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Survey of Medical Informatics

Survey of Medical Informatics. CS 493 – Fall 2004 October 4, 2004. Health Care Data Standards. Chapter 4: Patient Safety - Achieving a New Standard of Care. IOM Report. Knowledge Representation. Clinical Guideline Representation Model. Clinical Guidelines.

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Survey of Medical Informatics

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  1. Survey of Medical Informatics CS 493 – Fall 2004 October 4, 2004

  2. Health Care Data Standards Chapter 4: Patient Safety - Achieving a New Standard of Care. IOM Report

  3. Knowledge Representation Clinical Guideline Representation Model

  4. Clinical Guidelines • National Guideline Clearinghouse  contains 1,000 publicly accessible guidelines • http://www.guideline.gov/ • Box 4-2 pg. 159 • Comparison of these representative schemes • http://www.openclinical.org/gmmcomparison.html • http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=150359

  5. Guideline Interchange Format • Developed by InterMed Collaboratory – Harvard, Stanford and Columbia • Goals of GLIF • Encode clinicians requirements for decision making • Support verification and validation of guidelines • Support guideline dissemination and local adaptation • Support integration with clinical information systems

  6. Guide-line Expression Language, Object Oriented (GELLO) • Based on HL7 RIM model • Developed for GLIF • Syntax for querying EHR for relevant patient information

  7. Representation of Medical Literature • Need tools that will interface clinical decision support applications with published literature • NLM provides access to a large array of literature in medicine • MEDLINEplus  provides access to consumer friendly information sources • Cochrane Collaborations – to develop practice guidelines • Disease-specific registries • DailyMed database from NLM tracks medication information for consumers

  8. Establishing Comprehensive Patient Safety Programs Part II – Chapter 5: Patient Safety - Achieving a New Standard of Care. IOM Report

  9. A culture of patient safety • Delivery process designed to prevent failures • Organization commitment to detecting and analyzing patient injuries and near misses • Process that balances the need for reporting adverse events and the need to take disciplinary action

  10. Culture of patient safety • Shared beliefs and values • Recruitment and training with patient safety in mind • Organizational commitment to detecting patient injuries and near misses • Active surveillance based on real-time, interventional, data-based clinical triggers • Passive surveillance based on retrospective chart review • Making it easy for front-line workers and family members to report ADE and near misses • Appropriate protections and rewards for reporting near misses and injuries • Box 5-1 page 176

  11. Organizational commitment to analyzing errors • Management structure that is geared towards tracking, analyzing and fixing patient safety issues • Process in place to determine the efficacy of the actions taken to prevent errors • Open communication • A Just Culture

  12. Safety • A model for introducing safer care • Pg 179 – Figure 5-1 • Retrospective reviews based on ICD-9 CM discharge codes and External Causes of Injury Codes (E-Codes) • Pg 182 – Figure 5-2 • Pg 183 –Table 5-1

  13. ADE – Case Study • Table 5-2, page 187 • Figure 5-3, page 187

  14. Case Study – Postoperative Deep Wound and Organ Space Infections • Table 5-3, page 189 • Figure 5-4, page 190

  15. Tools • Tools needed for: • Early detection • Prevention • Physician order system • Drug interactions verifications • Verifying adverse events • Data mining for large patient safety databases • NLP • Knowledge dissemination • Audit procedures

  16. Source: http://www.dec.org/pdf_docs/PNACN715.pdf

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