Evidence map›Paper›PMID 16704675›Full record

ArticleHealth services research2006

Health services research as a source of legislative analysis and input: the role of the California Health Benefits Review Program.

Thomas R Oliver, Rachel Friedman Singer

Abstract read
In one paragraph

Article in Health services research, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. The Massachusetts health insurance law: providing health insurance to all.Journal of the National Medical Association · 2006
    Article
  7. State-mandated benefit review laws.Health services research · 2006
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Thomas R OliverDepartment of Health Policy and Management, Johns Hopkins University, Bloomberg School of Public Health, 624 N. Broadway, Room 403, Baltimore, MD 21205, USA.
Rachel Friedman Singer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article examines the role of the California Health Benefits Review Program (CHBRP) as a source of information in state health policy making. It explains why the California benefits review process relies heavily on university-based researchers and employs a broad set of criteria for review, which set it apart from similar programs in other states. It then analyzes the politics of health insurance mandates and how independent research and analysis might alter the perceived benefits and costs of health insurance mandates and thus political outcomes. It considers how research and analysis is typically used by policy makers, and illustrates how participants inside and outside of state government have used the reports prepared by CHBRP as both guidance in policy design and as political ammunition. Although there is consensus that the review process has reduced the number of mandate bills that are passed out of the legislature, both supporters and opponents favor the new process and generally believe the reports strengthen their case in legislative debates over health insurance mandates. The role of the CHBRP is narrowly defined by statute at the present time, but the program may well face pressure to evolve from its current academic orientation into a more interactive, advisory role for legislators in the future.

Indexed as

Health Services ResearchInsurance, HealthRoleUniversitiesCaliforniaHealth PolicyInsurance BenefitsMandatory ProgramsPoliticsProgram DevelopmentProgram Evaluation

Identifiers

PMID16704675
PMCPMC1713221

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.