Evidence map›Paper›PMID 36217115›Full record

Trial reportBMC pregnancy and childbirth2022

Impact of an educational program and decision tool on choice of maternity hospital: the delivery decisions randomized clinical trial.

Ateev Mehrotra, Adam Wolfberg, Neel T Shah, Avery Plough, Amber Weiseth, Arianna I Blaine, Katie Noddin, Carter H Nakamoto, Jessica V Richard, Dani Bradley

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC pregnancy and childbirth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02987803 (Helping Mothers Select Better Childbirth Hospitals), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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.

NCT02987803 nacompletednot on this map

Helping Mothers Select Better Childbirth Hospitals

TypeinterventionalSponsorHarvard School of Public Health (HSPH)Ran2019 to 2021Enrolled120,621ConditionsCesarean SectionArmsData
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

10 authors.

Ateev MehrotraDepartment of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA, 02115, 617-432-3905, US. mehrotra@hcp.med.harvard.edu.
Adam WolfbergOvia Health, Boston, MA, US.
Neel T ShahAriadne Labs, Harvard T.H. Chan School of Public Health, Boston, MA, US.
Avery PloughAriadne Labs, Harvard T.H. Chan School of Public Health, Boston, MA, US.
Amber WeisethAriadne Labs, Harvard T.H. Chan School of Public Health, Boston, MA, US.
Arianna I BlaineOvia Health, Boston, MA, US.
Katie NoddinOvia Health, Boston, MA, US.
Carter H NakamotoDepartment of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA, 02115, 617-432-3905, US.
Jessica V RichardDepartment of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA, 02115, 617-432-3905, US.
Dani BradleyOvia Health, Boston, MA, US.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReducing cesarean rates is a public health priority. To help pregnant people select hospitals with lower cesarean rates, numerous organizations publish publically hospital cesarean rate data. Few pregnant people use these data when deciding where to deliver. We sought to determine whether making cesarean rate data more accessible and understandable increases the likelihood of pregnant people selecting low-cesarean rate hospitals.

methodsWe conducted a 1:1 randomized controlled trial in 2019-2021 among users of a fertility and pregnancy mobile application. Eligible participants were trying to conceive for fewer than five months or were 28-104 days into their pregnancies. Of 189,456 participants approached and enrolled, 120,621 participants met entry criteria and were included in analyses. The intervention group was offered an educational program explaining the importance of hospital cesarean rates and an interactive tool presenting hospital cesarean rates as 1-to-5-star ratings. Control group users were offered an educational program about hospital choice and a hospital choice tool without cesarean rate data. The primary outcome was the star rating of the hospital selected by each patient during pregnancy. Secondary outcomes were the importance of cesarean rates in choosing a hospital and delivery method (post-hoc secondary outcome).

resultsOf 120,621 participants (mean [SD] age, 27.8 [7.9]), 12,284 (10.2%) reported their choice of hospital during pregnancy, with similar reporting rates in the intervention and control groups. Intervention group participants selected hospitals with higher star ratings (2.52 vs 2.16; difference, 0.37 [95% CI, 0.32 to 0.43] p < 0.001) and were more likely to believe that the hospitals they chose would impact their chances of having cesarean deliveries (38.5% vs 33.1%, p < 0.001) but did not assign higher priority to cesarean delivery rates when choosing their hospitals (76.2% vs 74.3%, p = 0.05). There was no difference in self-reported cesarean rates between the intervention and control groups (31.4% vs 31.4%, p = 0.98).

conclusionPeople offered an educational program and interactive tool to compare hospital cesarean rates were more likely to use cesarean data in selecting a hospital and selected hospitals with lower cesarean rates but were not less likely to have a cesarean. CLINICAL

trial registrationRegistered December 9, 2016 at clinicaltrials.gov, First enrollment November 2019. ID NCT02987803, https://clinicaltrials.gov/ct2/show/NCT02987803.

Indexed as

Cesarean SectionHospitals, MaternityAdultFemaleHumansPregnancyResearch DesignCesarean deliveryPatient engagementPublic reporting of qualityRandomized controlled trial

Identifiers

PMID36217115
PMCPMC9549827

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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.