A Characterisation and Profiling of District Health Indicators in Zimbabwe: An Application of Principal Component Analysis in a Data Limited Setting
**Background:** The Ministry of Health and Child Care, Zimbabwe does not have a method for prioritization and equitable allocation of its share of the national health budget and other resources in the sector. Regional allocations at the provincial level are made regardless of the provinces’ disease...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Columbia Data Analytics, LLC
2015-12-01
|
| Series: | Journal of Health Economics and Outcomes Research |
| Online Access: | https://doi.org/10.36469/9833 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823860371576848384 |
|---|---|
| author | Shepherd Shamu Simbarashe Rusakaniko Charles Hongoro |
| author_facet | Shepherd Shamu Simbarashe Rusakaniko Charles Hongoro |
| author_sort | Shepherd Shamu |
| collection | DOAJ |
| description | **Background:** The Ministry of Health and Child Care, Zimbabwe does not have a method for prioritization and equitable allocation of its share of the national health budget and other resources in the sector. Regional allocations at the provincial level are made regardless of the provinces’ disease burden, population size, or needs. Currently there is no method available to show how the provinces eventually allocate these resources to the lower levels of care. In a data limited country such as Zimbabwe, Principal Component Analysis method can be used to identify a set of indicators that account for cross variation between different regions. This set of indicators could then be used by planners as reference indicators for equitable allocation of resources and prioritization of health care interventions.
**Objective:** The aim of the study was to construct a set of simple, feasible, reliable and valid composite health indicators for use in characterising and profiling of the different districts in Zimbabwe.
**Method:** This was a retrospective analysis of secondary data to derive composite indices for the 57 administrative health districts in Zimbabwe using routinely collected secondary data. The data was extracted from the 2012 Zimbabwe Health information database, the 2012 National Census and the 2011 Prices, Income and Expenditure Survey.
**Results:** The analysis of the data resulted in the construction of 10 mutually exclusive principal composite indices, which included demographic, child related, disease related and health systems related indices. The 10 composite indices (population, immunisation, child mortality, antenatal care, HIV/TB, malaria, non-communicable diseases, socioeconomic, health seeking behaviour and infrastructure) were tested for construct and content validity and were found to be statistically robust, reliable and consistent with observed behaviour.
**Conclusion:** The composite indices exhibited internal consistency and construct validity to be regarded as true representations of the cross variation of the 57 districts in Zimbabwe; hence these indices could be used to characterise the behaviour and assess the performance of these districts. There is also potential use for these indices in the areas of resource allocation and prioritisation of health interventions. |
| format | Article |
| id | doaj-art-bd9234c9a5224babbcf12f63d1eca114 |
| institution | Kabale University |
| issn | 2327-2236 |
| language | English |
| publishDate | 2015-12-01 |
| publisher | Columbia Data Analytics, LLC |
| record_format | Article |
| series | Journal of Health Economics and Outcomes Research |
| spelling | doaj-art-bd9234c9a5224babbcf12f63d1eca1142025-02-10T16:12:29ZengColumbia Data Analytics, LLCJournal of Health Economics and Outcomes Research2327-22362015-12-0132A Characterisation and Profiling of District Health Indicators in Zimbabwe: An Application of Principal Component Analysis in a Data Limited SettingShepherd ShamuSimbarashe RusakanikoCharles Hongoro**Background:** The Ministry of Health and Child Care, Zimbabwe does not have a method for prioritization and equitable allocation of its share of the national health budget and other resources in the sector. Regional allocations at the provincial level are made regardless of the provinces’ disease burden, population size, or needs. Currently there is no method available to show how the provinces eventually allocate these resources to the lower levels of care. In a data limited country such as Zimbabwe, Principal Component Analysis method can be used to identify a set of indicators that account for cross variation between different regions. This set of indicators could then be used by planners as reference indicators for equitable allocation of resources and prioritization of health care interventions. **Objective:** The aim of the study was to construct a set of simple, feasible, reliable and valid composite health indicators for use in characterising and profiling of the different districts in Zimbabwe. **Method:** This was a retrospective analysis of secondary data to derive composite indices for the 57 administrative health districts in Zimbabwe using routinely collected secondary data. The data was extracted from the 2012 Zimbabwe Health information database, the 2012 National Census and the 2011 Prices, Income and Expenditure Survey. **Results:** The analysis of the data resulted in the construction of 10 mutually exclusive principal composite indices, which included demographic, child related, disease related and health systems related indices. The 10 composite indices (population, immunisation, child mortality, antenatal care, HIV/TB, malaria, non-communicable diseases, socioeconomic, health seeking behaviour and infrastructure) were tested for construct and content validity and were found to be statistically robust, reliable and consistent with observed behaviour. **Conclusion:** The composite indices exhibited internal consistency and construct validity to be regarded as true representations of the cross variation of the 57 districts in Zimbabwe; hence these indices could be used to characterise the behaviour and assess the performance of these districts. There is also potential use for these indices in the areas of resource allocation and prioritisation of health interventions.https://doi.org/10.36469/9833 |
| spellingShingle | Shepherd Shamu Simbarashe Rusakaniko Charles Hongoro A Characterisation and Profiling of District Health Indicators in Zimbabwe: An Application of Principal Component Analysis in a Data Limited Setting Journal of Health Economics and Outcomes Research |
| title | A Characterisation and Profiling of District Health Indicators in Zimbabwe: An Application of Principal Component Analysis in a Data Limited Setting |
| title_full | A Characterisation and Profiling of District Health Indicators in Zimbabwe: An Application of Principal Component Analysis in a Data Limited Setting |
| title_fullStr | A Characterisation and Profiling of District Health Indicators in Zimbabwe: An Application of Principal Component Analysis in a Data Limited Setting |
| title_full_unstemmed | A Characterisation and Profiling of District Health Indicators in Zimbabwe: An Application of Principal Component Analysis in a Data Limited Setting |
| title_short | A Characterisation and Profiling of District Health Indicators in Zimbabwe: An Application of Principal Component Analysis in a Data Limited Setting |
| title_sort | characterisation and profiling of district health indicators in zimbabwe an application of principal component analysis in a data limited setting |
| url | https://doi.org/10.36469/9833 |
| work_keys_str_mv | AT shepherdshamu acharacterisationandprofilingofdistricthealthindicatorsinzimbabweanapplicationofprincipalcomponentanalysisinadatalimitedsetting AT simbarasherusakaniko acharacterisationandprofilingofdistricthealthindicatorsinzimbabweanapplicationofprincipalcomponentanalysisinadatalimitedsetting AT charleshongoro acharacterisationandprofilingofdistricthealthindicatorsinzimbabweanapplicationofprincipalcomponentanalysisinadatalimitedsetting AT shepherdshamu characterisationandprofilingofdistricthealthindicatorsinzimbabweanapplicationofprincipalcomponentanalysisinadatalimitedsetting AT simbarasherusakaniko characterisationandprofilingofdistricthealthindicatorsinzimbabweanapplicationofprincipalcomponentanalysisinadatalimitedsetting AT charleshongoro characterisationandprofilingofdistricthealthindicatorsinzimbabweanapplicationofprincipalcomponentanalysisinadatalimitedsetting |