Cost effectiveness of cervical cancer screening for the elderly.
OBJECTIVE
To analyze the costs and benefits of alternative cervical cancer screening schedules among elderly women.


METHODS
Population-based screening programs.


METHODS
A Markov model predicts the outcomes of periodic screening, diagnosis, and treatment for cervical cancer among women from 65 to 109 years of age.


METHODS
A hypothetical cohort of one million 65-year-old women; representative of the U.S. population.


METHODS
The costs and yields of screening.


RESULTS
Triennial screening reduced mortality from cervical cancer among the elderly by 74% at a cost of $2254 per year of life saved. Annual screening increased costs to $7345 per year of life saved; less frequent schedules yielded lower costs but decreased savings in life. These results were most sensitive to the quality of the Papanicolaou smear and the characteristics of the women using the benefit. If the sensitivity of the Papanicolaou smear was reduced from a baseline estimate of 75% to 50% and the specificity was decreased to 87% from 95%, the cost effectiveness ratio increased by nearly $7000 per year of life saved. If triennial screening is targeted to women who have not had regular screening, the program will save money as well as years of life; however, screening women who have been screened regularly is considerably less efficient, increasing costs to $33,572 per year of life saved.


CONCLUSIONS
The success of the new Medicare benefit depends substantially on physicians assuring that their elderly patients, particularly women without regular prior screening, obtain high quality Papanicolaou smears. The data also show that after a woman 65 years of age or older has a history of regular negative smears, screening is inefficient and can cease.
Fahs
M C
MC
Mount Sinai Medical Center, New York, NY.
Mandelblatt
J
J
Schechter
C
C
Muller
C
C
D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D003362:Cost-Benefit Analysis; D005260:Female; D006801:Humans; D008403:Mass Screening / Q000191:economics*; D006278:Medicare / Q000191:economics; D015233:Models, Statistical; D012680:Sensitivity and Specificity; D014481:United States; D002583:Uterine Cervical Neoplasms / Q000191:economics / Q000517:prevention & control*; D026712:Value of Life