Using Data to Improve Programs: Assessment of a Data Quality and Use Intervention Package for Integrated Community Case Management in Malawi

Elizabeth Hazel; Emmanuel Chimbalanga; Tiyese Chimuna; Humphreys Nsona; Angella Mtimuni; Ernest Kaludzu; Kate Gilroy; Tanya Guenther

doi:10.9745/GHSP-D-17-00103

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FIGURE 1
Malawi iCCM Routine Reporting Data Flow
Abbreviations: HSA, Health Surveillance Assistant; iCCM, integrated community case management.
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FIGURE 2
HSA Caseload Reporting Consistency at Baseline (2012) and Endline (2013) for Fever, Diarrhea, and Pneumonia, Dowa and Kasungu Districts Combined, Malawi
Abbreviations: HSA, Health Surveillance Assistant; RVR, results verification ratio.
An RVR of 1.00 indicates perfect reporting, while less than 1.00 indicates overreporting and greater than 1.00 underreporting.
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FIGURE 3
Wall Chart Template Use at the HSA and Health Facility Levels at Endline (2013), Dowa and Kasungu Districts Combined, Malawi
Abbreviation: HSA, Health Surveillance Assistant.
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Health Surveillance Assistants in Malawi review iCCM data using wall chart templates.

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TABLE 1.

Data Quality and Use Package Implemented in Malawi

Processes to Improve Data Demand and Use	Elements 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

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TABLE 2.
Sample Size for the DQU Intervention and Evaluation, Dowa and Kasungu Districts, Malawi, 2012–2013
DQU Implementation Baseline Assessment Endline Assessment Matched Data
Districts 2 2 2 2
Health facilities 69 10 9 9
HSAs 426 38 36 31
Abbreviations: DQU, data quality and use; HSA, Health Surveillance Assistant.

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TABLE 3

Availability and Completeness of Reporting Forms at the HSA and Health Facility Levels for the Previous Month, Baseline (May 2012) vs. Endline (June 2013)

	Kasungu		Dowa		Total
	Baseline	Endline	Baseline	Endline	Baseline	Endline
HSA level^a
Available	93% (25/27)	96% (23/24)	95% (57/60)	80% (37/46)	94% (82/87)	86% (60/70)
Complete	74% (20/27)	79% (19/24)	95% (57/60)	63% (29/46)	89% (77/87)	69% (48/70)
Health facility level^b
Available	Missing	100% (24/24)	100% (23/23)	44% (11/25)	N/A	71% (35/49)
Complete	Missing	100% (24/24)	95% (22/23)	16% (4/25)	N/A	57% (28/49)

Abbreviation: HSA, Health Surveillance Assistant; iCCM, integrated community case management.
↵^a Denominators represent all iCCM-trained HSAs associated with selected health facilities that would be expected to submit reports.
↵^b Denominators represent all health facilities supporting iCCM that would be expected to submit reports to the district.