Dataset Information

Health financing strategies to reduce out-of-pocket burden in India: a comparative study of three states.

ABSTRACT:

Background

To achieve the Sustainable Development Goals, Indian States have implemented different strategies to arrest high out-of-pocket expenditure (OOPE) and to increase equity into healthcare system. Tamil Nadu (TN) and Rajasthan have implemented free medicine scheme in all public hospitals and West Bengal (WB) has devised Fair Price Medicine Shop (FPMS) scheme, a public-private-partnership model in the state. In this background, the objectives of the paper are to - 1. Study the utilization pattern of public in-patient care facilities for the states, 2. Examine the effectiveness of the strategies adopted by the states to arrest high OOPE and 3. Analyze the extent of equity in public in-patient care services in the states.

Methods

National Sample Survey (71st and 60th round) data, Detailed Demand for Grants of the state governments and the National Rural/Urban Health Mission data have been used for the study. Exploratory data analysis and benefit incidence analysis have been applied to estimate the utilization, OOPE and extend of equity in the states.

Results

The results show that overall utilization of public facilities in TN and Rajasthan has increased substantially; whereas, utilization of public facility has decreased in WB even among the poorest. In addition, OOPE for both medical and medicine is the highest in WB among three states for public sector hospitalizations. Surprisingly, OOPE on medicine is the highest for the poorest class of WB. Analysis showed that the mismatch between actual need and FPMS drug-list has led to high OOPE in the state. Overall, benefit incidence of public subsidy is the highest among the poorest class in all the states. However, geographical sector-wise inequity in public subsidy distribution persists in the states. Analysis of cost of inpatient care shows that TN provides the maximum subsidy for hospitalization and WB provides the minimum. An inverse relationship between utilization of inpatient care and public subsidy has been observed from the analysis.

Conclusion

In conclusion we could say that TN & Rajasthan have successfully implemented their health financing strategies to reduce the health expenditure burden. However, policy-level changes are required to improve the situation in WB.

SUBMITTER: Bose M

PROVIDER: S-EPMC6215655 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Publications

Health financing strategies to reduce out-of-pocket burden in India: a comparative study of three states.

Bose Montu M Dutta Arijita A

BMC health services research 20181103 1

<h4>Background</h4>To achieve the Sustainable Development Goals, Indian States have implemented different strategies to arrest high out-of-pocket expenditure (OOPE) and to increase equity into healthcare system. Tamil Nadu (TN) and Rajasthan have implemented free medicine scheme in all public hospitals and West Bengal (WB) has devised Fair Price Medicine Shop (FPMS) scheme, a public-private-partnership model in the state. In this background, the objectives of the paper are to - 1. Study the util ...[more]

PMID: 30390701

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Project description:Rising non-communicable diseases (NCDs) coupled with increasing injuries have resulted in a significant increase in health spending in India. While out-of-pocket expenditure remains the major source of health care financing in India (two-thirds of the total health spending), the financial burden varies enormously across diseases and by the economic well-being of the households. Though prior studies have examined the variation in disease pattern, little is known about the financial risk to the families by type of diseases in India. In this context, the present study examines disease-specific out-of-pocket expenditure (OOPE), catastrophic health expenditure (CHE) and distress health financing.Unit data from the 71st round of the National Sample Survey Organization (2014) was used for this study. OOPE is defined as health spending on hospitalization net of reimbursement, and CHE is defined as household health spending exceeding 10% of household consumption expenditure. Distress health financing is defined as a situation when a household has to borrow money or sell their property/assets or when it gets contributions from friends/relatives to meet its health care expenses. OOPE was estimated for 16 selected diseases and across three broad categories- communicable diseases, NCDs and injuries. Multivariate logistic regression was used to understand the determinants of distress financing and CHE.Mean OOPE on hospitalization was INR 19,210 and was the highest for cancer (INR 57,232) followed by heart diseases (INR 40,947). About 28% of the households incurred CHE and faced distress financing. Among all the diseases, cancer caused the highest CHE (79%) and distress financing (43%). More than one-third of the inpatients reported distressed financing for heart diseases, neurological disorders, genito urinary problems, musculoskeletal diseases, gastro-intestinal problems and injuries. The likelihood of incurring distress financing was 3.2 times higher for those hospitalized for cancer (OR 3.23; 95% CI: 2.62-3.99) and 2.6 times for tuberculosis patients (OR 2.61; 95% CI: 2.06-3.31). A large proportion of households who had reported distress financing also incurred CHE.Free treatment for cancer and heart diseases is recommended for the vulnerable sections of the society. Risk-pooling and social security mechanisms based on contributions from both households as well as the central and state governments can reduce the financial burden of diseases and avert households from distress health financing.

Project description:ImportanceHigh out-of-pocket expenditure (OOPE) on health in India may limit achieving universal health coverage. A clear insight on the components of health expenditure may be necessary to make allocative decisions to reduce OOPE, and such details by sociodemographic group and state have not been studied in India.ObjectiveTo analyze the relative contribution of drugs, diagnostic tests, doctor and surgeon fees, and expenditure on other medical services and nonmedical health-related services, such as transport, lodging, and food, by sociodemographic characteristics of patients, geography, and type of illness.Design, setting, and participantsA population-based cross-sectional health consumption survey conducted by the National Sample Survey Organisation in 2018 was analyzed in this cross-sectional study. Respondents who provided complete information on costs of medicine, doctors, diagnostics tests, other medical costs, and nonmedical costs were selected. Data were analyzed from August through September 2021.Main outcomes and measuresMean and median share of components (ie, medicine, diagnostic tests, doctor fees, other medical costs, and nonmedical costs) in total health care expenditure and income were calculated. Bivariate survey-weighted mean (with 95% CI) and median (IQR) expenditures were calculated for each component across sociodemographic characteristics. The proportion of total expenditure and income contributed by each cost was calculated for each individual. Mean and median were then used to summarize such proportions at the population level. The association between state net domestic product per capita and component share of each health care service was graphically explored.ResultsHealth expenditure details were analyzed for 43 781 individuals for inpatient costs (27 272 [64.3%] women; 26 830 individuals aged 25-64 years [59.9%]) and 8914 individuals for outpatient costs (4176 [48.2%] women; 4901 individuals aged 25-64 years [54.2%]); most individuals were rural residents (24 106 inpatients [67.0]; 4591 outpatients [63.9%]). Medicines accounted for a mean of 29.1% (95% CI, 28.9%-29.2%) of OOPE among inpatients and 60.3% (95% CI, 59.7%-60.9%) of OOPE among outpatients. Doctor consultation charges were a mean of 15.3% (95% CI, 15.1%-15.4%) of OOPE among inpatients and 12.4% (95% CI, 12.1%-12.6%) of OOPE among outpatients. Diagnostic tests accounted for a mean of 12.3% (95% CI, 12.2%-12.4%) of OOPE for inpatient and 9.2% (95% CI, 8.9%-9.5%) of OOPE for outpatient services. Nonmedical costs accounted for a mean of 23.6% (95% CI, 23.3%-23.8%) of OOPE among inpatients and 14.6% (95% CI, 14.1%-15.1%) of OOPE among outpatients. Mean share of OOPE from doctor consultations and diagnostic test charges increased with socioeconomic status. For example, for the lowest vs highest monthly per capita income quintile among inpatients, doctor consultations accounted for 11.5% (95% CI, 11.1%-11.8%) vs 21.2% (95% CI, 20.8%-21.6%), and diagnostic test charges accounted for 10.9% (95% CI, 10.6%-11.1%) vs 14.3% (95% CI, 14.0%-14.5%). The proportion of mean annual health expenditure from mean annual income was $299 of $1918 (15.6%) for inpatient and $391 of $1788 (21.9%) for outpatient services.Conclusions and relevanceThis study found that nonmedical costs were significant, share of total health care OOPE from doctor consultation and diagnostic test charges increased with socioeconomic status, and annual cost as a proportion of annual income was lower for inpatient than outpatient services.

Project description:IntroductionOut-of-pocket (OOP) costs for medical and surgical care can result in substantial financial burden for patients and families. Relatively little is known regarding OOP costs for commercially insured patients receiving orthopaedic surgery. The aim of this study is to analyze the trends in OOP costs for common, elective orthopaedic surgeries performed in the hospital inpatient setting.MethodsThis study used an employer-sponsored insurance claims database to analyze billing data of commercially insured patients who underwent elective orthopaedic surgery between 2014 and 2019. Patients who received single-level anterior cervical diskectomy and fusion (ACDF), single-level posterior lumbar fusion (PLF), total knee arthroplasty (TKA), and total hip arthroplasty (THA) were identified. OOP costs associated with the surgical episode were calculated as the sum of deductible payments, copayments, and coinsurance. Monetary data were adjusted to 2019 dollars. General linear regression, Wilcoxon-Mann-Whitney, and Kruskal-Wallis tests were used for analysis, as appropriate.ResultsIn total, 10,225 ACDF, 28,841 PLF, 70,815 THA, and 108,940 TKA patients were analyzed. Most patients in our study sample had preferred provider organization insurance plans (ACDF 70.3%, PLF 66.9%, THA 66.2%, and TKA 67.0%). The mean OOP costs for patients, by procedure, were as follows: ACDF $3,180 (SD = 2,495), PLF $3,166 (SD = 2,529), THA $2,884 (SD = 2,100), and TKA $2,733 (SD = 1,994). Total OOP costs increased significantly from 2014 to 2019 for all procedures (P < 0.0001). Among the insurance plans examined, patients with high-deductible health plans had the highest episodic OOP costs. The ratio of patient contribution (OOP costs) to total insurer contribution (payments from insurers to providers) was 0.07 for ACDF, 0.04 for PLF, 0.07 for THA, and 0.07 for TKA.ConclusionAmong commercially insured patients who underwent elective spinal fusion and major lower extremity joint arthroplasty surgery, OOP costs increased from 2014 to 2019. The OOP costs for elective orthopaedic surgery represent a substantial and increasing financial burden for patients.

Project description:Abstract Background Atopic dermatitis (AD) is associated with elevated financial costs, including out‐of‐pocket (OOP) expenses. Yet, the full burden of OOP expenses in children with AD is poorly understood. Objectives We sought to characterise categories, impact, and associations of caregiver‐reported OOP AD healthcare expenses for US children. Methods An online survey was administered to National Eczema Association members (N = 113 502). Inclusion criteria (US resident; respondent age ≥18; self or caregiver report of AD diagnosis) was met by 77.3% (1118/1447) of those who completed the questionnaire. Results Caregivers of children (<18 years) with AD reported increased healthcare provider (HCP) visits, comorbid food allergy, cutaneous infections, and topical antimicrobial use (p < 0.005 for all), and increased OOP expenses for hospitalisation, emergency room visits, emollients, hygiene/bathing products, childcare, and specialised cleaning products, and clothing/bedding (p < 0.05 for all) compared to adults with AD. Children with AD had increased median total yearly OOP expenditures ($860 vs. $500, p = 0.002) and were more likely to spend ≥$1000 OOP per year (48.9% vs. 40.0%, p = 0.03). In children, yearly OOP expenses ≥$1000 were associated with increased AD severity, flares, HCP visits, prescription polypharmacy, and step‐up therapy use (p < 0.005 for all) compared with adults. Predictors of harmful financial impact among children included black race (adjusted OR [95% confidence interval]: 3.86 [1.66–8.98] p = 0.002) and ≥$1000 annual OOP expenditures (6.98 [3.46–14.08], p < 0.0001). Conclusion Children with AD have unique and increased OOP expenses that are associated with significant disease burden. Strategies are needed to reduce OOP costs and improve clinical outcomes in children with AD. Atopic dermatitis (AD) is associated with significant financial costs, including increased out‐of‐pocket (OOP) expenses. OOP healthcare expenses for AD are elevated for caregivers of children and are associated with increased disease activity. Healthcare providers should be mindful of this OOP financial burden strive to maximise clinical outcomes while minimising financial impact.

Project description:ImportanceMedicare beneficiaries with cancer are at risk for financial hardship given increasingly expensive cancer care and significant cost sharing by beneficiaries.ObjectivesTo measure out-of-pocket (OOP) costs incurred by Medicare beneficiaries with cancer and identify which factors and services contribute to high OOP costs.Design, setting, and participantsWe prospectively collected survey data from 18 166 community-dwelling Medicare beneficiaries, including 1409 individuals who were diagnosed with cancer during the study period, who participated in the January 1, 2002, to December 31, 2012, waves of the Health and Retirement Study, a nationally representative panel study of US residents older than 50 years. Data analysis was performed from July 1, 2014, to June 30, 2015.Main outcomes and measuresOut-of-pocket medical spending and financial burden (OOP expenditures divided by total household income).ResultsAmong the 1409 participants (median age, 73 years [interquartile range, 69-79 years]; 46.4% female and 53.6% male) diagnosed with cancer during the study period, the type of supplementary insurance was significantly associated with mean annual OOP costs incurred after a cancer diagnosis ($2116 among those insured by Medicaid, $2367 among those insured by the Veterans Health Administration, $5976 among those insured by a Medicare health maintenance organization, $5492 among those with employer-sponsored insurance, $5670 among those with Medigap insurance coverage, and $8115 among those insured by traditional fee-for-service Medicare but without supplemental insurance coverage). A new diagnosis of cancer or common chronic noncancer condition was associated with increased odds of incurring costs in the highest decile of OOP expenditures (cancer: adjusted odds ratio, 1.86; 95% CI, 1.55-2.23; P < .001; chronic noncancer condition: adjusted odds ratio, 1.82; 95% CI, 1.69-1.97; P < .001). Beneficiaries with a new cancer diagnosis and Medicare alone incurred OOP expenditures that were a mean of 23.7% of their household income; 10% of these beneficiaries incurred OOP expenditures that were 63.1% of their household income. Among the 10% of beneficiaries with cancer who incurred the highest OOP costs, hospitalization contributed to 41.6% of total OOP costs.Conclusions and relevanceMedicare beneficiaries without supplemental insurance incur significant OOP costs following a diagnosis of cancer. Costs associated with hospitalization may be a primary contributor to these high OOP costs. Medicare reform proposals that restructure the benefit design for hospital-based services and incorporate an OOP maximum may help alleviate financial burden, as can interventions that reduce hospitalization in this population.

Dataset Information

Health financing strategies to reduce out-of-pocket burden in India: a comparative study of three states.

Background

Methods

Results

Conclusion

Publications

Health financing strategies to reduce out-of-pocket burden in India: a comparative study of three states.

Similar Datasets

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