Evidence map›Paper›PMID 31709537›Full record

ArticleHealth services research2020

The impact of voluntary and nonpayment policies in reducing early-term elective deliveries among privately insured and Medicaid enrollees.

Lindsay Allen, Daniel Grossman

Open access · greenAbstract readComparative Study
In one paragraph

Article in Health services research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 26% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
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 at 1 institution in 1 country.

Lindsay AllenDepartment of Health Policy, Management, and Leadership, West Virginia University, Morgantown, West Virginia.ORCID 0000-0003-1723-9248
Daniel GrossmanDepartment of Economics, West Virginia University, Morgantown, West Virginia.ORCID 0000-0002-6878-6201
West Virginia University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo assess the impact of a voluntary pledge policy and a mandatory nonpayment policy on reducing early-term elective deliveries among privately insured and Medicaid-enrolled individuals. DATA SOURCES/STUDY

settingBirth certificate data from 2009 to 2015, from South Carolina and 16 control states. STUDY

designWe use a difference-in-differences approach to test the impact of two different policy types. Outcomes include the probability of an early elective delivery, gestation time, and birthweight. PRINCIPAL

findingsThe voluntary pledge and mandatory nonpayment policy reduced overall EED rates from 13.1 to 11.4 (-12.7 percent, [P < .05]), and 10.9 ([-16.6 percent, P < .05]), respectively. Compared to the privately insured, we found greater relative decreases in Medicaid EED rate, the proportion of Medicaid births occurring before 39 weeks, and the proportion of Medicaid babies born with low birthweight.

conclusionsBoth voluntary and mandatory nonpayment policies are effective in reducing the rate of EEDs, especially among Medicaid enrollees. Given the high costs and poor outcomes associated with EEDs, policy makers may consider using either tool as a way to improve care value.

Indexed as

AdultCesarean SectionElective Surgical ProceduresFemaleHealth ExpendituresHumansInsurance, HealthMedicaidPregnancyUnited Stateselective deliverieslow birthweightMedicaidpayment policiesprivate insurance

Identifiers

PMID31709537
PMCPMC6980963
OpenAlexW2984754684

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.