Evidence map›Paper›PMID 42035093›Full record

Trial reportBMC health services research2026

Does a paper-based information system based on a human-centred design (PHISICC) reduce the time needed for reporting health data in Nigeria?

Ogonna N O Nwankwo, Angela Oyo-Ita, Nnette Ekpenyong, Agbor Iwasam, Christian Auer, Amanda Ross, Kaspar Wyss, Xavier Bosch-Capblanch

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC health services research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Ogonna N O NwankwoSwiss Tropical and Public Health Institute, Allschwil, Switzerland. drogonnanwankwo@gmail.com.
Angela Oyo-ItaDepartment of Community Medicine, University of Calabar, Calabar, Nigeria.
Nnette EkpenyongDepartment of Community Medicine, University of Calabar, Calabar, Nigeria.
Agbor IwasamDepartment of Community Medicine, University of Calabar, Calabar, Nigeria.
Christian AuerSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
Amanda RossSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
Kaspar WyssSwiss Tropical and Public Health Institute, Allschwil, Switzerland.
Xavier Bosch-CapblanchSwiss Tropical and Public Health Institute, Allschwil, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFrontline health workers spend a substantial part of their time on data related tasks that mainly serve the reporting needs of the higher levels of the health system, potentially compromising the quality of care. This study aims to assess the effects of an innovative paper-based health information system (PHISICC), developed using a human centred design approach, on the time health workers spend on data-related activities, compared to the standard health information tools.

methodsThis is a time-motion study embedded within the PHISICC cluster randomised controlled trial in the Yala Local Government Area in Nigeria. In 25 primary health care facilities per arm, health workers carrying out their regular activities were continuously observed for one to three days over a three months period. A random effects logistic regression model was used to estimate the effect of the intervention on the proportion of time spent on several types of activities.

resultsThe median total observation time per health facility was 8 hours and 7 minutes in the intervention arm and 8 hours and 30 minutes in the control arm. Health workers using PHISICC spent significantly more proportion of time in meeting personal needs (16.6% vs 6.9%; O.R.: 2.87; 95% CI: 1.03 to 7.99) and on tallying tasks (9.5% vs 1.3%; O.R.: 7.86; 95% CI: 2.39 to 25.93). However, there was no significant difference in the proportion of time spent on overall data-related activities between the two arms (41.3% with PHISICC vs 45.0% with standard tools).

conclusionThe PHISICC intervention increased tallying time, expected by design, but this did not translate into an overall reduction of data related time due to the easing of monthly reporting. The uptake of the intervention did not change reporting practices, likely due to the heavily rooted habits of health workers. TRIAL REGISTRATION NUMBER: PACTR201904664660639

Indexed as

Health Information SystemsHumansNigeriaPrimary Health CareTime and Motion StudiesTime FactorsCluster randomised control trialHealth informationHealth systemHealth workersHuman resources for healthNigeriaPerformancePrimary healthcareQuality of careTime motion

Identifiers

PMID42035093
PMCPMC13270621

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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.