Background Health insurance is considered as a mechanism to accelerate the progress towards universal health coverage and ensure financial risk protection for households throughout the country. There is a growing body of evidence reporting that the health insurance coverage can significantly improve the access and utilization of healthcare services. Hence, we attempted to determine the impact of health insurance on the utilization of healthcare services during COVID‐19 pandemic. Methods A community‐based cross‐sectional study was conducted in rural Tamil Nadu. The primary data collection was conducted during November 2021. We employed a multi‐stage stratified random sampling technique. Propensity score matching analysis was performed using radius matching method at 0.05 calliper to estimate the following parameters: average treatment effect (ATE), average treatment effect on treated (ATT), and average treatment effect on untreated (ATU). Results In total, 2390 participants were included. Almost two‐third belonged to 18–45 years with almost equal distribution of males and females. Only 13.6% were covered by health insurance. Healthcare utilization was significantly higher among participants with health insurance (55.2%) compared to participants without coverage (42.5%). The ATT values in intervention and control group were 0.55 and 0.46 (p < 0.001). Similarly, the ATU values in intervention and control group were 0.42 and 0.51. The ATE value was 0.08. Conclusion Our study shows that the health insurance coverage had significant impact on utilization of healthcare services during COVID‐19 pandemic. Further longitudinal research exploring the effect of different forms of health insurance for improving access and utilization of healthcare services can be undertaken.

Background In ‘‘To Err is Human’’ released by the Institute of Medicine Committee on Quality of Health Care, it was emphasized that it is important to establish a safety culture in the hospitals and ensure that the patients are not inadvertently harmed by the errors. Hence, we developed and validated a questionnaire for assessing the perception of patient safety practices across the secondary and tertiary care facilities in India. Methods The scale was developed based on literature review and expert opinion. It consisted of 10 questions and response to these items were based on a 5-point Likert scale ranging from “strongly agree” to “strongly disagree”. All the analysis was performed using STATA version 14.2 software. Exploratory factor analysis (EFA) was run using principal components analysis with oblique Promax rotation, and confirmatory factor analysis (CFA) using structural equation modelling with maximum likelihood estimation. Results The entire dataset was split into testing set to run EFA (with 692 participants) and validation set to run CFA (with 645 participants). In EFA, two factors were retained as they had eigenvalue more than one (4.76, 1.09) and the scree plot also showed that the slope flattens off after two factors. Factor loadings were generated using oblique promax rotation. Factor 1 consisted of seven items (Item 1, Item 2, Item 3, Item 4, Item 5, Item 6, Item 7 – questions related to patient-doctor communication, hospital environment and procedures) accounting for 47.6% of variance, and Factor 2 had three items (Item 8, Item 9, Item 10 – infection prevention and control practices in hospital) explaining 10.9% of the variance. Thus, together the two factors explained 58.5% of the variance. CFA revealed good confirmatory fit indices of 0.85, standardized root mean square residual of 0.07 and acceptable Tucker-Lewis Index of 0.80. The reliability coefficient was 0.88 indicating very good internal consistency. Conclusion This study develops and validates a scale that can be used universally for assessing the patients’ perception on hospital safety practices across secondary and tertiary care facilities in India.

Identification of spatial gradient in the vulnerability of white leg shrimp production to climate change is imperative in the formulation and implementation of suitable adaptive measures. A composite vulnerability index was computed by employing 36 variables pertaining to exposure (11), sensitivity (11) and adaptive capacity ( 14) dimensions to map the extent of vulnerability in white leg shrimp production across Indian states. Based on its magnitude, the vulnerability index was categorized into three groups, namely low, moderate and high. Results showed that the mean composite vulnerability index was 0.65 and ranged from 0.34 to 0.99 indicating that there was a strong spatial pattern. Among the nine states, Goa (0.99), Kerala (0.84) and Odisha (0.77) were highly vulnerable; Gujarat (0.75), Karnataka (0.57) and West Bengal (0.56) were moderately vulnerable; and Tamil Nadu (0.54), Andhra Pradesh (0.46) and Maharashtra (0.34) were less vulnerable to shrimp production. About one-fourth of the production and culture area of white leg shrimp were in moderate and highly vulnerable regions. The impact of climate change on shrimp production is diverse but can be reduced by implementing adaptive measures-suitable policies and investment plans-which should be region-specific.