive health data in EHRs, including information related to substance use disorder (SUD), behavioral health, and other protected categories, and how these insights can enhance the design of context-aware data segmentation tools.</p><p><strong>Methods: </strong>We conducted semi-structured interviews with 24 board-certified physicians who reviewed constructed patient summaries and categorized selected data items into predefined sensitivity categories. Their confidence levels were inferred from language cues and validated through expert review of the rationale provided. We analyzed co-occurrences between context types and data categories to identify systematic reasoning patterns.</p><p><strong>Results: </strong>Of 24 physicians 19 (79%) explicitly used contextual reasoning, drawing on diagnoses, medical history, and medication history to inform their classifications. The most frequently categorized items were from medication history (38.9%) and laboratory results (36.1%). Diagnoses were the most common contextual reference (50%), often used to interpret medications and laboratory results. High-confidence categorizations were associated with structured data supported by clinical diagnoses; lower confidence was linked to ambiguous items, such as social history.</p><p><strong>Conclusion: </strong>Physicians routinely draw on contextual information when assessing the sensitivity of health data-especially for laboratories and medications-which current segmentation tools often overlook. Embedding clinician-informed reasoning patterns into segmentation logic can improve classification accuracy, reduce misclassification risk, and enhance alignment with real-world care practices and privacy regulations. Future research should explore generalizability across diverse provider types and incorporate patient perspectives to support equitable, context-aware data sharing.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 3","pages":"450-458"},"PeriodicalIF":2.7,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13286106/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148240499","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":"Systematic Review and Meta-analysis of Interactive Digital Self-management Interventions for Adults with Chronic Respiratory Disease in Randomized Controlled Trials.","authors":"Wade Michaelchuk, Shirley Quach, Anastasia N L Newman, Adam Benoit, Aline Maybank, Ana Oliveira, Roger Goldstein, Dina Brooks","doi":"10.1055/a-2897-2572","DOIUrl":"10.1055/a-2897-2572","url":null,"abstract":"<p><strong>Background: </strong>Interactive digital self-management (IDSM) interventions may help individuals with chronic respiratory disease self-manage their condition.</p><p><strong>Objective: </strong>This review aimed to summarize the characteristics and effectiveness of IDSM interventions for this population.</p><p><strong>Methods: </strong>Reviewers systematically screened titles, abstracts, and full texts of randomized controlled trials (RCTs) examining applications or wearable devices for IDSM in adults with chronic respiratory diseases. Study and intervention characteristics and outcomes were extracted. Meta-analysis was conducted in a subset of studies.</p><p><strong>Results: </strong>The search generated 109,900 unique records and 34 relevant RCTs were identified. These studies evaluated 2,320 individuals with asthma, 1,766 with chronic obstructive pulmonary disease (COPD; FEV₁ % predicted 36 to 69), and 33 with cystic fibrosis. In asthma, median (range) intervention length was 12 (1-52) weeks. In COPD, median (range) intervention length was 24 (2-48) weeks. In COPD, IDSM interventions showed greater effect than control for health status (COPD Assessment Test score mean difference [95% CI]: -1.6 [-3.2, 0.0], <i>p</i> < 0.05, very low quality of evidence), physical activity (steps per day: 937.9 [95% CI: 311.5, 1,564.4], <i>p</i> < 0.05, very low quality of evidence), and exercise capacity (six-minute walk test distance mean difference [95% CI]: 5.6 [1.7, 9.4], <i>p</i> < 0.05, low quality of evidence). In asthma, no statistically significant effect was observed for asthma control or quality of life and only one RCT in cystic fibrosis was identified.</p><p><strong>Conclusion: </strong>Interventions were heterogeneous and yielded very low to moderate quality evidence. In COPD, IDSM interventions were associated with statistically significant improvements in health status, physical activity, and exercise capacity; however, findings should be interpreted cautiously due to low or very low certainty of evidence. Evidence in asthma and cystic fibrosis remains limited and inconsistent. At present, IDSM tools should be considered adjunctive options rather than replacements for established self-management strategies.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 3","pages":"587-603"},"PeriodicalIF":2.7,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13372473/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148457386","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":"The Effect of Electronic Health Record-Based Central Line Maintenance Documentation on CLABSI Rates across Intensive Care Units at a Pediatric Hospital.","authors":"İlker Devrim, Hincal Ozbakir, Yeliz Oruc, Canan Dinc, Ozlem Yilman, Mehmet Can, Tezcan Ozbay, Nuriye Turgut, Tomris Birgili, Gulsen Ozdemir Pilavci, Utku Karaarslan, Arzu Sencan, Hasan Agin","doi":"10.1055/a-2838-8190","DOIUrl":"10.1055/a-2838-8190","url":null,"abstract":"<p><p>Central line-associated bloodstream infections (CLABSIs) are a significant concern in pediatric intensive care units (PICUs), leading to increased morbidity and limited treatment options. Electronic health record (EHR)-based documentation for monitoring CLABSIs may enhance bundle compliance and reduce infection rates. However, data in pediatric settings are limited.This study evaluated the impact of transitioning from paper-based to EHR-based documentation for central line maintenance on CLABSI rates in intensive care units (ICUs).A retrospective cohort study was conducted between the paper-based period and EHR-based period in the neonatal (NICU), pediatric surgery (PSICU), and pediatric (PICU) ICUs. CLABSI prevention bundle compliance was assessed using manual checklists in the paper-based period and EHR-based documentation in the EHR-based period. CLABSI rates were calculated per 1,000 catheter-days, and bundle adherence was tracked using manual checklists or EHR-based documentation.Among 3,278 patients, overall CLABSI rates decreased from 5.32 to 2.46 per 1,000 catheter-days (<i>p</i> = 0.008). In the NICU, rates dropped from 6.20 to 2.13 (<i>p</i> = 0.028); in the PSICU, from 1.45 to 0; and in the PICU, from 5.38 to 3.24 per 1,000 catheter-days (<i>p</i> > 0.05).Transitioning to EHR-based documentation for central line maintenance significantly reduced CLABSI rates across PICUs, particularly in the NICU. EHR systems improve compliance monitoring, promote standardization, and represent an effective tool for strengthening infection prevention in pediatric critical care.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 2","pages":"183-189"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13038349/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147595628","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":"Quality and Usability Evaluation of U.S. Clinical Informatics Fellowship Websites.","authors":"Jacqueline G You, Jeffrey Yuan, Gorang Gupta, Suhanee Mitragotri, Kevin Shannon, Ahmad Hassan, Allison Goff, Shuhan He, Ellen Kim","doi":"10.1055/a-2848-6012","DOIUrl":"10.1055/a-2848-6012","url":null,"abstract":"<p><strong>Background: </strong>Clinical informatics (CI) fellowship programs for physicians in the United States are growing with over 60 Accreditation Council for Graduate Medical Education-accredited fellowship programs. As a young clinical subspecialty, many have questions about the field; in addition, fellowship eligibility and structure vary significantly. Physicians apply for CI fellowships through Electronic Residency Application Service and the American Medical Informatics Association (AMIA) Match. Fellowship websites are essential resources for prospective applicants to learn about this subspecialty and fellowship programs.</p><p><strong>Objectives: </strong>The objective of this study is to evaluate the usability of CI fellowship program websites listed on the AMIA website.</p><p><strong>Methods: </strong>Forty-two U.S.-based CI fellowship programs were evaluated using web-crawler based usability analysis tools across (1) accessibility, (2) marketing, (3) content quality, (4) technology, and (5) general usability from November 1, 2024, through November 19, 2024.</p><p><strong>Results: </strong>Marketing had the lowest mean score of 5.75 and technology had the highest mean score of 8.44. Content quality had the highest standard deviation (1.58).</p><p><strong>Conclusion: </strong>This analysis established the baseline usability of CI fellowship program websites. Addressing gaps in usability will help with increasing CI fellowship visibility among potential applicants.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 2","pages":"246-251"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13256036/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786697","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":"Ambient Artificial Intelligence Scribes in Pediatric Hematology-Oncology: Early Implementation of DAX Copilot.","authors":"Molly Talman, Lamia Alam, Dara Mize, Yaa Kumah-Crystal, Carolynn Nall, Allison B McCoy, Adam Wright, Laura Zahn, Jennifer Andrews","doi":"10.1055/a-2873-3894","DOIUrl":"10.1055/a-2873-3894","url":null,"abstract":"<p><strong>Background: </strong>Ambient artificial intelligence scribes are increasingly integrated into electronic health records to reduce documentation burden, but limited data describe their performance in high-complexity pediatric subspecialties.</p><p><strong>Objectives: </strong>This study aimed to describe the early implementation of Dragon Ambient Experience (DAX) Copilot in a pediatric hematology-oncology division and evaluate patterns of use, documentation time, and workflow effect among providers who adopted the tool.</p><p><strong>Methods: </strong>We reviewed outpatient encounters from January to July 2025 and identified those using DAX. Analyses focused on providers who used DAX more than twice, given low overall adoption. Documentation time (minutes spent in active editing sessions) and note-closure timeliness were compared between DAX and non-DAX encounters. Implementation processes, barriers, and accuracy concerns were qualitatively summarized.</p><p><strong>Results: </strong>Of 11,544 outpatient encounters, 427 (3.7%) involved DAX; 10 of 29 providers used DAX at least once, while 6 (20.7%) used it more than twice. Among repeat users, for shorter encounters (≤40 minutes), median documentation time was lower for DAX versus non-DAX (11 [interquartile range, (IQR): 13] vs. 24 [IQR: 30] minutes), corresponding to an approximately 30% lower documentation time (95% confidence interval [CI], 19.9-38.4%; <i>p</i> < 0.001). For longer encounters (>40 minutes), documentation time did not differ significantly. Although unadjusted analyses showed lower rates of same-day and 7-day note closure with DAX, these differences were not significant after adjustment in mixed-effects logistic regression models. Providers reported improved engagement with families and narrative drafting; limitations were related to workflow alignment rather than transcription accuracy.</p><p><strong>Conclusion: </strong>For repeat users, DAX reduced active documentation time in shorter visits but showed limited benefit for longer encounters and did not improve the timeliness of note closure. Adoption remained modest, underscoring the importance of workflow fit and usability considerations in AI-scribe deployment.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"374-379"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13192280/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147876523","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":"Usability and Acceptability Evaluation of a Digital Health Physical Activity Intervention among Older Family Caregivers of Patients with Heart Failure.","authors":"Dawon Baik, Catherine Jankowski, Larry A Allen, Daniel Matlock, Heather Coats, Paul Cook, Blaine Reeder","doi":"10.1055/a-2842-0755","DOIUrl":"10.1055/a-2842-0755","url":null,"abstract":"<p><p>Digital health physical activity (PA) programs have shown promise for improving the health and wellness of family caregivers (FCGs). However, their use among older adult caregivers remains underexplored. To address this gap, we developed TPA4You, a tailored digital health PA program that integrates videoconferencing with a health coach, a fitness tracker, and motivational messaging. The program is designed to support older caregivers, a population whose health and self-care needs are underserved by digital health interventions.This study evaluated the usability and acceptability of TPA4You among older FCGs of patients with heart failure.An iterative design approach guided by the Rapid Iterative Testing and Evaluation methodology was employed. Usability and acceptability were assessed through a two-phase, 1-week trial. Participant feedback from each phase informed iterative refinements to the TPA4You design.Eleven participants were enrolled (Phase 1, <i>n</i> = 7; Phase 2, <i>n</i> = 4), similar in age (68.3 ± 7 vs. 68.0 ± 7). Ten participants identified as non-Hispanic White. All Phase 1 participants were female, while Phase 2 included one male. Participants in both phases reported high perceived usefulness, satisfaction, and ease of use. Interviews on usability and acceptability revealed four common themes in Phases 1 and 2: (1) overall usability and usefulness; (2) supporting self-care and awareness of PA needs; (3) enhancing physical and mental health; and (4) design and features as facilitators and barriers to engagement.Findings demonstrate the feasibility, usability, and acceptability of TPA4You and provide guidance for optimizing its design for a future randomized controlled trial in a larger and more diverse population.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 2","pages":"213-224"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13065363/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147647370","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 User-Centered Design: Programming Changes in a Self-Management Blood Pressure Application.","authors":"Shannon M Canfield, Abigail J Rolbiecki, Parijat Ghosh, Emma Montgomery, Victoria A Shaffer, Michelle Bobo, Matthew B Storer, Aisha Ghumman, LeAnne Michaels, David A Dorr, Richelle J Koopman","doi":"10.1055/a-2823-4533","DOIUrl":"10.1055/a-2823-4533","url":null,"abstract":"<p><p>Electronic patient-centered clinical decision support enhances chronic disease self-management, yet few studies describe how qualitative user feedback is systematically translated into programming improvements. The Collaboration-Oriented Approach to Controlling High Blood Pressure (COACH) is a patient-facing decision support tool for hypertension management, designed for primary care and integration with electronic health records (EHRs) and patient portals.This study aimed to describe how end-user feedback informed COACH programming decisions and the MoSCoW (Must have, Should have, Could have, Won't have) method operationalized prioritization for implementation.This secondary analysis draws on qualitative data from a Consolidated Framework for Implementation Research (CFIR)-informed data collected during a preimplementation evaluation of COACH with 70 care team members and 18 patients across three academic health systems using Cerner/Oracle and Epic EHRs. CFIR-coded data were reviewed, and design or usability \"recommendations\" were translated into discrete programming requirements, prioritized using the MoSCoW, and, where possible, completed before a multisite trial.Seven themes emerged: (1) Timely, actionable alerts, (2) messaging features for follow-up, (3) motivating patients through feedback, (4) reducing data entry burden, (5) setting blood pressure goals, (6) supporting workflow integration, and (7) equity and accessibility. Of the 35 potential recommendations, 25 were translated into changes and prioritized as \"Must have\" (12), \"Should have\" (6), and \"Could have\" (7). Our team completed 19 high-priority features (e.g., setting the blood pressure goal, structured alerts, messaging templates, and visual feedback) before the trial launch.This study demonstrates a replicable process for integrating qualitative insights into digital health programming through structured prioritization, advancing implementation-focused clinical informatics, and guiding decision-making for the future integration of patient-generated health data, such as home blood pressure monitoring.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 2","pages":"127-137"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13016953/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147516072","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}