Applied Clinical Informatics最新文献

{"title":"Collection of Patient-Reported Outcome Measures in Rural and Underserved Populations.","authors":"Andrea Cheville, Crystal L Patil, Andrew D Boyd, Leslie J Crofford, Dana Dailey, Victoria de Martelly, Guilherme Del Fiol, Miriam O Ezenwa, Keturah R Faurot, Mitch Knisely, Kaitlyn R McLeod, Natalia E Morone, Emily O'Brien, Rosa M Gonzalez-Guarda, Kathleen A Sluka, Karen Staman, Anne Thackeray, Christina K Zigler, Judith M Schlaeger","doi":"10.1055/a-2462-8699","DOIUrl":"10.1055/a-2462-8699","url":null,"abstract":"<p><strong>Background: </strong> The NIH Pragmatic Trials Collaboratory supports the design and conduct of 31 embedded pragmatic clinical trials, and many of these trials use patient-reported outcome measures (PROMs) to provide valuable information about the patients' health and wellness. Often these trials enroll medically underserved patients, including people with incomes below the federal poverty threshold, racial or ethnic minority groups, or rural or frontier communities.</p><p><strong>Objectives: </strong> In this series of trial case reports, we provide lessons learned about collecting PROMs in these populations. Unbiased collection of PROM data is critical to increase the generalizability of trial outcomes and to address health inequities. Use of electronic health records (EHRs) and other digital modes of PROM administration has gained traction. However, engagement with these modes is often low among populations prone to disparity due to lower digital proficiency, device access, and uptake of EHR portals and web interfaces.</p><p><strong>Methods: </strong> To maximize the completeness and representativeness of their trial outcome data, study teams tested a range of strategies to improve PROM response rates with emphasis on disparities prone and underserved patient groups. This manuscript describes the approaches, their implementation, and the targeted populations.</p><p><strong>Conclusion: </strong> Optimized PROM collection required hybrid approaches with multiple outreach modes, high-touch methods, creativity in promoting digital uptake, multimodal participant engagement, and text messaging.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"259-266"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11922614/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142605082","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":"Validation of an Algorithm to Classify Urine Cultures in Family Medicine.","authors":"Jack Zhang, Rachael Morkem, Akshay Rajaram","doi":"10.1055/a-2499-4207","DOIUrl":"https://doi.org/10.1055/a-2499-4207","url":null,"abstract":"<p><strong>Objectives: </strong> Automation of test follow-up offers potential reductions in workload for clinicians. The primary objective of the study was to evaluate the performance of <i>MicrobEx</i>, a regular expression-based algorithm in classifying urine culture reports in primary care.</p><p><strong>Methods: </strong> A retrospective validation of <i>MicrobEx</i> was performed using urine culture reports abstracted from a single academic family health team. <i>MicrobEx</i> classifications were compared with labels assigned manually by a human reviewer. Measures of diagnostic performance were calculated.</p><p><strong>Results: </strong> <i>MicrobEx</i> achieved 95.3% accuracy, 88.6% sensitivity, and 100% specificity in classifying 1,999 urine culture reports.</p><p><strong>Conclusion: </strong> The accuracy of <i>MicrobEx</i> was comparable to its performance in the original development and validation study by Eickelberg. Additional work is required to explore and improve the accuracy of <i>MicrobEx</i> and assess its performance across primary care settings and with more complex urine culture reports.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 2","pages":"357-361"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12020491/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144042721","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":"Creation of an Interactive Dashboard to Facilitate Early Detection of Cardiac Amyloidosis in African American Veterans.","authors":"Hamza Ghannam, Vikram Singh, Alberta L Warner, Ariel Powell, Ramona Gelzer Bell, Kevin Chow, Kimberly D Braswell, Rene Hearns, Vinod Aggarwal, Celina Roy, Douglas Stoehr, Jenice Guzman-Clark, Sandesh Dev","doi":"10.1055/a-2513-9400","DOIUrl":"10.1055/a-2513-9400","url":null,"abstract":"<p><strong>Background: </strong> Cardiac amyloidosis (CA) is an underdiagnosed cause of heart failure (HF) that disproportionately impacts men of African descent. Without a standardized method of screening and scattered patient health information, clinicians must integrate data that spans multiple disease systems and is stored across the electronic health record.</p><p><strong>Objectives: </strong> The aim of this project was to create a dashboard to facilitate identification of high-risk African American (AA) veterans who would benefit from CA screening tests. This paper described the development of the dashboard and identified barriers and opportunities in dashboard development.</p><p><strong>Methods: </strong> Three Veterans Affairs (VA) health systems participated in this project. Microsoft Structured Query Language (SQL) Report Builder was utilized to create an interactive dashboard that refreshes daily through stored procedures using SQL Server Integration Services and the SQL Server Job Agent. Inclusion criteria included AA patients less than 90 years old with a history of HF. The 2023 American College of Cardiology/American Heart Association consensus statement on diagnosis and treatment of transthyretin CA was the source of evidence in creating the inclusion criteria and parameters of interest.</p><p><strong>Results: </strong> The final dashboard contained 1,732 HF patients who met inclusion criteria, of which 949 (55%) were identified as high risk. We faced several challenges in this project, including time required for dashboard development, limited team experience in specifying dashboard requirements, identifying informatics counterparts at all sites, and standardizing data across three VA hospitals.</p><p><strong>Conclusion: </strong> In this clinical improvement project, we created a dashboard that identifies AA veterans with HF at risk for CA and that can help to mitigate the impact of CA on this population.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 2","pages":"429-438"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12077983/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144081471","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":"Effects of Aligning Residency Note Templates with CMS Evaluation and Management Documentation Requirements.","authors":"Sarah Stern, William C Lippert, Joseph Rigdon, Corey Obermiller, Lauren Witek, Matthew Anderson, Sneha Chebrolu, Adam Moses, Ted Xiao, Ajay Dharod, Joseph A Cristiano","doi":"10.1055/a-2480-4725","DOIUrl":"10.1055/a-2480-4725","url":null,"abstract":"<p><strong>Background: </strong> The Centers for Medicare & Medicaid Services (CMS) introduced changes in outpatient and inpatient evaluation and management (E/M) current procedural terminology (CPT) codes in 2021 and 2023, which were intended to streamline providers' clinical documentation.</p><p><strong>Objectives: </strong> This experiment aimed to study the effects of aligning inpatient and outpatient note templates with updated CMS guidelines on character length and documentation time per note at an internal medicine residency program in the southeastern United States.</p><p><strong>Methods: </strong> In April 2023, the Atrium Health Wake Forest Baptist Internal Medicine Residency Program's inpatient and outpatient note templates were updated according to the most recent CMS guidelines. A pre-post analysis of resident documentation time and length was conducted comparing notes written with the residency note templates from May 1, 2022, to August 31, 2022 (6,439 notes) to notes written with the residency note templates from May 1, 2023 to August 31, 2023 (8,828 notes). Interns were surveyed regarding their perceptions of the updated note templates.</p><p><strong>Results: </strong> After the note template updates, on adjusting for differing percentages of note types in the pre- and postperiods and accounting for multiple notes written by each resident, notes written with the residency note templates decreased by a mean character length of -882 characters (95% CI: -953, -811, <i>p</i> < 0.0001), while time spent writing notes did not significantly decrease. 17/17 respondents had favorable perceptions of the note templates.</p><p><strong>Conclusion: </strong> The internal medicine residency inpatient and outpatient note templates were updated to align with the most recent CMS E/M documentation requirement changes. These note template changes were associated with a meaningful decrease in documentation length but no overall significant reduction in mean documentation time when adjusted for differing percentages of note types in the pre- and postperoids and multiple notes written by the same author. The interns perceived the note template changes positively.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"275-282"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11945219/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142688948","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 Ambient Artificial Intelligence Notes on Provider Burnout.","authors":"Jason Misurac, Lindsey A Knake, James M Blum","doi":"10.1055/a-2461-4576","DOIUrl":"10.1055/a-2461-4576","url":null,"abstract":"<p><strong>Background: </strong> Healthcare provider burnout is a critical issue with significant implications for individual well-being, patient care, and healthcare system efficiency. Addressing burnout is essential for improving both provider well-being and the quality of patient care. Ambient artificial intelligence (AI) offers a novel approach to mitigating burnout by reducing the documentation burden through advanced speech recognition and natural language processing technologies that summarize the patient encounter into a clinical note to be reviewed by clinicians.</p><p><strong>Objective: </strong> To assess provider burnout and professional fulfillment associated with ambient AI technology during a pilot study, assessed using the Stanford Professional Fulfillment Index (PFI).</p><p><strong>Methods: </strong> A pre-post observational study was conducted at University of Iowa Health Care with 38 volunteer physicians and advanced practice providers. Participants used a commercial ambient AI tool over a 5-week trial in ambulatory environments. The AI tool transcribed patient-clinician conversations and generated preliminary clinical notes for review and entry into the electronic medical record. Burnout and professional fulfillment were assessed using the Stanford PFI at baseline and postintervention.</p><p><strong>Results: </strong> Pre- and posttest surveys were completed by 35/38 participants (92% survey completion rate). Results showed a significant reduction in burnout scores, with the median burnout score improving from 4.16 to 3.16 (<i>p</i> = 0.005), with validated Stanford PFI cut-off for overall burnout of 3.33. Burnout rates decreased from 69 to 43%. There was a notable improvement in interpersonal disengagement scores (3.6 vs. 2.5, <i>p</i> < 0.001), although work exhaustion scores did not change significantly. Professional fulfillment showed a modest, nonsignificant upward trend (6.1 vs. 6.5, <i>p</i> = 0.10).</p><p><strong>Conclusion: </strong> Ambient AI significantly reduces healthcare provider burnout and may enhance professional fulfillment. By alleviating documentation burdens, ambient AI can improve operational efficiency and provider well-being. These findings suggest that broader implementation of ambient AI could be a strategic intervention to combat burnout in healthcare settings.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"252-258"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11922620/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584760","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":"\"Be Really Careful about That\": Clinicians' Perceptions of an Intelligence Augmentation Tool for In-Hospital Deterioration Detection.","authors":"Jorie M Butler, Alyssa Doubleday, Usman Sattar, Mary Nies, Amanda Jeppesen, Melanie Wright, Thomas Reese, Kensaku Kawamoto, Guilherme Del Fiol, Karl Madaras-Kelly","doi":"10.1055/a-2505-7743","DOIUrl":"https://doi.org/10.1055/a-2505-7743","url":null,"abstract":"<p><strong>Objective: </strong> This study aimed to explore clinicians' perceptions and preferences of prototype intelligence augmentation (IA)-based visualization displays of in-hospital deterioration risk scores to inform future user interface design and implementation in clinical care.</p><p><strong>Methods: </strong> Prototype visualization displays incorporating an IA-based early warning score (EWS) for in-hospital deterioration were developed using cognitive theory and user-centered design principles. The displays featured variations of EWS and clinical data arranged in multipatient and single-patient views. Physician and nurse participants with at least 5 years of clinical experience were recruited to participate in semistructured qualitative interviews focused on understanding their experiences with IA and thoughts and preferences about the prototype displays. A thematic analysis was performed on these data.</p><p><strong>Results: </strong> Six themes were identified: (1) clinicians perceive IA as valuable with some caveats related to function and context; (2) individual differences among users influence preferences for customizability; (3) EWS are particularly useful for patient triage; (4) need for patient-centered contextual information to complement EWS; (5) perspectives related to understanding the EWS composition; and (6) design preferences that focus on clarity for interpretation of information.</p><p><strong>Conclusion: </strong> This study demonstrates clinicians' interest in and reservations about IA tools for clinical deterioration. The findings underscore the importance of understanding clinicians' cognitive needs and framing IA-generated tools as complementary to support them. A clinician focuses on high-level pattern matching information, and clinician's comments related to the power of consistency with typical views (e.g., this is \"how I usually see things\"), and questions regarding support of score interpretation (e.g., age of the data, questions about what the model \"knows\") suggest some of the challenges of IA implementation. The findings also identify design implications including the need for contextualizing the EWS for the patient's specific situation, incorporating trend information, and explaining the display purpose for clinical use.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 2","pages":"377-392"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12043375/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144057862","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 Honest Enterprise Research Broker: Facilitating Ethical, Efficient, and Secure Access to Health Data for Research.","authors":"Michelle S Keller, Pamela Roberts, Kevin Japardi, Joseph E Ebinger, Tod Davis, Joshua Pevnick, Sivathmika Chevvuri, Hudson Stuck, Shao-Chi Huang, Edward Kowalewski, Ashley Lin, Andrew Sanapanya, Alan Tomines, Spencer SooHoo","doi":"10.1055/a-2499-4090","DOIUrl":"https://doi.org/10.1055/a-2499-4090","url":null,"abstract":"<p><strong>Background: </strong> Health systems generate and store vast amounts of clinical data, requiring structured processes to ensure that secondary use of the data is available to researchers in an efficient, ethical, and secure manner.</p><p><strong>Objective: </strong> We describe a process to provide data to health system researchers at a large, multi-hospital health system that balances efficiency with security and ethics.</p><p><strong>Methods: </strong> The Honest Enterprise Research Broker (HERB) Committee has enacted a systematic process to deliver investigators requesting data, using pre-written SQL code, when possible, to increase efficiency, providing a suite of self-service tools for cohort size estimation, and assessing the security and privacy of data leaving the institution. We evaluated the number of extracts per year, the average time to delivery of the data extract, and user satisfaction with the process.</p><p><strong>Results: </strong> From 2018 to 2023, the HERB Committee completed 487 data extracts. The number of requests increased from 51 in 2018 to 121 in 2023. Even as the number of extracts increased, the number of hours per extract decreased from 12.5 in 2018 to 9 in 2023. User satisfaction surveys found a high degree of satisfaction with the process.</p><p><strong>Conclusion: </strong> Through a process of continuous improvement, the HERB Committee has developed an expedient process to support the research needs of a large academic multi-hospital health system.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 2","pages":"362-368"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12043374/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144002310","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":"Patient and Family Perceptions of Real-Time Access to Electronic Health Information: A Social Media Survey.","authors":"Caitlan S Pinotti, Rajdeep Pooni, Vincent Del Gaizo, Melanie Kohlheim, Emily Schildt, Alysha J Taxter, Tova Ronis","doi":"10.1055/a-2487-7414","DOIUrl":"https://doi.org/10.1055/a-2487-7414","url":null,"abstract":"<p><strong>Objective: </strong> This study seeks to understand pediatric rheumatology patients' and caregivers' utilization and perceptions of immediate access to their electronic health information (EHI) via patient portals.</p><p><strong>Methods: </strong> An anonymous, 23-question Qualtrics survey was distributed via social media to patients and families with pediatric rheumatic diseases. The survey link and Quick Response (QR) code were posted on disease-specific Facebook accounts. Descriptive statistics were used with a thematic content analysis performed on free-text responses.</p><p><strong>Results: </strong> The survey received 253 eligible responses. Nearly 48% of participants reported accessing their electronic patient portal >12 times in the last year, while only 0.4% (one respondent) reported accessing it zero times and 8% reported accessing it 1 to 2 times. Following a medical appointment, 45% reported regularly accessing their portal the same day as their appointment, 36% when they get an alert for new results, and 0.8% only in response to a healthcare provider message. About 98% use the patient portal to access laboratory results, 98% provider notes, 80% healthcare provider messages, 64% imaging results, 53% appointments, and 28% medications. Thematic content analysis found that respondents use the portal for coordination of care and to advocate for themselves or their child. The emotional impact of access to EHI without provider explanation was variable by respondent, with some reporting increased worry and some less worry. Many respondents (18%) found value in posting results to social media sites for help in interpretation.</p><p><strong>Conclusion: </strong> This study demonstrates pediatric rheumatology patients' and caregivers' strong portal engagement and expectation for immediate access to EHI through the patient portal. Although some did report that access to EHI without provider input can increase worry or anxiety, families perceive the patient portal as a tool for self-advocacy and engagement in care, leading to a stronger sense of their role as a member of the care team.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 2","pages":"327-336"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12020537/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144038886","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":"Managing the Transition from Tradition to Innovation for the Heidelberg/Heilbronn Medical Informatics Master of Science Program.","authors":"Petra Knaup, Rolf Bendl, Urs Eisenmann, Mark Hastenteufel, Alexandra Reichenbach","doi":"10.1055/a-2482-9071","DOIUrl":"10.1055/a-2482-9071","url":null,"abstract":"<p><strong>Background: </strong> To keep pace with the developments in the medical informatics field, the curriculum of the Heidelberg/Heilbronn Medical Informatics Master of Science program is continuously updated. In its latest revision we restructured our master's program to allow more flexibility to accommodate updates and include current topics and to enable students' choices.</p><p><strong>Objectives: </strong> This study aimed to present our new concepts for graduate medical informatics education, share our experiences, and provide insights into the perception of these concepts by advanced students and graduates.</p><p><strong>Methods: </strong> Our new curriculum consists of three core components: Areas of concentration that bundle elective courses in an important domain of medical informatics, a large catalog of elective courses, and introductory/alignment courses for students without a bachelor's degree in medical informatics. We conducted an online survey of graduates and students with at least 75 credits to assess their opinion on the program's effectiveness and attractiveness.</p><p><strong>Results: </strong> Mandatory courses include clinical medicine, project management, research, and practical training in biomedical informatics. Five areas of concentration bundle elective courses for 30 credits to provide a solid foundation in an important domain in medical informatics. These are bioinformatics, data science, computer-aided diagnosis and therapy systems, information management, and software engineering in medicine. The catalog of electives offers a total of 67 courses. About 75% of the courses are assigned to more than one area of concentration. Our survey demonstrates that the participants highly appreciate the flexibility of the electives and the opportunity to develop an area of expertise.</p><p><strong>Conclusion: </strong> Offering a high degree of flexibility to our students has motivated them to join our program and resulted in a high level of student satisfaction. By designing the curriculum with areas of concentration and providing an infrastructure that permits courses on emerging topics to be added easily to the curriculum, we were able to meet our students' expectations.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"305-313"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12020540/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142717357","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 Eldercare: Assessing Clinician's Perception of Linguistic Summaries in Health Monitoring Alert Systems.","authors":"Olabode B Ogundele, Butros M Dahu, Mutiyat Hameed, Mirna Becevic, Mihail Popescu","doi":"10.1055/a-2515-1630","DOIUrl":"https://doi.org/10.1055/a-2515-1630","url":null,"abstract":"<p><strong>Background: </strong> With an aging population preferring to age in place, there's a need for efficient health monitoring systems in eldercare. This study assesses the effectiveness of a linguistic summary alert system compared with a standard health alert system requiring data visualization interpretation by clinicians.</p><p><strong>Methods: </strong> A total of 110 older adults from seven facilities were monitored for health alerts throughout 2019. The study analyzed the frequency of email alert interactions and surveyed clinicians' perceptions before and after system-specific training.</p><p><strong>Results: </strong> Linguistic alerts demonstrated a significant reduction in the need for data interface consultation, as indicated by a lower click-through rate for email alerts. Clinicians expressed a strong preference for linguistic alerts, which streamlined their decision-making process. Despite this, the post-training survey interval and limited participant demographic constrained the findings' generalizability.</p><p><strong>Conclusion: </strong> The linguistic summary alert system was found to improve nursing efficiency by succinctly communicating health trends, thus alleviating workload. The system's potential to augment care by preempting health declines was acknowledged. To fully realize its benefits, further research is warranted to explore its direct impact on health outcomes and the factors influencing technology acceptance in eldercare.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 2","pages":"439-446"},"PeriodicalIF":2.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12077984/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144081445","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}