Evidence map›Paper›PMID 30977860›Full record

ArticleJAMA network open2019

Estimation of 1-Year Changes in Medicaid Expenditures Associated With Reducing Cigarette Smoking Prevalence by 1.

Stanton A Glantz

Erratum issuedAbstract readEvaluation Study
In one paragraph

Article in JAMA network open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Development of a Tobacco Control Prescription in a Southern US City.Progress in community health partnerships : research, education, and action · 2019
    Article
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Stanton A GlantzCenter for Tobacco Control Research and Education, Philip R. Lee Institute for Health Policy Studies, Department of Medicine, University of California, San Francisco.

Funding

Effect of Tobacco Advocacy at the State LevelR01DA043950 · NIDA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI APOLLONIO, DOROTHY ELINOR · 2016 to 2020
$2.6M
NIDA NIH HHS R01 DA043950
6 · The paper itself

Abstract

Importance: Reducing smoking is associated with a reduction in health care costs, including in the short run. Medicaid recipients smoke at higher rates than the general population, which suggests that investments to reduce smoking in this population would reduce short-run Medicaid costs. Objective: To estimate the short-run (1-year) change in health care expenditure associated with a 1% decrease in absolute smoking prevalence in all US states. Design, Setting, and Participants: Economic evaluation based on state Medicaid expenditures and the elasticity between changes in smoking prevalence and health care costs. Data sources were the 2017 Behavioral Risk Factors Surveillance System, 2017 National Health Interview Survey, and Kaiser Family Foundation Total Medicaid Spending for fiscal year 2017. Analysis was conducted in 2018. Participants were all people receiving Medicaid in all US states and the District of Columbia. Exposures: Cigarette smoking. Main Outcomes and Measures: Short-run (1-year) change in health care costs. Results: Reducing absolute smoking prevalence by 1% in each state was associated with substantial Medicaid savings the following year, totaling $2.6 billion (in 2017 dollars). Each state saved a median (interquartile range) of $25 million ($8 million to $35 million). Conclusions and Relevance: Effective efforts to reducing smoking could be a cost-effective way to reduce Medicaid costs in the short run.

Indexed as

AdultCigarette SmokingCost-Benefit AnalysisFemaleHealth ExpendituresHumansMaleMedicaidMiddle AgedPrevalenceSmoking CessationUnited States

Identifiers

PMID30977860
PMCPMC6481435

What OpenQuestion holds

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LicenceTDM
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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.