Evidence map›Paper›PMID 39348171›Full record

ArticleOnline journal of public health informatics2024

Harnessing Generalizable Real-World Ophthalmic Big Data: Descriptive Analysis of the Bodhya Eye Consortium Model for Collaborative Research.

Ishaana Sood, Shalinder Sabherwal, Umang Mathur, Elesh Jain, Madhu Bhadauria, Deepshikha Agrawal, Ashi Khurana, Vikas Mittal, Avinash Mahindrakar, Vishal Govindahari and 2 more

Abstract read
In one paragraph

Article in Online journal of public health informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

12 authors.

Ishaana SoodDr Shroff's Charity Eye Hospital, New Delhi, India.ORCID https://orcid.org/0000-0003-4907-2956
Shalinder SabherwalDr Shroff's Charity Eye Hospital, New Delhi, India.ORCID https://orcid.org/0000-0001-7687-0748
Umang MathurDr Shroff's Charity Eye Hospital, New Delhi, India.ORCID https://orcid.org/0009-0008-8459-0170
Elesh JainBodhya Eye Consortium, India, India.ORCID https://orcid.org/0000-0002-5718-052X
Madhu BhadauriaBodhya Eye Consortium, India, India.ORCID https://orcid.org/0000-0003-2340-9506
Deepshikha AgrawalBodhya Eye Consortium, India, India.ORCID https://orcid.org/0000-0002-2365-4053
Ashi KhuranaBodhya Eye Consortium, India, India.ORCID https://orcid.org/0000-0003-4205-5256
Vikas MittalBodhya Eye Consortium, India, India.ORCID https://orcid.org/0000-0002-9905-9146
Avinash MahindrakarBodhya Eye Consortium, India, India.ORCID https://orcid.org/0000-0003-3544-910X
Vishal GovindahariBodhya Eye Consortium, India, India.ORCID https://orcid.org/0000-0002-1630-6798
Sucheta KulkarniBodhya Eye Consortium, India, India.ORCID https://orcid.org/0000-0002-3217-8108
Ken K NischalBodhya Eye Consortium, India, India.ORCID https://orcid.org/0000-0001-5616-5275

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEye care organizations and professionals worldwide are increasingly focusing on bridging the gap between population health and medical practice. Recent advances in genomics and anthropology have revealed that most Indian groups trace their ancestry to a blend of 2 genetically distinct populations: Ancestral North Indians, who share genetic affinities with Central Asians, Middle Easterners, Caucasians, and Europeans; and Ancestral South Indians, genetically distinct from groups outside the Indian subcontinent. Studies conducted among North Indian populations can therefore offer insights that are potentially applicable to these diverse global populations, underscoring significant implications for global health.

objectiveThe Bodhya Eye Consortium is a collaboration among 8 high-volume nonprofit eyecare organizations from across North India. The consortium aims to harness real-world data consistently and with assured quality for collaborative research. This paper outlines the formation of the consortium as a proposed model for controlled collaborative research among the leading eyecare organizations of North India.

methodsWe detail the creation and effective implementation of a consortium following a structured road map that included planning and assessment, establishing an exploratory task force, defining specialty areas, setting objectives and priorities, and conducting a SWOT (strengths, weaknesses, opportunities, and threats) analysis. Central to this process was a comprehensive data audit aimed at standardizing data collection across all participating organizations.

resultsThe consortium currently comprises 9 organizations, each represented in the governance structure by the Governing Council. Scientific standards for published research are established and overseen by the Scientific Committee, while the Conflict Resolution Committee manages any unresolved disputes. The consortium's working groups, organized by various eyecare specialties, collaborate on research projects through virtual interactions. A foundational step in this process was the organizationwide data audit, which revealed that most organizations complied with accurate and standardized data collection practices. Organizations with deficiencies in data completeness developed action plans to address them. Subsequently, the consortium adopted data collection proformas, contributing to the publication of high-quality manuscripts characterized by low dropout rates.

conclusionsThe collaborative research conducted by the Bodhya Eye Consortium-a group of high-volume eyecare organizations primarily from North India-offers a unique opportunity to contribute to scientific knowledge across various domains of eyecare. By leveraging the established heterogeneity of anthropological and genomic origins within the population, the findings can be generalizable, to some extent, to European, Middle Eastern, and European American populations. This access to potentially invaluable, generalizable data has significant global health implications and opens possibilities for broader collaboration. The model outlined in this descriptive paper can serve as a blueprint for other health care organizations looking to develop similar collaborations for research and knowledge sharing.

Indexed as

anthropological and genomic heterogeneitybig datacollaborative researchconsortiumgeneralizabilityglobal health impactNorth India

Identifiers

PMID39348171
PMCPMC11474137

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.