A COMPARATIVE EFFECTIVENESS INDEX TO INFORM CLINICAL DECISIONS

Author(s)

Horowicz-Mehler N1, Doyle J2, Arikian S3, Hagan M41Quintiles Global Consulting, Hawthorne, NY, USA, 2Quintiles, Hawthorne, NY, USA, 3Genesis BioPharma, Hoboken, NJ, USA, 4TBD, New York, NY, USA

OBJECTIVES: Present a framework to systematically measure and combine key attributes of health interventions into a single Comparative Effectiveness Index (CEI). METHODS: Relevant attributes including efficacy/effectiveness, compliance/persistency, safety, health-related quality of life (HRQoL)/utility are linked through a transparent formula. Efficacy and effectiveness are gathered from a meta-analysis of randomized controlled trials and observational studies, accordingly. Compliance and persistency are be derived from pharmacy claims data using metrics such as the medication possession ratio. We propose a 5-point rating scale for the safety measure from low risk “suitable for widespread use” to high risk “careful consideration of risk versus benefit”. We also consider a combined measure of risk-benefit assessment borrowing from existing quantitative methods such as a Number Needed to Treat and Number Needed to Harm. Generic or disease-specific patient-reported outcome measures provide information on the impact of the intervention on the patient’s HRQoL and indicate the value of a specific treatment for a given health state. To ensure relevant comparisons, we account for therapeutic area when assessing the CEI of multiple interventions. Finally, a measure of quality of evidence (Jadad score) ensure that only evidence from robust designs fed the CEI. CONCLUSION: The CEI aims to provide a comprehensive and balanced picture of disparate yet linked performance attributes. Currently, a complete picture of health interventions is not centralized and not easily accessible thus limiting informed clinical decision-making by various stakeholders (physicians, patients, payers and policy makers). This index is intended to guide healthcare participants in making evidence-based clinical decisions at the population and patient levels such that a provider might want to trade-off effectiveness for increase safety when treating a patient with severe comorbidities. For full transparency and use, we propose the creation of a US publically available web-based database of the information underlying the index.

Conference/Value in Health Info

2011-05, ISPOR 2011, Baltimore, MD, USA

Value in Health, Vol. 14, No. 3 (May 2011)

Code

EV3

Topic

Methodological & Statistical Research

Topic Subcategory

Confounding, Selection Bias Correction, Causal Inference

Disease

Multiple Diseases

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