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M&E Data Quality
Discussion about Data quality and double counting
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What Is Data quality
Data quality refers to accurate and reliable information collected through a monitoring and evaluation data management system. -
Why Is Data Quality Important?
Having accurate information about program results allows programs to:
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- Show accountability and good governance
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- Provide decision-makers with information required for planning, resource allocation, program design, program improvement, and effectiveness of program
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- Correctly assess whether minimum standards exist for comprehensive prevention, care, and treatment services
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- Monitor progress toward meeting established goals and targets
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What Can Happen In The Absence Of Quality Data?
A lack of quality data can hurt a program in several ways.
Programs suffering from poor data may:
- Have to use additional resources to correct the data,
- Experience reduced stakeholder confidence and support,
- Miss opportunities to identify areas of strength or gaps in program activities, or
- Face the undesirable consequences of inappropriate decisions based on poor data.
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Dimensions Of Data Quality
Data quality has seven dimensions:- Accuracy
- Reliability
- Completeness
- Timeliness
- Precision
- Integrity
- Confidentiality
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What Is Double Counting?
An important data quality issue that programs face is overestimating results by double counting individuals or service sites that receive assistance.Multiple programs and partners provide services to meet the range of needs related to HIV and AIDS. A number of countries have programs and services funded and implemented by a variety of entities, including:
- Government
- Donors
- Non-governmental organizations
- Faith-based organizations
- Private sector entities
Inevitably, there will be overlap in services received by individuals and in subsequent reporting by partners.
It is important that a data management system be able to differentiate unique units according to standardized indicator definitions in order to reliably and accurately aggregate data while avoiding double counting.
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How Can Double Counting Occur?
The problem of double counting can be categorized into three essential types:Type I:Within Partner Double Counting of Individuals
One partner at one site provides the same service (training, treatment, care, etc.) multiple times to the same individual within one reporting period and counts the individual as having received the service multiple times within the same reporting period.
Type II: Between Partner Double Counting of Individuals
Two or more partners supply the same service (prevention, treatment, care, etc.) to the same individual at the same site or different sites within one reporting period and both partners add the individual to their count of the service delivery.
Type III: Double Counting of Sites
Two or more partners provide the supplies and/or services to the same organization within one reporting period and count that siteas one of their service points.
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