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Clinical Information Systems

Clinical Information Systems. HINF 371 - Medical Methodologies Session 5. Objective. To review types of information needed in decision making in a clinical setting. Reading.

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Clinical Information Systems

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  1. Clinical Information Systems HINF 371 - Medical Methodologies Session 5

  2. Objective • To review types of information needed in decision making in a clinical setting

  3. Reading • Geisbuhler A and Miller RA (2000) Chapter 14: Computer Assisted Clinical Decision Support, in Decision Making In Health Care: Theory, Psychology and Applications, Cambridge University Press, USA

  4. Decision Support Needs • 52 percent patient specific information • 23 percent general knowledge that could be found in a library, textbook, or Medline • 26 percent synthesis of patient information and medical knowledge

  5. Patient Information • Computerized patient information • Better availability • Better readability • Clear and well organized displays of informatin • Ability display trends and patterns • Ability to select and organize subsets of information • Physicians most interested in • Which drugs • What happened in last hospitalization • What are the lab results • What is the status during the last visit to the physicians

  6. Difficulties with Computerized Patient Information • Getting data into the system – physicians are not good at it • Transcription and interpretations of patients records • Voice recognition • Provision of immediate feedback as data entered • Getting information out of the system • Difficulties in implementation • Busy care providers are reluctant to use systems that slow their work • 25percent of difficulties are technology related • 75 percent of difficulties are caused by inadequate social engineering/change management

  7. General Knowledge • Ability to perform literature searches using Medline • Improved decisions • Reduce costs and length of stay • Other sources of information • Textbooks • Full-text journals • Practice guidelines • Printable educational material for patients • Drug information database

  8. General Knowledge • Local policy and procedures • Formalized policy and procedures • Operational rules • Functioning of institution • How to apply and break rules • Resource inventories, operating hours, names of people, turn around times for lab tests, etc.

  9. General Knowledge • Many medical errors are results of intrinsic limits in physician’s ability to process ongoing events • Attention focusing tools • Drug interactions (can be done through EMR or Order Entry) • Reminders for tests, follow-ups, information transfer, etc. • Results of past tests • Ranges of normal and likelihood of normal for given tests

  10. Patient Specific Support • Diagnostic decision support systems • Clinical algorithms – BC Nurseline or Healthwise http://bchealthguide.org/kbaltindex.asp • Predictive Tools http://groups.csail.mit.edu/medg/projects/hdp/hdp-intro-tab.html

  11. Patient Specific Support • Clinical Algorithms • Problems of scalability • Inability to deal with uncertainty or incorrectness inherent in the nature of clinical data • Better used in non-intersecting subsets • Predictive tools • How representative are the patients who were used in developing a given predictive tool • Which patients are likely to be misclassified and subjected to unnecessary interventions • How severe are the adverse effects that occur in patients receiving unnecessary interventions • How integrated the system to the workflow of physicians within the architecture of clinical information systems

  12. The clinical significance of a computer based decision support tool resides in the ability to augment the native skills of the physician during clinical practice, not its function in isolation as an “omniscient oracle” Miller 1996

  13. Is Medicine a science or an art? Discussion

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