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1.
J Surg Res ; 250: 125-134, 2020 06.
Article in English | MEDLINE | ID: mdl-32044509

ABSTRACT

BACKGROUND: In prior reports from population-based databases, black patients with extremity soft tissue sarcoma (ESTS) have lower reported rates of limb-sparing surgery and adjuvant treatment. The objective of this study was to compare the multimodality treatment of ESTS between black and white patients within a universally insured and equal-access health care system. METHODS: Claims data from TRICARE, the US Department of Defense insurance plan that provides health care coverage for 9 million active-duty personnel, retirees, and dependents, were queried for patients younger than 65 y with ESTS who underwent limb-sparing surgery or amputation between 2006 and 2014 and identified as black or white race. Multivariable logistic regression analysis was used to evaluate the impact of race on the utilization of surgery, chemotherapy, and radiation. RESULTS: Of the 719 patients included for analysis, 605 patients (84%) were white and 114 (16%) were black. Compared with whites, blacks had the same likelihood of receiving limb-sparing surgery (odds ratio [OR], 0.861; 95% confidence interval [95% CI], 0.284-2.611; P = 0.79), neoadjuvant radiation (OR, 1.177; 95% CI, 0.204-1.319; P = 0.34), and neoadjuvant (OR, 0.852; 95% CI, 0.554-1.311; P = 0.47) and adjuvant (OR, 1.211; 95% CI, 0.911-1.611; P = 0.19) chemotherapy; blacks more likely to receive adjuvant radiation (OR, 1.917; 95% CI, 1.162-3.162; P = 0.011). CONCLUSIONS: In a universally insured population, racial differences in the rates of limb-sparing surgery for ESTS are significantly mitigated compared with prior reports. Biologic or disease factors that could not be accounted for in this study may contribute to the increased use of adjuvant radiation among black patients.


Subject(s)
Healthcare Disparities/statistics & numerical data , Not-For-Profit Insurance Plans/statistics & numerical data , Patient Acceptance of Health Care/statistics & numerical data , Sarcoma/therapy , United States Department of Defense/statistics & numerical data , Administrative Claims, Healthcare/statistics & numerical data , Adult , Black or African American/statistics & numerical data , Age Factors , Databases, Factual/statistics & numerical data , Extremities , Female , Humans , Male , Middle Aged , Not-For-Profit Insurance Plans/economics , Organ Sparing Treatments/economics , Organ Sparing Treatments/statistics & numerical data , Radiotherapy, Adjuvant/economics , Radiotherapy, Adjuvant/statistics & numerical data , Retrospective Studies , United States , United States Department of Defense/economics , White People/statistics & numerical data , Young Adult
3.
Mil Med ; 183(11-12): e354-e358, 2018 11 01.
Article in English | MEDLINE | ID: mdl-29547994

ABSTRACT

Introduction: We estimate the effect on health care spending of an option to change TRICARE. Under the option, which is based on a proposal made by the Military Compensation and Retirement Modernization Commission (MCRMC), most beneficiaries could choose from a range of commercial health networks instead of the current TRICARE plans. Military treatment facilities would become network providers under the commercial plans. Materials and Methods: We used data from the Department of Defense (DoD) to estimate the cost of providing the current health care benefit to working-age retirees and their dependents and survivors, and active duty family members. We then adjusted those data to estimate what the private insurance premiums would be for those groups. Greater details about the methodology can be found in earlier work by the Congressional Budget Office. Because payments by TRICARE to physicians and hospitals are tied to payments made by Medicare, we used the information from studies that compare Medicare payment rates to rates paid to doctors and hospitals by private insurance to estimate what it would cost private insurers to provide approximately the same level of care, with adjustments to account for the higher out-of-pocket costs that beneficiaries would pay under the option. We also made adjustments to account for the possibility that many beneficiaries would decrease their use of the MTFs in favor of private providers, which could increase the overall costs of DoD. We then estimated that increasing the cost sharing to a level found in popular civilian plans would lower overall demand for services by about 10% for military retiree households and about 18% for active duty family members. Results: We estimated that DoD would pay subsidies to retain about half of the excess capacity created by beneficiaries switching their care from MTFs to the private sector. Evaluated at the midpoint of the ranges, the net effect on DoD's budget would be approximately $0, we estimate, but costs could fall in a likely range from about $3 billion in annual savings to about $3 billion in annual costs. Thus, the MCRMC estimate of $3.2 billion implicitly assumed that no excess capacity would be retained by MTFs. In 2031, under current law, the average retiree family is expected to cost the federal government about $24,100 (in 2017 dollars) and that family's out-of-pocket costs are expected to amount to about $1,900. The option would reduce the government's costs for the average retiree family to $23,500, but retiree families could see their out-of-pocket costs rise to $7,500 per year. Conclusion: This article outlined a method of identifying two particular sources of that uncertainty: the extent to which people will receive care outside of MTFs and the extent to which the MTFs can adjust to reductions in demand. For one particular option, we demonstrate that the potential savings from changing the system depends on increasing the share of costs paid by beneficiaries - particularly working-age retirees - and on DoD's ability to reduce excess capacity in the system.


Subject(s)
For-Profit Insurance Plans/economics , Not-For-Profit Insurance Plans/economics , Cost-Benefit Analysis , For-Profit Insurance Plans/standards , For-Profit Insurance Plans/statistics & numerical data , Humans , Military Personnel/statistics & numerical data , Not-For-Profit Insurance Plans/standards , Not-For-Profit Insurance Plans/statistics & numerical data , Quality of Health Care , United States , United States Department of Defense/organization & administration , United States Department of Defense/statistics & numerical data , United States Department of Veterans Affairs/organization & administration , United States Department of Veterans Affairs/statistics & numerical data , Veterans/statistics & numerical data
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