TY - JOUR
T1 - Linking household surveys and facility assessments
T2 - a comparison of geospatial methods using nationally representative data from Malawi
AU - Peters, Michael A.
AU - Mohan, Diwakar
AU - Naphini, Patrick
AU - Carter, Emily
AU - Marx, Melissa A.
N1 - Funding Information:
The authors would like to give thanks to Samuel Chipokosa, Sautso Wachepa, Tiope Mleme, Jameson Nadawala, and Mercy Kanyuka from the Malawi National Statistical Office; Amos Misomali, Rebecca Heidkamp, and Tricia Aung from NEP; and Anooj Pattnaik from RADAR for their support throughout the duration of the project and the writing of the paper. The authors wish to acknowledge the Department of Global Affairs Canada for their support of the National Evaluations Platform (grant number 7059904) and for their support of the Real Accountability, Data Analysis for Results program (grant number 7061914) to the Institute for International Programs at the Johns Hopkins Bloomberg School of Public Health, and in partnership with the Malawi National Statistical Office and Ministry of Health.
Funding Information:
The authors would like to give thanks to Samuel Chipokosa, Sautso Wachepa, Tiope Mleme, Jameson Nadawala, and Mercy Kanyuka from the Malawi National Statistical Office; Amos Misomali, Rebecca Heidkamp, and Tricia Aung from NEP; and Anooj Pattnaik from RADAR for their support throughout the duration of the project and the writing of the paper. The authors wish to acknowledge the Department of Global Affairs Canada for their support of the National Evaluations Platform (grant number 7059904) and for their support of the Real Accountability, Data Analysis for Results program (grant number 7061914) to the Institute for International Programs at the Johns Hopkins Bloomberg School of Public Health, and in partnership with the Malawi National Statistical Office and Ministry of Health.
Funding Information:
Funding for this research was provided by the Global Affairs Canada. The funding body played no role in the design of the study nor the collection, analysis, and interpretation of data, or the writing of the manuscript.
Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12
Y1 - 2020/12
N2 - Background: Linking facility and household surveys through geographic methods is a popular technique to draw conclusions about the relationship between health services and population health outcomes at local levels. These methods are useful tools for measuring effective coverage and tracking progress towards Universal Health Coverage, but are understudied. This paper compares the appropriateness of several geospatial methods used for linking individuals (within displaced survey cluster locations) to their source of family planning (at undisplaced health facilities) at a national level. Methods: In Malawi, geographic methods linked a population health survey, rural clusters from the Woman’s Questionnaire of the 2015 Malawi Demographic and Health Survey (MDHS 2015), to Malawi’s national health facility census to understand the service environment where women receive family planning services. Individuals from MDHS 2015 clusters were linked to health facilities through four geographic methods: (i) closest facility, (ii) buffer (5 km), (iii) administrative boundary, and (iv) a newly described theoretical catchment area method. Results were compared across metrics to assess the number of unlinked clusters (data lost), the number of linkages per cluster (precision of linkage), and the number of women linked to their last source of modern contraceptive (appropriateness of linkage). Results: The closest facility and administrative boundary methods linked every cluster to at least one facility, while the 5-km buffer method left 288 clusters (35.3%) unlinked. The theoretical catchment area method linked all but one cluster to at least one facility (99.9% linked). Closest facility, 5-km buffer, administrative boundary, and catchment methods linked clusters to 1.0, 1.4, 21.1, and 3.3 facilities on average, respectively. Overall, the closest facility, 5-km buffer, administrative boundary, and catchment methods appropriately linked 64.8%, 51.9%, 97.5%, and 88.9% of women to their last source of modern contraceptive, respectively. Conclusions: Of the methods studied, the theoretical catchment area linking method loses a marginal amount of population data, links clusters to a relatively low number of facilities, and maintains a high level of appropriate linkages. This linking method is demonstrated at scale and can be used to link individuals to qualities of their service environments and better understand the pathways through which interventions impact health.
AB - Background: Linking facility and household surveys through geographic methods is a popular technique to draw conclusions about the relationship between health services and population health outcomes at local levels. These methods are useful tools for measuring effective coverage and tracking progress towards Universal Health Coverage, but are understudied. This paper compares the appropriateness of several geospatial methods used for linking individuals (within displaced survey cluster locations) to their source of family planning (at undisplaced health facilities) at a national level. Methods: In Malawi, geographic methods linked a population health survey, rural clusters from the Woman’s Questionnaire of the 2015 Malawi Demographic and Health Survey (MDHS 2015), to Malawi’s national health facility census to understand the service environment where women receive family planning services. Individuals from MDHS 2015 clusters were linked to health facilities through four geographic methods: (i) closest facility, (ii) buffer (5 km), (iii) administrative boundary, and (iv) a newly described theoretical catchment area method. Results were compared across metrics to assess the number of unlinked clusters (data lost), the number of linkages per cluster (precision of linkage), and the number of women linked to their last source of modern contraceptive (appropriateness of linkage). Results: The closest facility and administrative boundary methods linked every cluster to at least one facility, while the 5-km buffer method left 288 clusters (35.3%) unlinked. The theoretical catchment area method linked all but one cluster to at least one facility (99.9% linked). Closest facility, 5-km buffer, administrative boundary, and catchment methods linked clusters to 1.0, 1.4, 21.1, and 3.3 facilities on average, respectively. Overall, the closest facility, 5-km buffer, administrative boundary, and catchment methods appropriately linked 64.8%, 51.9%, 97.5%, and 88.9% of women to their last source of modern contraceptive, respectively. Conclusions: Of the methods studied, the theoretical catchment area linking method loses a marginal amount of population data, links clusters to a relatively low number of facilities, and maintains a high level of appropriate linkages. This linking method is demonstrated at scale and can be used to link individuals to qualities of their service environments and better understand the pathways through which interventions impact health.
KW - DHS
KW - Family planning
KW - GIS
KW - Linking
KW - Malawi
KW - Misclassification
KW - Small area estimation
KW - Spatial linkage
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U2 - 10.1186/s12963-020-00242-z
DO - 10.1186/s12963-020-00242-z
M3 - Article
C2 - 33302989
AN - SCOPUS:85097416558
VL - 18
JO - Population Health Metrics
JF - Population Health Metrics
SN - 1478-7954
IS - 1
M1 - 30
ER -