Lessons in Digital Epidemiology from COTS-1 : Coordinating Multicentre Research across 10 Countries Using Operational and Technology Innovation to Overcome Funding Deficiencies
Purpose: There is controversy regarding the diagnosis and management of ocular tuberculosis (TB) due to lack of robust evidence. The Collaborative Ocular Tuberculosis Study (COTS) was conducted in stages to enable swift, accurate data collection across 25 participating centers.Method: Data collection was facilitated by a cloud-based data aggregation platform with programmed logic based on anecdotal evidence from uveitis experts corroborated with literature review.Results: The platform enabled standardization of interpretation and collection of data from patient medical records. The pre-programmed logic also ensured the platform only prompted the entry of relevant data based on initial data entered for each unit of analysis. This enabled collection of the vast amounts of data without compromising either of the breadth nor the depth of data collection.Conclusion: The final output from this effort was an in-depth retrospective analysis to facilitate the design of future prospective investigations on ocular TB and develop best practice guidelines.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2020 |
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Erschienen: |
2020 |
Enthalten in: |
Zur Gesamtaufnahme - volume:28 |
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Enthalten in: |
Ocular immunology and inflammation - 28(2020), sup1 vom: 30. Sept., Seite 1-7 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Gunasekeran, Dinesh Visva [VerfasserIn] |
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Links: |
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Themen: |
Clinical research |
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Anmerkungen: |
Date Revised 04.08.2022 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
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doi: |
10.1080/09273948.2020.1744669 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM309047285 |
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520 | |a Purpose: There is controversy regarding the diagnosis and management of ocular tuberculosis (TB) due to lack of robust evidence. The Collaborative Ocular Tuberculosis Study (COTS) was conducted in stages to enable swift, accurate data collection across 25 participating centers.Method: Data collection was facilitated by a cloud-based data aggregation platform with programmed logic based on anecdotal evidence from uveitis experts corroborated with literature review.Results: The platform enabled standardization of interpretation and collection of data from patient medical records. The pre-programmed logic also ensured the platform only prompted the entry of relevant data based on initial data entered for each unit of analysis. This enabled collection of the vast amounts of data without compromising either of the breadth nor the depth of data collection.Conclusion: The final output from this effort was an in-depth retrospective analysis to facilitate the design of future prospective investigations on ocular TB and develop best practice guidelines | ||
650 | 4 | |a Journal Article | |
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700 | 1 | |a Mahajan, Sarakshi |e verfasserin |4 aut | |
700 | 1 | |a Nguyen, Quan Dong |e verfasserin |4 aut | |
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