Predictors of Medicare costs in elderly beneficiaries with breast, colorectal, lung, or prostate cancer

Determining the apportionment of costs of cancer care and identifying factors that predict costs are important for planning ethical resource allocation for cancer care, especially in markets where managed care has grown. This study linked tumor registry data with Medicare administrative claims to de...

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Bibliographic Details
Published in:Health care management science 1999-07, Vol.2 (3), p.149-160
Main Authors: Penberthy, L, Retchin, S M, McDonald, M K, McClish, D K, Desch, C E, Riley, G F, Smith, T J, Hillner, B E, Newschaffer, C J
Format: Article
Language:English
Subjects:
Aged
Beneficiaries
Breast cancer
Colorectal cancer
Cost estimates
Costs
Demographics
Female
Health Care Costs - statistics & numerical data
Health care expenditures
Health care policy
Health insurance
Health services utilization
Humans
Least-Squares Analysis
Lung cancer
Male
Medical Record Linkage
Medicare
Medicare - economics
Models, Econometric
Neoplasms - economics
Neoplasms - epidemiology
Patients
Prostate cancer
Reimbursement
SEER Program - statistics & numerical data
Statistical analysis
Studies
Surgery
United States - epidemiology
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Summary:Determining the apportionment of costs of cancer care and identifying factors that predict costs are important for planning ethical resource allocation for cancer care, especially in markets where managed care has grown. This study linked tumor registry data with Medicare administrative claims to determine the costs of care for breast, colorectal, lung and prostate cancers during the initial year subsequent to diagnosis, and to develop models to identify factors predicting costs. Patients with a diagnosis of breast (n = 1,952), colorectal (n = 2,563), lung (n = 3,331) or prostate cancer (n = 3,179) diagnosed from 1985 through 1988. The average costs during the initial treatment period were $12,141 (s.d. = $10,434) for breast cancer, $24,910 (s.d. = $14,870) for colorectal cancer, $21,351 (s.d. = $14,813) for lung cancer, and $14,361 (s.d. = $11,216) for prostate cancer. Using least squares regression analysis, factors significantly associated with cost included comorbidity, hospital length of stay, type of therapy, and ZIP level income for all four cancer sites. Access to health care resources was variably associated with costs of care. Total R2 ranged from 38% (prostate) to 49% (breast). The prediction error for the regression models ranged from < 1% to 4%, by cancer site. Linking administrative claims with state tumor registry data can accurately predict costs of cancer care during the first year subsequent to diagnosis for cancer patients. Regression models using both data sources may be useful to health plans and providers and in determining appropriate prospective reimbursement for cancer, particularly with increasing HMO penetration and decreased ability to capture complete and accurate utilization and cost data on this population.
ISSN:1386-9620
1572-9389
DOI:10.1023/A:1019096030306