Evidence map›Paper›PMID 40512696›Full record

ArticlePLOS digital health2025

Missed opportunities for digital health data use in healthcare decision-making: A cross-sectional digital health landscape assessment in Homa Bay county, Kenya.

Mercy Chepkirui, Stephanie Dellicour, Rosemary Musuva, Isdorah Odero, Benson Omondi, Benard Omondi, Eric Onyango, Hellen Barsosio, Lilian Otiso, Gordon Okomo and 7 more

Abstract read
In one paragraph

Article in PLOS digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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

17 authors.

Mercy ChepkiruiMalaria Branch, Kenya Medical Research Institute, Center for Global Health Research, Kisumu, Kenya.ORCID https://orcid.org/0000-0002-3493-574X
Stephanie DellicourDepartment of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
Rosemary MusuvaLVCT Health, Nairobi, Kenya.
Isdorah OderoMalaria Branch, Kenya Medical Research Institute, Center for Global Health Research, Kisumu, Kenya.
Benson OmondiMalaria Branch, Kenya Medical Research Institute, Center for Global Health Research, Kisumu, Kenya.
Benard OmondiMalaria Branch, Kenya Medical Research Institute, Center for Global Health Research, Kisumu, Kenya.
Eric OnyangoMalaria Branch, Kenya Medical Research Institute, Center for Global Health Research, Kisumu, Kenya.
Hellen BarsosioMalaria Branch, Kenya Medical Research Institute, Center for Global Health Research, Kisumu, Kenya.
Lilian OtisoLVCT Health, Nairobi, Kenya.
Gordon OkomoDepartment of Health, Homa Bay County, Homa Bay, Kenya.
Maina WaweruGoldInData (GIND), Nairobi, Kenya.
Maia LesoskyNational Heart and Lung Institute, Imperial College, London, United Kingdom.
Tara TancredDepartment of International Public Health, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
Yussif AlhassanDepartment of International Public Health, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
Simon KariukiMalaria Branch, Kenya Medical Research Institute, Center for Global Health Research, Kisumu, Kenya.
Feiko terKuileMalaria Branch, Kenya Medical Research Institute, Center for Global Health Research, Kisumu, Kenya.
Miriam TaegtmeyerDepartment of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The proliferation of digital health systems in Sub-Saharan Africa is driven by the need to improve healthcare access and decision-making. This digitisation has been marked by fragmented implementation, the absence of universal patient identifiers, inadequate system linkages, limited data sharing, and reliance on donor-driven funding. Consequently, the increase in digital health data generation is not matched by similar growth in data use for decision-making, patient-centric care, and research. This study aimed to describe the digital health landscape in Homa Bay County and highlight the strengths and limitations of using digital health data for healthcare decision-making. We used mixed methods. A cross-sectional survey was conducted between June 2022 and October 2023 in 112 healthcare facilities to identify available digital health systems and assess their adoption and utilisation. Thirty-three in-depth interviews were conducted with relevant digital health stakeholders to seek stakeholder perspectives. Our study identified ten different digital health systems, nine of which were in active use. 91% (102/112) of surveyed health facilities had Kenya Electronic Medical Record system deployed for HIV patient management. Eight additional digital systems were available alongside this HIV system, but deployment was fragmented. Challenges to digital systems usage included lack of interoperability, unreliable internet, system downtime, power outages, staff turnover, patient workload, and lack of universal patient identifiers. The study identified multiple systems in use, with the HIV care management system being the most prevalent. The primary challenge hindering effective digital data utilisation is network instability, alongside issues such as the lack of interoperability, disjointed data quality assurance processes, and non-standardised patient identifiers. Recommendations include establishing a routine care data governance framework, implementing universal unique patient identifiers, harmonised data quality practices, advocating for universally compatible digital systems, promoting interoperability, and evaluating the suitability of the existing digital health data for surveillance research and decision-making.

Identifiers

PMID40512696
PMCPMC12165431

What OpenQuestion 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 OpenQuestion graph.