SPARSH electronic sub-health centers (e-SHCs) - A model of nurse-run SHCs supported by general practitioners through telemedicine.

Background: The primary health care services in India suffer from inconsistent availability of providers, lack of quality, poor availability of medicines and diagnostics, and a poorly functioning referral linkage. A multi-pronged approach is required to address these issues. Methods: We describe here a model of electronic sub-health centers (e-SHCs) managed by trained nurses supported by a general practitioner over telemedicine. The e-SHCs are expected to meet two objectives - 1) to create a point of comprehensive primary health care delivery at an affordable cost and 2) to create a referral support system backed by information technology and physical movement. Results: The model is described in nine sections - service delivery framework, human resources, diagnostics, infrastructure, quality improvement, health management information system, materials management, financing, and branding. It is a video-based real-time (synchronous) health worker to the registered medical practitioner telemedicine facility. The model has been compared with five other telemedicine and five other tele-rehabilitation models. Conclusion: Although there are inherent challenges to operationalize this model, it also presents a unique opportunity of testing an innovative approach of providing quality primary health care at an affordable cost. The process will generate learnings for addressing the primary care health care delivery gaps in the country.

Automated versus physician assignment of cause of death for verbal autopsies: randomized trial of 9374 deaths in 117 villages in India.

BACKGROUND: Verbal autopsies with physician assignment of cause of death (COD) are commonly used in settings where medical certification of deaths is uncommon. It remains unanswered if automated algorithms can replace physician assignment. METHODS: We randomized verbal autopsy interviews for deaths in 117 villages in rural India to either physician or automated COD assignment. Twenty-four trained lay (non-medical) surveyors applied the allocated method using a laptop-based electronic system. Two of 25 physicians were allocated randomly to independently code the deaths in the physician assignment arm. Six algorithms (Naïve Bayes Classifier (NBC), King-Lu, InSilicoVA, InSilicoVA-NT, InterVA-4, and SmartVA) coded each death in the automated arm. The primary outcome was concordance with the COD distribution in the standard physician-assigned arm. Four thousand six hundred fifty-one (4651) deaths were allocated to physician (standard), and 4723 to automated arms. RESULTS: The two arms were nearly identical in demographics and key symptom patterns. The average concordances of automated algorithms with the standard were 62%, 56%, and 59% for adult, child, and neonatal deaths, respectively. Automated algorithms showed inconsistent results, even for causes that are relatively easy to identify such as road traffic injuries. Automated algorithms underestimated the number of cancer and suicide deaths in adults and overestimated other injuries in adults and children. Across all ages, average weighted concordance with the standard was 62% (range 79-45%) with the best to worst ranking automated algorithms being InterVA-4, InSilicoVA-NT, InSilicoVA, SmartVA, NBC, and King-Lu. Individual-level sensitivity for causes of adult deaths in the automated arm was low between the algorithms but high between two independent physicians in the physician arm. CONCLUSIONS: While desirable, automated algorithms require further development and rigorous evaluation. Lay reporting of deaths paired with physician COD assignment of verbal autopsies, despite some limitations, remains a practicable method to document the patterns of mortality reliably for unattended deaths. TRIAL REGISTRATION: ClinicalTrials.gov , NCT02810366. Submitted on 11 April 2016.

Training Village Health Workers in Detection and Monitoring of Noncommunicable Diseases: A Low Cost Option for Rural Areas Facing the Emerging Health Epidemic.

Noncommunicable diseases account for 53% of deaths and 44% of disability-adjusted life years lost in India. Village health workers (VHWs) were trained in blood pressure (BP) and blood sugar (BS) measurement and assessed using a checklist. A total of 38 VHWs with a mean age of 44.8 years, schooling of 9.9 years, scored 10.0 (76.9%) for BP and 9.74 (69.6%) for BS. There was no difference in scores for education and age. It is possible to train VHWs in BP and BS measurement and utilize them for screening and monitoring of hypertension and diabetes in a noncommunicable disease care program.

Burden of Self-Reported Noncommunicable Diseases in 26 Villages of Anand District of Gujarat, India.

Introduction. Noncommunicable diseases (NCDs) account for 53% of deaths and 44% of disability adjusted life years lost in India. A survey was undertaken to measure the prevalence of tobacco and alcohol use and self-reported NCDs in a rural community in western part of India. Methodology. Trained Village Health Workers did the survey in the years 2012-13 under supervision. The data was collected for five NCDs, namely, hypertension, diabetes mellitus, cancer, heart disease, and mental illnesses. Results. 18,269 households with a population of 89755 were covered. Prevalence of any form of tobacco use in the age group of >20 years was 34.5 and 52.7% and 15.2% in males and females, respectively. Prevalence of any NCD was 5.3% with a slightly higher prevalence in females (5.4%) than males (5.2%) in the age group of 20-69 years. Prevalence of NCD multimorbidity (≥2 NCDs) was 0.7% in the age group of 20-69 years. 80.7% of hypertensives and 94.9% of diabetics were taking treatment. More females than males were taking antihypertensive treatment. Conclusion. Tobacco use was high. Prevalence of NCDs was less than that reported in other studies. Data generated from this study can be useful in planning a community based NCD programme.