SMARThealth Pregnancy: Development of a complex intervention using clinical decision support to detect & refer high-risk pregnant women in rural India

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Context of Research: Heart disease is the leading cause of death in women worldwide, with the greatest burden affecting low and middle income countries (LMICs). Risk factors for heart disease include high blood pressure (hypertension) and diabetes. These risk factors can be modified through early detection and management using evidence-based lifestyle interventions and medications. Pregnancy may unmask an underlying susceptibility to the future development of non-communicable diseases (NCDs) such as hypertension and diabetes, and can identify women at increased risk of heart disease. Through early detection of high-risk women in pregnancy and in the first 5 years following pregnancy, NCDs may be prevented or more effectively managed, and serious complications associated with high blood pressure and diabetes in pregnancy (affecting mother and baby) may be reduced. This is of great importance in order to reduce maternal deaths in line with the UN's Sustainable Development Goals. Evidence-based interventions include the International Diabetes Federation's Model of Care for lifestyle modification during and after pregnancy, which reduces the risks associated with diabetes in pregnancy and beyond to baseline values. Such interventions may be delivered in a community context.In rural India, there is a shortage of doctors. Community Health Workers (CHWs) represent the main link to pregnant women in the community and provide basic antenatal and postnatal care to women. They are in the ideal position to screen and refer women with high-risk pregnancies, however they need adequate training, support and supervision. This study utilises mobile technology to provide clinical decision support to empower CHWs to screen, detect and refer high-risk women to primary health centres, where they can be managed and receive follow-up care. Intervention: The Systematic Medical Appraisal, Referral and Treatment (SMARThealth) platform is validated clinical decision support system, already in use in rural India. SMARThealth has been adapted to screen for mental health disorders, diabetes and TB in rural India, and the programme has been extended to China and Indonesia. This platform will be adapted to integrate evidence-based national and international guidelines on screening for high-risk pregnancies during routine antenatal and postnatal care to form SMARThealth Pregnancy. Overall Aim:To improve screening, detection, referral and management of women with high-risk pregnancies in rural Andhra Pradesh, India, so as to reduce: a) maternal and perinatal mortality and morbidity, and in the longer term, b) the burden of pregnancy-associated, non-communicable diseases for these women.Specific Objectives:1) Conduct formative research to identify the barriers and enablers within the health system and identify the evidence-practice gap.2) Develop and validate a clinical decision support system (SMARThealth Pregnancy) to improve detection and referral of high-risk pregnancies in rural India. 3) Conduct training, content and usability testing of SMARThealth Pregnancy with end-users.4) Evaluate the feasibility and acceptability of SMARThealth Pregnancy for use by Community Health Workers and Primary Health Care doctors to improve detection, referral and management of high-risk pregnancies. Potential Applications & Benefits:The development and feasibility study of SMARThealth Pregnancy will inform the evidence base on taking a life-course approach to women's health to prevent NCDs. It will also inform the debate on task-shifting of screening and counselling for lifestyle interventions to lower cadres of health workers in similar resource-poor settings. Additionally, the SMARThealth system enables bidirectional communication between primary care doctor and CHWs, thus helping to strengthen existing health systems and referral pathways, improve feedback and follow-up practices of high-risk women within the community.