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Our Work: Year 3 Highlights

Author(s): Data for Impact
Year: 2022
Filed under: annual report, Data Quality, Data use, evidence, Gender

Brief: Considerations for the Use of Routine Data for Evaluation of Public Health Programs

Author(s): Measure Evaluation
Year: 2020
Filed under: Data Quality, Data use, Evaluation, RHIS, Routine Health Information Systems

Training Curriculum for the Integrated Approach to Family Planning Data Quality Assessment

Author(s): Data for Impact
Year: 2021
Filed under: Curriculum, Data Quality, Family Planning, Training

User Guidelines for the Integrated Approach to Family Planning Data Quality Assessment

Author(s): Data for Impact
Year: 2021
Filed under: Curriculum, Data Quality, Family Planning, Guidance and Tools, Training

Improved Reporting of Performance Data Supports Health Decision Making in Bangladesh

Author(s): MEASURE Evaluation
Year: 2019
Filed under: Bangladesh, Data, Data Quality, Evaluation, M&E, Monitoring

Needs Assessment on Resources for Use of Routine and Other Secondary Data for Health Evaluation and Research

Author(s): Fehringer, J., Millar, E., Wilkes, B. (Data for Impact)
Year: 2020
Filed under: assessment, Data Quality, Data use, Evaluation, Health System, Routine data, secondary data

Strengthening Collection, Management, and Use of Quality Routine Data for Alternative Care in Uganda

Author(s): Data for Impact
Year: 2020
Filed under: Alternative care, Care for children, Data Quality, Data use, Routine data, Uganda

A Practical Guide to Using Routine Data in Evaluation

Author(s): Eva Silvestre (MEASURE Evaluation)
Year: 2020
Filed under: assessment, Data Quality, Evaluation, evidence, MEASURE Evaluation, method, RHIS, Routine data, Routine Health Information Systems

Strengthening Collection, Management and Use of Quality Routine Data for the Provision of Child Protection and Care in Armenia

Author(s): Data for Impact
Year: 2020
Filed under: Armenia, Case management, CECA, child protection, Children, Data Quality, Data quality assessment, Data use, Data visualization, Evaluation, Routine data, Social work

Advances in Solutions for Data Quality

Author(s): Jim Thomas, David Boone
Year: 2018
Filed under: Data, Data Quality

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This website was produced with the support of the United States Agency for International Development (USAID) under the terms of the Data for Impact (D4I) associate award 7200AA18LA00008, which is implemented by the Carolina Population Center at the University of North Carolina at Chapel Hill, in partnership with Palladium International, LLC; ICF Macro, Inc.; John Snow, Inc.; and Tulane University. The views expressed in this website do not necessarily reflect the views of USAID or the United States government.

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Data for Impact (D4I) is funded by the United States Agency for International Development (USAID) under the terms of the D4I associate award 7200AA18LA00008, which is implemented by the Carolina Population Center at the University of North Carolina at Chapel Hill, in partnership with Palladium International, LLC; ICF Macro, Inc.; John Snow, Inc.; and Tulane University. The views expressed in this website do not necessarily reflect the views of USAID or the United States government.
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