The effect of HMO penetration on physician retirement.
OBJECTIVE
To examine the effect of HMO penetration on physician retirement.


METHODS
We linked together historical data from the Physician Masterfile of the American Medical Association for successive years to track changes in physicians' activity status between 1980 and 1997. We used a multivariate discrete-time survival model to examine how the probability of physician retirement was affected by the level of HMO penetration in the physician's market area, controlling for other physician and market characteristics. The study population included all active allopathic patient-care physicians in the United States who reached age 55 between the years of 1980 and 1996. The main outcome measure was physician retirements as reported on the Physician Masterfile.


RESULTS
HMO penetration had a statistically significant positive effect on the retirement probabilities of generalists and medical/surgical specialists, but it s effect on hospital-based specialists and psychiatrists was not significant . For generalists regression-adjusted retirement probabilities were roughly 13 percent greater in high-penetration markets (HMO penetration of 45 percent ) than in low-penetration markets (HMO penetration of 5 percent ). For medical/surgical specialist s regression-adjusted retirement probabilities were roughly 17 percent greater in high-penetration markets than in low-penetration markets.


CONCLUSIONS
Our findings suggest that many older physicians have found it preferable to retire rather than adapt their practices to an environment with a high degree of managed care penetration . Because the number of physicians entering the older age categories will increase rapidly over the next 20 years, the growth of managed care and other influences on physician retirement will play an increasingly important role in determining the size of the physician workforce.
Kletke
P R
PR
Center for Health
Polsky
D
D
Wozniak
G D
GD
Escarce
J J
JJ
D000368:Aged; D000574:American Medical Association; D003625:Data Collection; D003657:Decision Making; D005260:Female; D006279:Health Maintenance Organizations / Q000706:statistics & numerical data*; D006280:Health Workforce; D006801:Humans; D007325:Institutional Practice / Q000706:statistics & numerical data / Q000639:trends; D008297:Male; D008875:Middle Aged; D010563:Personnel Turnover / Q000706:statistics & numerical data / Q000639:trends*; D010820:Physicians / Q000600:supply & distribution*; D011336:Probability; D011365:Professional Practice Location; D012179:Retirement / Q000706:statistics & numerical data / Q000639:trends*; D013038:Specialization; D013043:Specialties, Surgical; D016019:Survival Analysis; D014481:United States