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Routine Health Information System (RHIS) improvements for strengthened health system management.

Authors
  • Leon, Natalie1, 2
  • Balakrishna, Yusentha3
  • Hohlfeld, Ameer4
  • Odendaal, Willem A1, 5
  • Schmidt, Bey-Marrié4
  • Zweigenthal, Virginia6, 7
  • Anstey Watkins, Jocelyn8
  • Daniels, Karen1, 7
  • 1 Health Systems Research Unit, South African Medical Research Council, Cape Town, South Africa. , (South Africa)
  • 2 School of Public Health, Department of Epidemiology, Brown University, Providence, Rhode Island, USA.
  • 3 Biostatistics Unit, South African Medical Research Council, Durban, South Africa. , (South Africa)
  • 4 Cochrane South Africa, South African Medical Research Council, Cape Town, South Africa. , (South Africa)
  • 5 Department of Psychiatry, Stellenbosch University, Cape Town, South Africa. , (South Africa)
  • 6 Health Impact Assessment Directorate, Department of Health: Western Cape Province, Cape Town, South Africa. , (South Africa)
  • 7 School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa. , (South Africa)
  • 8 Warwick Medical School, University of Warwick, Coventry, UK.
Type
Published Article
Journal
The Cochrane database of systematic reviews
Publication Date
Aug 13, 2020
Volume
8
Identifiers
DOI: 10.1002/14651858.CD012012.pub2
PMID: 32803893
Source
Medline
Language
English
License
Unknown

Abstract

A well-functioning routine health information system (RHIS) can provide the information needed for health system management, for governance, accountability, planning, policy making, surveillance and quality improvement, but poor information support has been identified as a major obstacle for improving health system management. To assess the effects of interventions to improve routine health information systems in terms of RHIS performance, and also, in terms of improved health system management performance, and improved patient and population health outcomes. We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library, MEDLINE Ovid and Embase Ovid in May 2019. We searched Global Health, Ovid and PsycInfo in April 2016. In January 2020 we searched for grey literature in the Grey Literature Report and in OpenGrey, and for ongoing trials using the International Clinical Trials Registry Platform (ICTRP) and ClinicalTrials.gov. In October 2019 we also did a cited reference search using Web of Science, and a 'similar articles' search in PubMed. Randomised and non-randomised trials, controlled before-after studies and time-series studies comparing routine health information system interventions, with controls, in primary, hospital or community health care settings. Participants included clinical staff and management, district management and community health workers using routine information systems. Two authors independently reviewed records to identify studies for inclusion, extracted data from the included studies and assessed the risk of bias. Interventions and outcomes were too varied across studies to allow for pooled risk analysis. We present a 'Summary of findings' table for each intervention comparisons broadly categorised into Technical and Organisational (or a combination), and report outcomes on data quality and service quality. We used the GRADE approach to assess the certainty of the evidence. We included six studies: four cluster randomised trials and two controlled before-after studies, from Africa and South America. Three studies evaluated technical interventions, one study evaluated an organisational intervention, and two studies evaluated a combination of technical and organisational interventions. Four studies reported on data quality and six studies reported on service quality. In terms of data quality, a web-based electronic TB laboratory information system probably reduces the length of time to reporting of TB test results, and probably reduces the overall rate of recording errors of TB test results, compared to a paper-based system (moderate certainty evidence). We are uncertain about the effect of the electronic laboratory information system on the recording rate of serious (misidentification) errors for TB test results compared to a paper-based system (very low certainty evidence). Misidentification errors are inaccuracies in transferring test results between an electronic register and patients' clinical charts. We are also uncertain about the effect of the intervention on service quality (timeliness of starting or changing a patient's TB treatment) (very low certainty evidence). A hand-held electronic device probably improves the length of time to report TB test results, and probably reduces the total frequency of recording errors in TB test results between the laboratory notebook and the electronic information record system, compared to a paper-based system (moderate-certainty evidence). We are, however, uncertain about the effect of the intervention on the frequency of serious (misidentification) errors in recording between the laboratory notebook and the electronic information record, compared to a paper-based system (very low certainty evidence). We are uncertain about the effect of a hospital electronic health information system on service quality (length of time outpatients spend at hospital, length of hospital stay, and hospital revenue collection), compared to a paper-based system (very low certainty evidence). High-intensity brief text messaging (SMS) may make little or no difference to data quality (in terms of completeness of documentation of pregnancy outcomes), compared to low-intensity brief text messaging (low-certainty evidence). We are uncertain about the effect of electronic drug stock notification (with either data management support or product transfer support) on service quality (in terms of transporting stock and stock levels), compared to paper-based stock notification (very low certainty evidence). We are uncertain about the effect of health information strengthening (where it is part of comprehensive service quality improvement intervention) on service quality (health worker motivation, receipt of training by health workers, health information index scores, quality of clinical observation of children and adults) (very low certainty evidence). The review indicates mixed effects of mainly technical interventions to improve data quality, with gaps in evidence on interventions aimed at enhancing data-informed health system management. There is a gap in interventions studying information support beyond clinical management, such as for human resources, finances, drug supply and governance. We need to have a better understanding of the causal mechanisms by which information support may affect change in management decision-making, to inform robust intervention design and evaluation methods. Copyright © 2020 The Authors. Cochrane Database of Systematic Reviews published by John Wiley & Sons, Ltd. on behalf of The Cochrane Collaboration.

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