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Research
Referral transit time between sending and first-line receiving health facilities: a geographical analysis in Tanzania
  1. Michelle M Schmitz1,
  2. Florina Serbanescu1,
  3. George E Arnott1,
  4. Michelle Dynes1,
  5. Paul Chaote2,
  6. Abdulaziz Ally Msuya3,
  7. Yi No Chen1
  1. 1Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
  2. 2Kigoma Regional Medical Office, Kigoma, Tanzania, United Republic of
  3. 3AMCA Inter-Consult Ltd, Dar es Salaam, Tanzania, United Republic of
  1. Correspondence to Michelle M Schmitz; MSchmitz1{at}cdc.gov

Abstract

Background Timely, high-quality obstetric services are vital to reduce maternal and perinatal mortality. We spatially modelled referral pathways between sending and receiving health facilities in Kigoma Region, Tanzania, identifying communication and transportation delays to timely care and inefficient links within the referral system.

Methods We linked sending and receiving facilities to form facility pairs, based on information from a 2016 Health Facility Assessment. We used an AccessMod cost-friction surface model, incorporating road classifications and speed limits, to estimate direct travel time between facilities in each pair. We adjusted for transportation and communications delays to create a total travel time, simulating the effects of documented barriers in this referral system.

Results More than half of the facility pairs (57.8%) did not refer patients to facilities with higher levels of emergency obstetric care. The median direct travel time was 25.9 min (range: 4.4–356.6), while the median total time was 106.7 min (22.9–371.6) at the moderate adjustment level. Total travel times for 30.7% of facility pairs exceeded 2 hours. All facility pairs required some adjustments for transportation and communication delays, with 94.0% of facility pairs’ total times increasing.

Conclusion Half of all referral pairs in Kigoma Region have travel time delays nearly exceeding 1 hour, and facility pairs referring to facilities providing higher levels of care also have large travel time delays. Combining cost-friction surface modelling estimates with documented transportation and communications barriers provides a more realistic assessment of the effects of inter-facility delays on referral networks, and can inform decision-making and potential solutions in referral systems within resource-constrained settings.

  • AccessMod
  • referral system
  • transportation
  • communication
  • Kigoma

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjgh-2019-001568

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    Footnotes

    • Handling editor Seye Abimbola

    • Contributors MMS, FS and YNC conceived and designed the study. MMS, GEA and YNC conducted the analysis and interpreted the data. MMS, FS and YNC coordinated the data collection and wrote the first draft of the manuscript. PC, AA, and MD were involved in revising the manuscript based on fieldwork-based experience. MMS, FS and YNC agreed to be accountable for all aspects of the work ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors read and approved the final manuscript submitted for publication.

    • Funding This study was funded by Bloomberg Philanthropies and the Fondation H&B Agerup.

    • Competing interests None declared.

    • Patient consent for publication Not required.

    • Ethics approval This study was reviewed and approved by the CDC's Center for Global Health Human Subject Review Board and was determined not to comprise human subjects research.

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

    • Data availability statement Data may be obtained from a third party and are not publicly available.