Clinical Decision Support Systems Dimitar Hristovski, Ph.D. Institute of Biomedical Informatics Medical Faculty University of Ljubljana, Slovenia

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Definition  A medical decision-support system is any computer program designed to help health professionals make clinical decisions.  In a sense, any computer system that deals with clinical data or medical knowledge is intended to provide decision support.  Three types of decision-support function, ranging from generalized to patient specific.

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Tools for Information Management  Examples:  Hospital information systems  Bibliographic retrieval systems (PubMed)  Specialized knowledge-management workstations (e.g. electronic textbooks, …)  These tools provide the data and knowledge needed, but they do not help to apply that information to a particular decision task (particular patient)

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Tools for Focusing Attention  Examples:  Clinical laboratory systems that flag abnormal values or that provide lists of possible explanations for those abnormalities.  Pharmacy systems that alert providers to possible drug interactions or incorrect drug dosages  Are designed to remind the physician of diagnoses or problems that might be overlooked.

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Tools for Patient-Specific Consultation  Provide customized assessments or advice based on sets of patient-specific data:  Suggest differential diagnoses  Advice about additional tests and examinations  Treatment advice (therapy, surgery, …)

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Alternative (more specific) Definition  Clinical decision support systems are active knowledge systems which use two or more items of patient data to generate case- specific advice.  Main components:  Medical knowledge  Patient data  Case-specific advice

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Characterizing Decision-Support Systems along Five Dimensions  System function  Determining what is true about a patient (e.g. correct diagnosis)  Determining what to do (what test to order, to treat or not, what therapy plan …)  The mode for giving advice  Passive role (physician uses the system when advice needed)  Active role (the system gives advice automatically under certain conditions)

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Passive Systems  The user has total control:  Requires advice  Analyses the advice  Accepts/Rejects the advice  Domain of use:  Wide domain like internal medicine  Examples: QMR, DXPLAIN  Narrow domain  Acute abdominal pain  Analysis of ECG

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Passive Systems (cont.)  Characteristics:  Stand-alone  Data entry:  System initiative  User initiative  Consultation style  Consulting model  Critiquing model

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Active Systems  The user has partial control  System gives advice  User evaluates the advice  The user accepts/rejects the advice  Domain of use  Limited domain  Drug interactions  Protocol conformance control  Laboratory results warnings  Medical devices control

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Active Systems (cont.)  Characteristics  Built-in/integrated with other system (e.g. laboratory information system, or pharmacy system)  Data entry  By the user  Related to the main application  Consultation style  Critiquing model  Examples:  HELP (advices and reminders, therapy)  CARE (reminders)

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems  Consultation style  The system operates under consulting model  The system operates under critiquing model  ATTENDING (anesthesia)  HELP  ONCOCIN (oncology, therapy plan)

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Underlying Decision-Science Methodology  Problem-specific algorithms  Pattern recognition  Statistical methods (Bayesian statistics, decision analysis, …)  Artificial intelligence (knowledge-based systems)  Expert systems (MYCIN – therapy selection for patients with bacteremia or meningitis)  Machine learning  Neural networks  Knowledge representation formalisms:  Decision trees  Decision rules

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Example: Decision Tree 1

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Example: Decision Tree 2

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Example: Decision Rule 1

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems System MYCIN – a Decision Rule

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems System MYCIN – Explanation Example

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems System HELP – MLM Example (Medical Logic Module)

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems System ONCOCIN – Cancer-Treatment Protocol Example

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems  Human factors  Logistics  User interface  Psychology of human-computer interaction  Legal and regulatory questions  Integration  Stand-alone systems have no future  Data have to be entered only once  Advice integrated in the basic information system (e.g. electronic medical record)

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems General Architecture of a Knowledge-Based Clinical Decision Support System User Knowledge base Inference Mechanism Patient diagnosis explanations questions Therapy Data Entry

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems  Characteristics of modern knowledge- based decision support systems:  The used medical knowledge (knowledge base) separated from the mechanisms using that knowledge (inference mechanisms)  Medical knowledge acquisition:  Experts  Medical literature  Automatically from medical data (induction, machine learning)

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems Example: DXplain  Can be accessed at:

Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems

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Alpe Adria Master Course :: Medical Informatics :: Dr. D. Hristovski: Clinical Decision Support Systems