Scott B Cantor1, Tanya Rajan2, Suzanne K Linder3, Robert J Volk2. 1. Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. Electronic address: sbcantor@mdanderson.org. 2. Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. 3. Department of General Internal Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Abstract
OBJECTIVE: Patient decision aids are important tools for facilitating balanced, evidence-based decision making. However, the potential of decision aids to lower health care utilization and costs is uncertain; few studies have investigated the cost-effectiveness of decision aids that change patient behavior. Using an example of a decision aid for colorectal cancer screening, we provide a framework for analyzing the cost-effectiveness of decision aids. METHODS: A decision-analytic model with two strategies (decision aid or no decision aid) was used to calculate expected costs in U.S. dollars and benefits measured in life-years saved (LYS). Data from a systematic review of ten studies about decision aid effectiveness was used to calculate the percentage increase in the number of people choosing screening instead of no screening. We then calculated the incremental cost per LYS with the use of the decision aid. RESULTS: The no decision aid strategy had an expected cost of $3023 and yielded 18.19 LYS. The decision aid strategy cost $3249 and yielded 18.20 LYS. The incremental cost-effectiveness ratio for the decision aid strategy was $36,126 per LYS. Results were sensitive to the cost of the decision aid and the percentage change in behavior caused by the decision aid. CONCLUSIONS: This study provides proof-of-concept evidence for future studies examining the cost-effectiveness of decision aids. The results suggest that decision aids can be beneficial and cost-effective. Published by Elsevier Inc.
OBJECTIVE:Patient decision aids are important tools for facilitating balanced, evidence-based decision making. However, the potential of decision aids to lower health care utilization and costs is uncertain; few studies have investigated the cost-effectiveness of decision aids that change patient behavior. Using an example of a decision aid for colorectal cancer screening, we provide a framework for analyzing the cost-effectiveness of decision aids. METHODS: A decision-analytic model with two strategies (decision aid or no decision aid) was used to calculate expected costs in U.S. dollars and benefits measured in life-years saved (LYS). Data from a systematic review of ten studies about decision aid effectiveness was used to calculate the percentage increase in the number of people choosing screening instead of no screening. We then calculated the incremental cost per LYS with the use of the decision aid. RESULTS: The no decision aid strategy had an expected cost of $3023 and yielded 18.19 LYS. The decision aid strategy cost $3249 and yielded 18.20 LYS. The incremental cost-effectiveness ratio for the decision aid strategy was $36,126 per LYS. Results were sensitive to the cost of the decision aid and the percentage change in behavior caused by the decision aid. CONCLUSIONS: This study provides proof-of-concept evidence for future studies examining the cost-effectiveness of decision aids. The results suggest that decision aids can be beneficial and cost-effective. Published by Elsevier Inc.
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