Undetermined impact of patient decision support interventions on healthcare costs and savings: systematic review

• Published in: BMJ (Online) 2014-01, Vol.348 (7944), p.g188-g188
• Main Authors: Walsh, Thom, Barr, Paul James, Thompson, Rachel, Ozanne, Elissa, O’Neill, Ciaran, Elwyn, Glyn
• Format: Article
• Language: English
• Subjects: Clinical decision making; Cost control; Cost-Benefit Analysis; Decision making; Decision support systems; Decision Support Techniques; Design; Evidence-based medicine; Health care; Health Care Costs; Health care expenditures; Health care policy; Health costs; Health Promotion - economics; Humans; Intervention; Interventions; Medical treatment; Patients; Quality of care; Resource utilization; Risk assessment; Savings; Sensitivity analysis; Systematic review
• ISSN: 0959-8138; 1756-1833; 0959-8146; 1756-1833
• DOI: 10.1136/bmj.g188

Objective To perform a systematic review of studies that assessed the potential of patient decision support interventions (decision aids) to generate savings. Design Systematic review. Data sources After registration with PROSPERO, we searched 12 databases, from inception to 15 March 2013, using relevant MeSH terms and text words. Included studies were assessed with Cochrane’s risk of bias method and Drummond’s quality checklist for economic studies. Per patient costs and projected savings associated with introducing patient decision support interventions were calculated, as well as absolute changes in treatment rates after implementation. Eligibility criteria Studies were included if they contained quantitative economic data, including savings, spending, costs, cost effectiveness analysis, cost benefit analysis, or resource utilization. We excluded studies that lacked quantitative data on savings, costs, monetary value, and/or resource utilization. Results After reviewing 1508 citations, we included seven studies with eight analyses. Of these seven studies, four analyses predicted system-wide savings, with two analyses from the same study. The predicted savings range from $8 (£5, €6) to $3068 (£1868, €2243) per patient. Larger savings accompanied reductions in treatment utilization rates. The impact on utilization rates was mixed. Authors used heterogeneous methods to allocate costs and calculate savings. Quality scores were low to moderate (median 4.5, range 0-8 out of 10), and risk of bias across the studies was moderate to high (3.5, range 3-6 out of 6), with studies predicting the most savings having the highest risk of bias. The range of issues identified in the studies included the relative absence of sensitivity analyses, the absence of incremental cost effectiveness ratios, and short time periods. Conclusion Although there is evidence to show that patients choose more conservative approaches when they become better informed, there is insufficient evidence, as yet, to be confident that the implementation of patient decision support interventions leads to system-wide savings. Further work—with sensitivity analyses, longer time horizons, and more contexts—is required to avoid premature or unrealistic expectations that could jeopardize implementation and lead to the loss of already proved benefits. Registration PROSPERO registration CRD42012003421.