Clinical Decision Support System

1. Clinical Decision Support System

2. 교재 • Clinical Decision Support • The Road Ahead • Robert A. Greenes • Academic Press, 2007

3. Chapter I Definition, Scope, and Challenges

4. 1.1 Introduction • The application of computers in health care • early 1960s • Rate of adoption and degree of impact of computers and IT • Low, compared to engineering, physics, finance

5. 1.1 Introduction • Challenges to healthcare providers • seeking to make difficult diagnoses • avoid errors • ensure highest quality • maximize efficacy • save money • Patients and the public • needs in evaluating their health • needs in making decisions •  decisions are more complex •  require more detailed knowledge

6. 1.1Introduction • CDSSs are useful • simple types of CDS • laboratory test result : out of normal range • Medication: dangerous interaction with another one • patient is now due for a flu shot • usefulness evaluated over the past 40+ years • checks, warnings, and reminders - effective

7. 1.1 Introduction • But, not widely used! • even for the more simple aids • like alerts and reminders or drug interaction checks • Using computers in decision support • much harder problem • Challenges • wider deployment beyond a single application • multi-institutional setting • Regional, national adoption

8. Difficulties in Knowledge Management Maintenance & updating of the knowledge Knowledge management- conflicts, overlaps, gaps Best ways to deploy various forms of DS integration with practice impact on efficiency and workflow disseminating knowledge- reuse in multiple sites making such knowledge platform-independent knowledge management economically feasible on a broad scale

9. 1.2 Definition of Computer-Based CDS • the use of the computer to bring relevant knowledge to bear on the health care and well being of a patient. • Computer: information and communication technologies • the management of health and health care of an individual person (the patient) • Support: aiding of rather than the making of decisions • relevant knowledge : knowledge that is directly pertinent to the specific patient

10. 1.3 Features of CDS • The general aim of CDS • To make data about a patient easier to assess • more apparentto a human • optimal problem-solving, decision-making, and actionbythe human • Users of CDS • physician, anurse, a laboratory technologist, a pharmacist, a patient • computer program • A primary task of CDS • to select knowledge that is pertinent • patient-specific data  relevance of the CDS enhanced • The selection of knowledge and processing of data • inferencing process • Algorithm • Rule • association method • The result of CDS • to perform some action – usually recommendation

11. History of CDS

12. Why CDS Is a Hard Problem • simple forms of CDS • if.. .then rule:checking a laboratory test result • in a single computer system:is relatively easy • interact with users • not just the single use • cost effective • not too many false positives • knowledge maintain and update • interfacing with the application • how it relates to other rules • how it can be deployed in other applications or in other system platforms • how knowledge can be disseminated

13. Differential Diagnosis Process of A CDSS • Ascertain values for the various findings in a patient • Eliminate diseases for which finding(s) are incompatible with the presence of the disease • For pathognomonic findings, exclude all diseases that do not have the finding(s) • For those diseases remaining under consideration • perform a Bayestheorem calculation of the conditional probability of each disease

14. Components of CDS • Decision model • representation of the problem • e.g. combination of logical and Bayesian manipulation • Knowledge base • logical constraints • prior probabilities of disease – P(D) • conditional probabilities of findings given disease - P(F|D) • Information model • data elements needed for calculations, logic manipulations • Result specification • output or means of representing the results of the operation of the model • Application environment • interacting with a user or an information system • to obtain necessary inputs, and communicate results, • to enable a host application to interpret the results

15. Computer-Aided Diagnosis • deDombal system: • deDombal, 1975 • a Bayesian algorithm for diagnosis of abdominal pain • artificial intelligence models • rule-based, frame-based, and heuristic-reasoning-based • DXplain • Barnett, Cimino et al. 1987 • one of the few that remains widely available • Isabel • Ramnarayan, Tomlinson et al., 2004

16. Computer-aided diagnosis is rarely actually used in practice • Diagnostic challenges do not arise often in medicine • Actual clinical situation: • optimal workup strategy • choosing or modifying treatments • assessing prognosis and response to treatment. • Diagnostic problems • require analysis of many detailed data items • not readily available in the electronic health record • if present, are not sufficiently structured • must be encoded or mapped to the format required by the programs • e.g., as present/absent or high/medium/low •  requires considerable manual entry of data • Differential diagnosis CDS: passive system • must be actively invoked by the physician when needed