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Cost per outcome of ICU care under Biju Swasthya Kalyan Yojana in Odisha
For correspondence: Dr Satyajit Choudhury, Department of Critical Care Medicine, IMS and SUM Hospital, Bhubaneswar, Odisha, 751 003, India e-mail: satyajitchoudhury@soa.ac.in
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Received: ,
Accepted: ,
How to cite this article: Mishra SB, Samal S, Choudhury S. Cost per outcome of ICU care under Biju Swasthya Kalyan Yojana in Odisha. Indian J Med Res. 2026;164:91-7. doi: 10.25259/IJMR_2665_2025.
Abstract
Background and objectives
The Biju Swasthya Kalyan Yojana (BSKY), a State-run health insurance programme in Odisha, provides financial protection for high-cost care, including intensive care unit (ICU) services. This study aimed to evaluate the clinical outcomes and economic value of ICU care delivered under BSKY over a two-year period at a tertiary centre.
Methods
A retrospective observational study was conducted among adults (≥18 years) with an APACHE II (acute physiology and chronic health evaluation) score ≥15 who were admitted to the ICU between January 2022 and December 2023 under BSKY coverage. Financial data (government reimbursement, hospital costs) and clinical outcomes (demographics, length of stay, mortality) were analysed. The cost per life saved and the cost per disability-adjusted life year (DALY) averted were calculated using the WHO-CHOICE (World Health Organization Choosing Interventions that are Cost-Effective) methodology.
Results
Of 2,805 ICU admissions, 1,799 eligible patients were analysed (mean age: 57.1 years; 64% male). The survival rate to discharge was 78.7%. Median ICU stay was 5.46 (1.86 – 9.06) days for survivors and 7.53 (1.4 – 13.66) days for non-survivors. The average hospital cost per patient was INR (₹) 69,381.62 (US$831.28), while the mean BSKY reimbursement was ₹1,03,411.4 (US$1,239) for survivors and ₹1,51,402.97 (US$1,814) for non-survivors. The cost per life saved was ₹1,44,366.99 (US$1,729.7). The study population yielded 8502 DALYs, with a cost per DALY averted of ₹74,941.97 (US$897.9) overall, ₹11,376 (US$136.3) for patients <60 yr, and ₹1,03,194.4 (US$1,236.4) for those ≥60 yr.
Interpretation and conclusions
ICU care under BSKY reduced patients’ financial burden and achieved favourable cost per outcome across age groups, with particularly high value among younger patients. The findings support the need to sustain and expand critical care coverage under State health insurance schemes in India.
Keywords
Biju Swasthya Kalyan Yojana
Cost per outcome
Disability-adjusted life years
India
Intensive care unit (ICU)
Intensive care units (ICUs) provide specialised care for critically ill patients but incur substantial costs due to advanced equipment, specialised staffing, infection control, and complex care requirements.1-3 Indian studies report daily ICU costs ranging from INR (₹) 6,637 (US$ 79.52) to ₹11,241 (US$ 134.68) per patient, with total per-patient expenditures varying significantly by medical condition and hospital setting.4-8 Given these costs, evaluating the economic implications of ICU services is critical for healthcare financing and resource allocation.
Globally, national health insurance schemes have improved healthcare affordability and outcomes. Studies from South Africa, Ghana, Bosnia and Herzegovina, and Tanzania demonstrate the cost-effectiveness of critical care coverage, showing improved patient outcomes and favourable cost-effectiveness ratios even in resource-constrained settings.9-13 In India, financial protection schemes evolved from Rashtriya Swasthya Bima Yojana (RSBY)—which faced limitations including poor reimbursement and restricted coverage14-16 —to Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (AB-PMJAY), which expanded coverage to ₹5 lakhs (US$5,991) per family for secondary and tertiary care.17,18
Odisha implemented the Biju Swasthya Kalyan Yojana (BSKY) instead of AB-PMJAY to address the State’s socioeconomic challenges, including high poverty rates (33% overall, 46.9% rural, 75.6% among scheduled tribes).19,20 BSKY has two components: Component I provides universal healthcare coverage for all State residents at public institutions, including ICU services; Component II targets economically vulnerable populations (identified through BPL(below poverty line), Antyodaya Anna Yojana, NFSA (National food security act), and ration cards), offering annual cashless coverage of ₹5 lakhs per family, with an additional ₹5 lakhs for female members, valid at empanelled private and government hospitals.21,22
Despite BSKY’s implementation, comprehensive evaluations of its financial expenditure and clinical outcomes specifically for ICU care remain limited. There is insufficient evidence regarding the actual cost per outcome of ICU services under BSKY using standardised metrics like disability-adjusted life years (DALYs), cost per life saved across different age groups, whether government reimbursements adequately cover hospital costs for critical care, and long-term value for money in sustaining ICU services under State insurance schemes. We conducted this study to document a cost per outcome analysis of ICU care delivered under BSKY by calculating the cost per DALY averted and cost per life saved. The secondary objective was to assess survival rates and clinical outcomes among critically ill patients.
Methods
This retrospective observational study was undertaken by the department of Critical Care Medicine, IMS and SUM Hospital, Bhubaneswar, Odisha, India. The study analysed patient records over a two-year period (January 2022 to December 2023). Ethical approval was obtained from the Institutional Ethical Committee. All patient data were anonymised to ensure confidentiality. Approval was obtained from all local ethics committees.
Eligibility criteria
The study was conducted at a tertiary private teaching hospital in Bhubaneswar, Odisha, with a capacity of 1600 beds and a 100-bed medical ICU. ICU staffing maintained a nurse-to-patient ratio of 1:2 and a junior doctor-to-patient ratio of 1:10. We focused on patients with APACHE II (acute physiology and chronic health evaluation) scores ≥15 due to their documented higher baseline risk of mortality.
Patients were eligible for inclusion if they were adults aged 18 years or older and their hospital admission was fully covered under the BSKY scheme. An additional requirement was an APACHE II score of 15 or greater at the time of ICU admission, reflecting a moderate to severe level of illness severity. Only patients with complete clinical and financial records available in the hospital’s database were included in the analysis.
Data collection
Data were collected from two perspectives to evaluate sustainability and resource allocation comprehensively:
Government perspective (BSKY coverage)
The BSKY scheme provided a condition-specific reimbursement package covering routine investigations (labs, X-rays, CT/MRI), procedures (e.g., vascular access, dialysis), consumables, hospital infrastructure, staffing, and overheads. Patients incurred no out-of-pocket expenses under BSKY, which offered coverage up to INR₹ 5 lakhs per family annually, with an additional INR ₹5 lakhs for female members. Beneficiaries were explicitly identified using the NFSA (National Food Security Act) and ration cards.
Hospital perspective (micro costing analysis)
A detailed analysis of intensive care unit (ICU) costs was performed and categorised into four major components, with supporting details provided in Supplementary Material. Human resource expenditure was calculated based on the annual salaries of consultants, junior doctors, nurses, and support staff. The total salary pool was divided by the average annual ICU admissions (∼1,166 patients per year) to derive the per-patient cost. Infrastructure costs were annualised using a 3% discount rate over the estimated useful life of equipment and facilities, and this value was subsequently allocated on a per-patient basis. Overheads, including utilities, maintenance, and security, were proportionally distributed to the ICU from the hospital’s total overhead expenditures.
Expenditure on drugs and consumables was calculated separately, with an average daily cost estimated at ₹4,000 (∼US$48) per patient. When multiplied by the average ICU stay of five days, this amounted to ₹20,000 (US$240) per patient. The summation of these four components yielded an estimated total hospital cost of ₹54,841 (∼US$657) per ICU patient. The conversion rate used was 1 USD = ₹83.4636, based on the exchange rate of May 31, 2024. No out-of-pocket expenditures were incurred by any patient, as the BSKY programme covered all expenses from admission to discharge or death.
Clinical data collection
Comprehensive clinical data were obtained from electronic medical and billing records. Information collected included demographic details such as age, sex, and socioeconomic status, along with APACHE II scores assessed within 24 h of ICU admission.23 Additional clinical parameters recorded included the length of ICU stay, defined as the duration from ICU admission to discharge or death, and clinical outcomes, such as in-hospital mortality and survival status. Comorbidity data, including diabetes mellitus, hypertension, and chronic kidney disease, were also collected for risk stratification and subgroup analysis.
DALY and cost per outcome analysis
Disability-Adjusted Life Years (DALYs) were calculated in accordance with the WHO-CHOICE framework, which defines DALY as the sum of years of life lost (YLL) due to premature mortality and years lived with disability (YLD) due to non-fatal health outcomes.24,25
Life expectancy (L) estimates were based on WHO reference life tables, and a 3% annual discount rate was applied to future years of life lost. YLL was calculated as L multiplied by the number of deaths. YLD was calculated as the number of incident cases (I) multiplied by the disability weight (DW) and the duration of disability (L).24,25 Disability weights corresponding to moderate disability were applied to reflect the burden of post-intensive care unit (ICU) syndrome among survivors. Age weighting was not applied in this analysis. To account for the specific role of critical care access, ICU care benefits under the BSKY programme were assumed to contribute approximately 70% of the overall survival benefit. This assumption aligns with similar health economic evaluations conducted in resource-limited settings.
Cost per year of life saved (YLS) was calculated as total cost divided by the estimated number of life-years gained (beyond what would be expected without ICU care). Cost per DALY averted was computed by subtracting DALYs under standard ICU care from the projected DALYs in the ‘no ICU’ scenario (70% higher burden). The total ICU cost (from either perspective) was then divided by the number of DALYs averted to yield the cost per DALY averted.
Implementation of micro costing
Micro-costing was chosen for its precision in evaluating the financial impact of the BSKY, providing a granular analysis of resource allocation and expenditure. The collected data were analysed to determine the cost per life-year gained, providing insights into the programme’s cost per outcome and financial benefits. By assessing costs per survivor and adjusting for life expectancy, the study quantified the economic and health impacts of BSKY on ICU care.
Subgroup and sensitivity analyses
Patients were stratified by age groups (<60 vs. ≥60 yr) and APACHE II severity (15–25 vs. >25) to analyse differences in mortality, length of stay, costs, and DALYs. Formal multi-way sensitivity analyses were not performed; potential variations in drug and consumable costs were acknowledged during interpretation.
Statistical analysis
Data normality was assessed using the Kolmogorov-Smirnov test. Continuous variables were expressed as mean±standard deviation (SD) and compared using Student’s t-test for normally distributed data or Mann-Whitney U-test for non-normal data. Categorical variables were compared using Chi-square tests with Yates’ correction when appropriate. Statistical analyses were performed using IBM SPSS Statistics version 29 (IBM Corp., Armonk, NY, United States), while DALY calculations were conducted using R software version 4.3.1.
Results
Patient selection and characteristics
Hospital records were assessed during the study period, January 2022 to December 2023. Participant flow is depicted in Figure. Men accounted for a slightly higher proportion of admissions, and the mean APACHE II score across the entire cohort was 24.19 (±5.78) ( Table I).
| Parameter | Death (n=383) (Mean±SD/%) | Survived (n=1416) (Mean±SD/%) | P value |
|---|---|---|---|
| Age (yr) | 55.6±17.18 | 57.5±16.15 | 0.053 |
| Gender (male); n (%) | 241 (62.92) | 1178 (64.41) | 0.343 |
| APACHE II (acute physiology and chronic health evaluation II) | 29.6±5.18 | 23.1±4.89 | < 0.001 |
| SOFA (sequential organ failure assessment) | 9.2±2.77 | 5.8±2.45 | < 0.001 |
| Organ failure (number) | 2.8±1.05 | 1.57±0.90 | < 0.001 |
| Nutrition risk in the critically ill (score) | 5.9±1.39 | 4.9±1.26 | < 0.001 |
| Intensive care unit length of stay (d) | 7.5 (1.4–13.66) | 5.5 (1.86–9.06) | <0.001 |
| Hospital length of stay (days) | 11.47 (5.29–17.65) | 8.12 (3.46–12.78) | <0.001 |
| Expenditure | US$ 1814±3655 | US$ 1239±1210 | 0.0026 |
| Comorbidities; n (%) | |||
| Diabetes mellitus | 126 (32.9) | 499 (35.3) | 0.441 |
| Hypertension | 172 (45.0) | 692 (48.9) | 0.198 |
| Chronic kidney disease | 97 (25.4) | 374 (26.4) | 0.731 |
| Chronic obstructive pulmonary disease | 31 (8.1) | 171 (12.1) | 0.037 |
| Any 2 of the above comorbidities | 92 (15.1) | 171 (14.3) | |
| Any 3 of the above comorbidities | 57 (9.4) | 102 (8.6) | |
| All 4 of the above comorbidities | 34 (5.6) | 60 (5) | |
| Number of patients on mechanical ventilation | 433 (71.2) | 672 (56.4) | <0.001 |
| Duration of mechanical ventilation [mean (SD)] | 11.7 (6.9) | 5.1 (3.6) | <0.001 |
| Number of patients on vasopressor | 411 (67.6) | 504 (42.3) | <0.001 |
| Number of patients undergoing renal replacement therapy/dialysis | 396 (65.1) | 687 (57.7) | 0.002 |
Clinical outcomes and mortality
Of the 1,799 patients, 383 (21.3%) died, while 1,416 (78.7%) survived hospital discharge. Table I compares the demographic and clinical characteristics of the survivors and non-survivors. Non-survivors consistently had higher APACHE II scores, SOFA scores, longer ICU stay, and more frequent requirements for mechanical ventilation and vasopressor support. When stratified by age, mean ICU costs per admission were broadly similar in patients younger than 60 years and those aged 60 years or older (Supplementary Table).
Cost per outcome analysis
From the hospital’s perspective, micro costing revealed an average ICU cost of ₹69,381.62 (US$831.28) per patient. Detailed analyses are provided in Table II. Costs were higher among non-survivors than among survivors. Mean BSKY reimbursement – a proxy for the government perspective was also higher for non-survivors. Overall, the cost per life saved (combining these figures) was calculated at ₹ 1,44,366.99 (US$1,729.7) for the entire cohort.
| Cost component/Indicator | Cost INR (US$) | Notes |
|---|---|---|
| Hospital perspective (Micro-costing) | ||
| Human resources | 18,289.38 (219.13) | Consultants, junior doctors, nurses, support staff |
| Infrastructure | 5951.79 (71.31) | Annualised at 3% discount rate |
| Overheads | 740.32 (8.87) | Electricity, water, maintenance, security |
| Drugs and consumables | 44,400.13 (531.97) | Avg. daily INR 7400 ($88.66) × 6 days stay |
| Total hospital cost per patient | 69,381.62 (831.28) | Base micro-costing estimate |
| Survivors | 65,320 (782.6) | Mean cost per survivor |
| Non-survivors | 84,547 (1,013.1) | Higher due to longer stay/severity |
| Age <60 yr | 68,587 (821.7) | Stratified hospital cost |
| Age ≥60 yr | 68,858 (825.0) | Stratified hospital cost |
| Government perspective (BSKY reimbursement) | ||
| Survivors | 1,03,410 (1,239) | Average reimbursement |
| Non-survivors | 151409 (1,814) | Higher reimbursement due to longer ICU care |
| Age <60 yr | 114011 (1,366) | By patient subgroup |
| Age ≥60 yr | 113177 (1,356) | By patient subgroup |
| Cost per outcomes | ||
| Cost per life saved | 144363 (1,729.7) | Whole cohort |
| Cost per DALY averted (overall) | 74944 (897.9) | Below India’s GDP per capita ($2,396) |
| Cost per DALY averted (<60 yr) | 11377 (136.3) | Very cost-effective |
| Cost per DALY averted (≥60 yr) | 103185 (1,236.4) | Cost-effective |
DALY calculations and cost per outcome
Disability-adjusted life years (DALYs) were estimated based on the assumption that 50% of survivors develop post-ICU syndrome (PICS) with a moderate disability weight (0.3) over a five-year period, and that life expectancy at age 60 extends to 75 years. Under a hypothetical ‘no ICU’ comparator—where DALYs were assumed to increase by 70% due to higher mortality and prolonged morbidity—the study population demonstrated a cost per DALY averted of ₹74,941.97 (US$897.90) overall. Stratifying further, younger adults (<60 years) exhibited a notably lower cost per DALY averted ₹11,376.09 (US$136.30), while older individuals (≥60 years) incurred a higher figure ₹1,03,194.40 (US$1,236.40). However, both values remained below India’s GDP per capita threshold [∼₹1,99,978.79 (US$2,396)], indicating that ICU care under BSKY is sustainable across age groups, with an especially pronounced benefit in younger patients ( Table III).
| Group | YLL (years of life lost) | YLD (years with disability) | Total DALY |
|---|---|---|---|
| Study population | 7,440 | 1,062 | 8,502 |
| Age ≤ 60 yr | 6,816 | 568.5 | 7,384.5 |
| Age > 60 yr | 624 | 492.75 | 1,116.75 |
| APACHE II ≤ 25 | 1,623 | 757.5 | 2,380.5 |
| APACHE II > 25 | 5,817 | 304.5 | 6,121.5 |
Discussion
This study assessed the financial and clinical outcomes of intensive care provision under BSKY for critically ill patients with APACHE II scores ≥15. The findings suggest that BSKY alleviates financial burdens while achieving favourable cost per outcome ratios across age groups. The observed mortality rate aligned with the severity of illness, and despite longer ICU stays among non-survivors, the economic burden remained manageable under BSKY coverage. These results may inform the development of comprehensive critical care coverage within universal health coverage frameworks, particularly in regions with high poverty and health inequities.
Our average hospital expenditure of ₹69,381.62 (US$831.28) per patient was lower than previously reported Indian ICU costs, which documented per-survivor costs ranging from ₹74,677 (US$894.76) to ₹1,32,015 ($1,581.52), with total ICU costs from ₹97,156 ($1,163.92) to ₹1,80,588 (US$2,163.72).4-8 This difference may reflect BSKY’s reimbursement structure and institutional efficiencies. The cost per life saved of ₹1,44,363 (US$1,729.70) showed minimal variation across age groups. Our DALY-based analysis revealed costs of ₹74,944 (US$897.90) per DALY averted overall, with ₹11,377 (US$136.30) for younger patients and ₹1,03,185 (US$1,236.40) for older patients. Both figures fall below India’s GDP per capita of ₹2,00,000 (∼US$2,396), consistent with evidence from Bosnia and Herzegovina, Tanzania, and other LMICs.12,13 The lower cost per DALY among younger patients may reflect their greater remaining life expectancy. International evidence from Ghana10,11 and South Africa9 showed similar benefits from health insurance schemes, supporting our findings that State-level schemes can deliver ICU services with favourable cost per outcome ratios. When stratified by age, mean ICU costs per admission were similar for patients <60 years and those ≥60 years.3-5,7,8 However, because survivors under 60 years contributed a larger pool of additional active life years (average 15.2 years per survivor; 10,773 life years gained in total), the DALYs averted and years of life saved were disproportionately concentrated in this younger group. In contrast, older survivors accrued fewer additional life years by design of the DALY framework26, leading to a higher apparent cost per DALY averted in the elderly despite comparable per-patient expenditure. This pattern reflects the interaction between age, remaining life expectancy, and the DALY metric rather than major differences in the intensity or cost of ICU care across age groups.6,12
Study strengths include the large sample size, two-year duration, dual-perspective costing, and use of DALYs based on WHO-CHOICE methods. Restricting analysis to high-severity patients (APACHE II ≥15) ensured evaluation of resource-intensive ICU care. However, the single-centre design limits generalisability, as ICU costs vary across hospitals and regions; multicentre studies with a larger sample size would provide more robust evidence. Wide variability in ICU length of stay and BSKY reimbursement indicates heterogeneous patient trajectories, reducing the precision of cost estimates. The absence of a non-BSKY control group prevented comparison with alternative financing models. Long-term outcomes, indirect costs, and post-discharge utilisation were not captured, and formal sensitivity analyses were not performed. Operational sustainability remains uncertain because current costs reflect subsidised infrastructure, raising concerns about whether reimbursements alone can support ICU services long term.26,27 DALYs were used instead of QALYs because the study followed the WHO-CHOICE framework26 and DALYs could be estimated from available retrospective data, whereas QALYs would have required prospective utility measurement and extended follow up.
These findings suggest that BSKY appears to offer economically viable ICU care for vulnerable populations, aided by flexible eligibility criteria that reduce financial barriers. Ensuring adequate reimbursement will be essential for long-term sustainability. Key policy priorities include periodic review of reimbursement rates, evaluation of similar models in other States, quality-monitoring mechanisms, and systems for long-term outcome tracking. These results also support continued investment in ICU infrastructure and workforce training, as cost-per-outcome patterns suggest value across age groups.
Author contributions
SBM: Conceived and designed the study; SS, SC: Data collection and compilation; SS: Statistical analysis; SC, SS: Manuscript writing. All authors have read and approved the final printed version of the manuscript.
Financial support and sponsorship
None.
Conflicts of Interest
None.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation
The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.
References
- Direct costs of chronic obstructive pulmonary disease among managed care patients. Int J Chron Obstruct Pulmon Dis.. 2010;5:341-9.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Thirty years of national health insurance in South Korea: Lessons for achieving universal health care coverage. Health Policy Plan.. 2009;24:63-71.
- [CrossRef] [PubMed] [Google Scholar]
- Direct Medical costs of tetanus, dengue, and sepsis patients in an intensive care unit in Vietnam. Front Public Health.. 2022;10:893200.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Study of length of stay and average cost of treatment in Medicine Intensive Care Unit at a tertiary care center. J Health Res Rev.. 2017;4:24-9.
- [Google Scholar]
- Economic analysis of costs associated with a Respiratory Intensive Care Unit in a tertiary care teaching hospital in Northern India. Indian J Crit Care Med.. 2013;17:76-81.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Cost-utility in medical intensive care patients: Rationalizing ongoing care and timing of discharge. Ann Am Thorac Soc.. 2015;12:1058-1065.
- [CrossRef] [PubMed] [Google Scholar]
- How much does it cost for a surgical ICU bed in a public hospital in India. Risk Manag Healthc Policy.. 2021;14:4149-54.
- [CrossRef] [PubMed] [Google Scholar]
- A prospective audit of costs of intensive care in cancer patients in India. Indian J Crit Care Med.. 2013;17:292-7.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Health and economic gains: what is at stake in South Africa’s health reform? World Med Health Policy. 2010. ;2:25-45.
- [Google Scholar]
- Evaluating the impact of the national health insurance scheme of Ghana on out of pocket expenditures: A systematic review. BMC Health Serv Res. 2018;18:426.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Does insurance protect individuals from catastrophic payments for surgical care? Analysis of Ghana’s National Health Insurance Scheme. BMC Health Serv Res.. 2020;20:45.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Cost effectiveness of intensive care in a low-resource setting: a prospective cohort. World J Crit Care Med.. 2016;5:150-164.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Cost effectiveness of strategies for caring for critically ill patients with COVID-19 in Tanzania. Pharmacoecon Open.. 2023;7:537-52.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Rashtriya Swasthya Bima Yojana (RSBY) and outpatient coverage. J Family Med Prim Care.. 2020;9:459-64.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Evolution of Government-funded health insurance for universal health coverage in India. Lancet Reg Health Southeast Asia.. 2023;13:100180.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Promoting universal financial protection: evidence from the RSBY in Gujarat, India. Health Res Policy Syst.. 2013;11:29.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Public health insurance coverage in India before and after PM-JAY: Repeated cross-sectional analysis of national survey data. BMJ Glob Health.. 2023;8:e012725.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- AB-PMJAY after four years: Impact on quality of inpatient care and financial protection. BMC Health Serv Res.. 2024;24:919.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Applying the ‘candidacy’ model to understand access to nutrition, food and health services in LMICs: A qualitative study in Odisha, India. Food Secur.. 2023;15:649-60.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Adivasis, preferential policy and the state in Odisha. Social Change.. 2019;49:199-215.
- [CrossRef] [Google Scholar]
- Contemporary universal health coverage in India: the case of Odisha. Risk Manag Healthc Policy.. 2023;16:1131-43.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- National Health Mission, Department of Health Family Welfare, Odisha. Biju Swasthya Kalyan Yojana. Available from: http://www.nrhmorissa. gov.in/writereaddata/Upload/Documents/BSKY.pdf, accessed on June 18, 2020.
- APACHE II: A severity of disease classification system. Crit Care Med.. 1985;13:818-29.
- [PubMed] [Google Scholar]
- Calculating disability-adjusted life years to quantify burden of disease. Int J Public Health.. 2014;59:565-9.
- [CrossRef] [PubMed] [Google Scholar]
- Calculating and presenting disability adjusted life years (DALYs) in cost-effectiveness analysis. Health Policy Plan.. 2001;16:326-31.
- [CrossRef] [PubMed] [Google Scholar]
- Methods for economic evaluation of health interventions: An update from WHO-CHOICE. Int J Health Policy Manag.. 2021;10:673-77.
- [CrossRef] [PubMed] [PubMed Central] [Google Scholar]
- Survival and quality of life after long-term intensive care stay. Thorac Cardiovasc Surg.. 2002;50:95-9.
- [CrossRef] [PubMed] [Google Scholar]