Evidence map›Paper›PMID 35655212›Full record

ArticleBMC health services research2022

Enablers and barriers to post-discharge follow-up among women who have undergone a caesarean section: experiences from a prospective cohort in rural Rwanda.

Theoneste Nkurunziza, Robert Riviello, Frederick Kateera, Edison Nihiwacu, Jonathan Nkurunziza, Magdalena Gruendl, Stefanie J Klug, Bethany Hedt-Gauthier

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2022. 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
1.5field-weighted citation impact, top 18% 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, 8 citations in OpenAlex.

  1. Pooled it
  2. Observational
  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

8 authors at 3 institutions in 3 countries.

Theoneste NkurunzizaPartners In Health/Inshuti Mu Buzima, KG 9 Avenue 46, PO Box 3432, Kigali, Rwanda. theonkrz@gmail.com.
Robert RivielloDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, USA.
Frederick KateeraPartners In Health/Inshuti Mu Buzima, KG 9 Avenue 46, PO Box 3432, Kigali, Rwanda.
Edison NihiwacuPartners In Health/Inshuti Mu Buzima, KG 9 Avenue 46, PO Box 3432, Kigali, Rwanda.
Jonathan NkurunzizaPartners In Health/Inshuti Mu Buzima, KG 9 Avenue 46, PO Box 3432, Kigali, Rwanda.
Magdalena GruendlEpidemiology Department of Sports and Health Sciences, Technical University of Munich, Munich, Germany.
Stefanie J KlugEpidemiology Department of Sports and Health Sciences, Technical University of Munich, Munich, Germany.
Bethany Hedt-GauthierDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, USA.
University of Global Health Equity · RWHarvard Global Health Institute · USTechnical University of Munich · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCaesarean sections account for roughly one third of all surgical procedures performed in low-income countries. Due to lack of standardised post-discharge follow-up protocols and practices, most of available data are extracted from clinical charts during hospitalization and are thus sub-optimal for answering post-discharge outcomes questions. This study aims to determine enablers and barriers to returning to the hospital after discharge among women who have undergone a c-section at a rural district hospital in Rwanda.

methodsWomen aged ≥ 18 years who underwent c-section at Kirehe District Hospital in rural Rwanda in the period March to October 2017 were prospectively followed. A structured questionnaire was administered to participants and clinical data were extracted from medical files between March and October 2017. At discharge, consenting women were given an appointment to return for follow-up on postoperative day 10 (POD 10) (± 3 days) and provided a voucher to cover transport and compensation for participation to be redeemed on their return. Study participants received a reminder call on the eve of their scheduled appointment. We used a backward stepwise logistic regression, at an α = 0.05 significance level, to identify enablers and barriers associated with post-discharge follow-up return.

resultsOf 586 study participants, the majority (62.6%) were between 21-30 years old and 86.4% had a phone contact number. Of those eligible, 90.4% returned for follow-up. The predictors of return were counselling by a female data collector (OR = 9.85, 95%CI:1.43-37.59) and receiving a reminder call (OR = 16.47, 95%CI:7.07-38.38). Having no insurance reduced the odds of returning to follow-up (OR = 0.03, 95%CI:0.03-0.23), and those who spent more than 10.6 Euro for transport to and from the hospital were less likely to return to follow-up (OR = 0.14, 95%CI:0.04- 0.50).

conclusionmHealh interventions using calls or notifications can increase the post-discharge follow-up uptake. The reminder calls to patients and discharge counselling by a gender-matching provider had a positive effect on return to care. Further interventions are needed targeting the uninsured and patients facing transportation hardship. Additionally, association between counselling of women patients by a female data collector and greater return to follow-up needs further exploration to optimize counselling procedures.

Indexed as

Cesarean SectionPatient DischargeAdultAftercareFemaleFollow-Up StudiesHospitals, DistrictHumansPregnancyProspective StudiesRwandaYoung AdultFollow-upGlobal surgerymHealthPost-discharge careSub-Saharan AfricaSurgical site infections

Identifiers

PMID35655212
PMCPMC9160515
OpenAlexW4281737833

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.