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Abstract Background De-implementation of low-value care can increase health care sustainability. We evaluated the reporting of direct costs of de-implementation and subsequent change (increase or decrease) in health care costs in randomized trials of de-implementation research. Methods We searched MEDLINE and Scopus databases without any language restrictions up to May 2021. We conducted study screening and data extraction independently and in duplicate. We extracted information related to study characteristics, types and characteristics of interventions, de-implementation costs, and impacts on health care costs. We assessed risk of bias using a modified Cochrane risk-of-bias tool. Results We screened 10,733 articles, with 227 studies meeting the inclusion criteria, of which 50 included information on direct cost of de-implementation or impact of de-implementation on health care costs. Studies were mostly conducted in North America (36%) or Europe (32%) and in the primary care context (70%). The most common practice of interest was reduction in the use of antibiotics or other medications (74%). Most studies used education strategies (meetings, materials) (64%). Studies used either a single strategy (52%) or were multifaceted (48%). Of the 227 eligible studies, 18 (8%) reported on direct costs of the used de-implementation strategy; of which, 13 reported total costs, and 12 reported per unit costs (7 reported both). The costs of de-implementation strategies varied considerably. Of the 227 eligible studies, 43 (19%) reported on impact of de-implementation on health care costs. Health care costs decreased in 27 studies (63%), increased in 2 (5%), and were unchanged in 14 (33%). Conclusion De-implementation randomized controlled trials typically did not report direct costs of the de-implementation strategies (92%) or the impacts of de-implementation on health care costs (81%). Lack of cost information may limit the value of de-implementation trials to decision-makers. Trial registration OSF (Open Science Framework): https://osf.io/ueq32 .

Abstract Background Healthcare costs are rising, and a substantial proportion of medical care is of little value. De-implementation of low-value practices is important for improving overall health outcomes and reducing costs. We aimed to identify and synthesize randomized controlled trials (RCTs) on de-implementation interventions and to provide guidance to improve future research. Methods MEDLINE and Scopus up to May 24, 2021, for individual and cluster RCTs comparing de-implementation interventions to usual care, another intervention, or placebo. We applied independent duplicate assessment of eligibility, study characteristics, outcomes, intervention categories, implementation theories, and risk of bias. Results Of the 227 eligible trials, 145 (64%) were cluster randomized trials (median 24 clusters; median follow-up time 305 days), and 82 (36%) were individually randomized trials (median follow-up time 274 days). Of the trials, 118 (52%) were published after 2010, 149 (66%) were conducted in a primary care setting, 163 (72%) aimed to reduce the use of drug treatment, 194 (85%) measured the total volume of care, and 64 (28%) low-value care use as outcomes. Of the trials, 48 (21%) described a theoretical basis for the intervention, and 40 (18%) had the study tailored by context-specific factors. Of the de-implementation interventions, 193 (85%) were targeted at physicians, 115 (51%) tested educational sessions, and 152 (67%) multicomponent interventions. Missing data led to high risk of bias in 137 (60%) trials, followed by baseline imbalances in 99 (44%), and deficiencies in allocation concealment in 56 (25%). Conclusions De-implementation trials were mainly conducted in primary care and typically aimed to reduce low-value drug treatments. Limitations of current de-implementation research may have led to unreliable effect estimates and decreased clinical applicability of studied de-implementation strategies. We identified potential research gaps, including de-implementation in secondary and tertiary care settings, and interventions targeted at other than physicians. Future trials could be improved by favoring simpler intervention designs, better control of potential confounders, larger number of clusters in cluster trials, considering context-specific factors when planning the intervention (tailoring), and using a theoretical basis in intervention design. Registration OSF Open Science Framework hk4b2