Burden, patterns, and impact of multimorbidity in North India: findings from a rural population-based study.

AIM: To estimate the prevalence, socio-demographic determinants, common disease combinations, and health impact of multimorbidity among a young rural population. METHODS: We conducted a cross-sectional survey among participants aged ≥30 years in rural Punjab, North India, from Jan 2019 to April 2019. Multimorbidity was defined as the coexistence of ≥two conditions using a 14-condition tool validated in India. We also calculated a multimorbidity-weighted index (MWI), which provides a weight to each disease based on its impact on physical functioning. Logistic regression was conducted to evaluate the association with sociodemographic variables, mental health (PHQ-9), physical functioning (ADL scale), and self-rated health (SRH). RESULTS: We analyzed data from 3213 adults [Mean age 51.5 (±13), 54% women]. Prevalence of single chronic condition, multimorbidity, and MWI was 28.6, 18% and - 1.9 respectively. Age, higher wealth index and ever use alcohol were significantly associated with multimorbidity. Overall, 2.8% of respondents had limited physical functioning, 2.1% had depression, and 61.5% reported low SRH. Poorer health outcomes were more prevalent among the elderly, women, less educated, and those having lower wealth index and multimorbidity, were found to be significantly associated with poor health outcomes. CONCLUSIONS: The burden of multimorbidity was high in this young rural population, which portends significant adverse effects on their health and quality of life. The Indian health system should be reconfigured to address this emerging health priority holistically, by adopting a more integrated and sustainable model of care.

Improving care for hypertension and diabetes in india by addition of clinical decision support system and task shifting in the national NCD program: I-TREC model of care.

BACKGROUND: The growing burden of hypertension and diabetes is one of the major public health challenges being faced by the health system in India. Clinical Decision Support Systems (CDSS) that assist with tailoring evidence-based management approaches combined with task-shifting from more specialized to less specialized providers may together enhance the impact of a program. We sought to integrate a technology "CDSS" and a strategy "Task-shifting" within the Government of India's (GoI) Non-Communicable Diseases (NCD) System under the Comprehensive Primary Health Care (CPHC) initiative to enhance the program's impact to address the growing burden of hypertension and diabetes in India. METHODS: We developed a model of care "I-TREC" entirely calibrated for implementation within the current health system across all facility types (Primary Health Centre, Community Health Centre, and District Hospital) in a block in Shaheed Bhagat Singh (SBS) Nagar district of Punjab, India. We undertook an academic-community partnership to incorporate the combination of a CDSS with task-shifting into the GoI CPHC-NCD system, a platform that assists healthcare providers to record patient information for routine NCD care. Academic partners developed clinical algorithms, a revised clinic workflow, and provider training modules with iterative collaboration and consultation with government and technology partners to incorporate CDSS within the existing system. DISCUSSION: The CDSS-enabled GoI CPHC-NCD system provides evidence-based recommendations for hypertension and diabetes; threshold-based prompts to assure referral mechanism across health facilities; integrated patient database, and care coordination through workflow management and dashboard alerts. To enable efficient implementation, modifications were made in the patient workflow and the fulcrum of the use of technology shifted from physician to nurse. CONCLUSION: Designed to be applicable nationwide, the I-TREC model of care is being piloted in a block in the state of Punjab, India. Learnings from I-TREC will provide a roadmap to other public health experts to integrate and adapt their interventions at the national level. TRIAL REGISTRATION: CTRI/2020/01/022723.

A model for national assessment of barriers for implementing digital technology interventions to improve hypertension management in the public health care system in India.

BACKGROUND: There is substantial interest in leveraging digital health technology to support hypertension management in low- and middle-income countries such as India. The potential for healthcare infrastructure and broader context to support such initiatives in India has not been examined. We evaluated existing healthcare infrastructure to support digital health interventions and examined epidemiologic, socioeconomic, and geographical contextual correlates of healthcare infrastructure in 544 districts covering 29 states and union territories across India. METHODS: The study was a cross-sectional analysis of India's Fourth District Level Household and Facility Survey (DLHS-4; 2012-2014), the most up-to-date nationally representative district-level healthcare infrastructure data. Facilities were the unit of analysis, and analyses accounted for clustering within states. The main outcome was healthcare system infrastructural context to implement hypertension management programs. Domains included diagnostics (functional BP instrument), medications (anti-hypertensive medication in stock), essential clinical staff (e.g., staff nurse, medical officer, pharmacist), and IT specific infrastructure (regular power supply, internet connection, computer availability). Descriptive analysis was conducted for infrastructure indicators based on the Indian Public Health Standards, and logistic regression was conducted to estimate the association between epidemiologic and geographical context (exposures) and the composite measure of healthcare system. RESULTS: Data from 32,215 government facilities were analyzed. Among lowest-tier subcenters, 30% had some IT infrastructure, while at the highest-tier district hospitals, 92% possessed IT infrastructure. At mid-tier primary health centres and community health centres, IT infrastructure availability was 28 and 51%, respectively. For all but sub-centres, the availability of essential staff was lower than the availability of IT infrastructure. For all but district hospitals, higher levels of blood pressure, body mass index, and urban residents were correlated with more favorable infrastructure. By region, districts in Western India tended towards having the best prepared health facilities. CONCLUSIONS: IT infrastructure to support digital health interventions is more frequently lacking at lower and mid-tier healthcare facilities compared with apex facilities in India. Gaps were generally larger for staffing than physical infrastructure, suggesting that beyond IT infrastructure, shortages in essential staff impose significant constraints to the adoption of digital health interventions. These data provide early benchmarks for state- and district-level planning.

The Integrated Tracking, Referral, and Electronic Decision Support, and Care Coordination (I-TREC) program: scalable strategies for the management of hypertension and diabetes within the government healthcare system of India.

BACKGROUND: Hypertension and diabetes are among the most common and deadly chronic conditions globally. In India, most adults with these conditions remain undiagnosed, untreated, or poorly treated and uncontrolled. Innovative and scalable approaches to deliver proven-effective strategies for medical and lifestyle management of these conditions are needed. METHODS: The overall goal of this implementation science study is to evaluate the Integrated Tracking, Referral, Electronic decision support, and Care coordination (I-TREC) program. I-TREC leverages information technology (IT) to manage hypertension and diabetes in adults aged ≥30 years across the hierarchy of Indian public healthcare facilities. The I-TREC program combines multiple evidence-based interventions: an electronic case record form (eCRF) to consolidate and track patient information and referrals across the publicly-funded healthcare system; an electronic clinical decision support system (CDSS) to assist clinicians to provide tailored guideline-based care to patients; a revised workflow to ensure coordinated care within and across facilities; and enhanced training for physicians and nurses regarding non-communicable disease (NCD) medical content and lifestyle management. The program will be implemented and evaluated in a predominantly rural district of Punjab, India. The evaluation will employ a quasi-experimental design with mixed methods data collection. Evaluation indicators assess changes in the continuum of care for hypertension and diabetes and are grounded in the Reach, Effectiveness, Adoption Implementation, and Maintenance (RE-AIM) framework. Data will be triangulated from multiple sources, including community surveys, health facility assessments, stakeholder interviews, and patient-level data from the I-TREC program's electronic database. DISCUSSION: I-TREC consolidates previously proven strategies for improved management of hypertension and diabetes at single-levels of the healthcare system into a scalable model for coordinated care delivery across all levels of the healthcare system hierarchy. Findings have the potential to inform best practices to ultimately deliver quality public-sector hypertension and diabetes care across India. TRIAL REGISTRATION: The study is registered with Clinical Trials Registry of India (registration number CTRI/2020/01/022723 ). The study was registered prior to the launch of the intervention on 13 January 2020. The current version of protocol is version 2 dated 6 June 2018.

Seasonal variations in social contact patterns in a rural population in north India: Implications for pandemic control.

Social contact mixing patterns are critical to model the transmission of communicable diseases, and have been employed to model disease outbreaks including COVID-19. Nonetheless, there is a paucity of studies on contact mixing in low and middle-income countries such as India. Furthermore, mathematical models of disease outbreaks do not account for the temporal nature of social contacts. We conducted a longitudinal study of social contacts in rural north India across three seasons and analysed the temporal differences in contact patterns. A contact diary survey was performed across three seasons from October 2015-16, in which participants were queried on the number, duration, and characteristics of contacts that occurred on the previous day. A total of 8,421 responses from 3,052 respondents (49% females) recorded characteristics of 180,073 contacts. Respondents reported a significantly higher number and duration of contacts in the winter, followed by the summer and the monsoon season (Nemenyi post-hoc, p<0.001). Participants aged 0-9 years and 10-19 years of age reported the highest median number of contacts (16 (IQR 12-21), 17 (IQR 13-24) respectively) and were found to have the highest node centrality in the social network of the region (pageranks = 0.20, 0.17). A large proportion (>80%) of contacts that were reported in schools or on public transport involved physical contact. To the best of our knowledge, our study is the first from India to show that contact mixing patterns vary by the time of the year and provides useful implications for pandemic control. We compared the differences in the number, duration and location of contacts by age-group and gender, and studied the impact of the season, age-group, employment and day of the week on the number and duration of contacts using multivariate negative binomial regression. We created a social network to further understand the age and gender-specific contact patterns, and used the contact matrices in each season to parameterise a nine-compartment agent-based model for simulating a COVID-19 epidemic in each season. Our results can be used to parameterize more accurate mathematical models for prediction of epidemiological trends of infections in rural India.

Implementation outcomes and strategies for delivering evidence-based hypertension interventions in lower-middle-income countries: Evidence from a multi-country consortium for hypertension control.

Guidance on contextually tailored implementation strategies for the prevention, treatment, and control of hypertension is limited in lower-middle income countries (Lower-MIC). To address this limitation, we compiled implementation strategies and accompanying outcomes of evidence-based hypertension interventions currently being implemented in five Lower-MIC. The Global Research on Implementation and Translation Science (GRIT) Coordinating Center (CC) (GRIT-CC) engaged its global network sites at Ghana, Guatemala, India, Kenya, and Vietnam. Purposively sampled implementation science experts completed an electronic survey assessing implementation outcomes, in addition to implementation strategies used in their ongoing hypertension interventions from among 73 strategies within the Expert Recommendations for Implementing Change (ERIC). Experts rated the strategies based on highest priority to their interventions. We analyzed the data by sorting implementation strategies utilized by sites into one of the nine domains in ERIC and summarized the data using frequencies, proportions, and means. Seventeen implementation experts (52.9% men) participated in the exercise. Of Proctor's implementation outcomes identified across sites, all outcomes except for appropriateness were broadly assessed by three or more countries. Overall, 59 out of 73 (81%) strategies were being utilized in the five countries. The highest priority implementation strategies utilized across all five countries focused on evaluative and iterative strategies (e.g., identification of context specific barriers and facilitators) to delivery of patient- and community-level interventions, while the lowest priority was use of financial and infrastructure change strategies. More capacity building strategies (developing stakeholder interrelationships, training and educating stakeholders, and supporting clinicians) were incorporated into interventions implemented in India and Vietnam than Ghana, Kenya, and Guatemala. Although robust implementation strategies are being used in Lower -MICs, there is minimum use of financial and infrastructure change strategies. Our study contributes to the growing literature that demonstrates the use of Expert Recommendations for Implementing Change (ERIC) implementation strategies to deliver evidence-based hypertension interventions in Lower-MICs and will inform future cross-country data harmonization activities in resource-constrained settings.

Effectiveness of a Quality Improvement Program Using Difference-in-Difference Analysis for Home Based Newborn Care - Results of a Community Intervention Trial.

OBJECTIVE: To present evaluation of a quality improvement program for Accredited Social Health Activists (ASHAs). METHODS: This community intervention trial was conducted in Ballabgarh, India during 2012-2014 with two Primary Health Center (PHC) areas being the intervention areas and two PHC areas being non-intervention areas receiving standard care. Interventions included two-day training in technical and communication skills of ASHAs followed by supportive supervision in the field. Intervention was evaluated by comparing pre and post training scores, feedback from postnatal mothers and a difference-in-difference (DID) analysis on baseline and endline knowledge-practice survey of recently delivered mothers with 95% confidence intervals. RESULTS: Only 11.1% ASHAs addressed specific barriers for adopting healthy behaviors. Sixty eight (91.8%) ASHAs attended the training after which knowledge improved by 33.3% (p < 0.001). ASHAs in intervention areas were rated by mothers (n = 69) to have better communication skills (81.2% vs. 59.7%, p = 0.005), make more postnatal visits (52.2% vs. 22.2%; p < 0.001), give advice on newborn care (64% vs. 50.5%; p < 0.001) as compared to standard care area ASHAs. Endline survey (n = 1360) showed a significant improvement in frequency of antenatal visits (0.26;0.19-0.33), knowledge about free transport (0.12;0.05-0.18), better cord-care practices (0.15;0.07-0.22), kangaroo mother care (0.19;0.13-0.25), delayed first bath (0.13;0.06-0.20), restrictive handling (0.11;0.06-0.15) and hand-washing (0.19;0.13-0.25). CONCLUSIONS: Quality improvement program can help improve ASHA's performance which in turn can address higher neonatal mortality in India.

Who interacts with whom? Social mixing insights from a rural population in India.

Acute lower respiratory infections (ALRI) are a leading cause of morbidity and mortality globally, with most ALRI deaths occurring in children in developing countries. Computational models can be used to test the efficacy of respiratory infection prevention interventions, but require data on social mixing patterns, which are sparse in developing countries. We describe social mixing patterns among a rural community in northern India. During October 2015-February 2016, trained field workers conducted cross-sectional face-to-face standardized surveys in a convenience sample of 330 households in Faridabad District, Haryana State, India. Respondents were asked about the number, duration, and setting of social interactions during the previous 24 hours. Responses were compared by age and gender. Among the 3083 residents who were approached, 2943 (96%) participated, of whom 51% were male and the median age was 22 years (interquartile range (IQR) 9-37). Respondents reported contact (defined as having had a face-to-face conversation within 3 feet, which may or may not have included physical contact) with a median of 17 (IQR 12-25) people during the preceding 24 hours. Median total contact time per person was 36 person-hours (IQR 26-52). Female older children and adults had significantly fewer contacts than males of similar age (Kruskal-Wallis χ2 = 226.59, p<0.001), but spent a longer duration in contact with young children (Kruskal-Wallis χ2 = 27.26, p<0.001), suggesting a potentially complex pattern of differential risk of infection between genders. After controlling for household size and day of the week, respondent age was significantly associated with number and duration of contacts. These findings can be used to model the impact of interventions to reduce lower respiratory tract infections in India.