Evidence map›Paper›PMID 23819699›Full record

ArticleBMC health services research2013

Improving health information systems for decision making across five sub-Saharan African countries: Implementation strategies from the African Health Initiative.

Wilbroad Mutale, Namwinga Chintu, Cheryl Amoroso, Koku Awoonor-Williams, James Phillips, Colin Baynes, Cathy Michel, Angela Taylor, Kenneth Sherr, Population Health Implementation and Training – Africa Health Initiative Data Collaborative

Abstract read
In one paragraph

Article in BMC health services research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 160 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
160citing papers in PubMed, 8 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

160 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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100 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Wilbroad MutaleCentre for Infectious Disease Research in Zambia, Zambia. wmutale@yahoo.com
Namwinga Chintu
Cheryl Amoroso
Koku Awoonor-Williams
James Phillips
Colin Baynes
Cathy Michel
Angela Taylor
Kenneth Sherr
Population Health Implementation and Training – Africa Health Initiative Data Collaborative

Funding

HEALTH SYSTEMS STRENGTHENING TO IMPROVE HEALTH OUTCOMES: APPLYING IMPLEMENTATIONK02TW009207 · FIC · UNIVERSITY OF WASHINGTON · PI SHERR, KENNETH · 2011 to 2015
$403k
FIC NIH HHS K02TW009207
6 · The paper itself

Abstract

backgroundWeak health information systems (HIS) are a critical challenge to reaching the health-related Millennium Development Goals because health systems performance cannot be adequately assessed or monitored where HIS data are incomplete, inaccurate, or untimely. The Population Health Implementation and Training (PHIT) Partnerships were established in five sub-Saharan African countries (Ghana, Mozambique, Rwanda, Tanzania, and Zambia) to catalyze advances in strengthening district health systems. Interventions were tailored to the setting in which activities were planned. COMPARISONS ACROSS STRATEGIES: All five PHIT Partnerships share a common feature in their goal of enhancing HIS and linking data with improved decision-making, specific strategies varied. Mozambique, Ghana, and Tanzania all focus on improving the quality and use of the existing Ministry of Health HIS, while the Zambia and Rwanda partnerships have introduced new information and communication technology systems or tools. All partnerships have adopted a flexible, iterative approach in designing and refining the development of new tools and approaches for HIS enhancement (such as routine data quality audits and automated troubleshooting), as well as improving decision making through timely feedback on health system performance (such as through summary data dashboards or routine data review meetings). The most striking differences between partnership approaches can be found in the level of emphasis of data collection (patient versus health facility), and consequently the level of decision making enhancement (community, facility, district, or provincial leadership). DISCUSSION: Design differences across PHIT Partnerships reflect differing theories of change, particularly regarding what information is needed, who will use the information to affect change, and how this change is expected to manifest. The iterative process of data use to monitor and assess the health system has been heavily communication dependent, with challenges due to poor feedback loops. Implementation to date has highlighted the importance of engaging frontline staff and managers in improving data collection and its use for informing system improvement. Through rigorous process and impact evaluation, the experience of the PHIT teams hope to contribute to the evidence base in the areas of HIS strengthening, linking HIS with decision making, and its impact on measures of health system outputs and impact.

Indexed as

Africa South of the SaharaDecision Support Systems, ClinicalHealth Information SystemsQuality Improvement

Identifiers

PMID23819699
PMCPMC3668230

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.