Clinical Decision Support Systems (CDSS)

Goals of CDSS To capture the knowledge of a master clinician CDSS can notify health care professionals of drug- drug interactions, contraindicated drugs, alternative medications, costs of interventions and abnormal laboratory results CDSS provide an opportunity to improve care

Questions to Ask in Developing a CDSS What problem are you trying to solve? Quality Assurance (immunization prior to discharge) Safety (reduction of medication errors) Regulatory (in compliance with standards) Operational efficiencies (automatic requests for consultation) Financial (reduce duplicate test ordering)

Components of a Knowledge-based CDSS A knowledge base Combined with a reasoning program Leads to intelligent advice Need for a formal vocabulary Need a shared background so that developers and users interpret vocabulary in the same way Need the cognitive ability to translate concepts into this vocabulary The importance of a controlled vocabulary to the effectiveness of these systems is clear

Difficulties with a Knowledge-based CDSS Program developers and program users must share a standard vocabulary Terms may be ambiguous Use of the computer may constrain the meaning of certain terms Users may second-guess what developers mean by specific terms Many concepts in health care may have no verbal representation Many features of a patient may not register consciously People do not think in terms of controlled vocabulary terms People do not use the same process for solving all problems Research shows that medical school professors do not make clinical decisions using the same strategies that they teach in the classroom Research also shows that investment decisions made by stock brokers do not match the strategies that they claim to use

One Example – QMR (Quick Medical Reference) A commercial system Details at Began in early 1970s – a collaboration between a physician and a computer scientist A physician became project leader in the 1980s Internist-1 was mainframe version and was used to develop the extensive clinical knowledge base QMR is the version adapted for personal computers Contains hundreds of disease descriptions (for potential diagnosis) Contains thousands of manifestations of diseases (potential patient findings) Contains scores of relationships among diseases But health care professionals must express patient findings in terms of the QMR vocabulary

Characteristics of Rule-based CDSS They use If-Then rules in processing (IF I have a headache, THEN I take an aspirin – this is a very simplistic example) They contain inference engines that relate the rules to each other They are based on the theory that human thought can be represented by chains of rules They are used in the MYCIN system (Shortliffe, 1974) They are the most common framework for decision support system There are lots of “shells” available that you can use to create and edit rules, such as CLIPS and Decision Expert Rules are used in nearly all decision support systems Arden Syntax is a attempt to share decision rules across multiple vendors and projects

Problems with Rule-based CDSS How do individual rules contribute to problem- solving behavior? It is difficult to predict the interaction of rules The strong linkage between domain knowledge and problem-solving knowledge – changing the rules modifies both of these and that may not have been the intent

Characteristics of a Successful Rule-based System for CDSS Uses relevant and current data to find patients Clear and available interventions For high volume areas in the hospital Addresses problems with high mortality or morbidity In clinical areas of high importance to the organization Cost-benefits are clear Health care professionals are not overloaded with alerts Easy for clinicians to satisfy the alerts (simply ordering a test) Willingness of clinician to accept the alert Timeliness of the alert Rules differ depending on the audience – nurse or physician as example Easiest rules to implement that satisfy clinicians and that maintain their interest Need for partnership between clinical and IT groups

What Clinician’s Want in a CDSS Efficient Not time consuming Alerts are triggered only for eligible patients Exceptions can be indicated Repetition is minimized User-friendly interface and presentation Easy to see alerts Easy to respond to alerts Content is accurate and robust Easy to access additional information from the alert Integrated into the workflow Alert appears at an appropriate time Alert appears to the appropriate person

Computers can aid in decision making by: –Simplifying access to data that is needed to make decisions –Providing reminders and prompts –Assisting in order entry –Assisting in diagnosis –Reviewing new clinical data and alerting the health care professional when important new patterns are recognized

Hospital Information System (HIS) Support of Clinical and Medical Patient Care Activities in the Hospital Administration of the Hospital’s Daily Business transactions (financial, personnel, payroll, bed census etc.) Evaluation of Hospital Performance and Cost, and projection of the long-term forecast

HIS Business & Administration Components Material Services Accumulate payments Recharge Budgeting General ledger Patient ADT/Billing/Account receivable Payroll Cost accounting

HIS Operation Components OR scheduling Nursing management Clinical appointment Dietary Doctor ID system Employee health system Medical record system Pathology system Patient ADT

HIS Operation Components (Cont.) Pathology system Patient ADT Pharmacy system Radiology system Referring doctor system Cancer registry system

Radiology Information System (RIS) Process patient and film folder records Monitor the status of patients, examinations, and examination resources. Schedule examinations Create, format and store diagnostic reports with digital signature Track film folders Maintain timely billing information Perform profile and statistic analysis