Clinical Decision Support
Systems (CDSS)
Goals of CDSS
• To capture the knowledge of a master clinician
• CDSS can notify health care professionals of drugdrug 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 www.firstdatabank.com
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)
http://www.cbi.umn.edu/shp/entries/mycin.html
• 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 problemsolving 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