EVIDENCE AND VALUE- IMPACT ON DECISION MAKING - THE EVIDEM FRAMEWORK AND POTENTIAL APPLICATIONS
Author(s)
Mireille M Goetghebeur, PhD, VP Operations, Monika Wagner, PhD, Director Research Application, Hanane Khoury, PhD, Senior Research Application Associate, Randy Levitt, PhD, Senior Research Application Associate, Lonny J Erickson, PhD, Senior Associate, Health Technology Assessment, Donna Rindress, PhD, President & Managing Director BioMedCom Consultants Inc, Montreal, QC, Canada
Develop a quantitative and practical methodology to structure, objectify and facilitate health care decisionmaking. A conceptual framework was developed that segregated components of decision-making into three categories: 1) quality of evidence available; 2) intrinsic value of the health care intervention; and 3) extrinsic or system related value, usually not directly quantifiable. Using this framework, practical tools to assess health care interventions were designed drawing on an extensive review of the literature and of current decisionmaking processes for drug reimbursement around the world. A matrix to quantify the quality of evidence available for a healthcare intervention was designed including 5 elements defining quality, clustered into three criteria, and 12 components covering types of evidence required by decision-making bodies worldwide. A scoring process was developed based on international scientific standards in each field of research covered. To quantify the intrinsic value of an intervention, a multi-criteria decision analysis (MCDA) matrix was designed encompassing 15 value components. Scoring, which depends on the value system of the evaluator, was designed to allow inclusion of perspectives of a representative group of health care stakeholders. An integrated process to apply matrices was established. The EVIDEM methodology can be applied retrospectively to explore the contribution of quality of evidence and intrinsic value to past coverage decisions. Prospectively, matrices can be adapted to specific needs of decision-makers and applied to evaluate new health care interventions. The matrices also provide a practical collaborative framework for those who generate data and those who need data to make decisions, ultimately facilitating future health care decision-making.
Conference/Value in Health Info
2008-05, ISPOR 2008, Toronto, Ontario, Canada
Value in Health, Vol. 11, No. 3 (May/June 2008)
Code
PMC50
Topic
Methodological & Statistical Research
Topic Subcategory
Modeling and simulation
Disease
Multiple Diseases