It’s Complicated: Methods to assess medication nonadherence and regimen complexity

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 Mansur et al 2012. Am J GeriatrPharmacother10;223-229 Wilson et al 2014. Ann Pharmacother48(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 Med166:1836-41 Egedeet al.2011. The Annals of Pharmacotherapy45: 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+ additionalcomorbid 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 • 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 ServRsch 42:5 1871-94

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

18. KNOW: So, who do we help? • Two EMR-based approaches to ID patients • Medication Nonadherence • Medication Possession Ratio (MPR) • 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 Med166:1836-41 Egedeet al.2011. The Annals of Pharmacotherapy45: 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

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

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

28. All polypharmacy is not created equal

29. Putting it together: Population management of medication issues

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

34. Stage 1: R2D2C2 Dataset Hypothesis testing Stage 2: UCI Diabetes Registry Predictive modeling Adjust for ComorbidityPatient Char Outcomes A1c LDL ER Visits Hospital Admissions Adjust for ComorbidityPatient Char Outcomes A1c LDL ER Visits Hospital Admissions MRCI MRCI Patient Reported Nonadherence MPR 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 DaraSorkin Quyen Ngo-Metzger Shaista Malik Dana Mukamel Lisa Dahm Andrea Hwang UC Irvine Health Informatics & Research Computing Patient Advisory Group (La Vozde 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 • MylonRemley • 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