IMIA

IMIA See the IMIA website http://www.imia.org or the IMIA News site http://news.imia.info for further upd

As an 'association of associations', IMIA acts as a bridging organisation, bringing together the constituent organisations and their members. IMIA provides leadership and expertise to the multidisciplinary, health focused community and to policy makers, to enable the transformation of healthcare in accord with the world-wide vision of improving the health of the world population.

26/05/2026

Applying User-Centered Design to Develop a Prescriber Feedback Tool in Acute Outpatient Care Settings at the Veterans Health Administration

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

Objectives 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).

Methods 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.

Results 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.

Conclusion 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.
https://www.thieme-connect.com/products/ejournals/abstract/10.1055/a-2866-4361

26/05/2026

Development and Application of a Nurse-Led Clinical Decision Support System for Safe Intravenous Medication Administration: A Nonrandomized Controlled Trial
Fuling Zhang, Wenjuan Yun, Lili Qin

Background Intravenous medication administration is a high-risk clinical procedure, where medication errors can lead to adverse consequences. Evidence-based clinical practice guidelines provide recommendations for the administration and monitoring of intravenous infusions. These guidelines are being increasingly integrated into clinical decision support systems (CDSS). The development of CDSS should emphasize nurses as core users, closely align with their clinical workflows, and ultimately create practical, user-friendly tools through thoughtful interface design, functional logic, and intelligent alert mechanisms.

Objectives We aimed to design and develop a clinical decision support tool based on the Data-Information-Knowledge-Wisdom model, which minimizes infusion errors by providing real-time alerts and standardizing workflows.

Methods A nonrandomized trial (May–July 2024) in a tertiary hospital compared traditional practices (n = 1,204) with a CDSS (n = 1,207) using 300 clinical rules and a personal digital assistant interface. Outcomes included error rates, severity, nurse satisfaction, and efficiency.

Results The CDSS reduced errors by 56.8% (16.69–7.21%, p < 0.001), eliminated severe errors (Level 3–4), improved nurse satisfaction (mean: 69.1/85 on a 17–85 scale), and reduced prescription processing time by 41%.

Conclusion This nurse-led CDSS enhances infusion safety and efficiency, offering a scalable solution. Artificial intelligence-driven predictive error detection could further optimize outcomes.
https://www.thieme-connect.com/products/ejournals/abstract/10.1055/a-2867-0618

26/05/2026

Assessment of Clinical Informatics Interest and the Impact of Advanced Electronic Health Record Training on Trainee Proficiency

Tiranun Rungvivatjarus. Weena Joshi, Mario Bialostozky

Background While electronic health records (EHRs) have been almost universally adopted in academic health care settings, physician training has lagged in efficient use and application. Especially for trainees, EHR training is often confined to basic EHR onboarding, with few opportunities to develop advanced skills. Moreover, literature on advanced EHR Training is sparse, and curricula remain largely unstandardized.

Objectives This study surveys pediatric fellows and medical students (MS) on their experience, attitude, and interest regarding clinical informatics. Additionally, we assessed the change in trainees reported EHR proficiency after receiving data literacy and self-service EHR data extraction training.

Methods This cross-sectional study surveyed pediatric trainees at a large tertiary pediatric health care system and first-year MS at the University of California, San Diego School of Medicine. An electronic survey was distributed between July and November 2022 to trainees and repeated 14 months after Epic SlicerDicer training. Descriptive statistics were used to analyze responses.

Results In total, 33/57 fellows and 93/419 MS (26.5% response rate) completed the survey. Interest in clinical informatics was reported by 53% of fellows and 23% of MS. Most respondents agreed informatics is important in clinical care, research, health care management, and continuing education. Many reported receiving insufficient advanced EHR training. Before training, 33% of fellows and 8% of MS reported proficiency in basic EHR accessing/navigating/editing skills. None of the fellows reported proficiency in data visualization/extraction. Following training, both MS and fellows reported increased proficiency in data visualization/extraction.

Conclusion Pediatric MS and fellows recognize the value of informatics in modern health care. Opportunities for advanced EHR training are limited for trainees and a single training session demonstrated improve proficiency. Broadening access to advanced EHR training across all stages of training could better equip future clinicians for real-world practice.
https://www.thieme-connect.com/products/ejournals/abstract/10.1055/a-2873-3262

26/05/2026

Enhancing Data Quality and Remote Accessibility in Clinical Trials: A SeroSelectTB Case Study in Ethiopia, Tanzania, and South Africa

Sasho Najdov, Jordancho Arsov, Jovan Davchev, Tamirat Assefa, Jemrath Bikombo, Debora Kajeguka, Anna Okunola, Welile Nwamba, Aleksandar Josifoski, Carol Holm-Hansen

Background 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.

Objective 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.

Methods 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.

Results 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.

Conclusion 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.
https://www.thieme-connect.com/products/ejournals/abstract/10.1055/a-2873-5092

26/05/2026

Ambient Artificial Intelligence Scribes in Pediatric Hematology—Oncology: Early Implementation of DAX Copilot

Molly Talman, Lamia Alam, Dara Mize, Yaa Kumah-Crystal, Carolynn Nall, Allison B. McCoy, Adam Wright, Laura Zahn, Jennifer Andrews

Background 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.

Objectives 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.

Methods 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.

Results 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%; p < 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.

Conclusion 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.
https://www.thieme-connect.com/products/ejournals/abstract/10.1055/a-2873-3894

18/05/2026

Variation in Measures of Electronic Health Record Use Outside Scheduled Hours: A Cross-Sectional Study of Academic Primary Care Physicians

Adam Rule, Jeffrey J. Baltus, Mark A. Micek, Christine A. Sinsky, Brian G. Arndt

Background The amount of time ambulatory physicians spend in an electronic health record (EHR) outside scheduled hours has grown in recent years and been linked to burnout. Measures provided by EHR vendors can help health systems track EHR use outside scheduled hours, but different measures track different periods of EHR use and none currently tracks all EHR use outside patient scheduled hours. How much vendor-derived measures differ from one another or from total EHR use outside patient scheduled hours is unclear.

Objective The objective of this study is to compare measures of EHR use outside scheduled hours.

Methods We collected data on 195 academic primary care physicians' EHR use and clinic schedules between February and July 2025. We measured each physician's EHR use outside patient scheduled hours (i.e., Work Outside of Work) and compared this investigator-derived measure to three vendor-derived measures of EHR use outside scheduled hours.

Results Study physicians averaged 6.0 hours of total EHR use and 2.9 hours of EHR use outside patient scheduled hours (i.e., Work Outside of Work) for every eight patient scheduled hours. The vendor-derived measures of Pajama Time, Time on Unscheduled Days plus Time Outside Scheduled Hours, and Time Outside of Clinic Hours averaged 0.9, 2.2, and 2.6 hours per eight patient scheduled hours, respectively.





Conclusion Almost half of study physicians' EHR use occurred outside patient scheduled hours. Common vendor-derived measures captured varying amounts of EHR use outside scheduled hours and all were less than total EHR use outside patient scheduled hours. This variation could affect calculations used to inform EHR training, program evaluation, or expectations for patient scheduled hours. Health systems should thus exercise caution when using vendor-derived measures to estimate total EHR use outside patient scheduled hours and continue to work with EHR vendors to develop scalable measures of EHR use that support diverse operational applications.





https://www.thieme-connect.com/products/ejournals/abstract/10.1055/a-2859-0028

18/05/2026

Cybersecurity in Healthcare: A Systematic Review and Narrative Analysis

Clemens S. Kruse, Diane Dolezel, Ramalingam Shanmugam

Background Cybersecurity attacks in healthcare have increased in number and severity over the last decade. Healthcare targets are ten times more valuable than financial targets because of the potential for fraudulent medical claims. Medical providers and administrators must ensure their IT professionals constantly scan the internal and external environment for techniques to prevent, detect, respond to, and report cyberattacks. This review provides a scan of the literature.

Objective This study aimed to review the literature for over 10 years for techniques for prevention, detection, response, and reporting of cyberattacks. An extended objective was to collect the effect on patient care that has been documented from cyberattacks.

Methods Following a published protocol and reporting standard, this systematic literature review queried four research databases for published works that described cybersecurity in healthcare. Grey literature was included.

Results Twenty-two articles provided 139 observations and 13 themes that described current techniques to secure the healthcare infrastructure. These articles stressed the importance of a trained workforce and a cyber-aware culture.

Conclusion IT professionals must adopt techniques that form proper organizational cyber resiliency and augment security through monitoring tools, standard IT maintenance and practice, encryption and data loss prevention, risk-based management, Artificial Intelligence, Explainable AI, active AI, network segmentation, governance and leadership, disabling legacy protocols and systems that cannot be updated, postevent analysis, and big data.

https://www.thieme-connect.com/products/ejournals/abstract/10.1055/a-2865-4206

18/05/2026

Nursing Informatics Competency and Effective Clinical Decision-Making among Nurses in Saudi Arabia

Sabirin Alruwaili, Mohammad R. Alosta, Anas H. Khalifeh, Zainab Albikawi , Elham H. Othman

Objectives The current study examined the relationship between nursing informatics competency (NIC) and perceived clinical decision-making (CDM) skills among nurses in Saudi Arabia.

Methods 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.

Results 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 (r = 0.734, p < 0.001). However, NIC was the sole statistically significant predictor (β = 0.7, p < 0.001) of their perceived level of CDM.

Conclusion 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.

https://www.thieme-connect.com/products/ejournals/abstract/10.1055/a-2863-4806

06/05/2026

Leveraging a Large Language Model to Generate Quality Improvement Feedback for Clinical Notes



Christopher J. Kim, Joseph Gelfinbein, Nihan Gencerliler, Nusrat Jahan, Jahnavi Udaikumar, Lauren M. Heery, Adam Goodman, Sarah Ng, Joel Attard, Sharmin Asha, Jesse Burk-Rafel, Benedict V. Guzman, Katherine A. Hochman, Paul A. Testa, Jonah Feldman



Background Poor documentation quality can significantly affect health care operations, but the feedback process for clinicians to improve clinical notes is time-consuming and often insufficient. Large language models (LLMs) such as Generative Pre-trained Transformer 4 (GPT-4) have the potential to streamline this process.



Objectives This study aimed to determine whether an LLM can generate feedback to improve the medical contingency and discharge planning (MCDP) component of clinical documentation that is non-inferior to feedback by physicians.



Methods A cross-sectional study of GPT-4 feedback and physician feedback on inpatient progress notes was conducted. A random sample of 64 inpatient progress notes identified by the validated artificial intelligence (AI) Audit Tool as having a low likelihood of containing MCDP was included from adult general medicine patients hospitalized at New York University Langone Health (NYULH) in December 2023. Both the GPT-4 model and attending physicians generated feedback on these inpatient progress notes. A/B testing was then conducted on the measures of understandability, usefulness, acceptability, and impartiality. Evaluations employed 5-point Likert scales that were converted to 10-point bidirectional interval scales for interpretability, ranging from −10 (human suggestions significantly better) to +10 (GPT-4 suggestions significantly better), with a non-inferiority threshold set to −1 for the primary endpoint.



Results Sixty-four inpatient progress notes were included, representing 55% female patients with a median age of 73 years. GPT-4 feedback was non-inferior to physician feedback in all measures: Understandability (mean, 1.27, 95% CI: 0.73–1.8, p < 0.001), usefulness (mean, 2.09, 95% CI: 1.27–2.91, p < 0.001), acceptability (mean, 2.07, 95% CI: 1.33–2.81, p < 0.001), and impartiality (mean, −0.20, 95% CI: −0.52 to 0.12, p < 0.001).



Conclusion This study shows that an LLM can be leveraged to generate note quality feedback that is non-inferior to expert clinician feedback.

https://www.thieme-connect.de/products/ejournals/abstract/10.1055/a-2851-0739

06/05/2026

A Novel Workflow for Artificial Intelligence-Enhanced Patient Messaging Services

Matthew R. Allen, Vijay M. Tiyyala, Karthik Ramesh, Nimit Desai, Job Shiach, Mark Dredze, John W. Ayers

Background Current artificial intelligence (AI) integration in patient messaging often relies on generating AI drafts for clinician review, yet this workflow has achieved limited effect.

Objective This study aimed to describe and evaluate a novel, clinician-first workflow for patient messaging where AI enhances a clinician-generated draft.

Methods Using 268 patient questions from public data, we compared physician-only responses, AI-only responses, and AI-enhanced responses.

Results Responses were ranked on overall preference and the CREATE TRUST framework. AI-enhanced responses were significantly preferred overall, ranking first in 38.8% of evaluations (average rank 1.69; p < 0.01), outperforming both AI-only (27.6%; 2.29) and physician-only (25.5%; 2.11) responses. AI-enhanced responses ranked highest for Understandable (44.5%) and Tailored (39.4%). AI-only responses ranked highest for Thorough (71.0%) and Empathic (69.8%), while physician-only responses ranked highest in Authentic (90.9%; all p < 0.01). Safety analysis identified consequential additions in 3.36% and omissions in 1.12% of AI-enhanced messages.

Conclusion A novel workflow—based on the Clinical Action Support framework—where AI enhances a clinician's draft may offer an improved approach to AI implementation in patient messaging services.
https://www.thieme-connect.de/products/ejournals/abstract/10.1055/a-2852-9026

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