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National guidelines for data quality in surveys: An overview

Good quality health, nutrition and demographic survey data are vital for evidence-based decision-making. Existing literature indicates system specific, data collection and reporting gaps that affect quality of health, nutrition and demographic survey data, thereby affecting its usability and relevan...

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Autores principales: Rao, M. Vishnu Vardhana, Sahu, Damodar, Nair, Saritha, Sharma, Ravendra Kumar, Gulati, Bal Kishan, Acharya, Rajib, Mahapatra, Bidhubhusan, Ramesh, Sowmya, Khan, Nizamuddin, Chaudhuri, Trisha, Sandal, Kanika, Deepani, Vijit, Dey, Sangeeta, Saggurti, Niranjan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10278914/
https://www.ncbi.nlm.nih.gov/pubmed/37056070
http://dx.doi.org/10.4103/ijmr.ijmr_1261_22
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author Rao, M. Vishnu Vardhana
Sahu, Damodar
Nair, Saritha
Sharma, Ravendra Kumar
Gulati, Bal Kishan
Acharya, Rajib
Mahapatra, Bidhubhusan
Ramesh, Sowmya
Khan, Nizamuddin
Chaudhuri, Trisha
Sandal, Kanika
Deepani, Vijit
Dey, Sangeeta
Saggurti, Niranjan
author_facet Rao, M. Vishnu Vardhana
Sahu, Damodar
Nair, Saritha
Sharma, Ravendra Kumar
Gulati, Bal Kishan
Acharya, Rajib
Mahapatra, Bidhubhusan
Ramesh, Sowmya
Khan, Nizamuddin
Chaudhuri, Trisha
Sandal, Kanika
Deepani, Vijit
Dey, Sangeeta
Saggurti, Niranjan
author_sort Rao, M. Vishnu Vardhana
collection PubMed
description Good quality health, nutrition and demographic survey data are vital for evidence-based decision-making. Existing literature indicates system specific, data collection and reporting gaps that affect quality of health, nutrition and demographic survey data, thereby affecting its usability and relevance. To mitigate these, the National Data Quality Forum (NDQF), under the Indian Council of Medical Research (ICMR) - National Institute of Medical Statistics (NIMS) developed the National Guidelines for Data Quality in Surveys delineating assurance mechanisms to generate standard quality data in surveys. The present article highlights the principles from the guidelines for informing survey researchers/organizations in generating good quality survey data. It describes the process of development of the national guidelines, principles for each of the survey phases listed in the document and applicability of them to data user for ensuring data quality. The guidelines may be useful to a broad-spectrum of audience such as data producers from government and non-government organizations, policy makers, research institutions, as well as individual researchers, thereby playing a vital role in improving quality of health, nutrition and demographic data ecosystem.
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spelling pubmed-102789142023-06-20 National guidelines for data quality in surveys: An overview Rao, M. Vishnu Vardhana Sahu, Damodar Nair, Saritha Sharma, Ravendra Kumar Gulati, Bal Kishan Acharya, Rajib Mahapatra, Bidhubhusan Ramesh, Sowmya Khan, Nizamuddin Chaudhuri, Trisha Sandal, Kanika Deepani, Vijit Dey, Sangeeta Saggurti, Niranjan Indian J Med Res Policy: Process Paper Good quality health, nutrition and demographic survey data are vital for evidence-based decision-making. Existing literature indicates system specific, data collection and reporting gaps that affect quality of health, nutrition and demographic survey data, thereby affecting its usability and relevance. To mitigate these, the National Data Quality Forum (NDQF), under the Indian Council of Medical Research (ICMR) - National Institute of Medical Statistics (NIMS) developed the National Guidelines for Data Quality in Surveys delineating assurance mechanisms to generate standard quality data in surveys. The present article highlights the principles from the guidelines for informing survey researchers/organizations in generating good quality survey data. It describes the process of development of the national guidelines, principles for each of the survey phases listed in the document and applicability of them to data user for ensuring data quality. The guidelines may be useful to a broad-spectrum of audience such as data producers from government and non-government organizations, policy makers, research institutions, as well as individual researchers, thereby playing a vital role in improving quality of health, nutrition and demographic data ecosystem. Wolters Kluwer - Medknow 2022-12 2023-04-05 /pmc/articles/PMC10278914/ /pubmed/37056070 http://dx.doi.org/10.4103/ijmr.ijmr_1261_22 Text en Copyright: © 2023 Indian Journal of Medical Research https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Policy: Process Paper
Rao, M. Vishnu Vardhana
Sahu, Damodar
Nair, Saritha
Sharma, Ravendra Kumar
Gulati, Bal Kishan
Acharya, Rajib
Mahapatra, Bidhubhusan
Ramesh, Sowmya
Khan, Nizamuddin
Chaudhuri, Trisha
Sandal, Kanika
Deepani, Vijit
Dey, Sangeeta
Saggurti, Niranjan
National guidelines for data quality in surveys: An overview
title National guidelines for data quality in surveys: An overview
title_full National guidelines for data quality in surveys: An overview
title_fullStr National guidelines for data quality in surveys: An overview
title_full_unstemmed National guidelines for data quality in surveys: An overview
title_short National guidelines for data quality in surveys: An overview
title_sort national guidelines for data quality in surveys: an overview
topic Policy: Process Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10278914/
https://www.ncbi.nlm.nih.gov/pubmed/37056070
http://dx.doi.org/10.4103/ijmr.ijmr_1261_22
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