Dataset Information

Impact of mHealth interventions for reproductive, maternal, newborn and child health and nutrition at scale: BBC Media Action and the Ananya program in Bihar, India.

ABSTRACT:

Background

Mobile health (mHealth) tools have potential for improving the reach and quality of health information and services through community health workers in low- and middle-income countries. This study evaluates the impact of an mHealth tool implemented at scale as part of the statewide reproductive,maternal, newborn and child health and nutrition (RMNCHN) program in Bihar, India.

Methods

Three survey-based data sets were analysed to compare the health-related knowledge, attitudes and behaviours amongst childbearing women exposed to the Mobile Kunji and Dr. Anita mHealth tools during their visits with frontline workers compared with those who were unexposed.

Results

An evaluation by Mathematica (2014) revealed that exposure to Mobile Kunji and Dr. Anita recordings were associated with significantly higher odds of consuming iron-folic acid tablets (odds ratio (OR) = 2.3, 95% confidence interval (CI) = 1.8-3.1) as well as taking a set of three measures for delivery preparedness (OR = 2.8, 95% CI = 1.9-4.2) and appropriate infant complementary feeding (OR = 1.9, 95% CI = 1.0-3.5). CARE India's Community-based Household Surveys (2012-2017) demonstrated significant improvements in early breastfeeding (OR = 1.64, 95% CI = 1.5-1.78) and exclusive breastfeeding (OR = 1.46, 95% CI = 1.33-1.62) in addition to birth preparedness practices. BBC Media Action's Usage & Engagement Survey (2014) demonstrated a positive association between exposure to Mobile Kunji and Dr. Anita and exclusive breastfeeding (58% exposed vs 43% unexposed, P < 0.01) as well as maternal respondents' trust in their frontline worker.

Conclusions

Significant improvements in RMNCHN-related knowledge and behaviours were observed for Bihari women who were exposed to Mobile Kunji and Dr. Anita. This analysis is unique in its rigorous evaluation across multiple data sets of mHealth interventions implemented at scale. These results can help inform global understanding of how best to use mHealth tools, for whom, and in what contexts.

Study registration

ClinicalTrials.gov number NCT02726230.

SUBMITTER: Ward VC

PROVIDER: S-EPMC7758913 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe Government of Bihar (GoB) in India, the Bill and Melinda Gates Foundation and several non-governmental organisations launched the Ananya program aimed to support the GoB to improve reproductive, maternal, newborn and child health and nutrition (RMNCHN) statewide. Here we summarise changes in indicators attained during the initial two-year pilot phase (2012-2013) of implementation in eight focus districts of approximately 28 million population, aimed to inform subsequent scale-up.MethodsThe quasi-experimental impact evaluation included statewide household surveys at two time points during the pilot phase: January-April 2012 ("baseline") including an initial cohort of beneficiaries and January-April 2014 ("midline") with a new cohort. The two arms were: 1) eight intervention districts, and 2) a comparison arm comprised of the remaining 30 districts in Bihar where Ananya interventions were not implemented. We analysed changes in indicators across the RMNCHN continuum of care from baseline to midline in intervention and comparison districts using a difference-in-difference analysis.ResultsIndicators in the two arms were similar at baseline. Overall, 40% of indicators (20 of 51) changed significantly from baseline to midline in the comparison districts unrelated to Ananya; two-thirds (n?=?13) of secular indicator changes were in a direction expected to promote health. Statistically significant impact attributable to the Ananya program was found for 10% (five of 51) of RMNCHN indicators. Positive impacts were most prominent for mother's behaviours in contraceptive utilisation.ConclusionsThe Ananya program had limited impact in improving health-related outcomes during the first two-year period covered by this evaluation. The program's theories of change and action were not powered to observe statistically significant differences in RMNCHN indicators within two years, but rather aimed to help inform program improvements and scale-up. Evaluation of large-scale programs such as Ananya using theory-informed, equity-sensitive (including gender), mixed-methods approaches can help elucidate causality and better explain pathways through which supply- and demand-side interventions contribute to changes in behaviour among the actors involved in the production of population-level health outcomes. Evidence from Bihar indicates that deep structural constraints in health system organisation and delivery of interventions pose substantial limitations on behaviour change among health care providers and beneficiaries.Study registrationClinicalTrials.gov number NCT02726230.

Project description:BackgroundThe Ananya program in Bihar implemented household and community-level interventions to improve reproductive, maternal, newborn and child health and nutrition (RMNCHN) in two phases: a first phase of intensive ancillary support to governmental implementation and innovation testing by non-government organisation (NGO) partners in eight focus districts (2012-2014), followed by a second phase of state-wide government-led implementation with techno-managerial assistance from NGOs (2014 onwards). This paper examines trends in RMNCHN indicators in the program's implementation districts from 2012-2017.MethodsEight consecutive rounds of cross-sectional Community-based Household Surveys conducted by CARE India in 2012-2017 provided comparable data on a large number of indicators of frontline worker (FLW) performance, mothers' behaviours, and facility-based care and outreach service delivery across the continuum of maternal and child care. Logistic regression, considering the complex survey design and sample weights generated by that design, was used to estimate trends using survey rounds 2-5 for the first phase in the eight focus districts and rounds 6-9 for the second phase in all 38 districts statewide, as well as the overall change from round 2-9 in focus districts. To aid in contextualising the results, indicators were also compared amongst the formerly focus and the non-focus districts at the beginning of the second phase.ResultsIn the first phase, the levels of 34 out of 52 indicators increased significantly in the focus districts, including almost all indicators of FLW performance in antenatal and postnatal care, along with mother's birth preparedness, some breastfeeding practices, and immunisations. Between the two phases, 33 of 52 indicators declined significantly. In the second phase, the formerly focus districts experienced a rise in the levels of 14 of 50 indicators and a decline in the levels of 14 other indicators. There was a rise in the levels of 22 out of 50 indicators in the non-focus districts in the second phase, with a decline in the levels of 13 other indicators.ConclusionsImprovements in indicators were conditional on implementation support to program activities at a level of intensity that was higher than what could be achieved at scale so far. Successes during the pilot phase of intensive support suggests that RMNCHN can be improved statewide in Bihar with sufficient investments in systems performance improvements.Study registrationClinicalTrials.gov number NCT02726230.

Project description:BackgroundGeographical variations in the levels and trajectory of health indicators at local level can inform the adaptation of interventions and development of targeted approaches for efficient scale-up of intervention impact. We examined the hypothesis that time trends of a set of reproductive, maternal, newborn, and child health and nutrition (RMNCHN) indicators varied at block-level during the statewide scale-up phase of the Ananya program in Bihar, India.MethodsWe used data on 22 selected indicators from four rounds of the Community-based Household Survey carried out between 2014 and 2017. Indicator levels at each round were estimated for each block. We used hierarchical Bayesian spatiotemporal modelling to smooth the raw estimates for each block with the estimates from its neighbouring blocks, and to examine space-time interaction models for evidence of variations in trends of indicators across blocks. We expressed the uncertainty around the smoothed levels and the trends with 95% credible intervals.ResultsThere was evidence of variations in trends at block level in all but three indicators: facility delivery, public facility delivery, and age-appropriate initiation of complementary feeding. Fifteen indicators showed trends in opposite directions (increases in some blocks and declines in others). All blocks had at least 97.5% probability of a rise in immediate breastfeeding, early pregnancy registration, and having at least four antenatal care visits. All blocks had at least 97.5% probability of a decline in seeking care for pregnancy complications.ConclusionsThe findings underscore the value of monitoring and evaluation at local level for targeted implementation of RMNCHN interventions. There is a need for identifying systematic factors leading to universal trends, or variable contextual or implementation factors leading to variable trends, in order to optimise primary health care program impact.Study registrationClinicalTrials.gov number NCT02726230.

Project description:BackgroundSelf-help group (SHG) interventions have been widely studied in low and middle income countries. However, there is little data on specific impacts of health layering, or adding health education modules upon existing SHGs which were formed primarily for economic empowerment. We examined three SHG interventions from 2012-2017 in Bihar, India to test the hypothesis that health-layering of SHGs would lead to improved health-related behaviours of women in SHGs.MethodsA model for health layering of SHGs - Parivartan - was developed by the non-governmental organisation (NGO), Project Concern International, in 64 blocks of eight districts. Layering included health modules, community events and review mechanisms. The health layering model was adapted for use with government-led SHGs, called JEEViKA+HL, in 37 other blocks of Bihar. Scale-up of government-led SHGs without health layering (JEEViKA) occurred contemporaneously in 433 other blocks, providing a natural comparison group. Using Community-based Household Surveys (CHS, rounds 6-9) by CARE India, 62 reproductive, maternal, newborn and child health and nutrition (RMNCHN) and sanitation indicators were examined for SHGs with health layering (Pavivartan SHGs and JEEViKA+HL SHGs) compared to those without. We calculated mean, standard deviation and odds ratios of indicators using surveymeans and survey logistic regression.ResultsIn 2014, 64% of indicators were significantly higher in Parivartan members compared to non-members residing in the same blocks. During scale up, from 2015-17, half (50%) of indicators had significantly higher odds in health layered SHG members (Parivartan or JEEViKA+HL) in 101 blocks compared to SHG members without health layering (JEEViKA) in 433 blocks.ConclusionsHealth layering of SHGs was demonstrated by an NGO-led model (Parivartan), adapted and scaled up by a government model (JEEViKA+HL), and associated with significant improvements in health compared to non-health-layered SHGs (JEEViKA). These results strengthen the evidence base for further layering of health onto the SHG platform for scale-level health change.Study registrationClinicalTrials.gov number NCT02726230.

Project description:BackgroundDespite increasing focus on health inequities in low- and middle income countries, significant disparities persist. We analysed impacts of a statewide maternal and child health program among the most compared to the least marginalised women in Bihar, India.MethodsUtilising survey-weighted logistic regression, we estimated programmatic impact using difference-in-difference estimators from Mathematica data collected at the beginning (2012, n = 10 174) and after two years of program implementation (2014, n = 9611). We also examined changes in disparities over time using eight rounds of Community-based Household Surveys (CHS) (2012-2017, n = 48 349) collected by CARE India.ResultsAt baseline for the Mathematica data, least marginalised women generally performed desired health-related behaviours more frequently than the most marginalised. After two years, most disparities persisted. Disparities increased for skilled birth attendant identification [+16.2% (most marginalised) vs +32.6% (least marginalized), P < 0.01) and skin-to-skin care (+14.8% vs +20.4%, P < 0.05), and decreased for immediate breastfeeding (+10.4 vs -4.9, P < 0.01). For the CHS data, odds ratios compared the most to the least marginalised women as referent. Results demonstrated that disparities were most significant for indicators reliant on access to care such as delivery in a facility (OR range: 0.15 to 0.48) or by a qualified doctor (OR range: 0.08 to 0.25), and seeking care for complications (OR range: 0.26 to 0.64).ConclusionsDisparities observed at baseline generally persisted throughout program implementation. The most significant disparities were observed amongst behaviours dependent upon access to care. Changes in disparities largely were due to improvements for the least marginalised women without improvements for the most marginalised. Equity-based assessments of programmatic impacts, including those of universal health approaches, must be undertaken to monitor disparities and to ensure equitable and sustainable benefits for all.Study registrationClinicalTrials.gov number NCT02726230.

Project description:BackgroundmHealth technology holds promise for improving the effectiveness of frontline health workers (FLWs), who provide most health-related primary care services, especially reproductive, maternal, newborn, child health and nutrition services (RMNCHN), in low-resource - especially hard-to-reach - settings. Data are lacking, however, from rigorous evaluations of mHealth interventions on delivery of health services or on health-related behaviors and outcomes.MethodsThe Information Communication Technology-Continuum of Care Service (ICT-CCS) tool was designed for use by community-based FLWs to increase the coverage, quality and coordination of services they provide in Bihar, India. It consisted of numerous mobile phone-based job aids aimed to improve key RMNCHN-related behaviors and outcomes. ICT-CCS was implemented in Saharsa district, with cluster randomization at the health sub-center level. In total, evaluation surveys were conducted with approximately 1100 FLWs and 3000 beneficiaries who had delivered an infant in the previous year in the catchment areas of intervention and control health sub-centers, about half before implementation (mid-2012) and half two years afterward (mid-2014). Analyses included bivariate and difference-in-difference analyses across study groups.ResultsThe ICT-CCS intervention was associated with more frequent coordination of AWWs with ASHAs on home visits and greater job confidence among ASHAs. The intervention resulted in an 11 percentage point increase in FLW antenatal home visits during the third trimester (P = 0.04). In the post-implementation period, postnatal home visits during the first week were increased in the intervention (72%) vs the control (60%) group (P < 0.01). The intervention also resulted in 13, 12, and 21 percentage point increases in skin-to-skin care (P < 0.01), breastfeeding immediately after delivery (P < 0.01), and age-appropriate complementary feeding (P < 0.01). FLW supervision and other RMNCHN behaviors were not significantly impacted.ConclusionsImportant improvements in FLW home visits and RMNCHN behaviors were achieved. The ICT-CCS tool shows promise for facilitating FLW effectiveness in improving RMNCHN behaviors.

Project description:In 2010, the Bill and Melinda Gates Foundation (BMGF) partnered with the Government of Bihar (GoB), India to launch the Ananya program to improve reproductive, maternal, newborn and child health and nutrition (RMNCHN) outcomes. The program sought to address supply- and demand-side barriers to the adoption, coverage, quality, equity and health impact of select RMNCHN interventions. Approaches included strengthening frontline worker service delivery; social and behavior change communications; layering of health, nutrition and sanitation into women's self-help groups (SHGs); and quality improvement in maternal and newborn care at primary health care facilities. Ananya program interventions were piloted in approximately 28 million population in eight innovation districts from 2011-2013, and then beginning in 2014, were scaled up by the GoB across the rest of the state's population of 104 million. A Bihar Technical Support Program provided techno-managerial support to governmental Health as well as Integrated Child Development Services, and the JEEViKA Technical Support Program supported health layering and scale-up of the GoB's SHG program. The level of support at the block level during statewide scale-up in 2014 onwards was approximately one-fourth that provided in the pilot phase of Ananya in 2011-2013. This paper - the first manuscript in an 11-manuscript and 2-viewpoint collection on Learning from Ananya: Lessons for primary health care performance improvement - seeks to provide a broad description of Ananya and subsequent statewide adaptation and scale-up, and capture the background and context, key objectives, interventions, delivery approaches and evaluation methods of this expansive program. Subsequent papers in this collection focus on specific intervention delivery platforms. For the analyses in this series, Stanford University held key informant interviews and worked with the technical support and evaluation grantees of the Ananya program, as well as leadership from the India Country Office of the BMGF, to analyse and synthesise data from multiple sources. Capturing lessons from the Ananya pilot program and statewide scale-up will assist program managers and policymakers to more effectively design and implement RMNCHN programs at scale through technical assistance to governments.