Evidence map›Paper›PMID 42840279›Full record

ArticleBMC digital health2026

Development and implementation of "

Shifa Salman Habib, Ammarah Ali, Muhammad Fazal Hussain Qureshi, Shehla Zaidi, Fasih Hansmukh, Wardah Ahmed, Tahira Hasham, Sajad Alam, Khalid Memon, Naveed Bhutto and 2 more

Abstract read
In one paragraph

Article in BMC digital health, 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

12 authors.

Shifa Salman HabibDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.ORCID 0000-0002-4531-8472
Ammarah AliDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.
Muhammad Fazal Hussain QureshiDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.ORCID 0000-0002-4416-4379
Shehla ZaidiUniversity College London, Global Business School for Health, London, UK.
Fasih HansmukhDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.
Wardah AhmedDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.
Tahira HashamDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.
Sajad AlamDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.
Khalid MemonDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.
Naveed BhuttoDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.
Diwakar MohanDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA.ORCID 0000-0002-7532-366X
Zahid Ali MemonDepartment of Community Health Sciences, Aga Khan University, Karachi, Pakistan.

Funding

Bill & Melinda Gates Foundation INV-037378
6 · The paper itself

Abstract

Background: Undernutrition remains a leading driver of child mortality and morbidity in low- and middle-income countries, yet surveillance and case management in Pakistan still rely largely on infrequent surveys and paper-based registers that cannot track nutritional status in real time. The private sector, where most Pakistani households seek care, has been largely excluded from nutrition programming. We describe the development and early implementation of Mazboot Bunyad, a digital nutrition registry embedded within an integrated nutrition-immunization programme at private provider clinics in high-risk, low-income settlements of Karachi. Methods: The Android application and web dashboard used in this implementation study were designed through a participatory process using the AHEAD framework, in consultation with provincial health authorities, immunization staff, and community nutrition worker. The system used QR-linked child records, an embedded digital decision-support system that classified children by mid-upper arm circumference and has automated follow-up reminders. The tool was deployed across 33 clinics, and routinely collected programme data, a preliminary analysis of data from 1 July to 31 December 2024 were retrospectively reviewed. Results: During the period of 6 months, the Conclusions: Early implementation of Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s44247-026-00303-7.

Indexed as

Digital decision support systemDigital health interventionImplementation researchLow- and middle-income countriesNutrition–immunization integrationNutrition registryNutrition surveillancePakistanPrivate sector engagementUndernutrition

Identifiers

PMID42840279
PMCPMC13638715

What OpenQuestion holds

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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.