ACI open最新文献

{"title":"Advancing Real-World Evidence Generation: Growth and Lessons Learned from the Early Years of Cosmos.","authors":"Meghan Howat, Steven Martell, Yasir Tarabichi, David C Kaelber, Selina S Chen, Harry Freedman","doi":"10.1055/a-2842-3407","DOIUrl":"10.1055/a-2842-3407","url":null,"abstract":"<p><strong>Objective: </strong>Cosmos is a vendor-facilitated platform created in collaboration with healthcare systems using electronic health records (EHRs) from Epic Systems Corporation. Participating organizations can use the platform to advance research and apply insights at the point of care. This manuscript outlines evolutions in the platform's infrastructure, growth of available data, and usage.</p><p><strong>Methods: </strong>Data from participating systems is sent via encrypted Health Level Seven Clinical Document Architecture to the Cosmos host at Epic Systems Corporation. Deduplicated data are stored in two relational Structured Query Language (SQL) databases, which can be accessed remotely. Aggregate counts from a limited dataset (LDS) are accessed through a no-code data visualization and analysis tool. Line-level data from an expert-determined de-identified dataset are accessed in a secure virtual computing environment. Data quality and user support frameworks facilitate a feedback loop improving data quality and researcher efficiency. Platform growth was measured as participating organization counts, data elements, and proportion of patient records with data spanning over 5 years. Medical literature was reviewed for peer-reviewed studies using Cosmos data.</p><p><strong>Results: </strong>Over 330 organizations across Canada, Lebanon, Saudi Arabia, and the United States submit data to Cosmos. The platform includes more than 300 million deduplicated patient records, 39% of which have over 5 years of clinical data. Ongoing expansion of data elements within Cosmos has allowed the platform to serve as the data source for over 100 peer-reviewed studies across multiple disciplines.</p><p><strong>Discussion: </strong>With its expanding size, tooling, and breadth of data elements, Cosmos may enable a wide range of study types. Cosmos remains subject to limitations such as variation in workflows, documentation error, and bias inherent to a population sourced from healthcare organizations using a single EHR vendor.</p><p><strong>Conclusion: </strong>Cosmos demonstrates a use case of vendor-facilitated collaboration to enable a broad spectrum of research.</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"10 1","pages":"e10-e23"},"PeriodicalIF":0.0,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13404524/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148610654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ASTHMAXcelED: A Patient-Facing Asthma Mobile Application with High User Acceptance and Improved Clinical Outcomes.","authors":"Carlo Lutz, Arvind Haran, Sonia Sakleshpur, Nicholas Santavicca, Eddie Irizzary, Andrew Williams, Joshua Kaiser, Shilpa Kolli, Sunit Jariwala, Benjamin W Friedman","doi":"10.1055/a-2812-0739","DOIUrl":"10.1055/a-2812-0739","url":null,"abstract":"<p><strong>Background: </strong>Well-designed mobile health (mHealth) applications can improve patient outcomes; however few clinically tested apps are developed with user-centric design. ASTHMAXcelED is a patient-facing mobile application designed for emergency department (ED) asthma patients.</p><p><strong>Objectives: </strong>We studied user acceptance of the application and compared asthma control and quality of life measures before and after use of ASTHMAXcelED.</p><p><strong>Methods: </strong>This prospective cohort study was conducted in two large urban EDs. Inclusion criteria were patients ≥18 years, English literacy, smartphone access, and discharge from the ED diagnosed with asthma exacerbation. ASTHMAXcelED was downloaded onto participants' phones upon discharge. Asthma symptom control was measured using the Asthma Control Test (ACT). User acceptance of and intention to use the application after the study period was measured using a Unified Theory of Acceptance and Use of Technology.</p><p><strong>Results: </strong>A total of 149 participants were enrolled in the study, of which 124 completed follow-up visits. The proportion of patients with good asthma control (ACT > 19) improved from 27% at baseline to 54% at 4-week follow-up, <i>p</i>  < 0.01. The rate of ED revisit was 7% and hospitalization for asthma was 0%. A total of 39% of patients indicated they intended to continue using ASTHMAXcelED in the next 6 months, whereas 5% did not.</p><p><strong>Conclusion: </strong>While using ASTHMAXcelED for 4 weeks, participant's asthma symptom control and quality of life scores improved. Their ED revisit rate and asthma hospitalization during the study period were low. ASTHMAXcelED may be an easily adopted mhealth education platform that can improve patient outcomes.</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"10 1","pages":"e1-e9"},"PeriodicalIF":0.0,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13404525/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148610739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patient's Information Needs and Understanding When Reading Anatomic Pathology Reports in Patient Portals.","authors":"Pavithra I Dissanayake, Jacqueline Moss, Eta S Berner, James J Cimino","doi":"10.1055/a-2731-4730","DOIUrl":"10.1055/a-2731-4730","url":null,"abstract":"<p><strong>Objective: </strong>To improve our understanding of the information needs of patients/caregivers when accessing anatomic pathology reports (APRs) via the patient portals (PPs) without further clarification by a clinician and to evaluate their opinion toward accessing APRs through a PP.</p><p><strong>Materials and methods: </strong>We conducted an exploratory mixed-method study using a questionnaire and a think-aloud protocol based on three mock APRs of gastrointestinal specimens. Participants verbalized the cognitive processes used to understand report content, discussed concerns/questions, underlined all unknown terms/phrases, and summarized each APR in their own words. Interviews were transcribed and thematic analysis was performed. APR summaries and term descriptions were assessed for accuracy. Finally, the underlined terms/phrases were grouped to create an ontology.</p><p><strong>Results: </strong>All participants ( <i>n</i>  = 15) had difficulty with most of the medical and technical terms in the APRs. Of the terms that participants said they were confident of knowing, only 48% were accurate and accuracy declined to 38% when guessed. The thematic analysis identified six main themes: information sources, interpreting the APR, emotional reactions, finding answers, opinion on accessing the APR on the portal, and preference for doctor-patient communication. The underlined terms were categorized into 12 domains creating the ontology of unknown terms in APRs.</p><p><strong>Conclusion: </strong>This study's findings suggest that patients, regardless of the diagnosis, have difficulties in understanding APRs, mainly due to complex medical terminology. Providing access to APRs via PPs alone is not sufficient to improve patient understanding. Further research is necessary to develop effective solutions that improve patients' understanding of these documents.</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"9 2","pages":"e65-e78"},"PeriodicalIF":0.0,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13393550/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148610682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing a Digital Public Health Intervention: Survey Implementation and Analysis in Washington State Using an Address-Based Sample.","authors":"Adam S Elder, Andrea R Molino, Rebecca A Hills, Debra Revere, Chris Baumgartner, Bryant T Karras, Janet G Baseman","doi":"10.1055/a-2695-8451","DOIUrl":"10.1055/a-2695-8451","url":null,"abstract":"<p><strong>Background: </strong>In November 2021, the Washington State Department of Health launched WA Verify, a quick-response (QR) code-based tool that allows users to share their coronavirus disease 2019 (COVID-19) vaccine status using a mobile phone.</p><p><strong>Objectives: </strong>This study aimed to gather an unbiased sample of Washington residents to collect information about their experiences and opinions on digital public health interventions, with a particular focus on WA Verify.</p><p><strong>Materials and methods: </strong>The WA Verify evaluation team designed and implemented a statewide survey using an address-based sample to assess respondents' knowledge, attitudes, and practices regarding COVID-19, WA Verify, and technology. To facilitate comparisons with known characteristics of the Washington State population, the survey included questions also found in state and national surveys and the U.S. Census. Weights based on demographic characteristics were developed to allow for weighted analyses in the future.</p><p><strong>Results: </strong>The unweighted demographic distribution of respondents mostly matched that of the Washington State population, with the largest discrepancy in education; 58.9% of respondents reported having a four-year degree or higher versus 37.3% of the state population. Across race, education level, age and gender, there were differences in reported experiences with and views on requirements to provide vaccination verification and awareness and use of WA Verify.</p><p><strong>Conclusion: </strong>Despite differences in experiences and views on WA Verify, there is broad interest in the tool, suggesting opportunities to expand its adoption. Data and information gathered with this survey, conducted using an address-based sample, provide a strong foundation for further analyses to inform public health interventions, particularly informatics-focused projects.</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"9 2","pages":"e54-e64"},"PeriodicalIF":0.0,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13393551/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148610582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Success and Challenges Querying OMOP-transformed EHR Data from Different Healthcare Organizations.","authors":"Colin T Purmal, Michael E Matheny, Lucila Ohno-Machado, Gary Tarasovsky, Rick Larsen, Mary A Whooley","doi":"10.1055/a-2668-3461","DOIUrl":"10.1055/a-2668-3461","url":null,"abstract":"<p><strong>Background: </strong>Adoption of a common data model (CDM), such as the Observational Medical Outcomes Partnership (OMOP) CDM, is a critical component of health information exchange, but the extent to which CDMs facilitate patient-level interoperability is unclear. We sought to determine the feasibility of using a CDM for health information exchange between two healthcare organizations.</p><p><strong>Materials and methods: </strong>We executed a single Structured Query Language (SQL) query on OMOP-transformed data from the University of California, San Francisco (UCSF) and the San Francisco VA Healthcare System for five patients.</p><p><strong>Results: </strong>The SQL query was successfully executed, and complementary healthcare information was obtained for five of five patients, but interoperability was limited by (1) lack of uniform patient identifiers, (2) use of different coding vocabularies, and (3) variations in mapping of source data to the CDM.</p><p><strong>Conclusion: </strong>Although transformation of EHR data to a CDM can facilitate health information exchange, our study suggests that patient-level interoperability of a CDM may require further alignment of both semantics and syntax.</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"9 2","pages":"e42-e53"},"PeriodicalIF":0.0,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13393552/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148610693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum: Agile User-Centered Design of a Clinical Research Project Management System in a Pediatric Health Institute.","authors":"Danny T Y Wu, Manhar Suharwardy, Aniruddhan Ramesh, Shubhra Gupta, Chen Xin, Ting Zhang, Ching-Tzu Tsai, Jenna Dawn, Michelle Faust, Adam Kushner","doi":"10.1055/a-2658-0791","DOIUrl":"10.1055/a-2658-0791","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1055/a-2625-1046.].</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"9 2","pages":"e41"},"PeriodicalIF":0.0,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13393545/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148610629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Agile User-Centered Design of a Clinical Research Project Management System in a Pediatric Health Institute.","authors":"Danny T Y Wu, Manhar Suharwardy, Aniruddhan Ramesh, Shubhra Gupta, Chen Xin, Ting Zhang, Ching-Tzu Tsai, Jenna Dawn, Michelle Faust, Adam Kushner","doi":"10.1055/a-2625-1046","DOIUrl":"10.1055/a-2625-1046","url":null,"abstract":"<p><strong>Background: </strong>Project management is crucial in academic hospitals due to the intensive involvement in research and clinical trials. Designing an application in a user-centered and workflow-compatible manner can prevent issues arising from hospital's limited resources and various risks (e.g., financial risk and ethical misconduct).</p><p><strong>Objectives: </strong>This study aimed to (1) develop a hybrid method combining user-centered design (UCD) and agile software development (ASD) principles, (2) apply the hybrid model to develop a Clinical Research Project Management System (CRPMS), (3) assess the usability of the CRPMS and iteratively refine the application.</p><p><strong>Materials and methods: </strong>A CRPMS was developed following the UCD and ASD principles and supported by a research core in a pediatric heart institute. In Phase 0, semi-structured interviews were conducted to understand processes and bottlenecks. In Phase 1, the project management and budgeting sections of the CRPMS were simultaneously developed. In Phase 2, the Principal Investigator dashboard and the intake section of the CRPMS were developed. Usability evaluation metrics included the System Usability Scale (SUS), Single Ease Question, and severity scores.</p><p><strong>Results: </strong>In Phase 1, the average SUS score was 88.65. There were 126 usability issues and 68 were considered high severity due to the SUS score cutoff (>1.5). In Phase 2, the average SUS score was 87.1. All of the 71 usability issues were addressed during the iterative refinements.</p><p><strong>Conclusion: </strong>A workflow-compatible and highly user-friendly CRPMS was developed by employing a hybrid Agile UCD model. Future work includes continuing development and expanding the CRPMS within and outside the institute.</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"9 2","pages":"e30-e40"},"PeriodicalIF":0.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13393553/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148610402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum: An Online Tool for Correcting Performance Measures of Electronic Phenotyping Algorithms for Verification Bias.","authors":"Ajay Bhasin, Suzette J Bielinski, Abel N Kho, Nicholas B Larson, Laura Rasmussen-Torvik","doi":"10.1055/s-0045-1809611","DOIUrl":"10.1055/s-0045-1809611","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1055/a-2402-5937.].</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"9 1","pages":"e29"},"PeriodicalIF":0.0,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13393549/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148610360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human-Centered Design and Iterative Refinement of Tools and Methods to Implement a Surveillance and Risk Prediction System for Clinical Deterioration in Ambulatory Cancer Care.","authors":"Daniel J France, Paromita Nath, Jason Slagle, Shilo Anders, Megan Salwei, Timothy Vogus, Hannah Slater, Carrie Reale, Laurie Novak, Lori-Anne Parker-Danley, Zachary Kohutek, Rajiv Agarwal, Joyce Harris, Barbara Yudiskas, Ralph Conwill, Terrell Smith, Evan Rhodes, Emma Schremp, Erin A Gillaspie, Adam Wright, Robert E Freundlich, Ryan Myles, Janelle Faiman, Sankaran Mahadevan, Matthew Weinger","doi":"10.1055/a-2437-9977","DOIUrl":"10.1055/a-2437-9977","url":null,"abstract":"<p><p><b>Background</b>  A common cause of preventable harm is the failure to detect and appropriately respond to clinical deterioration. Timely intervention is needed, particularly in medically complex patients, to mitigate the effects of adverse events, disease progression, and medical error. This challenging problem requires clinical surveillance, early recognition, timely notification of the appropriate clinicians, and effective intervention. <b>Objectives</b>  We determined the feasibility of designing, developing, and implementing the tools and processes to create a surveillance-and-risk prediction system to detect clinical deterioration in cancer outpatients. <b>Methods</b>  We used systems engineering and iterative human-centered design to develop a functional prototype of a surveillance-and-risk prediction system. The system includes passive surveillance involving wearable sensors, active surveillance involving patient event and symptom reporting as well as extraction of selected patient data from the electronic health record (EHR), a predictive model, and communication of estimated risk to clinicians. System usability was evaluated using patient and clinician interviews and clinician ratings using the System Usability Scale (SUS). <b>Results</b>  Fifty of 71 recruited patients enrolled in the feasibility study. Patient-reported outcome measures and clinical data extracted from the EHR were the best predictors of a patient's 7-day risk of experiencing unplanned treatment events (UTEs, i.e., emergency room visits, hospital admissions, or major treatment changes). Deep learning neural network models using these predictors demonstrated modest performance in predicting 7-day UTE risk (PROMS, F-measure: 0.900, area under the receiver operating characteristic curve [AUC-ROC]: 0.983; clinical data from EHR F-measure: 0.625, AUC-ROC: 0.983). Patient risk scores were communicated to clinicians using a risk communication prototype rated favorably by clinicians with a SUS score of 76 out of 100 (median = 80; range: 60-85). <b>Conclusion</b>  We demonstrate the feasibility of a surveillance-and-risk prediction system for detecting and reporting clinical deterioration in cancer outpatients. Future research is needed to fully implement and evaluate system adoption and effectiveness under different clinical situations.</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"9 1","pages":"e18-e28"},"PeriodicalIF":0.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13390218/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148610352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How do Clinicians Use Electronic Health Records for Respiratory Support Decisions? A Qualitative Study in Critical Care.","authors":"Tianyi Zhang, Jarrod Mosier, Vignesh Subbian","doi":"10.1055/a-2521-2557","DOIUrl":"10.1055/a-2521-2557","url":null,"abstract":"<p><p><b>Objectives</b>  Selecting appropriate respiratory support in critical care is complex, and some decisions require information that may be unknown when the treatment assignment is necessary. Digital technologies such as electronic health records (EHR) are essential components in critical care medicine to support respiratory support care delivery and management of patients with respiratory failure. However, there are limited studies on EHR use that enable clinical decisions related to respiratory support. The objective of this study is to understand how clinicians use EHRs for their decision-making related to respiratory support in intensive care units (ICUs). <b>Methods</b>  Using a socio-technical systems approach, we conducted nine observations with nine different care teams for 35 hours at two ICUs within a large academic hospital system. We created a journey map to illustrate clinicians' respiratory support decision-making processes. We identified barriers related to decision-making processes within the ICU socio-technical work context and characterized them based on macro-cognitive functions to derive themes that can capture the decision-making patterns associated with EHR use. <b>Results</b>  Our analysis identified three overarching themes that represent clinicians' use of EHR for their respiratory support decisions: (1) fragmented information and tasks for individual sensemaking; (2) EHR workarounds for collaborative decision-making; and (3) interruptive order entry and order execution. These three themes represent three major sequential stages (i.e., before, during, and after morning rounds) related to clinicians' respiratory support decision-making processes, and their interaction with EHR significantly varies between stages. <b>Conclusion</b>  Our findings reflected different EHR use patterns before, during, and after morning rounds for decision-making related to respiratory support. These findings indicated potential opportunities for diagnostic clinical decision support (CDS) to facilitate respiratory support decisions.</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"9 1","pages":"e9-e17"},"PeriodicalIF":0.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13393548/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148610350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}