Cost of screening, out-of-pocket expenditure & quality of life for diabetes & hypertension in India.

Background & objectives: The Government of India has initiated a population based screening (PBS) for noncommunicable diseases (NCDs). A health technology assessment agency in India commissioned a study to assess the cost-effectiveness of screening diabetes and hypertension. The present study was undertaken to estimate the cost of PBS for Type II diabetes and hypertension. Second, out-of-pocket expenditure (OOPE) for outpatient care and health-related quality of life (HRQoL) among diabetes and hypertension patients were estimated. Methods: Economic cost of PBS of diabetes and hypertension was assessed using micro-costing methodology from a health system perspective in two States. A total of 165 outpatients with diabetes, 300 with hypertension and 497 with both were recruited to collect data on OOPE and HRQoL. Results: On coverage of 50 per cent, the PBS of diabetes and hypertension incurred a cost of ₹ 45.2 per person screened. The mean OOPE on outpatient consultation for a patient with diabetes, hypertension and both diabetes and hypertension was ₹ 4381 (95% confidence interval [CI]: 3786-4976), ₹ 1427 (95% CI: 1278-1576) and ₹ 3932 (95% CI: 3614-4250), respectively. Catastrophic health expenditure was incurred by 20, 1.3 and 14.8 per cent of patients with diabetes, hypertension and both diabetes and hypertension, respectively. The mean HRQoL score of patients with diabetes, hypertension and both was 0.76 (95% CI: 0.72-0.8), 0.89 (95% CI: 0.87-0.91) and 0.68 (95% CI: 0.66-0.7), respectively. Interpretations & conclusions: The findings of our study are useful for assessing cost-effectiveness of screening strategies for diabetes and hypertension.

CHSI costing study-Challenges and solutions for cost data collection in private hospitals in India.

INTRODUCTION: Ayushman Bharat Pradhan Mantri Jan Aarogya Yojana (AB PM-JAY) has enabled the Government of India to become a strategic purchaser of health care services from private providers. To generate base cost evidence for evidence-based policymaking the Costing of Health Services in India (CHSI) study was commissioned in 2018 for the price setting of health benefit packages. This paper reports the findings of a process evaluation of the cost data collection in the private hospitals. METHODS: The process evaluation of health system costing in private hospitals was an exploratory survey with mixed methods (quantitative and qualitative). We used three approaches-an online survey using a semi-structured questionnaire, in-depth interviews, and a review of monitoring data. The process of data collection was assessed in terms of time taken for different aspects, resources used, level and nature of difficulty encountered, challenges and solutions. RESULTS: The mean time taken for data collection in a private hospital was 9.31 (± 1.0) person months including time for obtaining permissions, actual data collection and entry, and addressing queries for data completeness and quality. The longest time was taken to collect data on human resources (30%), while it took the least time for collecting information on building and space (5%). On a scale of 1 (lowest) to 10 (highest) difficulty levels, the data on human resources was the most difficult to collect. This included data on salaries (8), time allocation (5.5) and leaves (5). DISCUSSION: Cost data from private hospitals is crucial for mixed health systems. Developing formal mechanisms of cost accounting data and data sharing as pre-requisites for empanelment under a national insurance scheme can significantly ease the process of cost data collection.

Burden of Group A Streptococcal Pharyngitis, Rheumatic Fever, and Rheumatic Heart Disease in India: A Systematic Review and Meta-Analysis.

OBJECTIVE: To estimate the burden of group A streptococcal pharyngitis (GAS) pharyngitis, rheumatic fever (RF), and rheumatic heart disease (RHD) in India using existing data sources, as well as to recognize the most serious gaps in GAS disease burden data. METHODS: Four electronic databases-PubMed, Scopus, Embase, and Web of Science were searched using a comprehensive search strategy. Data were identified primarily from observational studies including school surveys, community-based and hospital-based studies. The standard methodological procedures as per Cochrane guidelines were used. Eligible studies were pooled for estimating prevalence, incidence, and case fatality rate using R software version 3.3.3. The protocol was registered with PROSPERO; registration number CRD42018075742. RESULTS: The pooled prevalence of GAS pharyngitis among asymptomatic children and pharyngitis cases aged 5 to 15 y was estimated as 2.79 percent [95% Confidence interval (CI): 1.58-4.89] and 13 percent (95% CI: 3.18-41.97), respectively. The prevalence rate of rheumatic fever was found to be 0.04% (95% CI: 0.01-0.17). The pooled prevalence rate of RHD among children aged 5-15 y using clinical auscultation and echocardiography was estimated as 0.36 percent (95% CI: 0.02-7.52) and 0.28 percent (95% CI: 0.08-1.03), respectively. CONCLUSION: The study emphasizes the importance of developing a population-based surveillance framework to track patterns, management strategies, and outcomes in order to develop informed recommendations for launching contextual measures to regulate RF and RHD.

Process evaluation of health system costing - Experience from CHSI study in India.

BACKGROUND: A national study, 'Costing of healthcare services in India' (CHSI) aimed at generating reliable healthcare cost estimates for health technology assessment and price-setting is being undertaken in India. CHSI sampled 52 public and 40 private hospitals in 13 states and used a mixed micro-costing approach. This paper aims to outline the process, challenges and critical lessons of cost data collection to feed methodological and quality improvement of data collection. METHODS: An exploratory survey with 3 components-an online semi-structured questionnaire, group discussion and review of monitoring data, was conducted amongst CHSI data collection teams. There were qualitative and quantitative components. Difficulty in obtaining individual data was rated on a Likert scale. RESULTS: Mean time taken to complete cost data collection in one department/speciality was 7.86(±0.51) months, majority of which was spent on data entry and data issues resolution. Data collection was most difficult for determination of equipment usage (mean difficulty score 6.59±0.52), consumables prices (6.09±0.58), equipment price(6.05±0.72), and furniture price(5.64±0.68). Human resources, drugs & consumables contributed to 78% of total cost and 31% of data collection time. However, furniture, overheads and equipment consumed 51% of time contributing only 9% of total cost. Seeking multiple permissions, absence of electronic records, multiple sources of data were key challenges causing delays. CONCLUSIONS: Micro-costing is time and resource intensive. Addressing key issues prior to data collection would ease the process of data collection, improve quality of estimates and aid priority setting. Electronic health records and availability of national cost data base would facilitate conducting costing studies.