BackgroundIn India, although the proportion of institutional births is increasing, there are concerns regarding quality of care. We assessed the effectiveness of a nurse-led onsite mentoring program in improving quality of care of institutional births in 24/7 primary health centres (PHCs that are open 24 hours a day, 7 days a week) of two high priority districts in Karnataka state, South India. Primary outcomes were improved facility readiness and provider preparedness in managing institutional births and associated complications during child birth.MethodsAll functional 24/7 PHCs in the two districts were included in the study. We used a parallel, cluster randomized trial design in which 54 of 108 facilities received six onsite mentoring visits, along with an initial training update and specially designed case sheets for providers; the control arm received just the initial training update and the case sheets. Pre- and post-intervention surveys were administered in April-2012 and August-2013 using facility audits, provider interviews and case sheet audits. The provider interviews were administered to all staff nurses available at the PHCs and audits were done of all the filled case sheets during the month prior to data collection. In addition, a cost analysis of the intervention was undertaken.ResultsBetween the surveys, we achieved coverage of 100% of facilities and 91.2% of staff nurse interviews. Since the case sheets were newly designed, case-sheet audit data were available only from the end line survey for about 80.2% of all women in the intervention facilities and 57.3% in the control facilities. A higher number of facilities in the intervention arm had all appropriate drugs, equipment and supplies to deal with gestational hypertension (19 vs.3, OR (odds ratio) 9.2, 95% C.I 2.5 to33.6), postpartum haemorrhage (29 vs. 12, OR 3.7, 95% C.I 1.6 to8.3); and obstructed labour (25 vs.9, OR 3.4, 95% CI 1.6 to8.3). The providers in the intervention arm had better knowledge of active management of the third stage of labour (82.4% vs.35.8%, AOR (adjusted odds ratio) 10, 95% C.I 5.5 to 18.2); management of maternal sepsis (73.5% vs. 10.9%, AOR 36.1, 95% C.I 13.6 to 95.9); neonatal resuscitation (48.5% vs.11.7%, AOR 10.7, 95% C.I 4.6 to 25.0) and low birth weight newborn care (58.1% vs. 40.9%, AOR 2.4, 95% C.I 1.2 to 4.7). The case sheet audits revealed that providers in the intervention arm showed greater compliance with the protocols during labour monitoring (77.3% vs. 32.1%, AOR 25.8, 95% C.I 9.6 to 69.4); delivery and immediate post-partum care for mothers (78.6% vs. 31.8%, AOR 22.1, 95% C.I 8.0 to 61.4) and for newborns (73.9% vs. 32.8%, AOR 24.1, 95% C.I 8.1 to 72.0). The cost analysis showed that the intervention cost an additional $5.60 overall per delivery.ConclusionsThe mentoring program successfully improved provider preparedness and facility readiness to deal with institutional births and associated complications. It is feasible to improve the quality of institutional births at a large operational scale, with...

Background India accounts for more than two-third of mortality due to non-communicable diseases (NCDs) in south-east Asia. The burden is high in Karnataka, one of the largest states in southern India. There is a need for integration of disease prevention, health promotion, treatment and care within the national program at primary level. A public-private partnership initiative explored evidence gaps to inform a health system based, integrated NCD programme across care continuum with a focus on hypertension and diabetes. Methods The study was conducted during 2017–18 in urban parts of Mysore city, covering a population of 58,000. Mixed methods were used in the study; a population-based screening to estimate denominators for those with disease and at risk; cross-sectional surveys to understand distribution of risk factors, treatment adherence and out of pocket expenses; facility audits to assess readiness of public and private facilities; in-depth interviews and focus group discussions to understand practices, myths and perceptions in the community. Chi-square tests were used to test differences between the groups. Framework analysis approach was used for qualitative analysis. Results Twelve and 19% of the adult population had raised blood sugar and blood pressure, respectively, which increased with age, to 32 and 44% for over 50 years. 11% reported tobacco consumption; 5.5%, high alcohol consumption; 40%, inadequate physical activity and 81%, inappropriate diet consumption. These correlated strongly with elderly age and poor education. The public facilities lacked diagnostics and specialist services; care in the private sector was expensive. Qualitative data revealed fears and cultural myths that affected treatment adherence. The results informed intervention design across the NCD care continuum. Conclusions The study provides tools and methodology to gather evidence in designing comprehensive NCD programmes in low and middle income settings. The study also provides important insights into public-private partnership driving effective NCD care at primary care level. Electronic supplementary material The online version of this article (10.1186/s12889-019-6735-z) contains supplementary material, which is available to authorized users.

Background: Low-and middle-income countries (LMICs) account for a higher burden of noncommunicable diseases (NCD) and home to a higher number of premature deaths (before age 70) from NCDs. NCDs have become an integral part of the global development agenda; hence, the scope of action on NCDs extends beyond just the health-related sustainable development goal (SDG 3). However, the organization and integration of NCD-related health services have faced several gaps in the LMIC regions such as India. Although the national NCD programme of India has been in operation for a decade, challenges remain in the integration of NCD services at primary care. In this paper, we have analysed existing gaps in the organization and integration of NCD services at primary care and suggested plausible solutions that exist. Method: The identification of gaps is based out of a review of peer-reviewed articles, reports on national and global guidelines/protocols. The gaps are organized and narrated at four levels such as community, facility, health system, health policy and research, as per the WHO Innovative Care for Chronic Conditions framework (WHO ICCC). Result: The review found that challenges in the identification of eligible beneficiaries, shortage and poor capacity of frontline health workers, poor functioning of community groups and poor community knowledge on NCD risk factors were key gaps at the community level. Challenges at facility level such as poor facility infrastructure, lack of provider knowledge on standards of NCD care and below par quality of care led to poor management of NCDs. At the health system level, we found, organization of care, programme management and monitoring systems were not geared up to address NCDs. Multi-sectoral collaboration and coordination were proposed at the policy level to tackle NCDs; however, gaps remained in implementation of such policies. Limited research on the effect of health promotion, prevention and, in particular, non-medical interventions on NCDs was found as a key gap at the research level.

The Corona Virus Disease popularised as COVID-19 is a highly transmissible viral infection and has severe impact on global health. It impacted the global economy also very badly. Ift positive cases can be detected early, this pandemic disease spread can be curtailed. Prediction of COVID-19 disease is advantageous to identify patients at a risk of health conditions. Applications of Artificial Intelligence (AI) techniques for COVID prediction from X-rays can be very useful, and can help to overcome the shortage of availability of doctors and physicians in remote places. This paper proposes a transfer learning model using Googlenet for COVID-19 prediction from chest X-ray images. For image classification we used GoogleNet which is one of the CNN architecture and is also named as InceptionV1. The positively classified images by our model indicate the presence of COVID-19. The results obtained in COVID prediction using GoogleNet with a training accuracy of 99% and testing accuracy of 98.5% emphasize the use of Transfer Learning models in disease prediction. Keywords-X-ray images of chest, Prediction, COVID-19, GoogleNet. 1 INTRODUCTION THE 1 CoronaVirus Disease (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2) and is highly transmissible. It came into China government's notice in December, 2019 in Wuhan and more than twenty five million people all over the world were affected by it. Coronavirus is challenging all the people and the technology on the entire planet. As of August 2020, there are more than 27 million COVID-19 cases and 873,000 deaths globally [1]. There's no vaccine or immunizing agent found till date, thus the challenge is how best to fight against the Coronavirus to prevent its transmission. People with low immunity, old age, and medical issues especially associated with lungs are more vulnerable to COVID-19 sickness. The symptoms of COVID-19 are cough, cold, high fever and respiration issues. Preventive measures for COVID-19 square

Aim: Though Kangaroo Mother Care (KMC) has demonstrated benefits for low birth weight newborns, coverage continues to be low in India. As part of a World Health Organization (WHO) multi-country study, we explored intervention models to accelerate KMC coverage in a high priority district of Karnataka, India. Methods:We used implementation-research methods, formative assessments and quality improvement approaches to design and scale-up interventions. Evaluation was done using prospective cohort study design; data were collected from facility records, and client interviews during KMC initiation, at discharge and at home after discharge.Results: KMC was initiated at health facilities for 87.6% of LBW babies under 2000 g. At discharge, 85.0% received KMC; 67.9% continued to receive KMC at home on the 7th day post-discharge. The interventions included training, mentoring and constant advocacy at many levels: public health facilities, private sector and the community.Innovations like a KMC case sheet, counselling, peer support group triggered KMC in the facilities; a KMC-link card, a microplanning and communication tool for CHWs helped to sustain practice at homes. Conclusion:The study provides a novel approach to designing and scaling up interventions and suggests lessons that are applicable to KMC as well as to broader reproductive, maternal, neonatal and child health programmes.