ArticleThe Milbank quarterly2009
Translating medical effectiveness research into policy: lessons from the California Health Benefits Review Program.
Article in The Milbank quarterly, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Strategies for effective dissemination of research to United States policymakers: a systematic review.Implementation science : IS · 2020Pooled it
- Conflicts of interest and critiques of the use of systematic reviews in policymaking: an analysis of opinion articles.Systematic reviews · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextLegislatures and executive branch agencies in the United States and other nations are increasingly using reviews of the medical literature to inform health policy decisions. To clarify these efforts to give policymakers evidence of medical effectiveness, this article discusses the California Health Benefits Review Program (CHBRP). This program, based at the University of California, analyzes the medical effectiveness of health insurance benefit mandate bills for the California legislature, as well as their impact on cost and public health.
methodsThis article is based on the authors' experience reviewing benefit mandate bills for CHBRP and findings from evaluations of the program. General observations are illustrated with examples from CHBRP's reports. Information about efforts to incorporate evidence into health policymaking in other states and nations was obtained through a review of published literature.
findingsCHBRP produces reports that California legislators, legislative staff, and other major stakeholders value and use routinely in deliberations about benefit mandate bills. Where available, the program relies on previously published meta-analyses and systematic reviews to streamline the review of the medical literature. Faculty and staff responsible for the medical effectiveness sections of CHBRP's reports have learned four major lessons over the course of the program's six-year history: the need to (1) recognize the limitations of the medical literature, (2) anticipate the need to inform legislators about the complexity of evidence, (3) have realistic expectations regarding the impact of medical effectiveness reviews, and (4) understand the consequences of the reactive nature of mandated benefit reviews.
conclusionsCHBRP has demonstrated that it is possible to produce useful reviews of the medical literature within the tight time constraints of the legislative process. The program's reports have provided state legislators with independent analyses that allow them to move beyond sifting through conflicting information from proponents and opponents to consider difficult policy choices and their implications.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.