Evidence map›Paper›PMID 26989837›Full record

ArticleHealth services research2017

Effects of State Cervical Cancer Insurance Mandates on Pap Test Rates.

Marianne P Bitler, Christopher S Carpenter

Abstract read
In one paragraph

Article in Health services research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
–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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Government regulation of private health insurance.The Cochrane database of systematic reviews · 2021
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  9. Lessons from state mandates of preventive cancer screenings.The European journal of health economics : HEPAC : health economics in prevention and care · 2016
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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.

Marianne P BitlerDepartment of Economics, University of California, Davis, Davis, CA.
Christopher S CarpenterDepartment of Economics, Vanderbilt University, Nashville, TN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the effects of state insurance mandates requiring insurance plans to cover Pap tests, the standard screening for cervical cancer that is recommended for nearly all adult women. DATA SOURCES: Individual-level data on 600,000 women age 19-64 from the CDC's Behavioral Risk Factor Surveillance System. STUDY

designTwenty-four states adopted state mandates requiring private insurers in the state to cover Pap tests from 1988 to 2000. We performed a difference-in-differences analysis comparing within-state changes in Pap test rates before and after adoption of a mandate, controlling for the associated changes in other states that did not adopt a mandate. PRINCIPAL

findingsDifference-in-differences estimates indicated that the Pap test mandates significantly increased past 2-year cervical cancer screenings by 1.3 percentage points, with larger effects for Hispanic and non-Hispanic white women. These effects are plausibly concentrated among insured women.

conclusionsMandating more generous insurance coverage for even inexpensive, routine services with already high utilization rates such as Pap tests can significantly further increase utilization.

Indexed as

Mandatory ProgramsAdultBehavioral Risk Factor Surveillance SystemEarly Detection of CancerFemaleHumansInsurance CoverageInsurance, HealthMiddle AgedPapanicolaou TestState GovernmentUnited StatesUterine Cervical NeoplasmsYoung Adultcervical cancerdifference-in-differencesInsurance mandatesPap tests

Identifiers

PMID26989837
PMCPMC5264101

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.