1. VA HSR&D Salt Lake Informatics Decision Enhancement And Surveillance Center Human Factors in Prescription Medication Management Jonathan R. Nebeker MS MD VA Salt Lake City GRECC

2. Acknowledgements Charlene R. Weir, PhD Frank Drews, PhD Molly Leecaster, PhD Rand Rupper, MPH MD Kenneth Boockvar, MD Brittany Mallin, MS MPH AHRQ R18 HS017186 VA Salt Lake City GRECC VA Salt Lake City IDEAS Center 2

3. Overview The Electronic Health Record context Current Future How theory gets us to future Theoretical Framework Study design Preliminary Findings 3

4. 4 Current CPRS VistA Emphasis on access Information siloed in tabs

5. 5 Future CPRS VistA Emphasis on control Information integrated

6. 6 Goal: EHR of future

7. Decision Support v. Sense Making Computerized decision support is typically normative and targets the right decision. The CPRS of the future will emphasize an information-rich environment that targets sense making to support higher quality decisions in the highly variable context of patient care. 7

8. Progress The Electronic Health Record context Theoretical Framework (The pathway to the future) Joint Cognitive Systems or Cognitive Systems Engineering Contextual Control Model Study Design Preliminary Findings 8

9. Towards the Future Apply Cognitive Systems Engineering Human Factors in this talk Not about usability About the human-computer system 9

10. Joint Cognitive Systems Erik Hollnagel and David Woods System of artifact(s) + human(s) that accomplishes work. Not what do human and computer do best Control is a measure of the work’s quality. Examples of JCS: Scissors Fighter jets Combat robots 10

11. Contextual Control Model (CoCoM) Performance in context Different types of behaviors predict better outcomes Functional not structural approach Not about information processing models: Memory, programs, etc. Used in engineered systems ABS at Saab Nuclear Power Plants 11

12. CoCoM Main Concepts Competencies: possible actions in context Constructs: assumptions about situation Control modes: characteristics of performance that govern quality of performance Feed forward and feedback: anticipatory versus reactive control 12

13. Control Cycle in Healthcare 13 What is going on.

14. Control Modes Scrambled Lack of purposeful activity Opportunistic Addressing salient characteristics Tactical Following procedure, limited scope Strategic Broader scope and higher-level goals 14

15. Control Characteristics Goal Complexity (Number and Interaction) Perceived Time Pressure Evaluation of Outcome Selection of Action Expertise Motivation Familiarity 15

16. Progress The Electronic Health Record context Joint Cognitive Systems Contextual Control Model Study Design Preliminary Findings Control characteristics 16

17. Study Goals Immediate Aim Translate CoCoM to medication management for chronic diseases Explore associations between control characteristics and surrogate outcomes Next Aim Establish validity of adapted CoCoM control characteristics as predictor of higher quality outcomes through simulation 17

18. Study Design Subjects: 40-50 physicians, mid-levels, residents, nurses, pharmacists in 5 outpatient clinics/4 states. Focus on HTN Think-aloud protocol + Interview Saturation coding for control characteristics Content analysis Multi-dimensional scaling 18

19. Preliminary Findings Semi-Qualitative Stories of control modes Scrambled Opportunistic Tactical Strategic 19

20. Scrambled Mode Type: Trial and error performance Case of the new intern and forgetful patient. Low information quality and availability + Low experience 20

21. Opportunistic Mode Type: Reaction to salient characteristics Have not seen yet for HTN Reaction to SBP only Pain syndromes even among experienced Poor construct of problem Low information quality Vague goals: difficult to resolve competition Vague evaluation of outcome: not mentioned, then OK. 21

22. Tactical Type: Following procedure Dominant mode for HTN Use of protocol Focus on procedure* (forget clinical goal) Minimal consideration of interacting goals Low use of feed-forward control Problem with information quality-clinical inertia Less common in highly experienced MDs 22

23. Strategic Type: Broad consideration of context Almost exclusively with experienced MDs Awareness of protocols but deviation to accomplish conflicting patient goals Familiarity with past therapy a key factor Feed forward strategies account for physiologic and organizational factors Still, incomplete use of explicit control limits 23

24. Conclusions CoCoM reveals interesting characteristics of system performance. High-mode characteristics have face validity for predicting better outcomes. Implications for software design: Need to support efficient, rich reconstruction of mental model of patient Need to highlight interaction of goals and therapies Need to increase time horizon including feed forward 24

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