Applied Clinical Informatics最新文献

{"title":"Nursing Informatics Competency and Effective Clinical Decision-Making among Nurses in Saudi Arabia.","authors":"Sabirin Alruwaili, Mohammad R Alosta, Anas H Khalifeh, Zainab Albikawi, Elham H Othman","doi":"10.1055/a-2863-4806","DOIUrl":"10.1055/a-2863-4806","url":null,"abstract":"<p><strong>Objectives: </strong>The current study examined the relationship between nursing informatics competency (NIC) and perceived clinical decision-making (CDM) skills among nurses in Saudi Arabia.</p><p><strong>Methods: </strong>A cross-sectional, descriptive, and correlational design with convenience sampling was employed in the current study. A self-reported questionnaire, including demographic variables, the Nursing Informatics Competency Assessment Tool (NICAT), and the Clinical Decision-Making in Nursing Scale (CDMNS), was administered. Data were collected between May and July 2024 via Google Forms from registered nurses at three government hospitals in Saudi Arabia.</p><p><strong>Results: </strong>A total of 160 registered nurses participated in the study. The results show that nurses in Saudi Arabia were \"proficient\" in their nursing informatics competencies, with a total scale average (M = 110.5, SD ±24.3), and a \"medium\" level of perceived CDM (M = 148.6, SD ±32.0). Moreover, a statistically significant, strong linear relationship was found between NIC and perceived levels of CDM (<i>r</i> = 0.734, <i>p</i> < 0.001). However, NIC was the sole statistically significant predictor (β = 0.7, <i>p</i> < 0.001) of their perceived level of CDM.</p><p><strong>Conclusion: </strong>The study found that higher self-reported informatics competency was associated with higher perceived CDM. The results highlight to health care stakeholders and nursing management the importance of investing in targeted informatics training and integrating nursing informatics and clinical decision support tools into clinical nursing practice. Moreover, the findings encourage researchers to explore additional factors influencing CDM through longitudinal and qualitative research methods to gain a deeper understanding of this complex process.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 2","pages":"329-336"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13287928/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147950016","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":"Implementing Clinical Decision Support for Primary Care Preventive Screenings for People with Physical Disabilities.","authors":"Tyler G James, Suhas Kellampalli, Beatrice Palazzolo, Lorrie Carbone, Robert Heizelman, Elham Mahmoudi, Michael M McKee","doi":"10.1055/a-2830-2528","DOIUrl":"10.1055/a-2830-2528","url":null,"abstract":"<p><p>People with physical disabilities are one of the largest subgroups of people with disabilities, and this group experiences significant health disparities. Given the risk of preventable multimorbidity among this group, there is an opportunity to improve primary care for this population.The goal of this study was to use a clinical decision support (CDS) tool to improve preventive screenings in primary care for people with physical disabilities.We used a convergent mixed methods study design-integrating quantitative and qualitative data-within a pilot implementation study. Our CDS intervention was implemented at a single, family medicine clinic in an academic medical center in southeast Michigan. Quantitative data were focused on providers using the CDS tool within the electronic health record, while qualitative data were gathered from group meetings and semi-structured interviews with primary care providers at the intervention clinic.The CDS tool was triggered for 1,668 unique encounters and was used only 10% of the time. Among use cases, a recommended preventive screening order was placed 40% of the time. Three themes were developed, focused on (1) inadequate incentive and cognitive task management systems, (2) competing priorities and patient burden, and (3) liking the CDS alert.Although receptive, primary care providers in our study infrequently used the CDS alert. Through merging these mixed methods data, we identified several opportunities to improve the CDS tool including reducing cognitive burden, providing details on the justification for the recommended orders, and better workflow integration.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"145-152"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13004660/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147390978","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":"Factors Affecting Technology Acceptance and Usability of a Personalized Online Nutrition and Exercise Web-Based App (Heal-Me): A Multimethods Study.","authors":"Antonio Miguel Cruz, Ashley Hyde, Graeme Purdy, Kathleen P Ismond, Christofer Cruz, Evelyn Etruw, Kirsten Suderman, Michael Stickland, John C Spence, Dale C Lien, Rahima Bhanji, Carla M Prado, Margaret L McNeely, Puneeta Tandon","doi":"10.1055/a-2858-9079","DOIUrl":"10.1055/a-2858-9079","url":null,"abstract":"<p><strong>Objective: </strong>The Heal-Me (Healthy Eating, Active Living-Mindful Energy) version 1 is a web-based app designed to provide exercise and nutrition support to vulnerable chronic disease populations. As version 1 of the Heal-Me technology has not been evaluated for acceptance and usability within a clinical environment, this study sought to apply the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to investigate its acceptance and usability as part of a randomized controlled trial (RCT) involving adults diagnosed with cancer, chronic lung disease, or those who had undergone liver or lung transplantation.</p><p><strong>Methods: </strong>This single-group study used a multimethod design. Participants completed self-administered questionnaires before and after the intervention, without a control group. Near the end of the study, individual interviews were conducted with select participants. Technology acceptance and usability were assessed using five-point Likert scales from \"disagree (0)\" to \"agree (4).\" Data analysis included partial least squares structural equation modeling and thematic analysis of interview responses.</p><p><strong>Results: </strong>Participants' expectations for accepting the Heal-Me web-based app were met. Performance expectancy, effort expectancy, and social influence had direct effects on their intention to use the app, explaining 50.9% of the variance in behavioral intention. Both facilitating conditions and behavioral intention significantly influenced actual usage, accounting for 71.4% of its variance.</p><p><strong>Conclusion: </strong>Performance expectancy emerged as the most influential factor predicting participants' intention to use the Heal-Me web-based app, with findings clearly indicating a high level of acceptance of the first version of this technology.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 2","pages":"297-306"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13287951/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147822348","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":"Erratum.","authors":"","doi":"10.1055/a-2874-7476","DOIUrl":"10.1055/a-2874-7476","url":null,"abstract":"","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 2","pages":"e2"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13263118/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148240437","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":"Applying User-Centered Design to Develop a Prescriber Feedback Tool in Acute Outpatient Care Settings at the Veterans Health Administration.","authors":"Shilo Anders, Carrie Reale, Thomas Reese, Russ Beebe, Robert Winter, Dax Westerman, Jesse O Wrenn, Jin H Han, Milner Staub, Melissa Rubenstein, Michael J Ward, Michael E Matheny","doi":"10.1055/a-2866-4361","DOIUrl":"10.1055/a-2866-4361","url":null,"abstract":"<p><strong>Objectives: </strong>Acute care providers lack an easy way to assess their prescribing practices and track future-related care for their patients. Thus, we conducted design evaluations and subject matter expert (SME) design sessions in a user-centered design (UCD) approach to develop an audit and feedback tool that provides individualized, scalable prescribing feedback to clinical providers about their antibiotic and nonsteroidal anti-inflammatory drug (NSAID) prescriptions in unplanned care settings (e.g., emergency department and urgent primary care).</p><p><strong>Methods: </strong>A UCD approach was conducted with 11 individual interviews through two rounds of formative testing, focusing on interface design efficiency, effectiveness, and visualization interpretability. We conducted several design sessions with SMEs, prescribers in emergency and primary care medicine, where the design team asked the SMEs to comment and do a walk-through with various design prototypes for the tool, and then further iterate on new designs. Feedback about different user interface designs was obtained from future tool users in usability evaluation sessions where a provider interacted with the prototype through think-aloud, guided by a semistructured interview outline.</p><p><strong>Results: </strong>Through two rounds of usability evaluations, key usability issues were identified with the navigation, language, and interpretation of the data presented. This led to substantial interface design changes prior to implementation that improved usability and usefulness, as evidenced by a decrease in the number of usability issues found during the second round of evaluation. Participants appreciated the concept and usefulness of the tool presented; however, during usability sessions, they identified important optimizations, clarifications, and changes for improvement.</p><p><strong>Conclusion: </strong>Key generalizable findings include user preferences for nonjudgmental framing of prescribing, and a desire for intuitive presentation and summarization of recent care delivered to support actionable feedback. Required changes during UCD underscore the importance of this type of usability evaluation during tool ideation and development.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"337-346"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13287943/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147934605","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":"Corrigendum: Enhancing Data Quality and Remote Accessibility in Clinical Trials: A SeroSelectTB Case Study in Ethiopia, Tanzania, and South Africa.","authors":"Sasho Najdov, Jordancho Arsov, Jovan Davchev, Tamirat Assefa, Jemrath Bikombo, Debora Kajeguka, Anna Okunola, Welile Nwamba, Aleksandar Josifoski, Carol Holm-Hansen","doi":"10.1055/a-2894-9972","DOIUrl":"10.1055/a-2894-9972","url":null,"abstract":"","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 2","pages":"e3"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13278810/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148279589","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":"Stewardship of Inpatient A1c Testing: An Electronic Nudge to Limit Testing after Red Cell Transfusion.","authors":"Andrew A White, Brent E Wisse","doi":"10.1055/a-2838-8292","DOIUrl":"10.1055/a-2838-8292","url":null,"abstract":"<p><p>Guidelines recommend measuring glycated hemoglobin (HgbA1c) levels on all inpatients with diabetes mellitus, if untested in the prior 3 months. In response, our health system applies default HgbA1c orders in the electronic insulin orders for qualifying patients. However, recent red blood cell transfusions may cause falsely low HgbA1c values, leading to inappropriate management. Clinicians often forget to deselect default HgbA1c orders after transfusion, leading to erroneous results. We evaluated a non-interruptive clinical decision support (CDS) intervention to discourage automatic HgbA1c testing in patients with recent transfusions.A retrospective, observational analysis of the number and percentage of HgbA1c tests performed on inpatients within 7 days of a red blood cell transfusion over a 40-month period.Preintervention, clinicians ordered an average of 827 HgbA1c tests/month on inpatients. Of these, 11.7% (97 tests/month) were on patients who received a red blood cell transfusion within the preceding 7 days. Postintervention, clinicians ordered an average of 832 HgbA1c tests per month on inpatients, of which 5.8% (48 tests/month) were performed within 7 days of red blood cell transfusions.A non-interruptive CDS intervention can significantly decrease the number of HgbA1c tests performed in hospitalized patients who received a red blood cell transfusion, a common cause of erroneous HgbA1c values. This approach reduced waste without restricting clinician autonomy or requiring interruptive alerts that generate alert fatigue.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"190-193"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13038350/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147504056","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":"Passive Clinical Decision Support Penetrance: A Comparative Analysis in Two Pediatric Intensive Care Units.","authors":"Matthew D Kijowski, Mark V Mai, Adam C Dziorny","doi":"10.1055/a-2852-7390","DOIUrl":"10.1055/a-2852-7390","url":null,"abstract":"<p><strong>Background: </strong>Clinical decision support (CDS) tools are designed to streamline workflows and enhance care quality in pediatric intensive care units (PICUs). Prior research has largely focused on interruptive, or active, CDS, leaving little known about the usage of passive CDS (pCDS) tools such as note writing support, order sets, and laboratory result flagging across institutions.</p><p><strong>Objectives: </strong>This study aimed to quantify and compare the penetrance of pCDS across two academic PICUs, with the aim of identifying shared practices and opportunities for standardization.</p><p><strong>Methods: </strong>We conducted a retrospective observational cohort study of all patients admitted to two large PICUs from 2016 to 2023. Using Epic electronic health record data, we defined metrics across three domains of pCDS: note writing support, order set usage, and abnormal laboratory result highlighting. We harmonized elements and compared across institutions. We report descriptive statistics and compare sites using the Wilcoxon signed rank and chi-square test of significance.</p><p><strong>Results: </strong>The cohort included 90,575 PICU encounters and 2.65 million notes. We measured significant intersite variability in documentation practices: Children's Healthcare of Atlanta (CHOA) notes were significantly longer (2,020 vs. 1,434 characters) related to a 257% higher use of smart documentation elements and 10% greater reliance on copy/paste features. Across 8.36 million placed orders, order set usage differed by 20% (CHOA: 41 vs. University of Rochester Golisano Children's Hospital: 21%), with consistently higher use at CHOA, although both sites showed lower usage for medication and laboratory orders compared with nursing orders. Among >20 million laboratory results, abnormal flagging differed by 7% (56 vs. 49%), although variability was observed across test categories.</p><p><strong>Conclusion: </strong>Passive CDS usage in PICUs is highly variable across institutions and domains. These findings highlight the need for standardized implementation and cross-site learning to optimize efficiency, reduce cognitive burden, and improve CDS.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 2","pages":"259-268"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13287935/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786709","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":"Federal Healthcare Legislation that Promoted the Digitalization of Medicine and the Impact on Healthcare Delivery in 2025.","authors":"Kyle A Mani, Sanjna Nandal, Thomas Scharfenberger, Meghana Veldhuis, Kevin Tang, Bishoy Gad, Sunit P Jariwala","doi":"10.1055/a-2830-2591","DOIUrl":"10.1055/a-2830-2591","url":null,"abstract":"<p><strong>Background: </strong>Federal healthcare legislation has played a central role in shaping the digital transformation of U.S. healthcare. Key legislative milestones-including the Health Security Act of 1993, the Health Insurance Portability and Accountability Act (HIPAA), the Health Information Technology for Economic and Clinical Health (HITECH) Act, the Patient Protection and Affordable Care Act (ACA), and the 21st Century Cures Act-collectively accelerated the adoption of electronic health records (EHRs), promoted interoperability, and expanded access to digital health tools.</p><p><strong>Objective: </strong>This study aimed to examine how federal legislation across recent administrations has shaped the digitalization of healthcare delivery, and to evaluate the challenges and consequences associated with these policies.</p><p><strong>Methods: </strong>A targeted narrative review was conducted using primary legislative texts and federal policy documents from 1993 to 2016. Findings were organized chronologically and thematically to assess the intended objectives, observed impacts, and ongoing implementation challenges associated with major healthcare legislation.</p><p><strong>Results: </strong>Federal legislation significantly accelerated the adoption of EHR systems, expanded health information exchange, and enabled advances in patient safety, clinical quality, and population health analytics. Implementation has also introduced challenges, including high system costs, workflow disruption, documentation burden, and disparities in adoption amongst smaller practices. Emerging technologies, such as artificial intelligence, are further reshaping digital healthcare while raising new concerns regarding regulation, safety, and data governance.</p><p><strong>Conclusion: </strong>Federal policies have fundamentally transformed healthcare delivery by establishing the infrastructure for a digitally connected healthcare system. Despite measurable improvements in interoperability and data accessibility, persistent challenges remain. Future reforms should prioritize improved EHR design, enhanced clinician training frameworks, and policies that address adoption barriers to ensure that digital health innovations translate into safer, more effective, and equitable patient care.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"138-144"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13008495/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147391005","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":"Enhancing Data Quality and Remote Accessibility in Clinical Trials: A SeroSelectTB Case Study in Ethiopia, Tanzania, and South Africa.","authors":"Sasho Najdov, Jordancho Arsov, Jovan Davchev, Tamirat Assefa, Jemrath Bikombo, Debora Kajeguka, Anna Okunola, Welile Nwamba, Aleksandar Josifoski, Carol Holm-Hansen","doi":"10.1055/a-2873-5092","DOIUrl":"10.1055/a-2873-5092","url":null,"abstract":"<p><strong>Background: </strong>Ensuring data quality and maintaining remote accessibility remain key challenges in clinical trials conducted in low-resource settings. Although several software platforms and digital tools attempt to address these challenges, no single, comprehensive solution adequately meets the complex demands of decentralized and intermittently connected trial environments. Consequently, context-specific tools must be developed and adapted to ensure reliable performance under such constraints.</p><p><strong>Objective: </strong>The aim of this study was to enhance data quality and enable uninterrupted participant randomization in settings with limited internet and electricity through the implementation of an automated Quality Control (QC) reporting system and an online and offline participant randomization application.</p><p><strong>Methods: </strong>A centralized automated QC reporting system was developed using a Python-based script, which was integrated with the Research Electronic Data Capture system to extract and process data, and generate a web-based monitoring dashboard, which displayed data summaries, recruitment charts, and flags on missing or inconsistent records. Thereafter, a mobile randomization application built with React Native was developed for online and offline participant randomization, employing block randomization to ensure balanced allocation between study arms and enrollment continuity.</p><p><strong>Results: </strong>The automated QC system reduced data verification time from months to 1 hour, enabling real-time oversight and early error correction. The randomization application maintained balanced study arms and allowed uninterrupted participant enrollment during internet outages. These digital tools improved data completeness, reduced bias and human error, and increased trial efficiency across all study sites.</p><p><strong>Conclusion: </strong>Automation and offline functionality can significantly enhance data quality, efficiency, and integrity in clinical trials conducted in resource-constrained environments. The experience from this study demonstrates the value of combining automated QC and offline randomization tools to ensure robust and continuous study operations.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"17 2","pages":"365-373"},"PeriodicalIF":2.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13287932/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148007202","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}