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Medical Algorithms. Companion Books (publisher: Springer). Motivations. Accomplishments so far. Typical web-form algorithm. Most algorithms are Excel spreadsheets but there are 400 web-forms. Benefits of Medical Algorithms. Contact. www.medal.org , www.medicalalgorithms.com.
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Medical Algorithms Companion Books (publisher: Springer) Motivations Accomplishments so far Typical web-form algorithm Most algorithms are Excel spreadsheets but there are 400 web-forms Benefits of Medical Algorithms Contact www.medal.org, www.medicalalgorithms.com Future Work Registered Users Profile by Profession More than 12,000 algorithms in 45 medical subject areas Each Algorithm has a Documentation page with references Acknowledgements The Medical Algorithms Project: A Web-based Resource for Medical Education John R Svirbely, MDa, M. Sriram Iyengar, PhDb, Jack W Smith, MD, PhDb a TriHealth, Cincinnati, bSchool of Health Information Sciences, Univ of Texas, Houston • “A step-by-step procedure for solving a problem or accomplishing some end especially by a computer” • Any computation, formula, survey, or look-up table useful in healthcare • Amenable to numerous representations including spreadsheets, interactive web-forms • Numerous algorithms (estimated at about 50,000) in health care, but most practitioners use only a small subset routinely • APGAR, BMI, Apache, Glasgow Coma scale • Algorithms would be more widely used if they were readily available in a practical and computable format to clinicians, educators and researchers • A centralized, free repository of automated medical algorithms would be beneficial • MEDAL, www.medal.org is a web-based repository containing documentation, spreadsheets, and online web-forms. Currently 10 other titles are being prepared • Medical Education • Assist teachers in demonstrating principles of diagnosis and disease management • Develop drill-and-practice tools • Centralized resource for medical knowledge • Help students to gain in-depth understanding of clinical conditions by varying inputs to algorithms and analyzing changes in results • Research • Objective criteria for disease states & progressions • Assessments of treatment effectiveness • Interpretation, analysis, documentation of clinical trials • Clinical Practice • Enhance standardization, automation, and documentation of care • Can be made available at point-of-care for decision support purposes • Potentially reduce medical errors • Supports evidence-based medicine • Versions for Hand-held devices and point-of-care • Integration with Electronic Medical Records • Customization and localization (multiple languages) • No. 1 in web search for ‘Medical algorithms” and “algorithmic medicine” • In use worldwide (> 200 countries); majority of users from USA, UK, Western Europe • Seamless (non-login) access from US Veterans Admin. Hospitals • Collaboration with Springer-Verlag in developing companion pocket-guides • 100,803 registered users as of August 25, 2008 M. Sriram Iyengar, PhD, m.sriram.iyengar@uth.tmc.edu • Asst. Professor, School of Health Information Sciences, University of Texas Health Science Center at Houston • Informatics Research Scientist, Medical Informatics and Health Care Systems, NASA JSC, Houston, TX The second author gratefully acknowledges continued support and encouragement by Kathy Johnson-Throop, PhD, NASA Johnson Space Center, Houston, TX