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Our research aims to address a critical gap in the provision of quality antenatal care (ANC) in India and Nepal, by developing and evaluating an intervention comprising of a tablet-based electronic decision support system (EDSS). This intervention -"mIRA" - is an mHealth integrated model of hypertension, diabetes, and antenatal care in primary care settings. mIRA aims to (a) prompt frontline health workers (FHWs) to provide evidence-based routine ANC, and also enhance the detection and management of Pregnancy Induced Hypertension (PIH), Gestational Diabetes Mellitus (GDM), and anemia, whilst improving adherence to National ANC guidelines; (b) facilitate record-keeping and reporting and; (c) link providers across various levels of care to improve continuity of care.
A cluster randomized controlled (cRCT) to assess the effectiveness of the mIRA EDSS in improving ANC and enhancing the detection and management of Pregnancy Induced Hypertension (PIH), Gestational Diabetes Mellitus (GDM), and anemia will be conducted in Telangana, India. A mixed-methods process evaluation will be conducted in both India and Nepal. The process evaluation will contribute to our understanding of the mechanisms contributing to changes (improvement) in the quality of ANC by using the EDSS intervention.
Full description
The cRCT aims to evaluate the effectiveness of a tablet-based EDSS in improving the quality of ANC and enhancing the detection and management of PIH, GDM, and anemia at primary care level health facilities in five districts of Telangana State: Medak, Rangareddy, Siddipet, Vikarabad, and Yadadri Bhuvangiri. The EDSS will use evidence-based algorithms to suggest recommendations to the FHWs for providing ANC, based on the pregnant woman's history, examination, and investigations, as well as incorporate reminders to ensure all relevant components of ANC are recorded. The aim is to ensure that ANC components received during multiple visits from multiple healthcare providers are captured and contribute to coordinated care. FHWs, primarily Auxiliary Nurse Midwives (ANMs), will use the EDSS during ANC consultations with pregnant women at Sub-Centres, while at the Primary Health Centres (PHCs), this will be used by Medical Officers (MOs) and staff nurses.
In these selected districts, which are predominantly rural, 66 clusters with each cluster comprising a PHC and its two reporting Sub-Centres, will be randomized with a 1:1 allocation ratio to the intervention arm (providing ANC using the mIRA EDSS intervention) and the control arm (providing usual care), using a computer-generated randomization schedule stratified by the district. Covariate constrained randomization will be used to balance the arms on the following baseline covariates: the presence of a laboratory and laboratory technician (yes/no); more than three staff providing ANC (yes/no); facility type (PHCs that are open 24/7 or those not open 24/7).
The cRCT will not be conducted In Nepal, however, the mIRA EDSS will be implemented at government Health Posts (HP), government Primary Health Care Centers (PHCCs), and Dhulikhel Hospital Outreach Centers (DHORCs), in four catchment districts (Kavrepalanchok, Sindhupalchowk, Sindhuli, and Dolakha) of Dhulikhel Hospital. A pre-post EDSS implementation outcome evaluation will be conducted. The process evaluation research activities conducted in India and Nepal will be the same (including a baseline facility survey, routine monitoring, and audit of record-keeping), except for a longitudinal case study and a time-motion study that will be conducted only in Nepal. Additionally, endline qualitative in-depth interviews with healthcare providers, facility managers, district and state health officials and policymakers, and with members of the Public Health Foundation of India team (intervention implementors) will be conducted only in India.
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• Women coming to the trial facility for a non-routine ANC visit (for example, to get a laboratory investigation, to collect a report or her medicine)
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1,320 participants in 2 patient groups
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Central trial contact
Sailesh Mohan, PhD
Data sourced from clinicaltrials.gov
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