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Is the closest health facility the one used in pregnancy care-seeking? A cross-sectional comparative analysis of self-reported and modelled geographical access to maternal care in Mozambique, India and Pakistan
- Source :
- International Journal of Health Geographics, Vol 19, Iss 1, Pp 1-10 (2020), International Journal of Health Geographics
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- Background Travel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled access predicts fairly the vulnerability in women seeking maternal care across different spatial settings. Objectives This cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility. Methods Women were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland–Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used. Results Modelled geographical access (P) is generally lower than self-reported access (R), but there is a geography to this relationship. In India and Pakistan, potential access (P) compared fairly with self-reported travel times (R) [P (H0: Mean difference = 0)] 0: Mean difference = 0) = 0.31, limits of agreement: [− 187.26; 199.96]]. Conclusion Modelling access successfully predict potential vulnerability in populations. Differences between modelled (P) and self-reported travel times (R) are partially a result of women not seeking care at their closest facilities. Modelling access should not be viewed through a geographically static lens. Modelling assumptions are likely modified by spatio-temporal and/or socio-cultural settings. Geographical stratification of access reveals disproportionate variations in differences emphasizing the varied nature of assumptions across spatial settings. Trial registration ClinicalTrials.gov, NCT01911494. Registered 30 July 2013, https://clinicaltrials.gov/ct2/show/NCT01911494
- Subjects :
- Adult
medicine.medical_specialty
General Computer Science
Health geography
Psychological intervention
Vulnerability
India
Realised access
lcsh:Computer applications to medicine. Medical informatics
Health informatics
Health Services Accessibility
Pre-Eclampsia
Health facility
Pregnancy
Fixed bias
medicine
Humans
Maternal Health Services
Pakistan
Proportional bias
Mozambique
Limits of agreement
Bland–Altman Index
Travel
Box plot
Median
Geography
business.industry
Research
Public health
Public Health, Environmental and Occupational Health
Patient Acceptance of Health Care
General Business, Management and Accounting
Cross-Sectional Studies
lcsh:R858-859.7
Female
Self Report
business
Potential access
Demography
Subjects
Details
- ISSN :
- 1476072X
- Volume :
- 19
- Database :
- OpenAIRE
- Journal :
- International Journal of Health Geographics
- Accession number :
- edsair.doi.dedup.....9cc95d37f875a3a74b7e1218c231ccb1