Health-related quality of life and its determinants among cancer patients: evidence from 12,148 patients of Indian database.

BACKGROUND: Cancer survivors experience a decrement in health-related quality of life (HRQoL) resulting from the disease as well as adverse effects of therapy. We evaluated the HRQoL of cancer patients, stratified by primary cancer site, stage, treatment response and associated adverse events, along with its determinants. METHODS: Data were collected from 12,148 patients, sampled from seven purposively chosen leading cancer hospitals in India, to elicit HRQoL using the EuroQol questionnaire comprising of 5-dimensions and 5-levels (EQ-5D-5L). Multiple linear regression was used to determine the association between HRQoL and various socio-demographic as well as clinical characteristics. RESULTS: Majority outpatients (78.4%) and inpatients (81.2%) had solid cancers. The disease was found to be more prevalent among outpatients (37.5%) and inpatients (40.5%) aged 45-60 years and females (49.3-58.3%). Most patients were found to be in stage III (40-40.6%) or stage IV (29.4-37.3%) at the time of recruitment. The mean EQ-5D-5 L utility score was significantly higher among outpatients [0.630 (95% CI: 0.623, 0.637)] as compared to inpatients [0.553 (95% CI: 0.539, 0.567)]. The HRQoL decreased with advancing cancer stage among both inpatients and outpatients, respectively [stage IV: (0.516 & 0.557); stage III (0.609 & 0.689); stage II (0.677 & 0.713); stage I (0.638 & 0.748), p value < 0.001]. The outpatients on hormone therapy (B = 0.076) showed significantly better HRQoL in comparison to patients on chemotherapy. However, palliative care (B=-0.137) and surgery (B=-0.110) were found to be associated with significantly with poorer HRQoL paralleled to chemotherapy. The utility scores among outpatients ranged from 0.305 (bone cancer) to 0.782 (Leukemia). Among hospitalized cases, the utility score was lowest for multiple myeloma (0.255) and highest for testicular cancer (0.771). CONCLUSION: Older age, lower educational status, chemotherapy, palliative care and surgery, advanced cancer stage and progressive disease were associated with poor HRQoL. Our study findings will be useful in optimising patient care, formulating individualized treatment plan, improving compliance and follow-up.

Cost-effectiveness of population-based screening for oral cancer in India: an economic modelling study.

Background: Oral cancer screening reduces mortality associated with oral cancer. The current study evaluated the cost-effectiveness of commonly used screening techniques, namely conventional oral examination (COE), toluidine blue staining (TBS), oral cytology (OC), and light-based detection (LBD) in the Indian scenario. Methods: The study used a Markov modelling approach to estimate the cost and health outcomes of four different approaches (COE, TBS, OC, and LBD) for screening oral cancer over time from a societal perspective. The discount rate was assumed as 3%. The outcomes estimated were oral cancer incident cases, deaths averted, and quality-adjusted life years (QALYs). To address the high burden of risk factors (tobacco and/or alcohol) in India, two Markov models were developed: Model A adopted a mass-screening strategy, whereas Model B adopted a high-risk screening strategy versus no screening. Probabilistic sensitivity analysis (PSA) was undertaken to address any parameter uncertainty. Findings: Mass-screening using LBD at three years had the least incident cases (3271.68) and averted the maximum number of oral cancer deaths (459.76). High-risk screening using COE at ten years interval incurred the least lifetime cost of 2,292,816.21 US$ (182,794,468.26 INR). The high-risk strategies (US$/QALY), namely COE 5 years (-29.21), COE 10 years (-90.68), TBS 10 years (-60.54), and LBD 10 years (-13.51), were dominant over no-screening. Interpretation: The most cost-saving approach was the conventional oral examination at an interval of 10 years for oral screening in high-risk populations above 30 years of age. Funding: Department of Health Research, Ministry of Health & Family Welfare, Government of India.

Financial toxicity of cancer treatment in India: towards closing the cancer care gap.

Background: The rising economic burden of cancer on patients is an important determinant of access to treatment initiation and adherence in India. Several publicly financed health insurance (PFHI) schemes have been launched in India, with treatment for cancer as an explicit inclusion in the health benefit packages (HBPs). Although, financial toxicity is widely acknowledged to be a potential consequence of costly cancer treatment, little is known about its prevalence and determinants among the Indian population. There is a need to determine the optimal strategy for clinicians and cancer care centers to address the issue of high costs of care in order to minimize the financial toxicity, promote access to high value care and reduce health disparities. Methods: A total of 12,148 cancer patients were recruited at seven purposively selected cancer centres in India, to assess the out-of-pocket expenditure (OOPE) and financial toxicity among cancer patients. Mean OOPE incurred for outpatient treatment and hospitalization, was estimated by cancer site, stage, type of treatment and socio-demographic characteristics. Economic impact of cancer care on household financial risk protection was assessed using standard indicators of catastrophic health expenditures (CHE) and impoverishment, along with the determinants using logistic regression. Results: Mean direct OOPE per outpatient consultation and per episode of hospitalization was estimated as ₹8,053 (US$ 101) and ₹39,085 (US$ 492) respectively. Per patient annual direct OOPE incurred on cancer treatment was estimated as ₹331,177 (US$ 4,171). Diagnostics (36.4%) and medicines (45%) are major contributors of OOPE for outpatient treatment and hospitalization, respectively. The overall prevalence of CHE and impoverishment was higher among patients seeking outpatient treatment (80.4% and 67%, respectively) than hospitalization (29.8% and 17.2%, respectively). The odds of incurring CHE was 7.4 times higher among poorer patients [Adjusted Odds Ratio (AOR): 7.414] than richest. Enrolment in PM-JAY (CHE AOR = 0.426, and impoverishment AOR = 0.395) or a state sponsored scheme (CHE AOR = 0.304 and impoverishment AOR = 0.371) resulted in a significant reduction in CHE and impoverishment for an episode of hospitalization. The prevalence of CHE and impoverishment was significantly higher with hospitalization in private hospitals and longer duration of hospital stay (p < 0.001). The extent of CHE and impoverishment due to direct costs incurred on outpatient treatment increased from 83% to 99.7% and, 63.9% to 97.1% after considering both direct and indirect costs borne by the patient and caregivers, respectively. In case of hospitalization, the extent of CHE increased from 23.6% (direct cost) to 59.4% (direct+ indirect costs) and impoverishment increased from 14.1% (direct cost) to 27% due to both direct and indirect cost of cancer treatment. Conclusion: There is high economic burden on patients and their families due to cancer treatment. The increase in population and cancer services coverage of PFHI schemes, creating prepayment mechanisms like E-RUPI for outpatient diagnostic and staging services, and strengthening public hospitals can potentially reduce the financial burden among cancer patients in India. The disaggregated OOPE estimates could be useful input for future health technology analyses to determine cost-effective treatment strategies.

Cost of Surgical Care at Public Sector District Hospitals in India: Implications for Universal Health Coverage and Publicly Financed Health Insurance Schemes.

BACKGROUND: In low- and middle-income countries (LMICs), provisioning for surgical care is a public health priority. Ayushman Bharat Pradhan Mantri-Jan Aarogya Yojana (AB PM-JAY) is India's largest national insurance scheme providing free surgical and medical care. In this paper, we present the costs of surgical health benefit packages (HBPs) for secondary care in public district hospitals. METHODS: The costs were estimated using mixed (top-down and bottom-up) micro-costing methods. In phase II of the Costing of Health Services in India (CHSI) study, data were collected from a sample of 27 district hospitals from nine states of India. The district hospitals were selected using stratified random sampling based on the district's composite development score. We estimated unit costs for individual services-outpatient (OP) visit, per bed-day in inpatient (IP) and intensive care unit (ICU) stays, and surgical procedures. Together, this was used to estimate the cost of 250 AB PM-JAY HBPs. RESULTS: At the current level of utilization, the mean cost per OP consultation varied from US$4.10 to US$2.60 among different surgical specialities. The mean unit cost per IP bed-day ranged from US$13.40 to US$35.60. For the ICU, the mean unit cost per bed-day was US$74. Further, the unit cost of HBPs varied from US$564 for bone tumour excision to US$49 for lid tear repair. CONCLUSIONS: Data on the cost of delivering surgical care at the level of district hospitals is of critical value for evidence-based policymaking, price-setting for surgical care and planning to strengthen the availability of high quality and cost-effective surgical care in district hospitals.

An economic evaluation of implementing a decentralized dengue screening intervention under the National Vector Borne Disease Control Programme in Tamil Nadu, South India.

BACKGROUND: Lack of effective early screening is a major obstacle for reducing the fatality rate and disease burden of dengue. In light of this, the government of Tamil Nadu has adopted a decentralized dengue screening strategy at the primary healthcare (PHC) facilities using blood platelet count. Our objective was to determine the cost-effectiveness of a decentralized screening strategy for dengue at PHC facilities compared with the current strategy at the tertiary health facility (THC) level. METHODS: Decision tree analysis followed a hypothetical cohort of 1000 suspected dengue cases entering the model. The cost-effectiveness analysis was performed at a 3% discount rate for the proposed and current strategy. The outcomes are expressed in incremental cost-effectiveness ratios (ICERs) per quality-adjusted life years gained. One-way sensitivity analysis and probabilistic sensitivity analysis were done to check the uncertainty in the outcome. RESULTS: The proposed strategy was found to be cost-saving and ICER was estimated to be -41 197. PSA showed that the proposed strategy had a 0.84 probability of being an economically dominant strategy. CONCLUSIONS: The proposed strategy is cost-saving, however, it is recommended to consider optimal population coverage, costs to economic human resources and collateral benefits of equipment.

Development of National Cancer Database for Cost and Quality of Life (CaDCQoL) in India: a protocol.

INTRODUCTION: The rising economic burden of cancer on healthcare system and patients in India has led to the increased demand for evidence in order to inform policy decisions such as drug price regulation, setting reimbursement package rates under publicly financed health insurance schemes and prioritising available resources to maximise value of investments in health. Economic evaluations are an integral component of this important evidence. Lack of existing evidence on healthcare costs and health-related quality of life (HRQOL) makes conducting economic evaluations a very challenging task. Therefore, it is imperative to develop a national database for health expenditure and HRQOL for cancer. METHODS AND ANALYSIS: The present study proposes to develop a National Cancer Database for Cost and Quality of Life (CaDCQoL) in India. The healthcare costs will be estimated using a patient perspective. A cross-sectional study will be conducted to assess the direct out-of-pocket expenditure (OOPE), indirect cost and HRQOL among cancer patients who will be recruited at seven leading cancer centres from six states in India. Mean OOPE and HRQOL scores will be estimated by cancer site, stage of disease and type of treatment. Economic impact of cancer care on household financial risk protection will be assessed by estimating prevalence of catastrophic health expenditures and impoverishment. The national database would serve as a unique open access data repository to derive estimates of cancer-related OOPE and HRQOL. These estimates would be useful in conducting future cost-effectiveness analyses of management strategies for value-based cancer care. ETHICS AND DISSEMINATION: Approval was granted by Institutional Ethics Committee vide letter no. PGI/IEC-03/2020-1565 of Post Graduate Institute of Medical Education and Research, Chandigarh, India. The study results will be published in peer-reviewed journals and presented to the policymakers at national level.

Translating Research to Policy: Setting Provider Payment Rates for Strategic Purchasing under India's National Publicly Financed Health Insurance Scheme.

BACKGROUND: In 2018, the Government of India launched Ayushman Bharat Pradhan Mantri-Jan Aarogya Yojana (AB PM-JAY), a large tax-funded health insurance scheme. In this paper, we present findings of the Costing of Health Services in India (CHSI) study, describe the process of use of cost evidence for price-setting under AB PM-JAY, and estimate its fiscal impact. METHODS: Reference costs were generated from the first phase of CHSI study, which sampled 11 tertiary public hospitals from 11 Indian states. Cost for Health Benefit Packages (HBPs) was estimated using mixed (top-down and bottom-up) micro-costing methods. The process adopted for price-setting under AB PM-JAY was observed. The cost of each HBP was compared with AB PM-JAY prices before and after the revision, and the budgetary impact of this revision in prices was estimated. FINDINGS: Following the CHSI study evidence and price consultations, 61% of AB PM-JAY HBP prices were increased while 18% saw a decline in the prices. In absolute terms, the mean increase in HBP price was ₹14,000 (₹450-₹1,65,000) and a mean decline of ₹6,356 (₹200-₹74,500) was observed. Nearly 42% of the total HBPs, in 2018, had a price that was less than 50% of the true cost, which declined to 20% in 2019. The evidence-informed revision of HBP prices is estimated to have a minimal fiscal impact (0.7%) on the AB PM-JAY claims pay-out. INTERPRETATION: Evidence-informed price-setting helped to reduce wide disparities in cost and price, as well as aligning incentives towards broader health system goals. Such strategic purchasing and price-setting requires the creation of systems of generating evidence on the cost of health services. Further research is recommended to develop a cost-function to study changes in cost with variations in time, region, prices, skill-mix and other factors.