Improving Evaluation of International Public Health Programs Through the Use of a Geographically Informed Data Model

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Health & Medicine

Published on March 13, 2014

Author: measureevaluation

Source: slideshare.net

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Presented by John Spencer at 2013 American Evaluation Association Meeting in Washington, DC.

Improving Public Health Programs Through The Use of A Geographically Informed Data Model: A Strategy for Low Capacity Environments John Spencer Sr. Geospatial Analyst MEASURE Evaluation American Evaluation Association Meeting Washington D.C. October 16, 2013

Using data for evaluation and evidence based decision making

Transitioning to a data rich environment

Data has become stovepiped

Barriers to using reporting data

Barriers to using reporting data Technical • Do I have to clean the data? • Is it in a compatible format? • Can the data link to other data? Non-Technical • Who has the data? • How do I get a copy of the data? • When was it collected?

A geographically informed data model can address both technical and non-technical barriers

Data models Common in other sectors but not so common in global public health.

Data Model 1. Location of program 2. Service provided 3. Number of beneficiaries 4. Implementing organization 5. Year or date

Linked using Geography

Use numeric geographic identifiers District Population Coast 79,133 Mountain 66,251 North 23,415 ID District Population 101 Coast 79,133 103 Mountain 66,251 105 North 23,415 • Facilitates linking • Many countries have district codes, but they may not be widely used • If there aren’t codes, there are international standards that can be used to create codes. Hard to link Easier to link

Not rocket science Geography can be the common link across data

Non-technical side • Creates consistency with data • Can help achieve buy-in about sharing data – Makes it easier for data producers to link data themselves – More involved in the data community

At least 4 Steps 1. Standardize names • Le Tierge 2. Spelling • Karatu 3. Identify changes in boundaries • Totou 4. Definitional Changes • OVC Illustrative data linking Orphan and Vulnerable Children Programs District Orphan Est. 07 OVC Served by PEPFAR CT HH 2013 Koratu 21821 54 1604 Le Tiergé 21804 5015 2000 Salamansa 471204 2500 2229 Totou 108109 7074 -999 East Totou -999 -999 3473 District Orphan Est. 07 Koratu 21821 Le Tierge 21804 Salamansa 471204 Totou 108109 District OVC Served by PEPFAR Koratu 54 Letierge 5015 Salamansa 2500 Totou 7074 PEPFARHIV Prevalence Report District CT HH 2013 Karatu 1604 Le Tiergé 2000 Salamansa 2229 East Totou 3473 Cash Transfer Database Integrated Data Table

• Numeric code for districts • Spelling variation not an issue • Accommodates changes in geography Using a data model ID District Orphan Est. 07 OVC Served by PEPFAR CT HH 2013 101 Koratu 21821 54 1604 103 Le Tiergé 21804 5015 2000 105 Salamansa 471204 2500 2229 107 Totou 108109 7074 -999 108 East Totou -999 -999 3473 ID District Orphan Est. 07 101 Koratu 21821 103 Le Tierge 21804 105 Salamansa 471204 107 Totou 108109 ID District OVC Served by PEPFAR 101 Koratu 54 103 Letierge 5015 105 Salamansa 2500 107 Totou 7074 PEPFARHIV Prevalence Report ID District CT HH 2013 101 Karatu 1604 103 Le Tiergé 2000 105 Salamansa 2229 108 East Totou 3473 Cash Transfer Database Integrated Data Table

Not rocket science Geography can be the common link across data

Growing focus on data

Building blocks for better M&E Photo by ogimogi http://flic.kr/p/4r9zSK

Coming soon • Upcoming publication that goes into more detail

The research presented here has been supported by the President’s Emergency Plan for AIDS Relief (PEPFAR) through the United States Agency for International Development (USAID) under the terms of MEASURE Evaluation cooperative agreement GHA-A-00-08-00003-00. Views expressed are not necessarily those of PEPFAR, USAID or the United States government. MEASURE Evaluation is implemented by the Carolina Population Center at the University of North Carolina at Chapel Hill in partnership with Futures Group, ICF International, John Snow, Inc., Management Sciences for Health, and Tulane University. www.measureevaluation.org

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