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Guideline implementation Types of CDSS

Guideline implementation Types of CDSS. A.Hasman. Do physicians need support?. In 2.3% of the 1.3 million patients (30.000 patients) preventable errors were made during their stay in a hospital in the Netherlands.

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Guideline implementation Types of CDSS

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  1. Guideline implementationTypes of CDSS A.Hasman

  2. Do physicians need support? • In 2.3% of the 1.3 million patients (30.000 patients) preventable errors were made during their stay in a hospital in the Netherlands. • About 10.000 patients suffered a permanent injury. This could have been prevented in 6.000 patients. • For 4.1% of the 42.000 patients who died in the hospital death could have been prevented.

  3. Conclusion • Doctors are not infallible • Support physicians and nurses both in repeating and difficult tasks

  4. How to support physicians and nurses? • Easy access to the scientific literature • Guidelines • Computer-based diagnostic systems

  5. Medical decision support • Already available for years • ECG/EEG analysis (signal analysis and parameter interpretation) • Diagnostic systems (cardiology (congenital heart disease diagnosis), radiology (bone tumor classification)) • Radiotherapy planning • Medication selection, dosing • Clinical algorithms (flowcharts on paper, for nurses and ancillary personnel) • Guidelines

  6. Methodology used by CDSS • Decision trees • Statistical approaches • Bayes’ rule • Discriminant analysis • Logistic regression • Inference techniques • Rules • Logic • Semantic networks • Etc.

  7. Decision trees BP lower than 140/90 No Yes Send patient home First visit? Yes No

  8. x x O x Var 1 x x x O x O x O O O O x O Var 2

  9. Bayes’ rule P(Dj |Si ) = P(Dj) * P(Si|Dj)/P(Si) P(Dj) prior probability of disease j (prevalence) P(Si) probability of symptom i in population P(Si|Dj) conditional probability (sensitivity or specificity)) P(Dj|Si) posterior probability (predictive value)

  10. Types of decision support • Passive • Physician actively searches in the knowledge base for relevant information. Information indexed • Active • System pro-actively provides physician with relevant information • System re-actively provides physician with relevant information

  11. Guidelines • Systematically developed statements to assist practitioner and patient decisions about appropriate healthcare for specific clinical circumstances • They provide information for various types of patients having some common problem • Provide a common standard of care both within a healthcare organization and among different organizations • Based on consensus or evidence-based

  12. Use of guidelines • May lead to a reduction of errors, practice variability and patient care costs, while improving patient care • Narrative guidelines usually population-based, not patient specific • Healthcare organizations pay more attention to guideline development than to guideline implementation, evidently hoping • That clinicians will simply familiarize themselves with published guidelines and then apply them appropriately during the care of patients

  13. Background: paper-based guidelines

  14. Problems with guidelines • Guidelines often contain ambiguities, vague sentences and ‘open ends’ • Leads to different interpretations • This limits the use of guidelines

  15. Guideline Dissemination • Assumption: Practitioners will read the guidelines • Assumption: Practitioners will internalize and there after follow guidelines • Reality: Physicians do not use the guidelines or do not use them correctly

  16. Why was decision support not accepted? • Decision support systems were only applied in the institution where they were developed, if at all • Computer systems were stand-alone systems: no integration, so double data entry • Computer systems were slow and expensive • Initially physicians did not accept guidelines or clinical algorithms (Cookbook medicine, patients differ, useful for ancillary personnel) • Because of current emphasis on quality of care (evidence based medicine) guidelines are becoming relevant

  17. Myth-1 • Diagnosis is the dominant decision-making issue in medicine • Typical questions are not “What does this patient have?” but, rather, “What should I do for this patient? Ted Shortliffe

  18. Myth-2 • Clinicians will use knowledge-based systems if the programs can be shown to function at the level of experts • What do we know about “expertise” and the associated cognitive factors?

  19. The nature of clinical expertise • Tremendous variation in practice, even among “experts” • Need to understand better how experts meld personal heuristics and experience with data, and knowledge from the literature, in order to arrive at decisions (medical cognition) • Can we better teach such skills? • How could improved understanding affect the way decision-support systems offer their advice or information? • How will such insights affect our under-standing of clinicians as computer users?

  20. Myth-3 • Clinicians will use stand-alone decision-support tools. • The death of the “Greek Oracle” model →Integrated decision support in the context of routine workflow

  21. Systematic review of Garg et al • Systems that warn physicians have more effect on the physicians (success in 44/60 studies) than systems that have to be inititiated by physicians (17/36 studies) • In the case of diagnostic systems 4 out 10 trials indicated that the use of a DSS leads to better results (an improvement for at least 50% of the the measured outcomes)

  22. Reminder systems effective? • For 16/21 trials concerning reminder systems for prevention using a DSS led to a better performance of the physicians (screening, test requests, drug prescription, etc.) • Studies did not show a significant improvement in patient outcome

  23. Computer interpretable guidelines

  24. Computer-interpretable guidelines • Guideline implementations best affect clinician behaviour if they deliver patient specific advice during patient encounters • Computer-interpretable guidelines could provide such advice efficiently • Computerized guideline systems are crucial elements in long-term strategies for promoting the use of guidelines (IOM)

  25. Possibilities of ICT • Computersystems can not only show guideline texts but can also reason with the information from the guideline. To do that information about an individual patient is necessary • The combination of a formalized guideline and an EPR can lead to advice (pro-actively or reactively) concerning an individual patient

  26. Medical Protocols

  27. 20 Methods and techniques

  28. System description Guideline Base EPR Physician Guideline / Knowledge Base editor Execution engine Knowledge Base

  29. CIG ingredients • Guideline model • Guideline expression language for expressing decision criteria and eligibility criteria • Mapping of terminology in guideline to the terminology used in EPR • Scheduling constraint specification language for scheduling multiple steps • Guideline execution engine

  30. Guideline modeling and representation • System editor should provide • A domain ontology • A (visual) language for expressing the steps in a guideline

  31. Example: simple guideline • Primitive: If … then • Domain ontology: Digoxin, Potassium, … If Digoxin and Potassium>3 mmol/l then “warning”

  32. Phases in development process • Select guideline to be formalized • Formalize guideline • Enter guideline into guideline system • Guideline verification and testing • Guideline execution

  33. Acquiring guidelines

  34. Acquiring guidelines

  35. Acquiring guidelines

  36. Acquiring guidelines

  37. Acquiring guidelines5

  38. Acquiring guidelines6

  39. Complex guideline • Primitives: Branch step, Synchronization step, Decision step, …. • Domain ontology: Digoxin, ….

  40. Guideline representation in GastonMode structure

  41. Guideline representation in GastonMode structure

  42. Guideline representation in GastonMode contents

  43. ICPC- module IS ~ GP Reminder Re-active decision support Request module Evaluation module No reminder KB

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