F2: HOW DOES MEASUREMENT OF MULTIPLE MEDICATION ADHERENCE DIFFER BETWEEN CHRONIC DISEASES? An ISPOR Forum by the Multiple Medication Adherence Measurement Working Group of the ISPOR Medication Adherence and Persistence Special Interest Group Monday, May 22, 2017 HOW DOES MEASUREMENT OF MULTIPLE MEDICATION ADHERENCE DIFFER BETWEEN CHRONIC DISEASES? Mia Malmenäs, MSc, Director , Real World Strategy & Analytics, Mapi, Stockholm, Sweden Priti Pednekar, MPharm, Graduate Student (PhD), Mayes College of Healthcare Business and Policy, University of the Sciences, Philadelphia, PA, USA Bijan J. Borah, PhD, Associate Professor of Health Services Research, Director/Lead Consultant, Economic Evaluation Service, Kern Center for the Science of Healthcare Delivery, Mayo Clinic College of Medicine, Rochester, MN, USA Bryan Bennett, Director, Patient Centered Outcomes, Adelphi Values, Adelphi Mill, UK 2 1
MULTIPLE MEDICATION ADHERENCE MEASUREMENT WORKING GROUP Chairs: Mia Malmenäs, MSc, Director , Real World Strategy & Analytics, Mapi, Stockholm, Sweden Andrew M. Peterson, PharmD, PhD, Dean, Mayes College of Healthcare Business and Policy, University of the Sciences, Philadelphia, USA Leadership: Lusine Abrahamyan, MD, MPH, PhD , THETA, Toronto, Canada Tamás Ágh, MD, MSc, PhD , Principal Researcher, Syreon Research Institute, Budapest, Hungary Bryan Bennett , Director, Patient Centered Outcomes, Adelphi Values, Adelphi Mill, UK Bijan J. Borah, PhD, Associate Professor, Mayo Clinic College of Medicine, Division of Health Care Policy and Research, Rochester, MN, USA Thomas J. Bunz, Pharm.D., Ph.D, Director of Analytic Strategy, Aetna Consumer Analytics, Hartford, Conn., USA 3 MULTIPLE MEDICATION ADHERENCE MEASUREMENT WORKING GROUP Leadership: Mickaël Hiligsmann, PhD, Assistant Professor, Department of Health Services Research of Maastricht University, the Netherlands David Hutchins, MHSA, MBA , Senior Advisor, Strategic Research, CVS Caremark, USA Elizabeth Manias, PhD , University of Melbourne, Australia Priti Pednekar , M.Pharm, B. Pharm , Graduate Student, Mayes College of Healthcare Business and Policy, University of the Sciences, PA, USA Amit Raval, M.Pharm, PhD , Senior Researcher, Healthcore, Inc., Wilmington, DE, USA Adina Turcu-Stiolica, PharmD, PhD, Chair of Pharmaceutical Marketing and Management, University of Medicine and Pharmacy Craiova, Romania Allison F. Williams, RN, PhD , School of Nursing and Midwifery, Monash University, Victoria, Australia John E. Zeber, PhD , Central Texas Veterans Health Care System, Temple, TX ; Scott & White Healthcare, Center for Applied Health Research, Temple, TX, USA 4 2
SPECIAL INTEREST GROUP OBJECTIVE Conduct a systematic literature search of methods used calculating medication adherence for multiple drugs Summarize the results overall as well as by disease area Investing the accuracy of the measurements by conducting simulation Evaluate the measurements using real data Provide recommendations on measurements for evaluation of medication adherence in patients using multiple drugs 5 SPECIAL INTEREST GROUP OUTCOMES Two workshops One podium presentation Two publications, one submitted and one in process Today’s Forum 6 3
Is it necessary to have unique multiple adherence measurements for different diseases? 7 Is there an ideal multiple adherence measurement available today? 8 4
Bijan J. Borah, PhD, Associate Professor of Health Services Research, Director/Lead Consultant, Economic Evaluation Service, Kern Center for the Science of Healthcare Delivery, Mayo Clinic College of Medicine, Rochester, MN, USA 9 FLOW DIAGRAM OF THE SYSTEMATIC LITERATURE REVIEW PROCESS Records identified Additional records through database identified through Identification searching other sources (n = 1,706) (n = 8) Records after duplicates removed (n = 1,382) Screening Records screened Records excluded (n = 1,382) (n = 1,081) Full-text articles excluded, with reasons (n = 150) Full-text articles Eligibility assessed for eligibility • Not original research (n = 9) • (n = 301) No evaluation method for medication adherence (n= 52) • Studies not assessing multiple medication adherence (n= 83) • Studies assessing adherence to guidelines but not medications (n= 1) Studies included in • Studies assessing adherence to diet (n = 2) Included qualitative synthesis • Other (n= 22) (n = 151) 10 18 Based on the PRISMA template: Panic, N., et al., PLoS One, 2013. 8(12): e83138. 5
DISTRIBUTION OF STUDIES BY STUDY DESIGNS 140 130 Cross- sectional; 120 25; 19% Retrospecti 100 ve Cohort; 58; 45% 80 Prospectiv e Cohort; 47; 36% 60 40 20 20 1 0 Observational Studies Randomized Validation study Controlled Trial 11 NUMBER OF MMA METHODS USED BY STUDY DESIGN Number of MMA Methods Used Research Design 1 2 3 4 Total Observational Cross- sectional 20 1 4 0 25 Observational Prospective 33 10 3 1 47 Observational Retrospective 43 8 6 1 58 RCT 14 3 2 1 20 Validation Study 0 1 0 0 1 Total 110 23 15 3 151 12 6
TYPES OF DATA COLLECTED BY STUDY DESIGN 0 90 80 12 70 9 60 50 39 Validation Study 40 0 RCT 1 1 30 0 Obs. Retrospective 0 2 3 0 20 Obs. Prospective 3 26 0 6 24 17 8 16 Obs. Cross-sectional 10 5 0 3 0 0 6 3 4 3 2 0 1 3 2 2 2 2 0 1 1 1 1 0 0 5 13 SPECIFIC MMA METHODS BY STUDY DESIGN 90 0 80 12 70 9 60 50 39 40 Validation Study 0 RCT 30 2 1 Obs. Retrospective 4 20 0 0 Obs. Prospective 25 0 0 16 24 13 Obs. Cross-sectional 9 10 0 0 1 3 2 4 4 3 0 1 1 1 1 2 2 2 0 1 1 1 1 1 0 0 14 7
Priti Pednekar, MPharm, Graduate Student (PhD), Mayes College of Healthcare Business and Policy, University of the Sciences, Philadelphia, PA, USA 15 ADHERENCE MEASUREMENT METHODS BY DISEASE 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Cardivascular disorders Sexually transmitted Metabolic disorders Mental disorders disorders (HIV/AIDS) Quasi-Objective Self-report method Therapeutic outcome monitoring Drug level monitoring 16 8
QUASI-OBJECTIVE METHODS (1) 45% 46% of studies used 40% quasi-objective methods to measure MMA 35% 30% 25% 20% 15% 10% 5% 0% PDC MPR Medication gaps Other method Time to Persistence rate discontinuation Cardivascular disorders Sexually transmitted disorders (HIV/AIDS) Metabolic disorders Mental disorders 17 QUASI-OBJECTIVE METHODS (2) Cardiovascular Disorders Total Number of Studies 46 PDC 19 41.3% MPR 10 21.7% Medication gaps 1 2.2% Other method for calculating adherence rate 2 4.3% Time to discontinuation 9 19.6% Persistence rate 6 13.0% Sexually Transmitted Disease (HIV/AIDS) Total Number of Studies 45 PDC 3 6.7% MPR 1 2.2% Medication gaps 3 6.7% Other method for calculating adherence rate 8 17.8% Time to discontinuation 1 2.2% Persistence rate 1 2.2% 18 9
QUASI-OBJECTIVE METHODS (3) Metabolic Disorders Total Number of Studies 18 PDC 3 16.7% MPR 7 38.9% Medication gaps 1 5.6% Other method for calculating adherence rate 2 11.1% Time to discontinuation 3 16.7% Persistence rate 3 16.7% Mental Disorders Total Number of Studies 15 PDC 3 20.0% MPR 3 20.0% Medication gaps 1 6.7% Other method for calculating adherence rate 2 13.3% Time to discontinuation 1 6.7% Persistence rate 1 6.7% 19 MPR FOR MMA (N=25) Diseases investigated Calculation method n % Average of (∑days of supply for each medication/study period) 4 2.6% Cardiovascular (2), Metabolic (2) ∑days of supply for all medications/study period 3 2.0% Cardiovascular (3) ∑days with supply for any medication/study period 2 1.3% Mental (1), Urological (1) Average of (∑days of supply/(days between last prescription - first prescription) per medications); supply obtained in the last fill was 2 1.3% Cardiovascular (1), Metabolic (1) excluded (∑days of supply/(days between last prescription - first prescription) Cardiovascular (1), Mental (1), per medications) and if all were >80% then adherent; supply 1 0.7% Metabolic (1), Musculoskeletal (1), obtained in the last fill was excluded Respiratory (1) (∑days of supply/days of eligibility for that medication) per 1 0.7% Cardiovascular (1) medications and if all were ≥80% then adherent ∑days of supply for all medications/(days between last prescription - first prescription + days of supply for last fill - number of days in 1 0.7% Neurological (1) hospital) ∑days of supply for mutliple medications/(days between last 1 0.7% STD (1) prescription- first prescription + days of supply for last fill) ∑tablets dispensed/∑tablets recommended or prescribed 1 0.7% Metabolic (1) Weighted average of (∑days for supply)/days for which medication 1 0.7% Mental (1) was needed) per medications) 20 10
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