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Impact assessment and cost-effectiveness of m-health application used by community health workers for maternal, newborn and child health care services in rural Uttar Pradesh, India: a study protocol

BACKGROUND: An m-health application has been developed and implemented with community health workers to improve their counseling in a rural area of India. The ultimate aim was to generate demand and improve utilization of key maternal, neonatal, and child health services. The present study aims to a...

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Autores principales: Prinja, Shankar, Nimesh, Ruby, Gupta, Aditi, Bahuguna, Pankaj, Thakur, Jarnail Singh, Gupta, Madhu, Singh, Tarundeep
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Co-Action Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4870358/
https://www.ncbi.nlm.nih.gov/pubmed/27189200
http://dx.doi.org/10.3402/gha.v9.31473
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author Prinja, Shankar
Nimesh, Ruby
Gupta, Aditi
Bahuguna, Pankaj
Thakur, Jarnail Singh
Gupta, Madhu
Singh, Tarundeep
author_facet Prinja, Shankar
Nimesh, Ruby
Gupta, Aditi
Bahuguna, Pankaj
Thakur, Jarnail Singh
Gupta, Madhu
Singh, Tarundeep
author_sort Prinja, Shankar
collection PubMed
description BACKGROUND: An m-health application has been developed and implemented with community health workers to improve their counseling in a rural area of India. The ultimate aim was to generate demand and improve utilization of key maternal, neonatal, and child health services. The present study aims to assess the impact and cost-effectiveness of this project. METHODS/DESIGN: A pre–post quasi-experimental design with a control group will be used to undertake difference in differences analysis for assessing the impact of intervention. The Annual Health Survey (2011) will provide pre-intervention data, and a household survey will be carried out to provide post-intervention data. Two community development blocks where the intervention was introduced will be treated as intervention blocks while two controls blocks are selected after matching with intervention blocks on three indicators: average number of antenatal care checkups, percentage of women receiving three or more antenatal checkups, and percentage of institutional deliveries. Two categories of beneficiaries will be interviewed in both areas: women with a child between 29 days and 6 months and women with a child between 12 and 23 months. Propensity score matched samples from intervention and control areas in pre–post periods will be analyzed using the difference in differences method to estimate the impact of intervention in utilization of key services. Bottom-up costing methods will be used to assess the cost of implementing intervention. A decision model will estimate long-term effects of improved health services utilization on mortality, morbidity, and disability. Cost-effectiveness will be assessed in terms of incremental cost per disability-adjusted life year averted and cost per unit increase in composite service coverage in intervention versus control groups. CONCLUSIONS: The study will generate significant evidence on impact of the m-health intervention for maternal, neonatal, and child services and on the cost of scaling up m-health technology for accredited social health activists in India.
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spelling pubmed-48703582016-05-25 Impact assessment and cost-effectiveness of m-health application used by community health workers for maternal, newborn and child health care services in rural Uttar Pradesh, India: a study protocol Prinja, Shankar Nimesh, Ruby Gupta, Aditi Bahuguna, Pankaj Thakur, Jarnail Singh Gupta, Madhu Singh, Tarundeep Glob Health Action Study Design Article BACKGROUND: An m-health application has been developed and implemented with community health workers to improve their counseling in a rural area of India. The ultimate aim was to generate demand and improve utilization of key maternal, neonatal, and child health services. The present study aims to assess the impact and cost-effectiveness of this project. METHODS/DESIGN: A pre–post quasi-experimental design with a control group will be used to undertake difference in differences analysis for assessing the impact of intervention. The Annual Health Survey (2011) will provide pre-intervention data, and a household survey will be carried out to provide post-intervention data. Two community development blocks where the intervention was introduced will be treated as intervention blocks while two controls blocks are selected after matching with intervention blocks on three indicators: average number of antenatal care checkups, percentage of women receiving three or more antenatal checkups, and percentage of institutional deliveries. Two categories of beneficiaries will be interviewed in both areas: women with a child between 29 days and 6 months and women with a child between 12 and 23 months. Propensity score matched samples from intervention and control areas in pre–post periods will be analyzed using the difference in differences method to estimate the impact of intervention in utilization of key services. Bottom-up costing methods will be used to assess the cost of implementing intervention. A decision model will estimate long-term effects of improved health services utilization on mortality, morbidity, and disability. Cost-effectiveness will be assessed in terms of incremental cost per disability-adjusted life year averted and cost per unit increase in composite service coverage in intervention versus control groups. CONCLUSIONS: The study will generate significant evidence on impact of the m-health intervention for maternal, neonatal, and child services and on the cost of scaling up m-health technology for accredited social health activists in India. Co-Action Publishing 2016-05-13 /pmc/articles/PMC4870358/ /pubmed/27189200 http://dx.doi.org/10.3402/gha.v9.31473 Text en © 2016 Shankar Prinja et al. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for any purpose, even commercially, provided the original work is properly cited and states its license.
spellingShingle Study Design Article
Prinja, Shankar
Nimesh, Ruby
Gupta, Aditi
Bahuguna, Pankaj
Thakur, Jarnail Singh
Gupta, Madhu
Singh, Tarundeep
Impact assessment and cost-effectiveness of m-health application used by community health workers for maternal, newborn and child health care services in rural Uttar Pradesh, India: a study protocol
title Impact assessment and cost-effectiveness of m-health application used by community health workers for maternal, newborn and child health care services in rural Uttar Pradesh, India: a study protocol
title_full Impact assessment and cost-effectiveness of m-health application used by community health workers for maternal, newborn and child health care services in rural Uttar Pradesh, India: a study protocol
title_fullStr Impact assessment and cost-effectiveness of m-health application used by community health workers for maternal, newborn and child health care services in rural Uttar Pradesh, India: a study protocol
title_full_unstemmed Impact assessment and cost-effectiveness of m-health application used by community health workers for maternal, newborn and child health care services in rural Uttar Pradesh, India: a study protocol
title_short Impact assessment and cost-effectiveness of m-health application used by community health workers for maternal, newborn and child health care services in rural Uttar Pradesh, India: a study protocol
title_sort impact assessment and cost-effectiveness of m-health application used by community health workers for maternal, newborn and child health care services in rural uttar pradesh, india: a study protocol
topic Study Design Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4870358/
https://www.ncbi.nlm.nih.gov/pubmed/27189200
http://dx.doi.org/10.3402/gha.v9.31473
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