The Financial Burden of Medical Spending

Abramowitz, Joelle; O’Hara, Brett

doi:10.1177/1077558714563173

Cited by 10 publications

(2 citation statements)

References 9 publications

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“…Wang et al , 2015; Q. Wang et al , 2015), loss of a spouse (Rolden et al , 2014), distribution of illness conditions (Song et al , 2013) and out-of-pocket spending caps (Abramowitz and O’Hara, 2015; Riggs et al , 2015).…”

Section: Introductionmentioning

confidence: 99%

Applying GRA to analyze influencing factors of patients’ financial burden

Liao

Zhong

et al. 2019

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Purpose The purpose of this paper is to analyze the influencing factors of patients’ financial burden through a case study of hospital on public‒private partnerships (PPP) model (Chaonan Minsheng Hospital of Guangdong Province) and provide some useful information to policymakers for better development of hospitals on PPP model. Design/methodology/approach There are total six indicators that are defined as patients’ financial burden, basing on the policy of “indicators of medical quality management and control on the third level large general hospital (2011 edition),” issued by Chinese Government. In total, 23 potentially influencing factors of patients’ financial burden for hospital on PPP model were chosen from the above policy. The five-year (2007‒2011) data for the above 29 indicators come from statistic department of hospital on PPP model. Grey relational analysis (GRA) was applied to analyze the influencing factors of patients’ financial burden for hospital on PPP model. Findings A clear rank of influencing factors of patients’ financial burden is obtained and suggestions are provided from results of GRA, which provide reference for policymakers of hospital on PPP model. The five main influencing factors of patients’ financial burden for hospital on PPP model, in sequence, are rescuing critical ill patients on emergency, rescuing critical ill inpatients, inpatient bed occupancy rate, working days per bed and medical building area. Originality/value The study on the influencing factors of patients’ financial burden for hospital on PPP model not only provides decision-making for policymaker of hospital and controlling of medical expenditure but also contributes to release patients’ financial burden for hospitals on PPP model.

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Section: Introductionmentioning

confidence: 99%

Applying GRA to analyze influencing factors of patients’ financial burden

Liao

Zhong

et al. 2019

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“…The Current Population Survey Annual Social and Economic Supplement (CPS ASEC) is widely used as a source of information on the nation’s health insurance coverage and medical expenditures (Berchick et al, 2019). Since the CPS ASEC introduced three questions on out-of-pocket medical expenditures in 2011, these data have been extensively used to study the affordability of care (Abramowitz & O’Hara, 2015), the effects of Medicaid expansion on out-of-pocket medical expenditures (Abramowitz, 2020), and the role of medical expenses in exacerbating inequality (Christopher et al, 2018).…”

mentioning

confidence: 99%

Out-of-Pocket Medical Expenditures in the Redesigned Current Population Survey: Evaluating Improvements to Data Processing

Jackson,

Keisler-Starkey

2023

Med Care Res Rev

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Household surveys are an important source of information on medical spending and burden. We examine how recently implemented post-processing improvements to the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) affected estimates of medical expenditures and medical burden. The revised data extraction and imputation procedures mark the second stage of the CPS ASEC redesign and the beginning of a new time series for studying household medical expenditures. Using data for the calendar year 2017, we find that median family medical expenditures are not statistically different from legacy methods; however, updated processing does significantly reduce the percentage of families estimated to have a high medical burden (medical expenses are at least 10% of family income). The updated processing system also changes the characteristics of families with high medical spending and is primarily driven by changes in imputation of health insurance and medical spending.

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Disparities in survival by insurance status in patients with Hodgkin lymphoma

Parikh

Grossbard

Green

et al. 2015

Cancer

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BACKGROUND:The association between insurance status and outcomes has not been well established for patients with Hodgkin lymphoma (HL). The purpose of this study was to examine the disparities in overall survival (OS) by insurance status in a large cohort of patients with HL. METHODS: The National Cancer Data Base (NCDB) was used to evaluate patients with stage I to IV HL from 1998 to 2011. The association between insurance status, covariables, and outcomes was assessed in a multivariate Cox proportional hazards model. Survival was estimated with the Kaplan-Meier method. RESULTS: Among the 76,681 patients within the NCDB, 45,777 patients with stage I to IV HL were eligible for this study (median follow-up, 6.0 years). The median age was 39 years (range, 18-90 years). The insurance status was as follows: 3247 (7.1%) were uninsured, 7962 (17.4%) had Medicaid, 30,334 (66.3%) had private insurance, 3746 (8.2%) had managed care, and 488 (1.1%) had Medicare. Patients with an unfavorable insurance status (Medicaid/uninsured) were at a more advanced stage, had higher comorbidity scores, had B symptoms, and were in a lower income/education quartile (all P <.01). These patients were less likely to receive radiotherapy and start chemotherapy promptly and were less commonly treated at academic/research centers (all P <.01). Patients with unfavorable insurance had a 5-year OS of 54% versus 87% for those favorably insured (P <.01). When adjustments were made for covariates, an unfavorable insurance status was associated with significantly decreased OS (hazard ratio, 1.60; 95% confidence interval, 1.34-1.91; P <.01). The unfavorable insurance status rate increased from 22.8% to 28.8% between 1998 and 2011. CONCLUSIONS: This study reveals that HL patients with Medicaid and uninsured patients have outcomes inferior to those of patients with more favorable insurance. Targeting this subset of patients with limited access to care may help to improve outcomes. Cancer 2015;121:3515-24.

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The Financial Burden of Medical Spending

Cited by 10 publications

References 9 publications

Applying GRA to analyze influencing factors of patients’ financial burden

Applying GRA to analyze influencing factors of patients’ financial burden

Out-of-Pocket Medical Expenditures in the Redesigned Current Population Survey: Evaluating Improvements to Data Processing

Disparities in survival by insurance status in patients with Hodgkin lymphoma

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