Cargando…
Referral transit time between sending and first-line receiving health facilities: a geographical analysis in Tanzania
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 ineffic...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6703299/ https://www.ncbi.nlm.nih.gov/pubmed/31478017 http://dx.doi.org/10.1136/bmjgh-2019-001568 |
_version_ | 1783445390385741824 |
---|---|
author | Schmitz, Michelle M Serbanescu, Florina Arnott, George E Dynes, Michelle Chaote, Paul Msuya, Abdulaziz Ally Chen, Yi No |
author_facet | Schmitz, Michelle M Serbanescu, Florina Arnott, George E Dynes, Michelle Chaote, Paul Msuya, Abdulaziz Ally Chen, Yi No |
author_sort | Schmitz, Michelle M |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6703299 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-67032992019-09-02 Referral transit time between sending and first-line receiving health facilities: a geographical analysis in Tanzania Schmitz, Michelle M Serbanescu, Florina Arnott, George E Dynes, Michelle Chaote, Paul Msuya, Abdulaziz Ally Chen, Yi No BMJ Glob Health Research 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. BMJ Publishing Group 2019-08-17 /pmc/articles/PMC6703299/ /pubmed/31478017 http://dx.doi.org/10.1136/bmjgh-2019-001568 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. 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/. |
spellingShingle | Research Schmitz, Michelle M Serbanescu, Florina Arnott, George E Dynes, Michelle Chaote, Paul Msuya, Abdulaziz Ally Chen, Yi No Referral transit time between sending and first-line receiving health facilities: a geographical analysis in Tanzania |
title | Referral transit time between sending and first-line receiving health facilities: a geographical analysis in Tanzania |
title_full | Referral transit time between sending and first-line receiving health facilities: a geographical analysis in Tanzania |
title_fullStr | Referral transit time between sending and first-line receiving health facilities: a geographical analysis in Tanzania |
title_full_unstemmed | Referral transit time between sending and first-line receiving health facilities: a geographical analysis in Tanzania |
title_short | Referral transit time between sending and first-line receiving health facilities: a geographical analysis in Tanzania |
title_sort | referral transit time between sending and first-line receiving health facilities: a geographical analysis in tanzania |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6703299/ https://www.ncbi.nlm.nih.gov/pubmed/31478017 http://dx.doi.org/10.1136/bmjgh-2019-001568 |
work_keys_str_mv | AT schmitzmichellem referraltransittimebetweensendingandfirstlinereceivinghealthfacilitiesageographicalanalysisintanzania AT serbanescuflorina referraltransittimebetweensendingandfirstlinereceivinghealthfacilitiesageographicalanalysisintanzania AT arnottgeorgee referraltransittimebetweensendingandfirstlinereceivinghealthfacilitiesageographicalanalysisintanzania AT dynesmichelle referraltransittimebetweensendingandfirstlinereceivinghealthfacilitiesageographicalanalysisintanzania AT chaotepaul referraltransittimebetweensendingandfirstlinereceivinghealthfacilitiesageographicalanalysisintanzania AT msuyaabdulazizally referraltransittimebetweensendingandfirstlinereceivinghealthfacilitiesageographicalanalysisintanzania AT chenyino referraltransittimebetweensendingandfirstlinereceivinghealthfacilitiesageographicalanalysisintanzania |