AI Article Synopsis
- - The study focuses on rising healthcare costs and the need to stop low-value medical practices, aiming to analyze randomized controlled trials (RCTs) to better understand and enhance de-implementation strategies.
- - Out of 227 eligible trials, the majority were cluster randomized and took place mainly in primary care, with many interventions directed at reducing unnecessary drug treatments and predominantly targeting physicians.
- - Findings indicate that there are significant limitations in current de-implementation research, such as high risk of bias and lack of context-specific tailoring, which may affect the reliability and applicability of the results.
Article 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.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9526943 | PMC |
| http://dx.doi.org/10.1186/s13012-022-01238-z | DOI Listing |
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