The personal financial burden of cancer for the working-aged population.
OBJECTIVE
To present nationally representative estimates of the effect of cancer care on out-of-pocket medical expenditures and lost productivity for the working-aged population.


METHODS
Secondary data analysis.


METHODS
Pooled data from the Medical Expenditure Panel Survey were used for the analysis. We constructed the following 4 respondent groups for comparison during the analysis period: (1) respondents with no cancer, and (among those who reported having cancer) (2) respondents with active cancer care, (3) respondents with follow-up Cancer care, and (4) respondents with no cancer care. Using regression analysis, we estimated the effect of being in each of the cancer care groups on out-of-pocket medical expenditures, the probability of being employed, and the annual number of workdays missed because of illness or injury.


RESULTS
Being actively treated for cancer increases the mean annual out-of-pocket medical expenditures by $1170 compared with not having cancer. Less intensive cancer care is associated with lower medical expenditures (but still higher than for those without cancer). Respondents undergoing active cancer care were less likely to be employed full-time. Among respondents who were employed, those undergoing active cancer care missed 22.3 more workdays per year than those without cancer.


CONCLUSIONS
Changes to the health system need to consider not only how to reduce inappropriate medical utilization but also how to ensure that those diagnosed as having cancer and other serious medical conditions will not be doubly burdened with poor health and high medical expenditures.
Finkelstein
Eric A
EA
Division of Health Services Research, Duke-National University of Singapore Graduate Medical School, Singapore. eric.finkelstein@duke-nus.edu.sg
Tangka
Florence K
FK
Trogdon
Justin G
JG
Sabatino
Susan A
SA
Richardson
Lisa C
LC
D000041:Absenteeism; D000328:Adult; D017281:Cost of Illness; D004651:Employment / Q000706:statistics & numerical data; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006306:Health Surveys; D006801:Humans; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000191:economics*; D012044:Regression Analysis; D014481:United States