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Background: The Government of India launched the Ayushman Bharat (AB) program in 2018 which aims to transform 150,000 existing Sub Health Centres and Primary Health Centres into Ayushman Bharat Health and Wellness Centres (HWCs). In this study, we assessed health system readiness for establishment of HWCs. Methods: The assessment comprised of a cross sectional facility assessment and a knowledge assessment of community health officers (CHOs) and female multipurpose health workers also known as auxiliary nurse midwives (ANMs), in 26 HWCs in one community development block of Punjab state. HWCs were assessed for key input and process parameters such as a human resource, physical infrastructure, supplies, capacity building etc., and processes including health promotion, community participation, digitization of management information system, and service delivery. Results: It was observed that only 7 of the 26 HWCs had all human resources as per guidelines. The median knowledge score of CHOs and ANMs was 54% and 51% respectively. 11 of the 26 HWCs were co-located with Zila Parishad SHCs. Out of the 15 standalone HWCs, while 9 had independent buildings, 5 were located in buildings of other community level institutions. 50 percent of the HWCs were not able to perform diabetes screening due to lack of glucometers or testing supplies. While services for non-communicable diseases were available, a two-way referral tracking system for patients was missing. The mean job satisfaction rated by the newly appointed CHOs was 3.12 on a scale of 1 to 5, where 5 represented very high job satisfaction. Conclusion: The operationalization of HWCs requires State and local level interventions for strengthening of existing physical infrastructure, ensuring a regular supply of medicines and consumables, development of referral mechanisms for patients and enhancing community participation.

Background: The Government of India introduced a new cadre of Community Health Officers (CHOs) in the primary health-care system through the Ayushman Bharat Health and Wellness Centres (HWCs) program. Objectives: The study aimed to assess the activities performed and time spent by the existing and new primary health-care team members at the HWC level. Methods: A time and motion study was undertaken in four HWCs in Punjab over a period of 3 months, to assess the time spent by auxiliary nurse midwives (ANMs) and CHOs on different services and activities. Data were collected through direct continuous observation of four CHOs and four ANMs during working hours for a period of 6 consecutive days of a week, along with structured time allocation interviews of all participants. Results: The CHOs spent 5.7 (5.6–5.9) hours per day on duty of which 57% was productively involved in service delivery. The average time spent by ANMs was 4.9 (4.5–5.3) hours per day, with nearly 62% productive time. While the CHOs spent nearly 40% of their time on services for non-communicable diseases (NCDs), the ANMs spent 51% of their time on maternal, infant, child, and adolescent health services. Conclusion: The introduction of HWCs and CHOs has nudged the health system toward comprehensive primary health care by placing a renewed emphasis on NCDs. The study provides useful evidence for staff, program implementers, and policymakers, to aid informed decision-making for human resource management.

IntroductionAyushman 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.MethodsThe 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.ResultsThe 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).DiscussionCost 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.

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.