Evidence map›Paper›PMID 37006561›Full record

ArticleFrontiers in public health2023

How digital transformation can accelerate data use in health systems.

Laurie Werner, Chilunga Puta, Taonga Chilalika, Sara Walker Hyde, Hannah Cooper, Hallie Goertz, Maya Rivera Hildebrand, Christina Bernadotte, Veronica Kapnick

Full text read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–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

18 citing papers in PubMed.

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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

9 authors.

Laurie WernerPATH, Seattle, WA, United States.
Chilunga PutaPATH, Seattle, WA, United States.
Taonga ChilalikaPATH, Seattle, WA, United States.
Sara Walker HydeCooper/Smith, Austin, TX, United States.
Hannah CooperCooper/Smith, Austin, TX, United States.
Hallie GoertzPATH, Seattle, WA, United States.
Maya Rivera HildebrandPATH, Seattle, WA, United States.
Christina BernadottePATH, Seattle, WA, United States.
Veronica KapnickGreat Impacts Consulting, Seattle, WA, United States.

Funding

Gates Foundation INV-003316
6 · The paper itself

Abstract

Introduction: We are in an era of rapid technological advance and digitalization. Countries around the world want to leverage technology to improve health outcomes by accelerating data use and increasing evidence-based decision-making to inform action in the health sector. Yet, there is no "one size fits all" approach to achieving this. To understand more, PATH and Cooper/Smith conducted a study documenting and analyzing the experiences of five African countries (Burkina Faso, Ethiopia, Malawi, South Africa, and Tanzania) that are on this digitalization journey. The goal was to examine their different approaches and develop a holistic model of digital transformation for data use that identifies what the essential components for digitalization success are and how they interact with each other. Methods: Our research had two phases: first, we analyzed documentation from the five countries to identify core components and enabling factors for successful digital transformation, as well as barriers encountered; and second, we held interviews with key informants and focus groups within the countries to fill gaps and validate findings. Findings: Our findings show that the core components of digital transformation success are highly interrelated. We found that the more successful digitalization efforts address issues that cut across components-such as stakeholder engagement, health workforce capacity, and governance structures-and consider more than just systems and tools. Specifically, we found two critical components of digital transformation that have not been addressed in previous models like the eHealth strategy building blocks developed by the World Health Organization and the International Telecommunication Union: (a) cultivating a culture of data use throughout the health sector and (b) managing the process of system-wide behavior change required to move from manual or paper-based to digital systems. Conclusion: The resulting model is based on the study's findings and is intended to inform low- and middle-income (LMIC) country governments, global policymakers (such as WHO), implementers, and funders. It provides specific, concrete, evidence-based strategies these key stakeholders can implement to improve digital transformation for data use in health systems, planning, and service delivery.

Indexed as

Delivery of Health CareTelemedicineEthiopiaFocus GroupsGovernmentBurkina Fasodigital healthEthiopiahealth datahealth information systemMalawiSouth AfricaTanzania

Identifiers

PMID37006561
PMCPMC10050688

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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 OpenQuestion graph.