Dataset Information

Using open-source data to construct 20 metre resolution maps of children's travel time to the nearest health facility.

ABSTRACT: Physical access to health facilities is an important factor in determining treatment seeking behaviour and has implications for targets within the Sustainable Development Goals, including the right to health. The increased availability of high-resolution land cover and road data from satellite imagery offers opportunities for fine-grained estimations of physical access which can support delivery planning through the provision of more realistic estimates of travel times. The data presented here is of travel time to health facilities in Uganda, Zimbabwe, Tanzania, and Mozambique. Travel times have been calculated for different facility types in each country such as Dispensaries, Health Centres, Clinics and Hospitals. Cost allocation surfaces and travel times are provided for child walking speeds but can be altered easily to account for adult walking speeds and motorised transport. With a focus on Uganda, we describe the data and method and provide the travel maps, software and intermediate datasets for Uganda, Tanzania, Zimbabwe and Mozambique.

SUBMITTER: Watmough GR

PROVIDER: S-EPMC9113998 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Using open-source data to construct 20 metre resolution maps of children's travel time to the nearest health facility.

Watmough Gary R GR Hagdorn Magnus M Brumhead Jodie J Seth Sohan S Delamónica Enrique E Haddon Charlotte C Smith William C WC

Scientific data 20220517 1

Physical access to health facilities is an important factor in determining treatment seeking behaviour and has implications for targets within the Sustainable Development Goals, including the right to health. The increased availability of high-resolution land cover and road data from satellite imagery offers opportunities for fine-grained estimations of physical access which can support delivery planning through the provision of more realistic estimates of travel times. The data presented here i ...[more]

PMID: 35581259

Similar Datasets

Project description:ImportanceTravel distance to abortion services varies widely in the US. Some evidence shows travel distance affects use of abortion care, but there is no national analysis of how abortion rate changes with travel distance.ObjectiveTo examine the association between travel distance to the nearest abortion care facility and the abortion rate and to model the effect of reduced travel distance.Design, setting, and participantsThis cross-sectional geographic analysis used 2015 data on abortions by county of residence from 1948 counties in 27 states. Abortion rates were modeled using a spatial Poisson model adjusted for age, race/ethnicity, marital status, educational attainment, household poverty, nativity, and state abortion policies. Abortion rates for 3107 counties in the 48 contiguous states that were home to 62.5 million female residents of reproductive age (15-44 years) and changes under travel distance scenarios, including integration into primary care (<30 miles) and availability of telemedicine care (<5 miles), were estimated. Data were collected from April 2018 to October 2019 and analyzed from December 2019 to July 2020.ExposuresMedian travel distance by car to the nearest abortion facility.Main outcomes and measuresUS county abortion rate per 1000 female residents of reproductive age.ResultsAmong the 1948 counties included in the analysis, greater travel distances were associated with lower abortion rates in a dose-response manner. Compared with a median travel distance of less than 5 miles (median rate, 21.1 [range, 1.2-63.6] per 1000 female residents of reproductive age), distances of 5 to 15 miles (median rate, 12.2 [range, 0.5-23.4] per 1000 female residents of reproductive age; adjusted coefficient, -0.05 [95% CI, -0.07 to -0.03]) and 120 miles or more (median rate, 3.9 [range, 0-12.9] per 1000 female residents of reproductive age; coefficient, -0.73 [95% CI, -0.80 to -0.65]) were associated with lower rates. In a model of 3107 counties with 62.5 million female residents of reproductive age, 696 760 abortions were estimated (mean rate, 11.1 [range, 1.0-45.5] per 1000 female residents of reproductive age). If abortion were integrated into primary care, an additional 18 190 abortions (mean rate, 11.4 [range, 1.1-45.5] per 1000 female residents of reproductive age) were estimated. If telemedicine were widely available, an additional 70 920 abortions were estimated (mean rate, 12.3 [range, 1.4-45.5] per 1000 female residents of reproductive age).Conclusions and relevanceThese findings suggest that greater travel distances to abortion services are associated with lower abortion rates. The results indicate which geographic areas have insufficient access to abortion care. Modeling suggests that integrating abortion into primary care or making medication abortion care available by telemedicine may decrease unmet need.

Project description:ImportanceRecent reports have highlighted that expanding access to health care is ineffective at meeting the goal of universal health coverage if the care offered does not meet a minimum level of quality. Health care facilities nearest to patient's homes that are perceived to offer inadequate or inappropriate care are frequently bypassed in favor of more distant private or tertiary-level hospital facilities that are perceived to offer higher-quality care.ObjectiveTo estimate the frequency with which women in Ghana bypass the nearest primary health care facility and describe patient experiences, costs, and other factors associated with this choice.Design, setting, and participantsThis nationally representative survey study was conducted in 2017 and included 4203 households to identify women in Ghana aged 15 to 49 years (ie, reproductive age) who sought primary care within the last 6 months. Women who sought care within the past 6 months were included in the study. Data were analyzed from 2018 to 2019.ExposuresBypass was defined as a woman's report that she sought care at a health facility other than the nearest facility.Main outcomes and measuresSociodemographic characteristics, reasons why women sought care, reasons why women bypassed their nearest facility, ratings for responsiveness of care, patient experience, and out-of-pocket costs. All numbers and percentages were survey-weighted to account for survey design.ResultsA total of 4289 women met initial eligibility criteria, and 4207 women (98.1%) completed the interview. A total of 1993 women reported having sough health care in the past 6 months, and after excluding those who were ineligible and survey weighting, the total sample included 1946 women. Among these, 629 women (32.3%) reported bypassing their nearest facilities for primary care. Women who bypassed their nearest facilities, compared with women who did not, were more likely to visit a private facility (152 women [24.5%] vs 202 women [15.6%]) and borrow money to pay for their care (151 women [24.0%] vs 234 women [17.8%]). After adjusting for covariates, women who bypassed reported paying a mean of 107.2 (95% CI, 79.1-135.4) Ghanaian Cedis (US $18.50 [95% CI, $13.65-$23.36]) for their care, compared with a mean of 58.6 (95% CI, 28.1-89.2) Ghanaian Cedis (US $10.11 [95% CI, $4.85-15.35]) for women who did not bypass (P = .006). Women who bypassed cited clinician competence (136 women [34.3%]) and availability of supplies (93 women [23.4%]) as the most important factors in choosing a health facility.Conclusions and relevanceThe findings of this survey study suggest that bypassing the nearest health care facility was common among women in Ghana and that available services at lower levels of primary care are not meeting the needs of a large proportion of women. Among the benefits women perceived from bypassing were clinician competence and availability of supplies. These data provide insights to policy makers regarding potential gaps in service delivery and may help to guide primary health care improvement efforts.

Dataset Information

Using open-source data to construct 20 metre resolution maps of children's travel time to the nearest health facility.

Publications

Using open-source data to construct 20 metre resolution maps of children's travel time to the nearest health facility.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets