Health Management Information Systems

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1 Health Management Information Systems Clinical Decision Support Systems

2 Clinical Decision Support Systems (CDSS) Learning Objectives 1. Describe the history and evolution of clinical decision support 2. Describe the fundamental requirements of effective clinical decision support systems 3. Discuss how clinical practice guidelines and evidence-based practice affect clinical decision support systems 2

3 Clinical Decision Support Systems (CDSS) Learning Objectives 4. Identify the challenges and barriers to building and using clinical decision support systems 5. Discuss legal and regulatory considerations related to the distribution of clinical decision support systems 6. Describe current initiatives that will impact the future and effectiveness of clinical decision support systems 3

4 CDSS Challenges Achievement of the five rights of clinical decision support requires communicating the Right information To the right person In the right format Through the right channel At the right time 4

5 Challenges in Designing or Selecting CDSS Whose decisions are being supported? What information is presented? When is the information being presented? How is the information being presented? 5

6 User Control User presentation Automatically On demand User reaction 6

7 CDS Intent and Key Issues CDS Intent Reminder of actions user intends to do, but should not have to remember (automatic) Provide information when user is unsure what to do (on demand) Correct user s errors and/or recommend user change plans (automatic or on demand) High High Low Match to User s Intention Timing Key Issues Speed and ease of access Automatic: timing, autonomy and user control over response On demand: speed, ease of access, autonomy and user control over response Table 5.1 CDS Intent and Key Issues (Berner, 2009) 7

8 Challenges in Building CDSS Impact on Care Process and Patient Health Outcomes Match of CDS to user intentions User control, disruptiveness, and risk Integration of CDS into work processes Impact on structure Impact on resources 8

9 Barriers to Using CDSS Acquisition and validation of patient data Modeling of medical knowledge Elicitation of medical knowledge 9

10 Barriers to Using CDSS Representation of and reasoning about medical knowledge Validation of system performance Integration of decision-support tools 10

11 Legal Barriers Lack of detailed case laws for CDSS Which category of law Negligence law Product liability law 11

12 Legal Barriers Liability borne by Physicians Developers of systems 12

13 Regulatory Barriers Prerelease regulations of medical software Data privacy and security 13

14 Legislative and Regulatory Efforts Drive measurable progress toward priority performance goals for health care quality improvement through effective use of CDS Explore options to establish or leverage a publicprivate entity to facilitate collaboration Accelerate CDS development and adoption though federal government programs and collaborations 14

15 Future Directions for CDSS ONC initiatives IOM studies Meaningful use objectives and measures 15

16 ONC Initiatives Major activities Advancing CDS Development of a Roadmap for National Action on Clinical Decision Support AHIC CDS Work Group recommendations Clinical Decision Support (CDS) Workshop CDS Federal Collaboratory IOM study 16

17 IOM Studies 1999 IOM study To improve safety, health IT systems should be designed to make it easy to do the right thing IOM study Recommend ways to make patient care safer using health IT 17

18 Stage 1 Meaningful Use ARRA HITECH Programs Regulations Meaningful use of interoperable health information technology and qualified EHRs» Eligible Professional» Hospital 18

19 Clinical Decision Support Systems Summary Definition System requirements Affects of clinical practice guidelines and evidence-based practice on CDSS Challenges and barriers Legal and regulatory barriers Future directions for clinical decision support systems 19

20 Clinical Decision Support Systems References References Berner, E. S. (2009, June). Clinical decision support systems: State of the Art. AHRQ Publication No EF. Rockville, Maryland: Agency for Healthcare Research and Quality AHIC. (2008, April 22). CDS recommendations, Retrieved from Centers for Medicare and Medicaid Services. (2011, November 7). EHR incentive programs overview. Retrieved from https://www.cms.gov/ehrincentiveprograms/#bookmark1 Centers for Medicare and Medicaid Services; Medicare and Medicaid Programs; Electronic Health Record Incentive Program; Final Rule, 42 CFR Parts 412, 413, 422 et al. (July 28, 2010). Retrieved from Institute of Medicine. (2012). Health IT and patient safety: Building safer systems for better care. Washington, DC: The National Academies Press. Musen, M. A., Shahar, Y., & Shortliffe, E. H., (2006). Clinical decision-support systems. In Shortliffe. E. H., & Cimino, J. J. (Eds.), Biomedical informatics: Computer applications in health care and biomedicine (3 rd ed) (pp ). New York, NY: Springer Science + Business Media. National Academy of Sciences. (2011, November). Report brief. Retrieved from National Academy of Sciences. (2000). Report brief. Retrieved from Human/To%20Err%20is%20Human%201999%20%20report%20brief.pdf 20

21 Clinical Decision Support Systems References References Office of the National Coordinator for Health Information Technology. (2011). CDS activities. Retrieved from cds_activities/3787 Osheroff, J. A., Teich, J. M., Middleton, B. F., Steen, E. B., Wright, A., & Detmer, D. E. (2006, June 13). A roadmap for national action on clinical decision support (ONC Contract HHSP P). Retrieved from AMIA website: June pdf Sirajuddin, A. M., Osheroff, J. A., Sittig, D. F., Chuo, J., Velasco, F. & Collins, D. A. (2009, Fall). Implementation pearls from a new guidebook on improving medication use and outcomes with clinical decision support. Journal of Healthcare Information Management. 23(4), U.S. Department of Health and Human Services. (2010, September 29). Institute of Medicine will study best policies and practices for improving health care safety with health information technology. Retrieved from Table 5.1 Table: Berner, E. S. (2009, June). Clinical decision support systems: State of the Art. AHRQ Publication No EF. Rockville, Maryland: Agency for Healthcare Research and Quality 21

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