Interventions to improve district-level routine health data in low-income and middle-income countries: a systematic review

Abstract

Background: Routine health information system(s) (RHIS) facilitate the collection of health data at all levels of the health system allowing estimates of disease prevalence, treatment and preventive intervention coverage, and risk factors to guide disease control strategies. This core health system pillar remains underdeveloped in many low-income and middle-income countries. Efforts to improve RHIS data coverage, quality and timeliness were launched over 10 years ago.

Methods: A systematic review was performed across 12 databases and literature search engines for both peer-reviewed articles and grey literature reports on RHIS interventions. Studies were analysed in three stages: (1) categorisation of RHIS intervention components and processes; (2) comparison of intervention component effectiveness and (3) whether the post-intervention outcome improved above the WHO integrated disease surveillance response framework data quality standard of 80% or above.

Results: 5294 references were screened, resulting in 56 studies. Three key performance determinants-technical, organisational and behavioural-were proposed as critical to RHIS strengthening. Seventy-seven per cent [77%] of studies identified addressed all three determinants. The most frequently implemented intervention components were 'providing training' and 'using an electronic health management information systems'. Ninety-three per cent [93%] of pre-post or controlled trial studies showed improvements in one or more data quality outputs, but after applying a standard threshold of >80% post-intervention, this number reduced to 68%. There was an observed benefit of multi-component interventions that either conducted data quality training or that addressed improvement across multiple processes and determinants of RHIS.

Conclusion: Holistic data quality interventions that address multiple determinants should be continuously practised for strengthening RHIS. Studies with clearly defined and pragmatic outcomes are required for future RHIS improvement interventions. These should be accompanied by qualitative studies and cost analyses to understand which investments are needed to sustain high-quality RHIS in low-income and middle-income countries.

Keywords: epidemiology; health systems; public health; systematic review.

Figure 1

Performance of Routine Information Systems Management framework (adapted). DQ, data quality; HIS, health information system; RHIS, routine health information system.

Figure 2

Flow chart showing outcomes of selected studies (quantitative and qualitative). * Above threshold' studies: Data quality output improved and reached >=80% post-intervention ** 'Below threshold' studies: Data quality output did not improve and / or did not reach >=80% post-intervention. RHIS, routine health information system.

Figure 3

PRISMA flow chart showing the selection of studies. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Figure 4

RHIS data quality intervention components implemented in selected studies. eHMIS, electronic health management information system; RHIS, routine health information system.

Figure 5

Intervention components in studies that were effective in improving data accuracy above threshold (≥80%) versus that did not improve or did not reach the threshold, ranked by the greatest difference in the percentage of studies with intervention components. impr, improved; Stand, standardised, Enh, enhanced.

Figure 6

Intervention components in studies that were effective in improving data completeness above threshold (≥80%) versus that did not improve or did not reach the threshold, ranked by the greatest difference in the percentage of studies with intervention components. impr, improved; Stand, standardised, Enh, enhanced. DQA, data quality assessment; eHMIS, electronic health management information system.