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Background The main intervention under ReMiND program consisted of a mobile health application which was used by community health volunteers, called ASHAs, for counselling pregnant women and nursing mothers. This program was implemented in two rural blocks in Uttar Pradesh state of India with an overall aim to increase quality of health care, thereby increasing utilization of maternal & child health services. The aim of the study was to assess annual & unit cost of ReMiND program and its scale up in UP state. Method and materials Economic costing was done from the health system and patient’s perspectives. All resources used during designing & planning phase i.e., development of application; and implementation of the intervention, were quantified and valued. Capital costs were annualised, after assessing their average number of years for which a product could be used and accounting for its depreciation. Shared or joint costs were apportioned for the time value a resource was utilized under intervention. Annual cost of implementing ReMiND in two blocks of UP along and unit cost per pregnant woman were estimated. Scale-up cost for implementing the intervention in entire state was calculated under two scenarios – first, if no extra human resource were employed; and second, if the state government adopted the same pattern of human resource as employed under this program. Results The annual cost for rolling out ReMiND in two blocks of district Kaushambi was INR 12.1 million (US $ 191,894). The annualised start-up cost constituted 9% of overall cost while rest of cost was attributed to implementation of the intervention. The health system program costs in ReMiND were estimated to be INR 31.4 (US $ 0.49) per capita per year and INR 1294 (US $ 20.5) per registered women. The per capita incremental cost of scale up of intervention in UP state was estimated to be INR 4.39 (US $ 0.07) when no additional supervisory staffs were added. Conclusion The cost of scale up of ReMiND in Uttar Pradesh is 6% of annual budget for ‘reproductive and child health’ line item under state budget, and hence appears to be financially sustainable.

The Government of India launched a nationwide programme to save and educate the girl child, Beti Bachao Beti Padhao (B3P), by stringent prohibition of sex-selective abortion, enforcement of Preconception and Prenatal Diagnostic Technique (PC-PNDT) and Medical Termination of Pregnancy (MTP) Acts, and social mobilization. We undertook this study to assess the effectiveness of intervention in Haryana state to improve sex ratio at birth (SRB). The monthly data on SRB (represented as girls per 1000 boys) were collected from civil registration system for the entire state of Haryana to evaluate the impact of B3P programme. The segmented time-series regression analysis was used to estimate the change in SRB after B3P programme. In this process, the seasonal auto regressive integrated moving average model was used to control the seasonality, autocorrelation and secular trend imbibed in the data before calculating the estimate of change in slope using regression equation. Overall, the sex ratio at birth in Haryana increased from 827 girls per 1000 boys in January 2005 to 900 girls per 1000 boys in September 2016. The estimates from segmented time-series regression analysis show that there was an insignificant change in SRB of –0.012 units before the intervention. Post slope was estimated to be 1.684, which suggested an increase in SRB of 1.696 [(confidence interval: 0.23, 3.15), P = 0.025] in terms of the difference between pre- and post-slope. This indicates a statistically significant increase of SRB by 1.696 per month attributable to B3P programme. B3P programme has resulted in an improvement of SRB in Haryana. Le gouvernement de l’Inde a lancé Beti Bachao Beti Padhao (B3P), un programme national de sauvegarde et d'éducation de la fillette, visant à interdire de manière stricte l’avortement sélectif en fonction du sexe, en appliquant une technique de diagnostic préconceptionnel et prénatal (PCPNDT) ainsi que les actes d'interruption médicale de grossesse (MTP) et de mobilisation sociale. Nous avons entrepris cette étude pour évaluer l’efficacité d'une intervention dans I'État de Haryana visant à améliorer le rapport sexe à la naissance (SRB). Les données mensuelles du SRB (représentées en nombre de filles pour 1 000 garçons) ont été collectées à partir du système d’état-civil de l’ensemble de l’État d’Haryana afin d’évaluer l’impact du programme B3P. L'analyse de régression par séries chronologiques segmentée a été utilisée pour estimer le changement intervenu dans le SRB après l’introduction du programme B3P. Dans ce processus, le modèle autorégressif à moyennes mobiles intégrées a été utilisé pour contrôler la saisonnalité, l’autocorrélation et la tendance séculaire imbriquée dans les données avant de calculer l’estimation du changement de pente à l’aide de l’équation de régression. Dans l’ensemble, le rapport sexe des naissances à Haryana est passé de 827 filles pour 1000 garçons en janvier 2005 à 900 filles pour 1000 garçons en septembre 2016. Les estimations de l’analyse de régression par séries chronologiques segmentées montrent qu'il y a eu un changement peu important du SRB de -0,012 unité avant l’intervention. L’analyse post-pente a été estimée à 1,684, ce qui suggère une augmentation du SRB de 1,696 [(intervalle de confiance: 0,23, 3,15), P=0,025] en termes de différence entre la pré-pente et la post-pente. Cela indique une augmentation statistiquement significative du SRB de 1,696 par mois imputable au programme B3P. Le programme B3P a permis d’améliorer le SRB dans l’Etat de Haryana. 印度政府通过严格禁止性别选择堕胎, 执行孕产前诊断 技术 （PC-PNDT） 和医学终止妊娠法以及动员社会参与, 在 全国推行了拯救和教育女童的B3P 项目。本研究评估该项目 在哈里亚纳邦改善出生人口性别比 （SRB） 的有效性。从全 邦人口登记系统收集每月的 SRB 数据（每出生 1000 名男婴 相对的出生女婴数）, 评估 B3P 项目的影响。采用分段时间 序列回归模型分析实施 B3P 项目后SRB 的变化。在应用回 归方程计算斜率变化之前, 采用季节自回归滑动平均模型控制 数据的季节性、自相关作用和长期趋势。总体来看, 哈里亚纳 邦的出生人口性别比由 2005 年1月每 1000 名男婴827 名女 婴增加至2016 年9 月的每 1000 名男婴 900 名女婴。分段时 间序列回归分析显示, 干预前SRB有–0.012 单位的变化, 但没 有统计学意义。干预后斜率估计为 1.684, 即干预后与干预前 比较 SRB 增加 1.696[置信区间 ：0.23, 3.15, P=0.025]。这 一结果表明, 因为 B3P项目的效果, 每个月SRB显著增加 1.696。 B3P项目改善了哈里亚纳邦的出生人口性别比。 El Gobierno de India lanzóun programa a nivel nacional para salvar y educar a las niñas, Beti Bachao Beti Padao (B3P), con una estricta prohibición de los abortos selectivos por sexo, la ejecución de las Leyes de Técnica de Diagnostico de Preconcepción y Prenatal (TCPC-PN) y de Terminación Médica del Embarazo (TME), y la movilización social. Llevamos a cabo este estudio para examinar la efectividad de la intervención en el estado Haryana para mejorar la proporción del sexo en el nacimiento (PSN). Los datos mensuales en la PSN (representado como niñas por cada 1000 niños) se recolecto del sistema de registros civiles en todo el estado de Haryana para evaluar el impacto del programa B3P. Un análisis de regresión de series de tiempo segmentadas fue utilizado para estimar el cambio de PSN después del programa B3P. En este proceso, se usóel modelo de promedio en movimiento de estacionalidad auto regresivo integrado para calcular la estacionalidad, auto correlación, y tendencia secular existente dentro de los datos antes de calcular la estimación del cambio de la pendiente usando la ecuación de regresión. En general, la proporción de sexo en el nacimiento en Haryana aumentóde 827 niñas por cada 1000 niños en enero de 2005 a 900 niñas por cada 1000 niños en septiembre de 2016. Las estimaciones del análisis de la regresión de series de tiempo segmentadas muestran que hubo un cambio insignificante en la PSN de - 0.012 unidades antes de la intervención. La pendiente posterior estimada fue de 1.684, lo cual sugiere un incremento en la PSN de 1.969 [(intervalo de confianza: 0.23-3.15), p=0.025)] en términos de la diferencia entre la pendiente pre- y post-. Esto muestra un incremento estadísticamente significativo de la PSN de 1.696 por mes atribuible al programa B3P. El programa B3P ha resultado en una mejora de la PSN en Haryana.

Background A variety of mobile-based health technologies (mHealth) have been developed for use by community health workers to augment their performance. One such mHealth intervention—ReMiND program, was implemented in a poor performing district of India. Despite some research on the extent of its effectiveness, there is significant dearth of evidence on cost-effectiveness of such mHealth interventions. In this paper we evaluated the incremental cost per disability adjusted life year (DALY) averted as a result of ReMiND intervention as compared to routine maternal and child health programs without ReMiND. Methods A decision tree was parameterized on MS-Excel spreadsheet to estimate the change in DALYs and cost as a result of implementing ReMiND intervention compared with routine care, from both health system and societal perspective. A time horizon of 10 years starting from base year of 2011 was considered appropriate to cover all costs and effects comprehensively. All costs, including those during start-up and implementation phase, besides other costs on the health system or households were estimated. Consequences were measured as part of an impact assessment study which used a quasi-experimental design. Proximal outputs in terms of changes in service coverage were modelled to estimate maternal and infant illnesses and deaths averted, and DALYs averted in Uttar Pradesh state of India. Probabilistic sensitivity analysis was undertaken to account for parameter uncertainties. Results Cumulatively, from year 2011 to 2020, implementation of ReMiND intervention in UP would result in a reduction of 312 maternal and 149,468 neonatal deaths. This implies that ReMiND program led to a reduction of 0.2% maternal and 5.3% neonatal deaths. Overall, ReMiND is a cost saving intervention from societal perspective. From health system perspective, ReMiND incurs an incremental cost of INR 12,993 (USD 205) per DALY averted and INR 371,577 (USD 5865) per death averted. Conclusions Overall, findings of our study suggest strongly that the mHealth intervention as part of ReMiND program is cost saving from a societal perspective and should be considered for replication elsewhere in other states.

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. 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. 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.

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.