Evidence map›Paper›PMID 35613799›Full record

ArticleBMJ open2022

Comparing absolute and relative distance and time travel measures of geographic access to healthcare facilities in rural Haiti.

Kayleigh Pavitra Bhangdia, Hari S Iyer, Jean Paul Joseph, Rubin Lemec Dorne, Joia Mukherjee, Temidayo Fadelu

Abstract read
In one paragraph

Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the 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.

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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
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

6 authors.

Kayleigh Pavitra BhangdiaDepartment of Global Health and Population, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA kbhangdia@gmail.com.ORCID 0000-0003-4235-0685
Hari S IyerDivision of Population Science, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
Jean Paul JosephPartners In Health/Zanmi Lasante, Mirebalais, Haiti.
Rubin Lemec DornePartners In Health/Zanmi Lasante, Mirebalais, Haiti.
Joia MukherjeeDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Temidayo FadeluDivision of Population Science, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.ORCID 0000-0002-1323-4119

Funding

Training Program in Cancer EpidemiologyT32CA009001 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI A. Heather Eliassen, Meir Stampfer · 1985 to 2026
$17.3M
NCI NIH HHS T32 CA009001
6 · The paper itself

Abstract

introductionWhile travel distance and time are important proxies of physical access to health facilities, obtaining valid measures with an appropriate modelling method remains challenging in many settings. We compared five measures of geographic accessibility in Haiti, producing recommendations that consider available analytic resources and geospatial goals.

methodsEight public hospitals within the ministry of public health and population were included. We estimated distance and time between hospitals and geographic centroids of Haiti's section communes and population-level accessibility. Geographic feature data were obtained from public administrative databases, academic research databases and government satellites. We used validated geographic information system methods to produce five geographic access measures: (1) Euclidean distance (ED), (2) network distance (ND), (3) network travel time (NTT), (4) AccessMod 5 (AM5) distance (AM5D) and (5) AM5 travel time (AM5TT). Relative ranking of section communes across the measures was assessed using Pearson correlation coefficients, while mean differences were assessed using analysis of variance (ANOVA) and pairwise t-tests.

resultsAll five geographic access measures were highly correlated (range: 0.78-0.99). Of the distance measures, ED values were consistently the shortest, followed by AM5D values, while ND values were the longest. ND values were as high as 2.3 times ED values. NTT models generally produced longer travel time estimates compared with AM5TT models. ED consistently overestimated population coverage within a given threshold compared with ND and AM5D. For example, population-level accessibility within 15 km of the nearest studied hospital in the Center department was estimated at 68% for ED, 50% for AM5D and 34% for ND.

conclusionWhile the access measures were highly correlated, there were significant differences in the absolute measures. Consideration of the benefits and limitations of each geospatial measure together with the intended purpose of the estimates, such as relative proximity of patients or service coverage, are key to guiding appropriate use.

Indexed as

Health FacilitiesHealth Services AccessibilityHaitiHumansRural PopulationTravelgeographic information systemsHaitihealthcare accessibilityhealth equitytravel distancetravel time

Identifiers

PMID35613799
PMCPMC9174809

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.