SMARThealth pregnancy: the development & evaluation of a complex intervention using mobile clinical decision support to screen, refer and manage pregnant women at high risk of future cardiometabolic disorders in rural India
Keywords: cardiometabolic disease
pre-eclampsia
global maternal health
integrated care
task-sharing
complex intervention
hypertensive disorders of pregnancy
anaemia in pregnancy
mHealth
gestational diabetes mellitus
high-risk pregnancy

India has witnessed a rapid rise in cardiometabolic diseases (CMDs), and women with high-risk pregnancy conditions including hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM) are at increased risk. In rural India, Community Health Workers (CHWs) deliver antenatal care, and are ideally placed to screen at-risk women in their villages. The aims of my thesis were to design, develop and evaluate a contextually-relevant, theory-informed complex intervention to enable CHWs to screen, refer and counsel pregnant women at high risk of future CMDs during their transition between antenatal, postnatal and ongoing healthcare services.
Guided by the MRC conceptual framework for complex interventions, my study was conducted in three phases. In phase 1, I reviewed the evidence for the associations between high-risk pregnancy conditions and CMDs; community-level interventions for high-risk pregnant women (including mobile technologies), and the integration of non-communicable disease programmes into antenatal care platforms. Qualitative methods were then used to explore the context of maternal healthcare in rural districts of two diverse States in India. In-depth interviews and focus group discussions with key stakeholders (n=71), were thematically analysed. The study revealed three local priority conditions (anaemia, HDP and GDM), the need for improving local understanding of long-term sequelae of high-risk pregnancies, and highlighted important socio-cultural practices impacting intervention design. In phase 2, using behaviour change theory (COM-B/Behaviour Change wheel and Theoretical Domains Framework), the target behaviours, intervention functions and policy categories to be addressed through a complex intervention were identified, using data from the contextual study. A total of 15 Behaviour Change Techniques (the ‘active ingredients’) were embedded into intervention design, and the proposed mechanisms of action of SMARThealth Pregnancy were articulated in a logic model. The final intervention included: a) a village awareness programme; b) targeted training for CHWs to screen, refer and counsel women on the three priority high-risk pregnancy conditions and to conduct point-of-care testing for anaemia and blood pressure, and community-based GDM screening, and; c) mobile clinical decision support (App) to enable CHWs to deliver guideline-based care for women at home, at three timepoints: last trimester of pregnancy, week 1 and week 6 postpartum. In phase 3, feasibility and acceptability of the intervention was evaluated in a pilot cluster randomised controlled trial (n=4 primary health centre clusters), and a qualitative process evaluation using Normalisation Process Theory. A total of 200 pregnant women were randomised equally to the SMARThealth Pregnancy intervention or control. Recruitment was timely (4.5 months), with minimal loss to follow-up (2%). The intervention became embedded and integrated into the daily work of CHWs, who experienced increased social and professional recognition, with women perceiving improved quality of care. SMARThealth Pregnancy was feasible and acceptable as a model of task-sharing for CHWs to deliver integrated home-based care for women at high risk of future CMDs, in the context of rural India.