Understanding the extent of economic evidence usage for informing policy decisions in the context of India's national health insurance scheme: Ayushman Bharat Pradhan Mantri Jan Aarogya Yojana (PM-JAY).

INTRODUCTION: Ayushman Bharat Pradhan Mantri Jan Aarogya Yojana (PM-JAY) is one of the world's largest tax-funded insurance schemes. The present study was conducted to understand the decision-making process around the evolution (and revision) of health benefit packages (HBPs) and reimbursement rates within PM-JAY, with a specific focus on assessing the extent of use of economic evidence and role of various stakeholders in shaping these policy decisions. METHODS: A mixed-methods study was adopted involving in-depth interviews with seven key stakeholders involved in HBP design and reimbursement rates decisions, and a survey of 80 government staff and other relevant stakeholders engaged in the implementation of PM-JAY. The data gathered were thematically analysed, and a coding framework was developed to explore specific themes. Additionally, publicly available documents were reviewed to ensure a comprehensive understanding of the decision-making processes. RESULTS: Findings reveal a progressive transition towards evidence-based practices for policy decisions within PM-JAY. The initial version of HBP relied heavily on key criteria like disease burden, utilisation rates, and out-of-pocket expenditures, along with clinical opinion in shaping decisions around the inclusion of services in the HBP and setting reimbursement rates. Revised HBPs were informed based on evidence from a national-level costing study and broader stakeholder consultations. The use of health economic evidence increased with each additional revision with consideration of health technology assessment (HTA) evidence for some packages and reimbursement rates based on empirical cost evidence in the most recent update. The establishment of the Health Financing and Technology Assessment unit further signifies the use of evidence-based policymaking within PM-JAY. However, challenges persist, notably with regard to staff capacity and understanding of HTA principles, necessitating ongoing education and training initiatives. CONCLUSION: While substantial progress has been made in transitioning towards evidence-based practices within PM-JAY, sustained efforts and political commitment are required for the ongoing systematisation of processes.

Healthcare cost accounting in the Indian hospital sector.

Setting reimbursement rates in national insurance schemes requires robust cost data. Collecting provider generated cost accounting information is a potential mechanism for improving the cost evidence. To inform strategies for obtaining cost data to set reimbursement rates, this analysis aims to describe the role of cost accounting in public and private health sectors in India and describe the importance, perceived barriers, and facilitators to improving cost accounting systems. In-depth interviews (IDI) were conducted with 11 key informants. The interview tool guide was informed by a review of published and grey literature and government websites. The interviews were recorded for both audio and video and transcribed. A thematic coding framework was developed for the analysis. Multiple discussions were held to add, delete, classify, or merge the themes. The themes identified were: the status of cost accounting in the Indian hospital sector, legal and regulatory requirements for cost reporting, challenges to implementing cost accounting, and recommendations for improving cost reporting by healthcare providers. The findings indicate that the sector lacks maturity in cost accounting due to a lack of understanding of its benefits, limited capacity, and weak enforcement of cost reporting regulations. Providers recognize the value of cost analysis for investment decisions but have mixed opinions on the willingness to gather and report cost information, citing resource constraints and a lack of trust in payers. Additionally, heterogeneity among providers will require tailored approaches in developing cost accounting reporting frameworks and regulations. Healthcare cost accounting systems in India are rudimentary with a few exceptions, raising questions about how to source these data sustainably. Strengthening cost accounting systems will be contingent upon developing standardized formats that generate sufficient information for policymaking, are acceptable to private providers, and can be integrated with the existing data management systems.

Hospital care for critical illness in low-resource settings: lessons learned during the COVID-19 pandemic.

Care for the critically ill patients is often considered synonymous with a hospital having an intensive care unit. However, a focus on Essential Emergency and Critical Care (EECC) may obviate the need for much intensive care. Severe COVID-19 presented a specific critical care challenge while also being an exemplar of critical illness in general. Our multidisciplinary team conducted research in Kenya and Tanzania on hospitals' ability to provide EECC as the COVID-19 pandemic unfolded. Important basic inputs were often lacking, especially sufficient numbers of skilled health workers. However, we learnt that higher scores on resource readiness scales were often misleading, as resources were often insufficient or not functional in all the clinical areas they are needed. By following patient journeys, through interviews and group discussions, we revealed gaps in timeliness, continuity and delivery of care. Generic challenges in transitions between departments were identified in the receipt of critically ill patients, the ability to sustain monitoring and treatment and preparation for any subsequent transition. While the global response to COVID-19 focused initially on providing technologies and training, first ventilators and later oxygen, organisational and procedural challenges seemed largely ignored. Yet, they may even be exacerbated by new technologies. Efforts to improve care for the critically ill patients, which is a complex process, must include a whole system and whole facility view spanning all areas of patients' care and their transitions and not be focused on a single location providing 'critical care'. We propose a five-part strategy to support the system changes needed.

National hospital costing systems matter for universal healthcare: the India PM-JAY experience.

India envisions achieving universal health coverage to provide its people with access to affordable quality health services. A breakthrough effort in this direction has been the launch of the world's largest health assurance scheme Ayushman Bharat Pradhan Mantri Jan Arogya Yojana, the implementation of which resides with the National Health Authority. Appropriate provider payment systems and reimbursement rates are an important element for the success of PM-JAY, which in turn relies on robust cost evidence to support pricing decisions. Since the launch of PM-JAY, the health benefits package and provider payment rates have undergone a series of revisions. At the outset, there was a relative lack of cost data. Later revisions relied on health facility costing studies, and now there is an initiative to establish a national hospital costing system relying on provider-generated data. Lessons from PM-JAY experience show that the success of such cost systems to ensure regular and routine generation of evidence is contingent on integrating with existing billing or patient information systems or management information systems, which digitise similar information on resource consumption without any additional data entry effort. Therefore, there is a need to focus on building sustainable mechanisms for setting up systems for generating accurate cost data rather than relying on resource-intensive studies for cost data collection.

Refining the provider payment system of India's government-funded health insurance programme: an econometric analysis.

OBJECTIVES: Reimbursement rates in national health insurance schemes are frequently weighted to account for differences in the costs of service provision. To determine weights for a differential case-based payment system under India's publicly financed national health insurance scheme, the Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY), by exploring and quantifying the influence of supply-side factors on the costs of inpatient admissions and surgical procedures. DESIGN: Exploratory analysis using regression-based cost function on data from a multisite health facility costing study-the Cost of Health Services in India (CHSI) Study. SETTING: The CHSI Study sample included 11 public sector tertiary care hospitals, 27 public sector district hospitals providing secondary care and 16 private hospitals, from 11 Indian states. PARTICIPANTS: 521 sites from 57 healthcare facilities in 11 states of India. INTERVENTIONS: Medical and surgical packages of PM-JAY. PRIMARY AND SECONDARY OUTCOME MEASURES: The cost per bed-day and cost per surgical procedure were regressed against a range of factors to be considered as weights including hospital location, presence of a teaching function and ownership. In addition, capacity utilisation, number of beds, specialist mix, state gross domestic product, State Health Index ranking and volume of patients across the sample were included as variables in the models. Given the skewed data, cost variables were log-transformed for some models. RESULTS: The estimated mean costs per inpatient bed-day and per procedure were 2307 and 10 686 Indian rupees, respectively. Teaching status, annual hospitalisation, bed size, location of hospital and average length of hospitalisation significantly determine the inpatient bed-day cost, while location of hospital and teaching status determine the procedure costs. Cost per bed-day of teaching hospitals was 38-143.4% higher than in non-teaching hospitals. Similarly, cost per bed-day was 1.3-89.7% higher in tier 1 cities, and 19.5-77.3% higher in tier 2 cities relative to tier 3 cities, respectively. Finally, cost per surgical procedure was higher by 10.6-144.6% in teaching hospitals than non-teaching hospitals; 12.9-171.7% higher in tier 1 cities; and 33.4-140.9% higher in tier 2 cities compared with tier 3 cities, respectively. CONCLUSION: Our study findings support and validate the recently introduced differential provider payment system under the PM-JAY. While our results are indicative of heterogeneity in hospital costs, other considerations of how these weights will affect coverage, quality, cost containment, as well as create incentives and disincentives for provider and consumer behaviour, and integrate with existing price mark-ups for other factors, should be considered to determine the future revisions in the differential pricing scheme.

Cost Effectiveness of Strategies for Caring for Critically Ill Patients with COVID-19 in Tanzania.

BACKGROUND: The resources for critical care are limited in many settings, exacerbating the significant morbidity and mortality associated with critical illness. Budget constraints can lead to choices between investing in advanced critical care (e.g. mechanical ventilators in intensive care units) or more basic critical care such as Essential Emergency and Critical Care (EECC; e.g. vital signs monitoring, oxygen therapy, and intravenous fluids). METHODS: We investigated the cost effectiveness of providing EECC and advanced critical care in Tanzania in comparison with providing 'no critical care' or 'district hospital-level critical care' using coronavirus disease 2019 (COVID-19) as a tracer condition. We developed an open-source Markov model ( https://github.com/EECCnetwork/POETIC_CEA ) to estimate costs and disability-adjusted life-years (DALYs) averted, using a provider perspective, a 28-day time horizon, patient outcomes obtained from an elicitation method involving a seven-member expert group, a normative costing study, and published literature. We performed a univariate and probabilistic sensitivity analysis to assess the robustness of our results. , RESULTS: EECC is cost effective 94% and 99% of the time when compared with no critical care (incremental cost-effectiveness ratio [ICER] $37 [-$9 to $790] per DALY averted) and district hospital-level critical care (ICER $14 [-$200 to $263] per DALY averted), respectively, relative to the lowest identified estimate of the willingness-to-pay threshold for Tanzania ($101 per DALY averted). Advanced critical care is cost effective 27% and 40% of the time, when compared with the no critical care or district hospital-level critical care scenarios, respectively. CONCLUSION: For settings where there is limited or no critical care delivery, implementation of EECC could be a highly cost-effective investment. It could reduce mortality and morbidity for critically ill COVID-19 patients, and its cost effectiveness falls within the range considered 'highly cost effective'. Further research is needed to explore the potential of EECC to generate even greater benefits and value for money when patients with diagnoses other than COVID-19 are accounted for.

Modelling Methods of Economic Evaluations of HIV Testing Strategies in Sub-Saharan Africa: A Systematic Review.

BACKGROUND AND OBJECTIVE: Economic evaluations, a decision-support tool for policy makers, will be crucial in planning and tailoring HIV prevention and treatment strategies especially in the wake of stalled and decreasing funding for the global HIV response. As HIV testing and treatment coverage increase, case identification becomes increasingly difficult and costly. Determining which subset of the population these strategies should be targeted to becomes of vital importance as well. Generating quality economic evidence begins with the validity of the modelling approach and the model structure employed. This study synthesises and critiques the reporting around modelling methodology of economic models in the evaluation of HIV testing strategies in sub-Saharan Africa. METHODS: The following databases were searched from January 2000 to September 2020: MEDLINE, Embase, Scopus, EconLit and Global Health. Any model-based economic evaluation of a unique HIV testing strategy conducted in sub-Saharan Africa presenting a cost-effectiveness measure published from 2013 onwards was eligible. Data were extracted around three components: general study characteristics; economic evaluation design; and quality of model reporting using a novel tool developed for the purposes of this study. RESULTS: A total of 21 studies were included; 10 cost-effectiveness analyses, 11 cost-utility analyses. All but one study was conducted in Eastern and Southern Africa. Modelling approaches for HIV testing strategies can be broadly characterised as static aggregate models (3/21), static individual models (6/21), dynamic aggregate models (5/21) and dynamic individual models (7/21). Adequate reporting around data handling was the highest of the three categories assessed (74%), and model validation, the lowest (45%). Limitations to model structure, justification of chosen time horizon and cycle length, and description of external model validation process were all adequately reported in less than 40% of studies. The predominant limitation of this review relates to the potential implications of the narrow inclusion criteria. CONCLUSIONS: This review is the first to synthesise economic evaluations of HIV testing strategies in sub-Saharan Africa. The majority of models exhibited dynamic, stochastic and individual properties. Model reporting against the 13 criteria in our novel tool was mixed. Future model-based economic evaluations of HIV testing strategies would benefit from transparency around the choice of modelling approach, model structure, data handling procedures and model validation techniques.

Essential emergency and critical care as a health system response to critical illness and the COVID19 pandemic: what does it cost?

Essential Emergency and Critical Care (EECC) is a novel approach to the care of critically ill patients, focusing on first-tier, effective, low-cost, life-saving care and designed to be feasible even in low-resourced and low-staffed settings. This is distinct from advanced critical care, usually conducted in ICUs with specialised staff, facilities and technologies. This paper estimates the incremental cost of EECC and advanced critical care for the planning of care for critically ill patients in Tanzania and Kenya.The incremental costing took a health systems perspective. A normative approach based on the ingredients defined through the recently published global consensus on EECC was used. The setting was a district hospital in which the patient is provided with the definitive care typically provided at that level for their condition. Quantification of resource use was based on COVID-19 as a tracer condition using clinical expertise. Local prices were used where available, and all costs were converted to USD2020.The costs per patient day of EECC is estimated to be 1 USD, 11 USD and 33 USD in Tanzania and 2 USD, 14 USD and 37 USD in Kenya, for moderate, severe and critical COVID-19 patients respectively. The cost per patient day of advanced critical care is estimated to be 13 USD and 294 USD in Tanzania and USD 17 USD and 345 USD in Kenya for severe and critical COVID-19 patients, respectively.EECC is a novel approach for providing the essential care to all critically ill patients. The low costs and lower tech approach inherent in delivering EECC mean that EECC could be provided to many and suggests that prioritizing EECC over ACC may be a rational approach when resources are limited.

Resource use, availability and cost in the provision of critical care in Tanzania: a systematic review.

OBJECTIVES: Critical care is essential in saving lives of critically ill patients, however, provision of critical care across lower resource settings can be costly, fragmented and heterogenous. Despite the urgent need to scale up the provision of critical care, little is known about its availability and cost. Here, we aim to systematically review and identify reported resource use, availability and costs for the provision of critical care and the nature of critical care provision in Tanzania. DESIGN: This is a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. DATA SOURCES: Medline, Embase and Global Health databases were searched covering the period 2010 to 17 November 2020. ELIGIBILITY CRITERIA: We included studies that reported on forms of critical care offered, critical care services offered and/or costs and resources used in the provision of care in Tanzania published from 2010. DATA EXTRACTION AND SYNTHESIS: Quality assessment of the articles and data extraction was done by two independent researchers. The Reference Case for Estimating the Costs of Global Health Services and Interventions was used to assess quality of included studies. A narrative synthesis of extracted data was conducted. Costs were adjusted and reported in 2019 US$ and TZS using the World Bank GDP deflators. RESULTS: A total 31 studies were found to fulfil the inclusion and exclusion criteria. Critical care identified in Tanzania was categorised into: intensive care unit (ICU) delivered critical care and non-ICU critical care. The availability of ICU delivered critical care was limited to urban settings whereas non-ICU critical care was found in rural and urban settings. Paediatric critical care equipment was more scarce than equipment for adults. 15 studies reported on the costs of services related to critical care yet no study reported an average or unit cost of critical care. Costs of medication, equipment (eg, oxygen, personal protective equipment), services and human resources were identified as inputs to specific critical care services in Tanzania. CONCLUSION: There is limited evidence on the resource use, availability and costs of critical care in Tanzania. There is a strong need for further empirical research on critical care resources availability, utilisation and costs across specialties and hospitals of different level in low/middle-income countries like Tanzania to inform planning, priority setting and budgeting for critical care services. PROSPERO REGISTRATION NUMBER: CRD42020221923.

Cost of hospital services in India: a multi-site study to inform provider payment rates and Health Technology Assessment.

The 'Cost of Health Services in India (CHSI)' is the first large scale multi-site facility costing study to incorporate evidence from a national sample of both private and public sectors at different levels of the health system in India. This paper provides an overview of the extent of heterogeneity in costs caused by various supply-side factors.A total of 38 public (11 tertiary care and 27 secondary care) and 16 private hospitals were sampled from 11 states of India. From the sampled facilities, a total of 327 specialties were included, with 48, 79 and 200 specialties covered in tertiary, private and district hospitals respectively. A mixed methodology consisting of both bottom-up and top-down costing was used for data collection. Unit costs per service output were calculated at the cost centre level (outpatient, inpatient, operating theatre, and ICU) and compared across provider type and geographical location.The unadjusted cost per admission was highest for tertiary facilities (₹ 5690, 75 USD) followed by private facilities (₹ 4839, 64 USD) and district hospitals (₹ 3447, 45 USD). Differences in unit costs were found across types of providers, resulting from both variations in capacity utilisation, length of stay and the scale of activity. In addition, significant differences in costs were found associated with geographical location (city classification).The reliance on cost information from single sites or small samples ignores the issue of heterogeneity driven by both demand and supply-side factors. The CHSI cost data set provides a unique insight into cost variability across different types of providers in India. The present analysis shows that both geographical location and the scale of activity are important determinants for deriving the cost of a health service and should be accounted for in healthcare decision making from budgeting to economic evaluation and price-setting.

Role of healthcare cost accounting in pricing and reimbursement in low-income and middle-income countries: a scoping review.

OBJECTIVES: Progress towards universal health coverage (UHC) requires evidence-based policy including good quality cost data systems. Establishing these systems can be complex, resource-intensive and take time. This study synthesises evidence on the experiences of low-income and middle-income countries (LMICs) in the institutionalisation of cost data systems to derive lessons for the technical process of price-setting in the context of UHC. DESIGN: A scoping review and narrative synthesis of publicly available information. DATA SOURCES: PubMed, MEDLINE, EconLit, the Web of Science and grey literature searched from January 2000 to April 2021. ELIGIBILITY CRITERIA: English-language papers published since 2000 that identified and/or described development of and/or methods used to estimate or inform national tariffs for hospital reimbursement in LMICs. Papers were screened by two independent reviewers. DATA EXTRACTION AND SYNTHESIS: Extraction was performed by one reviewer and checked by the second reviewer on: the method and outputs of cost data collection; commentary on the use of cost data; description of the technical process of tariff setting; and strengths and challenges of the approach. Evidence was summarised using narrative review. RESULTS: Thirty of 484 papers identified were eligible. Fourteen papers reported on primary cost data collection; 18 papers explained how cost evidence informs tariff-setting. Experience was focused in Asia (n=22) with countries at different stages of developing cost systems. Experiences on cost accounting tend to showcase country costing experiences, methods and implementation. There is little documentation how data have been incorporated into decision making and price setting. Where cost information or cost systems have been used, there is improved transparency in decision making alongside increased efficiency. CONCLUSIONS: There are widely used and accepted methods for generating cost information. Countries need to build sustainable cost systems appropriate to their settings and budgets and adopt transparent processes and methodologies for translating costs into prices.

A costing analysis of B-GAP: index-linked HIV testing for children and adolescents in Zimbabwe.

BACKGROUND: By testing children and adolescents of HIV positive caretakers, index-linked HIV testing, a targeted HIV testing strategy, has the ability to identify high risk children and adolescents earlier and more efficiently, compared to blanket testing. We evaluated the incremental cost of integrating index-linked HIV testing via three modalities into HIV services in Zimbabwe. METHODS: A mixture of bottom-up and top-down costing was employed to estimate the provider cost per test and per HIV diagnosis for 2-18 year olds, through standard of care testing, and the incremental cost of index-linked HIV testing via three modalities: facility-based testing, home-based testing by a healthcare worker, and testing at home by the caregiver using an oral mucosal transudate test. In addition to interviews, direct observation and study process data, facility registries were abstracted to extract outcome data and resource use. Costs were converted to 2019 constant US$. RESULTS: The average cost per standard of care test in urban facilities was US$5.91 and US$7.15 at the rural facility. Incremental cost of an index-linked HIV test was driven by the uptake and number of participants tested. The lowest cost approach in the urban setting was home-based testing (US$6.69) and facility-based testing at the rural clinic (US$5.36). Testing by caregivers was almost always the most expensive option (rural US$62.49, urban US$17.49). CONCLUSIONS: This is the first costing analysis of index-linked HIV testing strategies. Unit costs varied across sites and with uptake. When scaling up, alternative testing solutions that increase efficiency such as index-linked HIV testing of the entire household, as opposed to solely targeting children/adolescents, need to be explored.

Resource availability, utilisation and cost in the provision of critical care in Tanzania: a protocol for a systematic review.

INTRODUCTION: Critical care is essential in saving lives of those that are critically ill, however, provision of critical care can be costly and heterogeneous across lower-resource settings. This paper describes the protocol for a systematic review of the literature that aims to identify the reported costs and resources available for the provision of critical care and the forms of critical care provision in Tanzania. METHODS AND ANALYSIS: The review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Three databases (MEDLINE, Embase and Global Health) will be searched to identify articles that report the forms of critical care, resources used in the provision of critical care in Tanzania, their availability and the associated costs. The search strategy will be developed from four key concepts; critical care provision, critical illness, resource use, Tanzania. The articles that fulfil the inclusion and exclusion criteria will be assessed for quality using the Reference Case for Estimating the Costs of Global Health Services and Interventions checklist. The extracted data will be summarised using descriptive statistics including frequencies, mean and median of the quantity and costs of resources used in the components of critical care services, depending on the data availability. This study will be carried out between February and November 2021. ETHICS AND DISSEMINATION: This study is a review of secondary data and ethical clearance was sought from and granted by the Tanzanian National Institute of Medical Research (reference: NIMR/HQ/R.8a/Vol. IX/3537) and London School of Hygiene and Tropical Medicine (ethics ref: 22866). We will publish the review in a peer-reviewed journal as an open access article in addition to presenting the findings at conferences and public scientific gatherings. PROSPERO REGISTRATION NUMBER: The protocol was registered with PROSPERO; registration number: CRD42020221923.

The costs of scaling up HIV and syphilis testing in low- and middle-income countries: a systematic review.

Around two-thirds of all new HIV infections and 90% of syphilis cases occur in low- and middle-income countries (LMICs). Testing is a key strategy for the prevention and treatment of HIV and syphilis. Decision-makers in LMICs face considerable uncertainties about the costs of scaling up HIV and syphilis testing. This paper synthesizes economic evidence on the costs of scaling up HIV and syphilis testing interventions in LMICs and evidence on how costs change with the scale of delivery. We systematically searched multiple databases (Medline, Econlit, Embase, EMCARE, CINAHL, Global Health and the NHS Economic Evaluation Database) for peer-reviewed studies examining the costs of scaling up HIV and syphilis testing in LMICs. Thirty-five eligible studies were identified from 4869 unique citations. Most studies were conducted in Sub-Saharan Africa (N = 17) and most explored the costs of rapid HIV in facilities targeted the general population (N = 19). Only two studies focused on syphilis testing. Seventeen studies were cost analyses, 17 were cost-effectiveness analyses and 1 was cost-benefit analysis of HIV or syphilis testing. Most studies took a modelling approach (N = 25) and assumed costs increased linearly with scale. Ten studies examined cost efficiencies associated with scale, most reporting short-run economies of scale. Important drivers of the costs of scaling up included testing uptake and the price of test kits. The 'true' cost of scaling up testing is likely to be masked by the use of short-term decision frameworks, linear unit-cost projections (i.e. multiplying an average cost by a factor reflecting activity at a larger scale) and availability of health system capacity and infrastructure to supervise and support scale up. Cost data need to be routinely collected alongside other monitoring indicators as HIV and syphilis testing continues to be scaled up in LMICs.

Cost of scaling-up comprehensive primary health care in India: Implications for universal health coverage.

India has announced the ambitious program to transform the current primary healthcare facilities to health and wellness centres (HWCs) for provision of comprehensive primary health care (CPHC). We undertook this study to assess the cost of this scale-up to inform decisions on budgetary allocation, as well as to set the norms for capitation-based payments. The scale-up cost was assessed from both a financial and an economic perspective. Primary data on resources used to provide services in 93 sub-health centres (SHCs) and 38 primary health care centres (PHCs) were obtained from the National Health System Cost Database. The cost of additional infrastructure and human resources was assessed against the normative guidelines of Indian Public Health Standards and the HWC. The cost of other inputs (drugs, consumables, etc.) was determined by undertaking the need estimation based on disease burden or programme guidelines, standard treatment guidelines and extent and pattern of care utilization from nationally representative sample surveys. The financial cost is reported in terms of the annual incremental cost at health facility level, as well as its implications at national level, given the planned scale-up path. Secondly, economic cost is assessed as the total annual as well as annual per capita cost of services at HWC level. Bootstrapping technique was undertaken to estimate 95% confidence intervals for cost estimations. Scaling to CPHC through HWC would require an additional ₹ 721 509 (US$10 178) million allocation of funds for primary healthcare >5 years from 2019 to 2023. The scale-up would imply an addition to Government of India's health budget of 2.5% in 2019 to 12.1% in 2023. Our findings suggest a scale-up cost of 0.15% of gross domestic product (GDP) for full provision of CPHC which compares with current public health spending of 1.28% of GDP and a commitment of 2.5% of GDP by 2025 in the National Health Policy. If a capitation-based payment system was used to pay providers, provision of CPHC would need to be paid at between ₹ 333 (US$4.70) and ₹ 253 (US$3.57) per person covered for SHC and PHC, respectively.

Cost savings from use of a neonatal sepsis calculator in Australia: A modelled economic analysis.

AIM: To estimate the change in average cost and length of stay (LOS) for the neonatal birth admission resulting from use of the neonatal early-onset sepsis (EOS) calculator compared to guideline-based management, in an Australian perinatal health-care setting. METHODS: A decision-analytic model (decision tree) was constructed to assess admission cost and LOS with EOS calculator use compared to guideline-based management. Probabilities of clinical sepsis-related outcomes were obtained via review of published literature. Costs and average LOS were obtained from Australia's Independent Hospital Pricing Authority. RESULTS: EOS calculator use was associated with a reduction in costs of AUD$25806 and in average LOS of 25.4 days per 1000 babies born. Sensitivity analyses demonstrated greater net benefits could be expected for services where there is a higher baseline rate of antibiotic use. CONCLUSION: This model demonstrates a significant cost reduction for the neonatal birth admission, associated with use of the EOS calculator as compared to existing guidelines. The net benefit may be greater in Australia, where rates of empiric antibiotic use are reportedly high, compared to some European countries and the United States. Future research opportunities include prospective collection of economic data alongside the introduction of the EOS calculator.

Cost variations in prevention of mother-to-child HIV transmission services integrated within maternal and child health services in rural Tanzania.

We estimated the costs of Option B+ for HIV-infected pregnant women in 12 facilities in Morogoro Region, Tanzania, from a provider perspective. Costs of prevention of mother-to-child (PMTCT) HIV services were measured over 12 months to September 2017 to estimate the average costs per HIV testing episode, per HIV-positive case diagnosed, per patient-year on antiretroviral therapy (ART), and per neonatal HIV care. A one-way sensitivity analysis was undertaken to understand how staffing levels and other core resource inputs affected costs. The total number of HIV testing episodes was 25,593 with 279 HIV cases identified yielding a 1.1% positivity rate. The average cost per testing episode was US$5.49 (range US$2.13 to US$13.93), and the average cost per HIV case detected was US$503.29 (range US$230.61 to US$3330.38). The number of pregnant women initiated on ART was 278. The mean cost per patient-year on ART was US$159.89 (range US$100.91 to US$812.23). The average cost of neonatal HIV care was US$90.09 (range US$41.53 to US$180.26). PMTCT service costs varied widely across facilities due to variations in resource use, number of women testing, and HIV prevalence. The study provides further evidence against generalising cost estimates, and that budgeting and planning requires context specific cost information.

Assessing the costs and efficiency of HIV testing and treatment services in rural Malawi: implications for future "test and start" strategies.

BACKGROUND: Reaching the 90-90-90 targets requires efficient resource use to deliver HIV testing and treatment services. We investigated the costs and efficiency of HIV services in relation to HIV testing yield in rural Karonga District, Malawi. METHODS: Costs of HIV services were measured over 12 months to September 2017 in five health facilities, drawing on recognised health costing principles. Financial and economic costs were collected in Malawi Kwacha and United States Dollars (US$). Costs were calculated using a provider perspective to estimate average annual costs (2017 US$) per HIV testing episode, per HIV-positive case diagnosed, and per patient-year on antiretroviral therapy (ART), by facility. Costs were assessed in relation to scale of operation and facility-level annual HIV positivity rate. A one-way sensitivity analysis was undertaken to understand how staffing levels and the HIV positivity rate affected HIV testing costs. RESULTS: HIV testing episodes per day and per full-time equivalent HIV health worker averaged 3.3 (range 2.0 to 5.7). The HIV positivity rate averaged 2.4% (range 1.9 to 3.7%). The average cost per testing episode was US$2.85 (range US$1.95 to US$8.55), and the average cost per HIV diagnosis was US$116.35 (range US$77.42 to US$234.11), with the highest costs found in facilities with the lowest daily number of tests and lowest HIV yield respectively. The mean facility-level cost per patient-year on ART was approximately US$100 (range US$90.67 to US$115.42). ART drugs were the largest cost component averaging 71% (range 55 to 76%). The cost per patient-year of viral load tests averaged US$4.50 (range US$0.52 to US$7.00) with cost variation reflecting differences in the tests to ART patient ratio across facilities. CONCLUSION: Greater efficiencies in HIV service delivery are possible in Karonga through increasing daily testing episodes among existing health workers or allocating health workers to tasks in addition to testing. Costs per diagnosis will increase as yields decline, and therefore, encouraging targeted testing strategies that increase yield will be more efficient. Given the contribution of drug costs to per patient-year treatment costs, it is critical to preserve the life-span of first-line ART regimens, underlining the need for continuing adherence support and regular viral load monitoring.

Establishing reference costs for the health benefit packages under universal health coverage in India: cost of health services in India (CHSI) protocol.

INTRODUCTION: To achieve universal health coverage, the Government of India has introduced Ayushman Bharat - Pradhan Mantri Jan Arogya Yojana (AB - PMJAY), a large tax-funded national health insurance scheme for the provision of secondary and tertiary care services in public and private hospitals. AB - PMJAY reimburses care for 1573 health benefit packages (HBPs). HBPs are designed to cover the treatment of diseases/conditions with high incidence/prevalence or which contribute to high out-of-pocket expenditure. However, there is a dearth of reference cost data against which provider payment rates can be assessed. METHODS AND ANALYSIS: The CHSI (Cost of Health Services in India) study will collect cost data from 13 Indian states covering 52 public and 40 private hospitals, using a mixed economic costing methodology (top-down and bottom-up), to generate unit costs for the HBPs. States will be sampled to capture economic status, development indicators and health service utilisation heterogeneity. The public sector hospitals will be chosen at secondary and tertiary care level. One tertiary facility will be selected from each state. At secondary level, three districts per state will be selected randomly from the district composite development score ranking. The private sector hospital sample will be stratified by nature of ownership (for-profit and not-for-profit), type of city (tier 1, 2 or 3) and size of the hospital (number of beds). Average costs for each HBP will be calculated across the different facility types. Multiple scenarios will be used to suggest rates which could be negotiated with the providers. Overall, the study will provide economic cost data for price setting, strategic purchasing, health technology assessment and a national cost database of India. ETHICS AND DISSEMINATION: The approval has been obtained from the Institutional Ethics Committee and Institutional Collaborative Committee of the Post Graduate Institute of Medical Education and Research, Chandigarh, India. The results shall be disseminated in conferences and peer-reviewed articles.