Dataset Information

High Coverage and Low Utilization of the Double Fortified Salt Program in Uttar Pradesh, India: Implications for Program Implementation and Evaluation.

ABSTRACT: Background:Double fortified salt (DFS) is efficacious in addressing iron deficiency, but evidence of its effectiveness is limited. The few published evaluations do not include details on program implementation, limiting their utility for programmatic decisions. Objectives:We sought to characterize the coverage of a DFS program implemented through the Public Distribution System (PDS) in Uttar Pradesh, India, and understand the drivers of DFS adherence. Methods:After 8 mo of implementation, we surveyed 1202 households in 5 districts and collected data on sociodemographic characteristics, asset ownership, food security, and regular PDS utilization. We defined DFS program coverage as the proportion of PDS beneficiaries who had heard of and purchased DFS, and we defined DFS adherence as DFS use reported by households. We used principal component analysis to create an asset-based index of relative wealth, and we categorized households into higher/lower relative wealth quintiles. We conducted path analyses to examine the drivers of DFS adherence, particularly the mediated influence of household wealth on DFS adherence. The evaluation is registered with 3ie's Registry for International Development Impact Evaluations (RIDIE-STUDY-ID-58f6eeb45c050). Results:The DFS program had good coverage: 83% of respondents had heard of DFS and 74% had purchased it at least once. However, only 23% exclusively used DFS. Respondents had low awareness about DFS benefits and considered DFS quality as poor. Being in a lower household wealth quintile and being food insecure were significant drivers of DFS adherence, and regular PDS utilization acted as a mediator. Adherence was lower in urban areas. Conclusions:We observed significant heterogeneity in DFS implementation as reflected by high coverage and low adherence. Findings from this process evaluation informed the design of an adaptive impact evaluation and provided generalizable insights for ensuring that the potential for impact is realized. Efforts are needed to increase awareness, improve product quality, as well as mitigate against the sensory challenges identified.

SUBMITTER: Cyriac S

PROVIDER: S-EPMC7455457 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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High Coverage and Low Utilization of the Double Fortified Salt Program in Uttar Pradesh, India: Implications for Program Implementation and Evaluation.

Cyriac Shruthi S Haardörfer Regine R Neufeld Lynnette M LM Girard Amy Webb AW Ramakrishnan Usha U Martorell Reynaldo R Mbuya Mduduzi N N MNN

Current developments in nutrition 20200810 9

<h4>Background</h4>Double fortified salt (DFS) is efficacious in addressing iron deficiency, but evidence of its effectiveness is limited. The few published evaluations do not include details on program implementation, limiting their utility for programmatic decisions.<h4>Objectives</h4>We sought to characterize the coverage of a DFS program implemented through the Public Distribution System (PDS) in Uttar Pradesh, India, and understand the drivers of DFS adherence.<h4>Methods</h4>After 8 mo of ...[more]

PMID: 32885134

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Project description:Shifting childbirth into facilities has not improved health outcomes for mothers and newborns as significantly as hoped. Improving the quality and safety of care provided during facility-based childbirth requires helping providers to adhere to essential birth practices-evidence-based behaviors that reduce harm to and save lives of mothers and newborns. To achieve this goal, we developed the BetterBirth Program, which we tested in a matched-pair, cluster-randomized controlled trial in Uttar Pradesh, India. The goal of this intervention was to improve adoption and sustained use of the World Health Organization Safe Childbirth Checklist (SCC), an organized collection of 28 essential birth practices that are known to improve the quality of facility-based childbirth care. Here, we describe the BetterBirth Program in detail, including its 4 main features: implementation tools, an implementation strategy of coaching, an implementation pathway (Engage-Launch-Support), and a sustainability plan. This coaching-based implementation of the SCC motivates and empowers care providers to identify, understand, and resolve the barriers they face in using the SCC with the resources already available. We describe important lessons learned from our experience with the BetterBirth Program as it was tested in the BetterBirth Trial. For example, the emphasis on relationship building and respect led to trust between coaches and birth attendants and helped influence change. In addition, the cloud-based data collection and feedback system proved a valuable asset in the coaching process. More research on coaching-based interventions is required to refine our understanding of what works best to improve quality and safety of care in various settings.Note: At the time of publication of this article, the results of evaluation of the impact of the BetterBirth Program were pending publication in another journal. After the impact findings have been published, we will update this article with a reference to the impact findings.

Project description:This paper explores the multilevel factors associated with maternal health utilization in India's most populous state, Uttar Pradesh. 3 key utilization practices: registration of pregnancy, receipt of antenatal care, and delivery at home are examined for district and individual level predictors. The data is based on 5666 household surveys conducted as part of a baseline evaluation of the Uttar Pradesh Technical Support Unit (UPTSU.) program.This intervention aims to assist the Government of Uttar Pradesh in increasing the efficiency, effectiveness, and equity of service delivery across a continuum of reproductive, maternal, new-born, child, and adolescent health (RMNCH+A) outcomes.The paper employs multilevel models that control for individuals being nested within districts in order to understand the predictors of maternal health care utilization.The study identifies several individual-level predictors of health care utilization, including: literacy of the woman, the husband's schooling, age at marriage, and socio-economic factors. Key predictors of pregnancy registration include husband's schooling (OR 1.49, 95% CI 1.26-1.76), having a bank account (OR 1.36, 95% CI 1.11-1.68), and owning a house (OR 2.28, 95% CI 1.85-2.80). Factors affecting antenatal care include the woman's literacy (OR 1.49, 95% CI 1.28-1.73), the respondent having had a job in the last year (OR 1.39, 95% CI 1.10-1.77), and owning a house (OR 2.83, 95% CI 2.27-3.53). Home delivery tends to be associated with woman's literacy (OR 0.62, 95% CI 0.54-0.72) and marriage age of 15 and younger (OR 1.48, 95% CI 1.26-1.73).Interventions having equity considerations need to disrupt existing patterns of the health gradient. Successful implementation of such interventions, necessitate understanding the mechanisms that can disrupt the unequal utilization patterns and target domains of disadvantage. Knowledge of key predictors of utilization can aid in the implementation of such complex interventions.

Project description:There are few published standards or methodological guidelines for integrating Data Quality Assurance (DQA) protocols into large-scale health systems research trials, especially in resource-limited settings. The BetterBirth Trial is a matched-pair, cluster-randomized controlled trial (RCT) of the BetterBirth Program, which seeks to improve quality of facility-based deliveries and reduce 7-day maternal and neonatal mortality and maternal morbidity in Uttar Pradesh, India. In the trial, over 6300 deliveries were observed and over 153,000 mother-baby pairs across 120 study sites were followed to assess health outcomes. We designed and implemented a robust and integrated DQA system to sustain high-quality data throughout the trial.We designed the Data Quality Monitoring and Improvement System (DQMIS) to reinforce six dimensions of data quality: accuracy, reliability, timeliness, completeness, precision, and integrity. The DQMIS was comprised of five functional components: 1) a monitoring and evaluation team to support the system; 2) a DQA protocol, including data collection audits and targets, rapid data feedback, and supportive supervision; 3) training; 4) standard operating procedures for data collection; and 5) an electronic data collection and reporting system. Routine audits by supervisors included double data entry, simultaneous delivery observations, and review of recorded calls to patients. Data feedback reports identified errors automatically, facilitating supportive supervision through a continuous quality improvement model.The five functional components of the DQMIS successfully reinforced data reliability, timeliness, completeness, precision, and integrity. The DQMIS also resulted in 98.33% accuracy across all data collection activities in the trial. All data collection activities demonstrated improvement in accuracy throughout implementation. Data collectors demonstrated a statistically significant (p?=?0.0004) increase in accuracy throughout consecutive audits. The DQMIS was successful, despite an increase from 20 to 130 data collectors.In the absence of widely disseminated data quality methods and standards for large RCT interventions in limited-resource settings, we developed an integrated DQA system, combining auditing, rapid data feedback, and supportive supervision, which ensured high-quality data and could serve as a model for future health systems research trials. Future efforts should focus on standardization of DQA processes for health systems research.ClinicalTrials.gov identifier, NCT02148952 . Registered on 13 February 2014.

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Dataset Information

High Coverage and Low Utilization of the Double Fortified Salt Program in Uttar Pradesh, India: Implications for Program Implementation and Evaluation.

Publications

High Coverage and Low Utilization of the Double Fortified Salt Program in Uttar Pradesh, India: Implications for Program Implementation and Evaluation.

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