Optimizing Impact in Fighting the Global HIV Epidemic
Introduction Linking healthcare expenditure data with health outputs and outcomes data is challenging. This is especially true in low-resource (LMIC) settings. Where such linking can be accomlished, however, it supports the development of IMPACT-per-DOLLAR metrics that may be leveraged to support pr...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Swansea University
2018-08-01
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| Series: | International Journal of Population Data Science |
| Online Access: | https://ijpds.org/article/view/769 |
| _version_ | 1797425458634031104 |
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| author | Derek Ritz Violet Ketani |
| author_facet | Derek Ritz Violet Ketani |
| author_sort | Derek Ritz |
| collection | DOAJ |
| description | Introduction
Linking healthcare expenditure data with health outputs and outcomes data is challenging. This is especially true in low-resource (LMIC) settings. Where such linking can be accomlished, however, it supports the development of IMPACT-per-DOLLAR metrics that may be leveraged to support programme optimization.
Objectives and Approach
This session will describe a new data-linking design for a global health programme targeted to low and middle-income countries (LMIC). The US Government's President's Emergency Plan for AIDS Relief (PEPFAR; www.pepfar.gov) is a \$7 billion/year programme spanning 58 LMICs. PEPFAR prepares annual budgets and plans. On a quarterly basis, Implementing Partners report programmatic district-level Monitoring, Evaluation and Reporting (MER) indicators to a central database. Starting in July, 2018, quarterly expenditure data will also be captured, broken down by major programme area and high level account code. The novel new data-linking approach triangulates the budget, indicator and expenditure datasets.
Results
The PEPFAR programme is managed by the US State Department's Office of the Global AIDS Coordinator (S/GAC). S/GAC undertook, in 2017, a significant re-design of its information system requirements and the software systems that will support these. A multi-year design and prototyping effort has yielded a novel new approach for financial monitoring intended to improve S/GAC's abilities to exert its mandates regarding both programmatic and financial oversight.
The new data-linking solutions are being implemented across all PEPFAR countries during the first half of 2018. Information model design choices (and trade-offs), solution architecture designs, and preliminary pilot results of this new implementation will be reported at the confernce. A discussion of implementation science lessons-learned specific to deploying in LMICs will also be presented.
Conclusion/Implications
PEPFAR's goal and mission is to operationalize HIV epidemic control and achieve an AIDS-free generation by 2030. Data analytics are proving essential to achieving this goal. S/GAC's re-design efforts will help better link its huge financial and programmatic (MER) datasets to support DALY-per-DOLLAR impact optimization on this important initiative. |
| first_indexed | 2024-03-09T08:16:26Z |
| format | Article |
| id | doaj.art-2ae29c48d1a64012bac5a2af956cfb2e |
| institution | Directory Open Access Journal |
| issn | 2399-4908 |
| language | English |
| last_indexed | 2024-03-09T08:16:26Z |
| publishDate | 2018-08-01 |
| publisher | Swansea University |
| record_format | Article |
| series | International Journal of Population Data Science |
| spelling | doaj.art-2ae29c48d1a64012bac5a2af956cfb2e2023-12-02T22:09:23ZengSwansea UniversityInternational Journal of Population Data Science2399-49082018-08-013410.23889/ijpds.v3i4.769Optimizing Impact in Fighting the Global HIV EpidemicDerek Ritz0Violet Ketani1ecGroup Inc.Cardno Emerging MarketsIntroduction Linking healthcare expenditure data with health outputs and outcomes data is challenging. This is especially true in low-resource (LMIC) settings. Where such linking can be accomlished, however, it supports the development of IMPACT-per-DOLLAR metrics that may be leveraged to support programme optimization. Objectives and Approach This session will describe a new data-linking design for a global health programme targeted to low and middle-income countries (LMIC). The US Government's President's Emergency Plan for AIDS Relief (PEPFAR; www.pepfar.gov) is a \$7 billion/year programme spanning 58 LMICs. PEPFAR prepares annual budgets and plans. On a quarterly basis, Implementing Partners report programmatic district-level Monitoring, Evaluation and Reporting (MER) indicators to a central database. Starting in July, 2018, quarterly expenditure data will also be captured, broken down by major programme area and high level account code. The novel new data-linking approach triangulates the budget, indicator and expenditure datasets. Results The PEPFAR programme is managed by the US State Department's Office of the Global AIDS Coordinator (S/GAC). S/GAC undertook, in 2017, a significant re-design of its information system requirements and the software systems that will support these. A multi-year design and prototyping effort has yielded a novel new approach for financial monitoring intended to improve S/GAC's abilities to exert its mandates regarding both programmatic and financial oversight. The new data-linking solutions are being implemented across all PEPFAR countries during the first half of 2018. Information model design choices (and trade-offs), solution architecture designs, and preliminary pilot results of this new implementation will be reported at the confernce. A discussion of implementation science lessons-learned specific to deploying in LMICs will also be presented. Conclusion/Implications PEPFAR's goal and mission is to operationalize HIV epidemic control and achieve an AIDS-free generation by 2030. Data analytics are proving essential to achieving this goal. S/GAC's re-design efforts will help better link its huge financial and programmatic (MER) datasets to support DALY-per-DOLLAR impact optimization on this important initiative.https://ijpds.org/article/view/769 |
| spellingShingle | Derek Ritz Violet Ketani Optimizing Impact in Fighting the Global HIV Epidemic International Journal of Population Data Science |
| title | Optimizing Impact in Fighting the Global HIV Epidemic |
| title_full | Optimizing Impact in Fighting the Global HIV Epidemic |
| title_fullStr | Optimizing Impact in Fighting the Global HIV Epidemic |
| title_full_unstemmed | Optimizing Impact in Fighting the Global HIV Epidemic |
| title_short | Optimizing Impact in Fighting the Global HIV Epidemic |
| title_sort | optimizing impact in fighting the global hiv epidemic |
| url | https://ijpds.org/article/view/769 |
| work_keys_str_mv | AT derekritz optimizingimpactinfightingtheglobalhivepidemic AT violetketani optimizingimpactinfightingtheglobalhivepidemic |