Applied Clinical Informatics最新文献

{"title":"Effect of Tiered Implementation of Clinical Decision Support System for Acute Kidney Injury and Nephrotoxin Exposure in Cardiac Surgery Patients.","authors":"Christopher M Justice, Connor Nevin, Rebecca L Neely, Brian Dilcher, Nicole Kovacic-Scherrer, Heather Carter-Templeton, Aaron Ostrowski, Jacob Krafcheck, Gordon Smith, Paul McCarthy, Jami Pincavitch, Sandra Kane-Gill, Robert Freeman, John A Kellum, Roopa Kohli-Seth, Girish N Nadkarni, Khaled Shawwa, Ankit Sakhuja","doi":"10.1055/s-0044-1791822","DOIUrl":"10.1055/s-0044-1791822","url":null,"abstract":"<p><strong>Background: </strong> Nephrotoxin exposure may worsen kidney injury and impair kidney recovery if continued in patients with acute kidney injury (AKI).</p><p><strong>Objectives: </strong> This study aimed to determine if tiered implementation of a clinical decision support system (CDSS) would reduce nephrotoxin use in cardiac surgery patients with AKI.</p><p><strong>Methods: </strong> We assessed patients admitted to the cardiac surgery intensive care unit at a tertiary care center from January 2020 to December 2021, and August 2022 to September 2023. A passive electronic AKI alert was activated in July 2020, followed by an electronic nephrotoxin alert in March 2023. In this alert, active nephrotoxic medication orders resulted in a passive alert, whereas new orders were met with an interruptive alert. Primary outcome was discontinuation of nephrotoxic medications within 30 hours after AKI. Secondary outcomes included AKI-specific clinical actions, determined through modified Delphi process and patient-centered outcomes. We compared all outcomes across five separate eras, divided based on the tiered implementation of these alerts.</p><p><strong>Results: </strong> A total of 503 patients met inclusion criteria. Of 114 patients who received nephrotoxins before AKI, nephrotoxins were discontinued after AKI in 6 (25%) patients in pre AKI-alert era, 8 (33%) patients in post AKI-alert era, 7 (35%) patients in AKI-alert long-term follow up era, 7 (35%) patients in pre nephrotoxin-alert era, and 14 (54%) patients in post nephrotoxin-alert era (<i>p</i> = 0.047 for trend). Among AKI-specific consensus actions, we noted a decreased use of intravenous fluids, increased documentation of goal mean arterial pressure of 65 mm Hg or higher, and increased use of bedside point of care echocardiogram over time. Among exploratory clinical outcomes we found a decrease in proportion of stage III AKI, need for dialysis, and length of hospital stay over time.</p><p><strong>Conclusion: </strong> Tiered implementation of CDSS for recognition of AKI and nephrotoxin exposure resulted in a progressive improvement in the discontinuation of nephrotoxins.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 1","pages":"1-10"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11693401/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916021","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":"Discrepancies in Aggregate Patient Data between Two Sources with Data Originating from the Same Electronic Health Record: A Case Study.","authors":"Allen J Yiu, Graham Stephenson, Emilie Chow, Ryan O'Connell","doi":"10.1055/a-2441-3677","DOIUrl":"10.1055/a-2441-3677","url":null,"abstract":"<p><strong>Background: </strong> Data exploration in modern electronic health records (EHRs) is often aided by user-friendly graphical interfaces providing \"self-service\" tools for end users to extract data for quality improvement, patient safety, and research without prerequisite training in database querying. Other resources within the same institution, such as Honest Brokers, may extract data sourced from the same EHR but obtain different results leading to questions of data completeness and correctness.</p><p><strong>Objectives: </strong> Our objectives were to (1) examine the differences in aggregate output generated by a \"self-service\" graphical interface data extraction tool and our institution's clinical data warehouse (CDW), sourced from the same database, and (2) examine the causative factors that may have contributed to these differences.</p><p><strong>Methods: </strong> Aggregate demographic data of patients who received influenza vaccines at three static clinics and three drive-through clinics in similar locations between August 2020 and December 2020 was extracted separately from our institution's EHR data exploration tool and our CDW by our organization's Honest Brokers System. We reviewed the aggregate outputs, sliced by demographics and vaccination sites, to determine potential differences between the two outputs. We examined the underlying data model, identifying the source of each database.</p><p><strong>Results: </strong> We observed discrepancies in patient volumes between the two sources, with variations in demographic information, such as age, race, ethnicity, and primary language. These variations could potentially influence research outcomes and interpretations.</p><p><strong>Conclusion: </strong> This case study underscores the need for a thorough examination of data quality and the implementation of comprehensive user education to ensure accurate data extraction and interpretation. Enhancing data standardization and validation processes is crucial for supporting reliable research and informed decision-making, particularly if demographic data may be used to support targeted efforts for a specific population in research or quality improvement initiatives.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 1","pages":"137-144"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11821296/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143411325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effect of Electronic Health Record and Immunization Information System Interoperability on Medical Practice Vaccination Workflow.","authors":"Kevin J Dombkowski, Pooja N Patel, Hannah K Peng, Anne E Cowan","doi":"10.1055/a-2434-5112","DOIUrl":"10.1055/a-2434-5112","url":null,"abstract":"<p><strong>Background: </strong> Interoperability between electronic health records (EHR) and immunization information systems (IIS) may positively influence data quality, affecting timeliness, completeness, and accuracy of these data. However, the extent to which EHR/IIS interoperability may influence the day-to-day vaccination workflow and related recordkeeping tasks performed at medical practices is unclear.</p><p><strong>Objective: </strong> This study aimed to assess how EHR/IIS interoperability may influence the vaccination workflow at medical practices and to identify related impacts on clinical and administrative activities.</p><p><strong>Methods: </strong> We identified practices (family medicine, pediatrics, internal medicine, local health departments) from the Michigan Care Improvement Registry (MCIR), the statewide IIS in Michigan, representing each of the three HL7 interoperability levels (non-HL7, unidirectional, bidirectional). We conducted semi-structured interviews to assess how practices interact with the MCIR throughout the vaccination workflow. Transcripts were reviewed and coded to characterize practices' use of EHRs, MCIR, and other related technologies across the vaccination workflow.</p><p><strong>Results: </strong> Practices completed Phase 1 (<i>n</i> = 45) and Phase 2 (<i>n</i> = 42) interviews, representing a range of medical specialties, geographic locations, and sizes. HL7 connectivity expanded among the participating practices; by the conclusion of the study, all practices had initiated at least unidirectional HL7 capability. Providers and staff relied heavily upon both their EHRs and MCIR throughout a wide range of vaccination-related activities. Most practices relied on MCIR as their primary source of vaccination history information, and nearly all practices also reported use of paper forms, documentation, and other summaries throughout the vaccination workflow.</p><p><strong>Conclusion: </strong> Practices employed both their EHRs and IIS throughout the entire vaccination workflow, although the use of each relied heavily on paper-based processes. While benefits of adopting EHR/IIS interoperability were reported by practices, this may require staff to learn and implement new workflow processes that can be time consuming and may introduce new challenges.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 1","pages":"101-110"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11798654/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143257053","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":"A Human-Centered Approach for Designing a Social Care Referral Platform.","authors":"David Haynes, Pengxu Cheng, Megan Weaver, Helen Parsons, Pinar Karaca-Mandic","doi":"10.1055/a-2425-8731","DOIUrl":"10.1055/a-2425-8731","url":null,"abstract":"<p><strong>Background: </strong> Health Information Technology is increasingly being used to help providers connect patients with community resources to meet health-related social needs (e.g., food, housing, transportation). Research is needed to design efficient, simple, and engaging interfaces during a sensitive process that involves multiple stakeholders. Research is also needed to understand the roles, expectations, barriers, and facilitators these different stakeholders (i.e., patients, providers, and community-based organizations [CBOs]) face during this process.</p><p><strong>Objectives: </strong> We applied the human-centered design approach to develop a multi-interface social care referral platform. This approach allowed us to understand the needs of each stakeholder and address potential workflow concerns.</p><p><strong>Methods: </strong> This paper reports on the research team's understanding of the design process from 48 different user tests. We conducted three rounds of user testing on an interactive prototype(s) and adapted the prototype after each round.</p><p><strong>Results: </strong> Our results summarize several key findings useful for patients, clinical teams, and staff of CBOs when designing a social care referral platform. Our user testing highlighted that patient-facing interfaces offer tremendous opportunities to allow patients to be the leader of the social care referral process. CBOs have varying needs that must be addressed, and providing CBO staff with opportunities to connect with patients is critical. Finally, health care teams have more structured workflows. Integration within the electronic health record system provides opportunities for health care staff to support their patients more easily given these barriers.</p><p><strong>Conclusion: </strong> Our resulting, patient-centered platform allows patients to self-screen and self-refer to organizations that match their unmet needs.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"67-76"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11753861/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373318","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":"Design and Implementation of Tabletop Cybersecurity Simulation for Health Informatics Graduate Students.","authors":"Erin E Blanchard, Sue S Feldman, Marjorie Lee White, Ryan Allen, Thad Phillips, Michelle R Brown","doi":"10.1055/s-0044-1790551","DOIUrl":"10.1055/s-0044-1790551","url":null,"abstract":"<p><strong>Background: </strong> Experiential learning through simulation allows students to apply didactic knowledge to real-world situations. Tabletop simulation allows for the exploration of a variety of topics, including cybersecurity in health care. Due to its low frequency, yet high-risk nature, simulation is a perfect educational modality to practice responding to a cybersecurity attack. As such, the authors designed and executed a tabletop cybersecurity simulation consisting of a prebriefing, four rounds of injects detailing potential cybersecurity breaches that students must address, and structured debriefings that included input from cybersecurity content experts. This simulation was performed in 2018, 2019, 2022, and 2023, during graduate Health Informatics (HI) students' residential visits.</p><p><strong>Objective: </strong> The simulation allowed opportunities for HI students to apply knowledge of cybersecurity principles to an unfolding tabletop simulation containing injects of scenarios they may encounter in the real world.</p><p><strong>Methods: </strong> Survey data were used to assess the students' perceptions of the simulation. Topics assessed included overall satisfaction, teamwork and communication, and length of the event. Additionally, in 2022 and 2023, data were collected on psychological safety and whether to include them in future HI residential visits.</p><p><strong>Results: </strong> Eighty-eight graduate HI students took part in the cybersecurity simulation over four annual residential visits. Most students were satisfied with the event, found it valuable, and could see it impacting their future practice as informaticists. Additionally, students indicated high levels of psychological safety. Multiple students requested that additional simulations be incorporated into the curriculum.</p><p><strong>Conclusion: </strong> A tabletop cybersecurity simulation was utilized to allow HI students the ability to apply knowledge related to cybersecurity breaches to real-world examples. The simulation's best practices of prebriefing, psychological safety, and structured debriefing with expert feedback were emphasized in the simulation's design and implementation. Students found the simulation valuable and worth including in the curriculum.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"15 5","pages":"921-927"},"PeriodicalIF":2.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540471/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142591736","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":"Impact of a Disease-Focused Electronic Health Record Dashboard on Clinical Staff Efficiency in Previsit Patient Review in an Ambulatory Pulmonary Hypertension Care Clinic.","authors":"Tapendra Koirala, Charles D Burger, Rajeev Chaudhry, Patricia Benitez, Heather A Heaton, Nilaa Gopikrishnan, Scott A Helgeson","doi":"10.1055/s-0044-1790552","DOIUrl":"10.1055/s-0044-1790552","url":null,"abstract":"<p><strong>Objectives: </strong> We aimed to improve the operational efficiency of clinical staff, including physicians and allied health professionals, in the previsit review of patients by implementing a disease-focused dashboard within the electronic health record system. The dashboard was tailored to the unique requirements of the clinic and patient population.</p><p><strong>Methods: </strong> A prospective quality improvement study was conducted at an accredited pulmonary hypertension (PH) clinic within a large academic center, staffed by two full time physicians and two allied health professionals. Physicians' review time before and after implementation of the PH dashboard was measured using activity log data derived from an EHR database. The review time for clinic staff was measured through direct observation, with review method-either conventional or newly implemented dashboard-randomly assigned.</p><p><strong>Results: </strong> Over the study period, the median number of patients reviewed by physicians per day increased slightly from 5.50 (interquartile range [IQR]: 1.35) before to 5.95 (IQR: 0.85) after the implementation of the PH dashboard (<i>p</i> = 0.535). The median review time for the physicians decreased with the use of the dashboard, from 7.0 minutes (IQR: 1.55) to 4.95 minutes (IQR: 1.35; <i>p</i> < 0.001). Based on the observed timing of 70 patient encounters among allied clinical staff, no significant difference was found for experienced members (4.65 minutes [IQR: 2.02] vs. 4.43 minutes [IQR: 0.69], <i>p</i> = 0.752), while inexperienced staff saw a significant reduction in review time after familiarization with the dashboard (5.06 minutes [IQR: 1.51] vs. 4.12 minutes [IQR: 1.99], <i>p</i> = 0.034). Subjective feedback highlighted the need for further optimization of the dashboard to align with the workflow of allied health staff to achieve similar efficiency benefits.</p><p><strong>Conclusion: </strong> A disease-focused dashboard significantly reduced physician previsit review time while that for clinic staff remained unchanged. Validation studies are necessary with our patient populations to explore further qualitative impacts on patient care efficiency and long-term benefits on workflow.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"15 5","pages":"928-938"},"PeriodicalIF":2.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540472/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142591738","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":"Realizing the Full Potential of Clinical Decision Support: Translating Usability Testing into Routine Practice in Health Care Operations.","authors":"Swaminathan Kandaswamy, Herbert Williams, Sarah Anne Thompson, Thomas Elijah Dawson, Naveen Muthu, Evan William Orenstein","doi":"10.1055/a-2404-2129","DOIUrl":"10.1055/a-2404-2129","url":null,"abstract":"<p><strong>Background: </strong> Clinical Decision Support (CDS) tools have a mixed record of effectiveness, often due to inadequate alignment with clinical workflows and poor usability. While there is a consensus that usability testing methods address these issues, in practice, usability testing is generally only used for selected projects (such as funded research studies). There is a critical need for CDS operations to apply usability testing to all CDS implementations.</p><p><strong>Objectives: </strong> In this State of the Art/Best Practice paper, we share challenges with scaling usability in health care operations and alternative methods and CDS governance structures to enable usability testing as a routine practice.</p><p><strong>Methods: </strong> We coalesce our experience and results of applying <i>guerilla in situ</i> usability testing to over 20 projects in a 1-year period with the proposed solution.</p><p><strong>Results: </strong> We demonstrate the feasibility of adopting \"<i>guerilla in situ</i> usability testing\" in operations and their effectiveness in incorporating user feedback and improving design.</p><p><strong>Conclusion: </strong> Although some methodological rigor was relaxed to accommodate operational speed, the benefits outweighed the limitations. Broader adoption of usability testing may transform CDS implementation and improve health outcomes.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"1039-1048"},"PeriodicalIF":2.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11617071/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142082328","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":"ChatGPT Performs Worse on USMLE-Style Ethics Questions Compared to Medical Knowledge Questions.","authors":"Tessa Danehy, Jessica Hecht, Sabrina Kentis, Clyde B Schechter, Sunit P Jariwala","doi":"10.1055/a-2405-0138","DOIUrl":"10.1055/a-2405-0138","url":null,"abstract":"<p><strong>Objectives: </strong> The main objective of this study is to evaluate the ability of the Large Language Model Chat Generative Pre-Trained Transformer (ChatGPT) to accurately answer the United States Medical Licensing Examination (USMLE) board-style medical ethics questions compared to medical knowledge-based questions. This study has the additional objectives of comparing the overall accuracy of GPT-3.5 to GPT-4 and assessing the variability of responses given by each version.</p><p><strong>Methods: </strong> Using AMBOSS, a third-party USMLE Step Exam test prep service, we selected one group of 27 medical ethics questions and a second group of 27 medical knowledge questions matched on question difficulty for medical students. We ran 30 trials asking these questions on GPT-3.5 and GPT-4 and recorded the output. A random-effects linear probability regression model evaluated accuracy and a Shannon entropy calculation evaluated response variation.</p><p><strong>Results: </strong> Both versions of ChatGPT demonstrated worse performance on medical ethics questions compared to medical knowledge questions. GPT-4 performed 18% points (<i>p</i> < 0.05) worse on medical ethics questions compared to medical knowledge questions and GPT-3.5 performed 7% points (<i>p</i> = 0.41) worse. GPT-4 outperformed GPT-3.5 by 22% points (<i>p</i> < 0.001) on medical ethics and 33% points (<i>p</i> < 0.001) on medical knowledge. GPT-4 also exhibited an overall lower Shannon entropy for medical ethics and medical knowledge questions (0.21 and 0.11, respectively) than GPT-3.5 (0.59 and 0.55, respectively) which indicates lower variability in response.</p><p><strong>Conclusion: </strong> Both versions of ChatGPT performed more poorly on medical ethics questions compared to medical knowledge questions. GPT-4 significantly outperformed GPT-3.5 on overall accuracy and exhibited a significantly lower response variability in answer choices. This underscores the need for ongoing assessment of ChatGPT versions for medical education.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"1049-1055"},"PeriodicalIF":2.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11617073/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142113864","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":"Coverage of Physical Therapy Assessments in the Observational Medical Outcomes Partnership Common Data Model.","authors":"Margaret A French, Paul Hartman, Heather A Hayes, Leah Ling, John Magel, Anne Thackeray","doi":"10.1055/a-2401-3688","DOIUrl":"10.1055/a-2401-3688","url":null,"abstract":"<p><strong>Background: </strong> High-value care aims to enhance meaningful patient outcomes while reducing costs and is accelerated by curating data across health care systems through common data models (CDMs), such as Observational Medical Outcomes Partnership (OMOP). Meaningful patient outcomes, such as physical function, must be included in these CDMs. However, the extent to which physical therapy assessments are covered in the OMOP CDM is unclear.</p><p><strong>Objective: </strong>This study aimed to examine the extent to which physical therapy assessments used in neurologic and orthopaedic conditions are in the OMOP CDM.</p><p><strong>Methods: </strong> After identifying assessments, two reviewer teams independently mapped the neurologic and orthopaedic assessments into the OMOP CDM. Agreement within the reviewer team was assessed by the number of assessments mapped by both reviewers, one reviewer but not the other, or neither reviewer. The reviewer teams then reconciled disagreements, after which agreement and the average number of concept ID numbers per assessment were assessed.</p><p><strong>Results: </strong> Of the 81 neurologic assessments, 48.1% (39/81) were initially mapped by both reviewers, 9.9% (8/81) were mapped by one reviewer but not the other, and 42% (34/81) were unmapped. After reconciliation, 46.9% (38/81) were mapped by both reviewers and 53.1% (43/81) were unmapped. Of the 79 orthopaedic assessments, 46.8% (37/79) were initially mapped by both reviewers, 12.7% (10/79) were mapped by one reviewer but not the other, and 48.1% (38/79) were unmapped. After reconciliation, 48.1% (38/79) were mapped by both reviewers and 51.9% (41/79) were unmapped. Most assessments that were mapped had more than one concept ID number (2.2 ± 1.3 and 4.3 ± 4.4 concept IDs per neurologic and orthopaedic assessment, respectively).</p><p><strong>Conclusion: </strong> The OMOP CDM includes some physical therapy assessments recommended for use in neurologic and orthopaedic conditions but many have multiple concept IDs. Including more functional assessments in the OMOP CDM and creating guidelines for mapping would improve our ability to include functional data in large datasets.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"1003-1012"},"PeriodicalIF":2.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602249/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142037446","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":"Teaching Data Science through an Interactive, Hands-On Workshop with Clinically Relevant Case Studies.","authors":"Alvin D Jeffery, Patricia Sengstack","doi":"10.1055/a-2407-1272","DOIUrl":"10.1055/a-2407-1272","url":null,"abstract":"<p><strong>Background: </strong> In this case report, we describe the development of an innovative workshop to bridge the gap in data science education for practicing clinicians (and particularly nurses). In the workshop, we emphasize the core concepts of machine learning and predictive modeling to increase understanding among clinicians.</p><p><strong>Objectives: </strong> Addressing the limited exposure of health care providers to leverage and critique data science methods, this interactive workshop aims to provide clinicians with foundational knowledge in data science, enabling them to contribute effectively to teams focused on improving care quality.</p><p><strong>Methods: </strong> The workshop focuses on meaningful topics for clinicians, such as model performance evaluation and introduces machine learning through hands-on exercises using free, interactive python notebooks. Clinical case studies on sepsis recognition and opioid overdose death provide relatable contexts for applying data science concepts.</p><p><strong>Results: </strong> Positive feedback from over 300 participants across various settings highlights the workshop's effectiveness in making complex topics accessible to clinicians.</p><p><strong>Conclusion: </strong> Our approach prioritizes engaging content delivery and practical application over extensive programming instruction, aligning with adult learning principles. This initiative underscores the importance of equipping clinicians with data science knowledge to navigate today's data-driven health care landscape, offering a template for integrating data science education into health care informatics programs or continuing professional development.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":" ","pages":"1074-1079"},"PeriodicalIF":2.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11634532/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142113865","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}