1. It’s Complicated: Methods to assess medication nonadherence and regimen complexity John Billimek, PhD Department of Medicine Grand Rounds | August 12, 2014 Division of General Internal Medicine | Health Policy Research Institute | UC Irvine School of Medicine

2. Two patients  58 year-old man  Type 2 diabetes  Middle class, educated  Good overall health Prescribed 4 medications  58 year-old man  Type 2 diabetes  Middle class, educated  Good overall health Prescribed 7 medications

3. Patient Complexity in Chronic Disease Management

4. Multiple Chronic Conditions Nationwide (CDC)  Among all adults in the US  50% have at least one chronic condition  25% have two or more  Adults over age 65  86% have at least one chronic condition  61% have two or more  Two-thirds of health care spending Ward 2014 Prev Chronic Dis 2014;11:130389 Anderson 2010. Chronic Care: Making the Case for Ongoing Care, RWJ

5. Complex Patients, Complex Regimens More Chronic Conditions More medications indicated Over- and under- prescribing Worse adherence More adverse events Higher costs Increased hospitalization Increased readmissions Increased mortality Mansur et al 2012. Am J Geriatr Pharmacother 10;223-229 Wilson et al 2014. Ann Pharmacother 48(1);26-32

6. Medication Nonadherence  Over 50% of patients either  Never fill Rx  Delay refills  Discontinue, and/or  Skip doses  Contributes to up to 69% of hospital admissions  And $100 billion Osterweil 2005. NEJM

7. How much nonadherence is too much?  Varies by condition, treatment and situation  In VA patients with diabetes  “Skipping” 20% of doses  +81% mortality risk  +58% all-cause admission rate  “Skipping” 50% of doses  12-fold mortality risk Ho. et al. 2006. Arch Intern Med 166:1836-41 Egede et al. 2011. The Annals of Pharmacotherapy 45: 169 –78

8. R2D2C2 Study  NIDDK, RWJ, Novo Nordisk funded RCT  Disparities in diabetes management  Poor, ethnically diverse sample (N=1484)  Data collection  Patient questionnaires  Chart review  Audiorecordings  Study Foci  Patient Participation Training  Patient Complexity  Medication Adherence Kaplan 2013. J Gen Int Med 28(10): 1340-9

9. Complex Patients at UCI: Diabetes  75% of R2D2C2 study patients have 2+ additional comorbid conditions  35% have 4+ additional comorbid conditions  87% taking 5 or more different medications  35% are taking 10+ medications  Over 60% report medication nonadherence

10. Reasons for nonadherence  Forgetting  Cost, Financial pressures  Side effects (currently experienced)  Regimen confusing, complicated  Side effects (possible, future damage)  Pharma advertising  Interferes with lifestyle  Concerns about alcohol  Concerns about effectiveness, value  Experimenting, “N-of-me trials”

11. DO: (Mixed) Evidence based approaches Patient PhysicianPharmacistNurse Professional Health Educators Community Health Workers Multifactorial & Coordinated Case Management Education Patient Engagement Tailored & Targeted One size fits none

12. DO: The Medical Visit  Where treatment decisions are made  All useful information may not be available  Little time to talk  Averages: 15 minutes | 6 topics  5 minutes for main topic  1 minute for each of the rest Tai-Seale 2007. Health Serv Rsch 42:5 1871-94 Patient PhysicianPharmacistNurse Professional Health Educators Community Health Workers

13. Many patients have problems with adherence …but few raise problems with the doctor

14. DO: Coached Care Patient Participation Training Audio Record Patient Questionnaire

15. DO: Patient Participation training Coached Care

16. Raising problems with adherence helps Patients with A1c>9% at recorded visit

17. DO: The Medical Visit Organize services to CUE UP topics and info for the medical visit Involve the patient to promote FOLLOW- THROUGH Patient PhysicianPharmacistNurse Professional Health Educators Community Health Workers

18. KNOW: So, who do we help?  Two EMR-based approaches to ID patients 1. Medication Nonadherence  Medication Possession Ratio (MPR) 2. Regimen Complexity:  Medication Regimen Complexity Index (MRCI)

19. Assessing Medication Nonadherence

20. Don’t we already know who isn’t taking their medications?

21. The way we ask matters A1c LDL * *

22. Look in the EMR: the Medication Possession Ratio (MPR)

23. How much nonadherence is too much?  Varies by condition and situation  In VA patients with diabetes  “Skipping” 20% of doses  +81% mortality risk  +58% all-cause admission rate  “Skipping” 50% of doses  12-fold mortality risk Ho. et al. 2006. Arch Intern Med 166:1836-41 Egede et al. 2011. The Annals of Pharmacotherapy 45: 169 –78

24. Assessing Regimen Complexity

25. Take two patients taking 7 medications 15 doses 4+ times/day 2 modalities 9 doses 2 times/day 1 modality 7 medsSMTWTHFS Morning7 (P) Midday2222222 Evening4 (P) Night2222222 7 medsSMTWTHFS Morning7777777 Midday Evening2222222 Night

26. Look in the EMR: Medication Regimen Complexity Index (MRCI)  One score for each patient  Objective  Actionable Patient A’s MRCI score 24 Patient A’s Med List -------- --- -- -- -------- --- -- -------- --- -- -- -------- --- -- Flag high-risk patients in a registry Available at point of care

27. MRCI = Total A + Total B + Total C for all current prescription medications Dosage Form Dosing Frequency Special Instructions + + Medication Regimen Complexity Index (MRCI) A weighted count of currently prescribed medications AB C A BC

28. All polypharmacy is not created equal

29. Putting it together: Population management of medication issues

30. MRCI Patient Reported Nonadherence Outcomes A1c LDL ER Visits Hospital Admissions Adjust for Comorbidity Patient Char Stage 1: R2D2C2 Dataset Hypothesis testing MRCI MPR Outcomes A1c LDL ER Visits Hospital Admissions Adjust for Comorbidity Patient Char Stage 2: UCI Diabetes Registry Predictive modeling 2012 2013 Stage 3: Stakeholder Engagement From KNOW to DO

31. Stage 1 R2D2C2 Dataset: Preliminary Findings

32. Stage 1 R2D2C2 Dataset: Linking MRCI to outcomes Higher rates with high MRCI Odds ratios comparing MRCI above vs. below 17 Adult UCI patients with type 2 diabetes (N=998) adjusted for: Age, Sex, Race/ethnicity, Education, Insurance type, Nativity, duration of diabetes and comorbidity (TIBI)*

33. MRCI Patient Reported Nonadherence Outcomes A1c LDL ER Visits Hospital Admissions Adjust for Comorbidity Patient Char Stage 1: R2D2C2 Dataset Hypothesis testing MRCI MPR Outcomes A1c LDL ER Visits Hospital Admissions Adjust for Comorbidity Patient Char Stage 2: UCI Diabetes Registry Predictive modeling 2012 2013 Stage 3: Stakeholder Engagement From KNOW to DO

34. MRCI Patient Reported Nonadherence Outcomes A1c LDL ER Visits Hospital Admissions Adjust for Comorbidity Patient Char Stage 1: R2D2C2 Dataset Hypothesis testing MRCI MPR Outcomes A1c LDL ER Visits Hospital Admissions Adjust for Comorbidity Patient Char Stage 2: UCI Diabetes Registry Predictive modeling 2012 2013 Stage 3: Stakeholder Engagement From KNOW to DO

35. Acknowledgments  Funders  DOM Chair’s Award  ICTS Pilot Awards program  NIDDK  Collaborators  Sheldon Greenfield  Sherrie Kaplan  Dara Sorkin  Quyen Ngo-Metzger  Shaista Malik  Dana Mukamel  Lisa Dahm  Andrea Hwang  UC Irvine Health Informatics & Research Computing  Patient Advisory Group (La Voz de la Esperanza)  Marco Angulo  Anabel Arroyo  MRCI/MPR Development team  Travis Nesbit  Daniel Orlovich  Audiocoding Team  Herlinda Guzman  Linh Vu  Katherine Vu  Sophia Nguyen  Kimberly Gardner  Taylor Gardner  Mylon Remley  Mei Chang  Sana Moosaji  Stephanie Torrez  Maria Paula Gonzalez  Alejandro Avina  Jessica Colin Escobar  Linda Nguyen

36. Summary  Nonadherence and Complex regimens are common  Problems with regimens are rarely discussed  Regimen complexity  Outcomes  Independent of comorbid disease burden  EMR-based approaches can identify patients struggling with medication regimen  Help direct interventions and resources

37. Questions? John Billimek, PhD | jbillime@uci.edu