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Access to care following injury in Northern Malawi, a comparison of travel time estimates between Geographic Information System and community household reports.
Whitaker, John; Brunelli, Giulia; Van Boeckel, Thomas P; Dube, Albert; Amoah, Abena S; Rickard, Rory F; Leather, Andrew J M; Davies, Justine.
Afiliação
  • Whitaker J; King's Centre for Global Health and Health Partnerships, School of Population Health & Environmental Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK; Academic Department of Military Surgery and Trauma, Royal Centre for Defence Medicine, Birmingham, UK; Centre f
  • Brunelli G; Health geography and Policy Group, ETH Zurich, Switzerland.
  • Van Boeckel TP; Health geography and Policy Group, ETH Zurich, Switzerland; Center for Disease Dynamics Economics and Policy, Washington DC, United States.
  • Dube A; Malawi Epidemiology and Intervention Research Unit (MEIRU), Chilumba, Karonga District Malawi.
  • Amoah AS; Malawi Epidemiology and Intervention Research Unit (MEIRU), Chilumba, Karonga District Malawi; Department of Population Health, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
  • Rickard RF; Academic Department of Military Surgery and Trauma, Royal Centre for Defence Medicine, Birmingham, UK.
  • Leather AJM; King's Centre for Global Health and Health Partnerships, School of Population Health & Environmental Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.
  • Davies J; Centre for Applied Health Research, University of Birmingham, Birmingham, UK; Medical Research Council/Wits University Rural Public Health and Health Transitions Research Unit, Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa.
Injury ; 53(5): 1690-1698, 2022 May.
Article em En | MEDLINE | ID: mdl-35153068
ABSTRACT

INTRODUCTION:

Injuries disproportionately impact low- and middle-income countries like Malawi. The Lancet Commission on Global Surgery's indicators include the population proportion accessing laparotomy and open fracture care, key trauma interventions, within two hours. The "Golden Hour" for receiving facility-based resuscitation also guides injury care system strengthening. Firstly, we estimated the proportion of the local population able to reach primary, secondary and tertiary facility care within two and one hours using Geographic Information System (GIS) analysis. Secondly, we compared community household-reported with GIS-estimated travel time.

METHODS:

Using information from a Health and Demographic Surveillance Site (Karonga, Malawi) on road network, facility location, and local staff-estimated travel speeds, we used a GIS-generated friction surface to calculate the shortest travel time from all households to each facility serving the population. We surveyed community households who reported travel time to their preferred, closest, government secondary and tertiary facilities. For recently injured community members, time to reach facility care was recorded. To assess the relationship between community household-reported travel time and GIS-estimated travel time, we used linear regression to generate a proportionality constant. To assess associations and agreement between injured patient-reported and GIS-estimated travel time, we used Kendall rank and Cohen's kappa tests.

RESULTS:

Using GIS, we estimated 79.1% of households could reach any secondary facility, 20.5% the government secondary facility, and 0% the government tertiary facility, within two hours. Only 28.2% could reach any secondary facility within one hour, 0% for the government secondary facility. Community household-reported travel time exceeded GIS-estimated travel time. The proportionality constant was 1.25 (95%CI 1.21-1.30) for the closest facility, 1.28 (95%CI 1.23-1.34) for the preferred facility, 1.45 (95%CI 1.33-1.58) for the government secondary facility, and 2.12 (95%CI 1.84-2.41) for tertiary care. Comparing injured patient-reported with GIS-estimated travel time, the correlation coefficient was 0.25 (SE 0.047) and Cohen's kappa was 0.15 (95%CI 0.078-0.23), suggesting poor agreement.

DISCUSSION:

Most households couldn't reach government secondary care within recognised thresholds indicating poor temporal access. Since GIS-estimated travel time was shorter than community-reported travel time, the true proportion may be lower still. GIS derived estimates of population emergency care access in similar contexts should be interpreted accordingly.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sistemas de Informação Geográfica / Serviços Médicos de Emergência Tipo de estudo: Qualitative_research Limite: Humans País/Região como assunto: Africa Idioma: En Revista: Injury Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sistemas de Informação Geográfica / Serviços Médicos de Emergência Tipo de estudo: Qualitative_research Limite: Humans País/Região como assunto: Africa Idioma: En Revista: Injury Ano de publicação: 2022 Tipo de documento: Article