Your browser doesn't support javascript.
loading
Exploring approaches to weighting estimates of facility readiness to provide health services used for estimating input-adjusted effective coverage: a case study using data from Tanzania.
Sheffel, Ashley; Carter, Emily; Niyeha, Debora; Yahya-Malima, Khadija I; Malamsha, Deogratius; Shagihilu, Shagihilu; Munos, Melinda K.
Affiliation
  • Sheffel A; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Carter E; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Niyeha D; Hellen Keller International, Dar Es Salaam, United Republic of Tanzania.
  • Yahya-Malima KI; School of Nursing, Muhimbili University of Health and Allied Sciences (MUHAS), Dar Es Salaam, United Republic of Tanzania.
  • Malamsha D; National Bureau of Statistics, Dar Es Salaam, United Republic of Tanzania.
  • Shagihilu S; National Bureau of Statistics, Dar Es Salaam, United Republic of Tanzania.
  • Munos MK; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Glob Health Action ; 16(1): 2234750, 2023 12 31.
Article in En | MEDLINE | ID: mdl-37462190
The ideal approach for calculating effective coverage of health services using ecological linking requires accounting for variability in facility readiness to provide health services and patient volume by incorporating adjustments for facility type into estimates of facility readiness and weighting facility readiness estimates by service-specific caseload. The aim of this study is to compare the ideal caseload-weighted facility readiness approach to two alternative approaches: (1) facility-weighted readiness and (2) observation-weighted readiness to assess the suitability of each as a proxy for caseload-weighted facility readiness. We utilised the 2014-2015 Tanzania Service Provision Assessment along with routine health information system data to calculate facility readiness estimates using the three approaches. We then conducted equivalence testing, using the caseload-weighted estimates as the ideal approach and comparing with the facility-weighted estimates and observation-weighted estimates to test for equivalence. Comparing the facility-weighted readiness estimates to the caseload-weighted readiness estimates, we found that 58% of the estimates met the requirements for equivalence. In addition, the facility-weighted readiness estimates consistently underestimated, by a small percentage, facility readiness as compared to the caseload-weighted readiness estimates. Comparing the observation-weighted readiness estimates to the caseload-weighted readiness estimates, we found that 64% of the estimates met the requirements for equivalence. We found that, in this setting, both facility-weighted readiness and observation-weighted readiness may be reasonable proxies for caseload-weighted readiness. However, in a setting with more variability in facility readiness or larger differences in facility readiness between low caseload and high caseload facilities, the observation-weighted approach would be a better option than the facility-weighted approach. While the methods compared showed equivalence, our results suggest that selecting the best method for weighting readiness estimates will require assessing data availability alongside knowledge of the country context.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Health Facilities / Health Services Aspects: Determinantes_sociais_saude / Patient_preference Limits: Humans Country/Region as subject: Africa Language: En Journal: Glob Health Action Year: 2023 Document type: Article Affiliation country: Estados Unidos Country of publication: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Health Facilities / Health Services Aspects: Determinantes_sociais_saude / Patient_preference Limits: Humans Country/Region as subject: Africa Language: En Journal: Glob Health Action Year: 2023 Document type: Article Affiliation country: Estados Unidos Country of publication: Estados Unidos