Data quality assurance tool for program-level indicators

Recommendations

Info

Section I. Objective I. Introduction to Data Quality To outline the essential parameters of data quality, to show how data quality fits within the President’s Emergency Plan for AIDS Relief (Emergency Plan) system of results reporting, and to provide an overview of the Data Quality Assurance Tool for Program-Level Indicators. Section I Map Section I is divided into three parts: 1. 2. 3. The Role of Data Quality in the Emergency Plan. What is Data Quality? The Data Quality Assurance Tool for Program-Level Indicators. I.1. The Role of Data Quality in The Emergency Plan The Emergency Plan emphasizes data quality because it is explicitly evidence based and results oriented. Good data are needed to inform the design of interventions and to monitor and evaluate the Plan’s quantitative progress toward pre-determined treatment, prevention, and care targets. Ultimately, the Emergency Plan is committed to accuracy of information for purposes of accountability and, more importantly, for use of quality data to improve programs. More specifically, the Plan’s emphasis on evidence and results places data quality at the center of a project cycle in which target setting and results reporting are inextricably linked. In order for targets to be meaningful and realistic, the quality of the data on which they are based must meet minimum standards of acceptability. Similarly, progress reports will only offer stakeholders a concise and accurate reflection of whether the Emergency Plan is “working” if the supporting data are of high quality. Attention to data quality ensures that target-setting and results reporting are informed by valid and sensitive information, and that reporting partners and participating country programs are thinking about and collecting and organizing this information in the same manner. In this way, attention to data quality leads to improved program performance and to more efficient resource management. The diagram above illustrates the idea that the value of periodic (annual) revision and the resetting of targets, and of periodic (semi-annual and annual) reporting of results, is only as high as the quality of the data informing these activities. Data Quality Assurance Tool for Program-Level Indicators
Diagram 1.1. Data Quality and the Emergency Plan Cycle of Program-Level Management I.2 What is Data Quality? In its most basic sense, data quality means that the information collected as part of the Emergency Plan’s monitoring and evaluation system adequately represents the program’s activities. Adequately represents means that the information is accurate and reliable. Accurate information is interpreted as measuring what we intend to measure (that the information is correct), and reliable information implies that it has been collected and measured in the same way (consistently) by all programs during all reporting periods. More specifically, a program’s information system adequately represents a program’s activities if, along with accuracy and reliability, the data have qualities of completeness, precision, timeliness, and integrity. A simple framework for this idea is illustrated in Diagram 1.1 on the following page. The dimensions of data quality shown in Diagram 1.2 are fundamentally influenced by the ways in which results of U.S. Government (USG) in-country program activities are monitored and mapped to information systems. Operational definitions of the six dimensions are presented in Table 1.1 on page 4. At a more macro level, data quality is systematically influenced by factors that are inherent to the Emergency Plan’s monitoring and evaluation system (e.g., definitions of programlevel indicators, upstream & downstream support, and double counting). These factors are ubiquitous and influence data quality regardless of country program, program-level indicator, or implementing partner. Data Quality Assurance Tool for Program-Level Indicators
Page 1 and 2: Data Quality Assurance Tool for Pro
Page 4 and 5: Contents I. Introduction to Data Qu
Page 8 and 9: Diagram 1.2. Schematic Framework of
Page 10: Box 1.1. Guiding Principles of the
Page 13 and 14: Diagram 2.1. The Emergency Plan Ups
Page 15 and 16: Box 2.1. Summary Definitions of the
Page 17 and 18: Framing results by category of supp
Page 19 and 20: Having used Checklist 2.1 to think
Page 21 and 22: A frequent downstream (direct) data
Page 23 and 24: Checklist 2.4. Assessing the Qualit
Page 25 and 26: II.3. When USG Support and Results
Page 27 and 28: II.4. How to Create an Audit Trail
Page 29 and 30: Upstream Activity Documentation: In
Page 32 and 33: Section III Objective III. Double C
Page 34 and 35: Type IV: Double Counting Due to Ove
Page 36 and 37: Worksheet 3.2 (below) is one exampl
Page 38 and 39: Diagram 3.1. Example: Emergency Pla
Page 40: Diagram 3.3. Example: Emergency Pla
Page 43 and 44: These data will provide OGAC with i
Page 45 and 46: IV.2.E. Using Three Data Points to
Page 47 and 48: IV.3. Documenting Outliers In the c
Page 50 and 51: V. Appendix V.1. Important Downstre

Data quality assurance tool for program-level indicators

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?