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Geographic access to emergency obstetric services: a model incorporating patient bypassing using data from Mozambique
  1. Emily B Keyes1,
  2. Caleb Parker2,
  3. Seth Zissette2,
  4. Patricia E Bailey3,
  5. Orvalho Augusto4
  1. 1Reproductive, Maternal, Newborn and Child Health, FHI 360, Durham, North Carolina, USA
  2. 2Behavioral, Epidemiological and Clinical Sciences, FHI 360, Durham, North Carolina, USA
  3. 3Averting Maternal Death and Disability Program (AMDD), Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York, USA
  4. 4Universidade Eduardo Mondlane, Maputo, Mozambique
  1. Correspondence to Emily B Keyes; ekeyes{at}fhi360.org

Abstract

Introduction Targeted approaches to further reduce maternal mortality require thorough understanding of the geographic barriers that women face when seeking care. Common measures of geographic access do not account for the time needed to reach services, despite substantial evidence that links proximity with greater use of facility services. Further, methods for measuring access often ignore the evidence that women frequently bypass close facilities based on perceptions of service quality. This paper aims to adapt existing approaches for measuring geographic access to better reflect women’s bypassing behaviour, using data from Mozambique.

Methods Using multiple data sources and modelling within a geographic information system, we calculated two segments of a patient’s time to care: (1) home to the first preferred facility, assuming a woman might travel longer to reach a facility she perceived to be of higher quality; and (2) referral between the first preferred facility and facilities providing the highest level of care (eg, surgery). Combined, these two segments are total travel time to highest care. We then modelled the impact of expanding services and emergency referral infrastructure.

Results The combination of upgrading geographically strategic facilities to provide the highest level of care and providing transportation to midlevel facilities modestly increased the percentage of the population with 2-hour access to the highest level of care (from 41% to 45%). The mean transfer time between facilities would be reduced by 39% (from 2.9 to 1.8 hours), and the mean total journey time by 18% (from 2.5 to 2.0 hours).

Conclusion This adapted methodology is an effective tool for health planners at all levels of the health system, particularly to identify areas of very poor access. The modelled changes indicate substantial improvements in access and identify populations outside timely access for whom more innovative interventions are needed.

  • geographic information systems
  • health systems
  • maternal health
  • obstetrics

This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

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Footnotes

  • Handling editor Sanni Yaya

  • Contributors EBK, CP and PEB contributed to all phases of the analysis and manuscript development. SZ contributed to the model design and analysis, and provided substantive review of the final article. OAJ was involved in implementing and analysing the facility-level data set and reviewed the final article.

  • Funding This study was carried out with support provided by the United States Agency for International Development (USAID) through MEASURE Evaluation (cooperative agreement AID-OAA-L-14-00004).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement All data sources are open source, other than the facility-level data. Access to facility data requires permission from the Mozambique Ministry of Health.