Evidence map›Paper›PMID 39348172›Full record

ArticleJournal of medical Internet research2024

Quality, Usability, and Trust Challenges to Effective Data Use in the Deployment and Use of the Bangladesh Nutrition Information System Dashboard: Qualitative Study.

Berhaun Fesshaye, Shivani Pandya, Lena Kan, Anna Kalbarczyk, Kelsey Alland, S M Mustafizur Rahman, Md Mofijul Islam Bulbul, Piyali Mustaphi, Muhammad Abu Bakr Siddique, Md Imtiaz Alam Tanim and 3 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Development and implementation of "BMC digital health · 2026
    Article
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

13 authors.

Berhaun FesshayeDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-2868-4187
Shivani PandyaDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-3524-9861
Lena KanDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-1910-577X
Anna KalbarczykDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-6143-8634
Kelsey AllandDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0001-8464-6308
S M Mustafizur RahmanNational Nutrition Services, Ministry of Health & Family Welfare, Dhaka, Bangladesh.ORCID 0000-0002-9606-3836
Md Mofijul Islam BulbulNational Nutrition Services, Ministry of Health & Family Welfare, Dhaka, Bangladesh.ORCID 0000-0002-1946-9058
Piyali MustaphiNutrition Section, UNICEF, Bangladesh Country Office, Dhaka, Bangladesh.ORCID 0009-0005-2767-6662
Muhammad Abu Bakr SiddiqueNutrition Section, UNICEF, Bangladesh Country Office, Dhaka, Bangladesh.ORCID 0000-0001-7854-5172
Md Imtiaz Alam TanimmPower Social Enterprises Ltd, Dhaka, Bangladesh.ORCID 0009-0003-6293-6365
Mridul ChowdhurymPower Social Enterprises Ltd, Dhaka, Bangladesh.ORCID 0000-0003-4854-3955
Tajkia RummanmPower Social Enterprises Ltd, Dhaka, Bangladesh.ORCID 0000-0003-0950-1306
Alain B LabriqueDepartment of Digital Health & Innovation, World Health Organization, Geneva, Switzerland.ORCID 0000-0003-2502-7819

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundEvidence-based decision-making is essential to improve public health benefits and resources, especially in low- and middle-income countries (LMICs), but the mechanisms of its implementation remain less straightforward. The availability of high-quality, reliable, and sufficient data in LMICs can be challenging due to issues such as a lack of human resource capacity and weak digital infrastructure, among others. Health information systems (HISs) have been critical for aggregating and integrating health-related data from different sources to support evidence-based decision-making. Nutrition information systems (NISs), which are nutrition-focused HISs, collect and report on nutrition-related indicators to improve issues related to malnutrition and food security-and can assist in improving populations' nutritional statuses and the integration of nutrition programming into routine health services. Data visualization tools (DVTs) such as dashboards have been recommended to support evidence-based decision-making, leveraging data from HISs or NISs. The use of such DVTs to support decision-making has largely been unexplored within LMIC contexts. In Bangladesh, the Mukto dashboard was developed to display and visualize nutrition-related performance indicators at the national and subnational levels. However, despite this effort, the current use of nutrition data to guide priorities and decisions remains relatively nascent and underused.

objectiveThe goal of this study is to better understand how Bangladesh's NIS, including the Mukto dashboard, has been used and areas for improvement to facilitate its use for evidence-based decision-making toward ameliorating nutrition-related service delivery and the health status of communities in Bangladesh.

methodsPrimary data collection was conducted through qualitative semistructured interviews with key policy-level stakeholders (n=24). Key informants were identified through purposive sampling and were asked questions about the experiences and challenges with the NIS and related nutrition dashboards.

resultsMain themes such as trust, data usability, personal power, and data use for decision-making emerged from the data. Trust in both data collection and quality was lacking among many stakeholders. Poor data usability stemmed from unstandardized indicators, irregular data collection, and differences between rural and urban data. Insufficient personal power and staff training coupled with infrastructural challenges can negatively affect data at the input stage. While stakeholders understood and expressed the importance of evidence-based decision-making, ultimately, they noted that the data were not being used to their maximum potential.

conclusionsLeveraging DVTs can improve the use of data for evidence-based decision-making, but decision makers must trust that the data are believable, credible, timely, and responsive. The results support the significance of a tailored data ecosystem, which has not reached its full potential in Bangladesh. Recommendations to reach this potential include ensuring a clear intended user base and accountable stakeholders are present. Systems should also have the capacity to ensure data credibility and support ongoing personal power requirements.

Indexed as

Qualitative ResearchBangladeshHealth Information SystemsHumansNutritional StatusTrustdashboarddata for decision-makingdeliverydigital healthexperienceexperienceshealth care managementhealth information systemsinformation systeminformation systemsinterviewinterviewsLMIClow- and middle-income countriesnutritionnutritionalserviceservices

Identifiers

PMID39348172
PMCPMC11474113

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.