TABLE 1.

Data Quality and Use Package Implemented in Malawi

Processes to Improve Data Demand and UseElements of the DQU Package Design and Implementation
1. Assess and improve the data use context

  • Participatory baseline data quality assessment, using tools based on the PRISM framework and MEASURE Evaluation data quality audit tools, and involving national and district iCCM managers

2. Engage data users and data producers

  • Engagement of HSAs, health facility staff, district manager, and national IMCI unit staff in designing the package training materials and tools

3. Improve data quality (quality defined as accurate, complete, and timely)

  • Baseline data quality assessment to identify barriers to data quality

  • Provision of calculators to HSAs to improve accuracy of monthly tallies

  • Refresher training on how to complete routine registers and reports

4. Improve data availability (availability defined as data synthesis, communication, and access to data)

  • Development and dissemination of standardized wall charts to display data onsite

  • Training on analysis, interpretation, and presentation of data for HSAs, health facility, and district staff

5. Identify information needs

  • Consultations with national, district, and facility staff and HSAs to document and prioritize information needs for monitoring iCCM

  • Working with district IMCI coordinators to identify reporting “benchmarks” and “action thresholds” and to agree on response to levels below the agreed-upon action threshold

6. Build capacity in data use core competencies

  • General training on data management, use, and interpretation

  • Involvement of district staff in data collection and supervision to build leadership capacity and to better advocate for data use in their districts

7. Strengthen the organization's data demand and use infrastructure

  • Development of written guidance on iCCM data analysis and use

  • Provision of data display templates

8. Monitor, evaluate, and communicate results of data use interventions

  • Evaluation of the DQU package through mixed-methods, pre-post assessment and estimation of cost for scale-up

  • Dissemination of findings in Malawi and globally to leverage resources to expand to other districts (and countries)

  • Abbreviations: DQU, data quality and use; HSA, Health Surveillance Assistant; iCCM, integrated community case management; IMCI, Integrated Management of Childhood Illness.

  • Based on the Nutley and Reynolds logic model to strengthen data demand and use.13