The Chest Pain Choice Decision Aid: a Randomized Trial

1. The Chest Pain Choice Decision Aid: a Randomized Trial ISDM Conference Maastricht, June 2011

2. E Hess, M. Knoedler, N. Shah, J Kline, M Breslin, M Branda, L Pencille, B Asplin, D Nestler, A Sadosty, H. Ting, M. Montori Knowledge and Evaluation Research Unit Mayo Clinic College of Medicine MN Foundation for Informed Medical Decision Making AHA Fellow-to-Faculty Transition Award

3. Chest pain 2nd most common complaint in U.S. Emergency Departments > 6 million patients annually 4% of ACS inappropriately discharged from ED Large #’s of low risk patients admitted for prolonged observation and cardiac stress testing False positive test results, unnecessary procedures,  cost Background Pope, NEJM, 2000

4. Background • Kline and colleagues developed a quantitative pretest probability calculator • Prospectively validated QPTP calculator in 3 Academic EDs • Demonstrated efficacy of QPTP calculator in RCT Kline JA, BMC Med Informed Decision Making, 2005 Mitchell AM, Kline JA, Annals of Emergency Medicine, 2006 Kline JA, Annals of Emergency Medicine, 2009

5. Background Decision Aids: knowledge (by 15 of 100, 95% confidence interval12-19%) % patients with realisticperceptions of the chances of benefits and harms by 60% (40-90%) uncertainty related tofeeling uninformed (by 8 of 100 (5-12) % passive patients in decision makingby 30% (10-50%) % remainingundecided after counseling by 57% (30-70%) O’Connor, Cochrane Database of Systematic Reviews, 2009

6. Hypothesis Facilitating a patient-centered discussion regarding the short-term risk for ACS in otherwise low-risk chest pain patients will:  patient knowledge  patient engagement Safely  resource use

7. Objectives (1) To design a DA for use in patients at low risk for ACS (2) To test the DA in a randomized trial

8. Methods

9. Decision Aid Design • Incorporate QPTP output in a literacy-sensitive DA, describe rationale of evaluation, list management options in value-neutral fashion • Iteratively test DA in patient encounters • Refine DA based on input from patients, clinicians, and investigative team  thematic saturation Breslin, Mullan, Montori Patient Educ Counseling 2008

10. Methods: Clinical Trial • Design: single-center; allocation concealed by password-protected, web-based randomization • Setting: Academic ED in Rochester, MN with 73,000 annual patient visits; 10-bed observation unit • Eligibility: • Included: Adults with chest pain considered for EDOU admission • Excluded: +troponin, known CAD, cocaine use within 72 hrs, unable to provide informed consent or use decision aid

11. Outcome measures • Decision quality • Patient knowledge** • Degree of patient participation (OPTION scale) • Decisional conflict (DCS) • Trust in physician (TPS) • Quantitative • Safety endpoint: 30-day MACE* • Resource use • Rate of cardiac stress testing in EDOU • 30-day rate of stress testing

12. Statistical analysis • Power: 200 patients • 90% power to detect > 25% ↑ in mean knowledge • 95% power to detect a 20% ↓ in proportion of patients who underwent stress testing in EDOU • Hypothesis testing: chi-square, Fisher’s exact, t-test or Wilcoxon rank-sum as appropriate • Intention-to-treat principle followed

13. Results

15. Baseline Characteristics

16. Knowledge and Participation

17. Decisional Conflict* and Physician Trust *Conflict related to feeling uninformed

18. Acceptability to Patients

19. Provider experience

20. Safety

21. Resource use

22. Limitations • Single center • Insufficient power to demonstrate safety

23. Conclusions

24. Summary of impact of DA

25. Lessons learned • Integration in process of care challenging • Care process redesign required?? • Feasibility of definitively demonstrating patient safety? • Use of DA in emergency department requires reliable access to outpatient follow-up

26. Future Directions • Identification of factors that promote or inhibit uptake of SDM in acute setting • Prospective multicenter randomized trial