Integrated Management of Diabetes and Tuberculosis in Rural India - Results From a Pilot Study.

Introduction: The World Health Organization and International Union against Tuberculosis (TB) recommends screening patients with TB for Diabetes Mellitus (DM) at the initiation of treatment. There are few pilot studies which screen TB patients for DM, but none of them have documented the feasibility of managing TB patients with DM in the Indian healthcare setting. Operational research is needed to determine the best way to manage individuals with both conditions. This pilot study aimed to develop, and field test an integrated, multidisciplinary program addressing the management of individuals with TB and DM and other associated chronic conditions in the Indian primary healthcare setting. Methods: This pilot study used a randomized controlled trial design with mixed-methods evaluation and was conducted in Guntur district of Andhra Pradesh, a southern state of India. All the 120 patients newly diagnosed with TB from 10 participating villages were screened for DM and associated cardiovascular risk factors. Non-physician health workers were trained to follow-up patients for a period of 8 months to encourage treatment adherence, monitor treatment response including blood glucose levels and provide lifestyle advice. Results: The intervention was well-accepted by the providers and patients. However, there were no statistically significant variations observed for mean blood glucose levels (mean [SD]: 5.3 [-23.3 to 33.8]) of patients for both intervention and control group participants in this feasibility study. Awareness about diabetes and tuberculosis comorbidity and cardiovascular risk increased among the non-physician health workers in the intervention arm of the study. Discussion: The co-management of TB-DM is acceptable to both the health providers and patients. With appropriate training, availability of infrastructure and planned intervention implementation, it is feasible to co-manage TB-DM within the existing primary health care system in India.

Why do strategies to strengthen primary health care succeed in some places and fail in others? Exploring local variation in the effectiveness of a community health worker managed digital health intervention in rural India.

INTRODUCTION: Digital health interventions (DHIs) have huge potential as support modalities to identify and manage cardiovascular disease (CVD) risk in resource-constrained settings, but studies assessing them show modest effects. This study aims to identify variation in outcomes and implementation of SMARTHealth India, a cluster randomised trial of an ASHA-managed digitally enabled primary healthcare (PHC) service strengthening strategy for CVD risk management, and to explain how and in what contexts the intervention was effective. METHODS: We analysed trial outcome and implementation data for 18 PHC centres and collected qualitative data via focus groups with ASHAs (n=14) and interviews with ASHAs, PHC facility doctors and fieldteam mangers (n=12) Drawing on principles of realist evaluation and an explanatory mixed-methods design we developed mechanism-based explanations for observed outcomes. RESULTS: There was substantial between-cluster variation in the primary outcome (overall: I2=62.4%, p<=0.001). The observed heterogeneity in trial outcomes was not attributable to any single factor. Key mechanisms for intervention effectiveness were community trust and acceptability of doctors' and ASHAs' new roles, and risk awareness. Enabling local contexts were seen to evolve over time and in response to the intervention. These included obtaining legitimacy for ASHAs' new roles from trusted providers of curative care; ASHAs' connections to community and to qualified providers; their responsiveness to community needs; and the accessibility, quality and appropriateness of care provided by higher level medical providers, including those outside of the implementing (public) subsystem. CONCLUSION: Local contextual factors were significant influences on the effectiveness of this DHI-enabled PHC service strategy intervention. Local adaptions need to be planned for, monitored and responded to over time. By identifying plausible explanations for variation in outcomes between clusters, we identify potential strategies to strengthen such interventions.

SMARThealth India: A stepped-wedge, cluster randomised controlled trial of a community health worker managed mobile health intervention for people assessed at high cardiovascular disease risk in rural India.

BACKGROUND: Cardiovascular diseases (CVD) are rising in India resulting in major health system challenges. METHODS: Eighteen primary health centre (PHC) clusters in rural Andhra Pradesh were randomised over three, 6-month steps to an intervention comprising: (1) household CVD risk assessments by village-based community health workers (CHWs) using a mobile tablet device; (2) electronic referral and clinical decision support for PHC doctors; and (3) a tracking system for follow-up care. Independent data collectors screened people aged ≥ 40 years in 54 villages serviced by the PHCs to create a high CVD risk cohort (based on WHO risk charts and blood pressure thresholds). Randomly selected, independent samples, comprising 15% of this cohort, were reviewed at each 6-month step. The primary outcome was the proportion meeting systolic blood pressure (SBP) targets (<140mmHg). FINDINGS: Eight-four percent of the eligible population (n = 62,254) were assessed at baseline (18.4% at high CVD risk). Of those at high risk, 75.3% were followed up over two years. CHWs screened 85.9% of the baseline cohort and doctors followed up 70.0% of all high risk referrals. There was no difference in the proportion of people achieving SBP targets (41.2% vs 39.2%; adjusted odds ratio (OR) 1.01 95% CI 0.76-1.35) or receiving BP-lowering medications in the intervention vs control periods respectively. There was a high discordance in risk scores generated by independent data collectors and CHWs, resulting in only 37.2% of the evaluation cohort exposed to the intervention. This discordance was mainly driven by fluctuating BP values (both normal variability and marked seasonal variations). In the pre-specified high risk concordant subgroup, there was greater use of BP-lowering medications in the intervention period (54.3% vs 47.9%, OR 1.22, 95% CI 1.03-1.44) but no impact on BP control. CONCLUSIONS: The strategy was well implemented with increased treatment rates among high risk individuals assessed by CHWs, however effects on BP were not demonstrated. Use of guideline-recommended BP thresholds for identifying high risk individuals substantially affected the reproducibility of risk assessment, and thus the ability to reliably evaluate the effectiveness of the intervention. In addition, unanticipated seasonal variation in BP in the context of a stepped-wedge trial highlights the inherent risks of this study design. TRIAL REGISTRATION: Clinical Trials Registry of India CTRI/2013/06/ 003753.