This course provides a practical survey and examination of clinical decision support systems over the past 20 years, along with how to apply the science of decision analysis with an emphasis on medical decision-making. The course also provides the foundation needed to apply clinical decision support in both patient care and clinical research settings. Students become familiar with the basic requirements for decision support systems, the graphical display of medical information to enhance decision-making, the application of rule-based systems, controlled medical terminologies, data standardization, clinical coding, structured data entry, natural language processing and data mining techniques.

Upon completion of this course, the student will be able to:

1. Describe past and current uses of decision support systems in health care.
2. Explain the benefits and limitations of medical decision-making techniques.
3. Explain why clinical decision support systems are not in widespread use but that the demand and supply for them are increasing.
4. Identify the basic features, benefits, and limitations of machine learning and intelligent decision support methods in the healthcare environment.
5. Develop a decision-tree to model and address a healthcare problem.

Decision Making in Health and Medicine, Hunink et al, Cambridge University Press, ISBN: 9780521770293.

Clinical Decision Support Systems: Theory and Practice, Berner, Eta S. (Ed.), 2nd ed., 2007, Springer, Health Informatics Series, XIV, 269 p., Hardcover, ISBN: 978-0-387-33914-6.

Improving Outcomes with Clinical Decision Support: An Implementer’s Guide, Osheroff et al, HIMSS, ISBN: 0-9761277-2-5.

Decision tree software TreeAge Pro Suite,http://server.treeage.com/treeagepro/purchase/stu.asp

Decision Tree Analysis

Medication Reconciliation Project Overview

Medication Reconciliation System

Some projects teach you about a particular health information technology topic. Some teach you about teamwork. This project was a lesson in both. Working with an ER Physician and a Registered Nurse enabled the team to deeply explore the clinical and practical challenges of performing proper medication reconciliations. The team studied the complexities of determining possible drug-drug interactions and considered the decision making required to resolve a patient’s list of medication at the point of hospital discharge. Communication between two clinical team members and three technical team members was a challenge. Learning to speak each other’s language was a barrier we had to overcome. It was not easy to balance the tight time-line deliverables of the project against the team’s desire to develop a system that accurately and completely performed the needed medication reconciliation functions. In the end, the specification produced provided thorough guidance on the system capabilities needed to provide safer, more efficient and more effective medication reconciliation functionality that could be added to an existing EMR system. The project showed how CDS functionality could be added to meet “Meaningful Use” requirements and improve operations. The communication and conflict management skills gained were also invaluable. The course heightened awareness of the challenges to adopting technology in the practice of medicine.