Economic and organizational determinants of HMO mergers and failures.
This study analyzed data from all operational health maintenance organizations (HMOs) in the United States from 1986 through 1993. Eighty HMOs disappeared through mergers and 149 failed over that period. We estimated a multinomial logit model to predict whether an HMO would merge and survive, merge and disappear, or fail, relative to the probability of no event. We found that enrollment and profitability play a critical role in explaining HMO mergers and failures: large and profitable HMOs were more likely to merge and survive, but less likely to merge and disappear or fail. These results explain why HMO merger and failure rates fell after 1988, as most surviving HMOs became larger and more profitable. Among several market-area variables in the model, state anti-takeover regulations had a negative impact on mergers. Mergers were more likely in markets with more competing HMOs, but the overall market penetration of HMOs had no effect on mergers. This result may have important implications for the current debate over the future of the competitive health care strategy. If public policy successfully stimulates the development of large numbers of new HMOs, another wave of mergers and failures is likely to occur. But it appears that growth in overall HMO penetration will not lead inevitably to increased market concentration.
Feldman
R
R
Institute for Health Services Research, School of Public Health, University of Minnesota, Minneapolis 55455-6151, USA.
Wholey
D
D
Christianson
J
J
D016361:Bankruptcy / Q000706:statistics & numerical data*; D004465:Economic Competition; D005381:Financing, Organized / Q000191:economics / Q000458:organization & administration / Q000706:statistics & numerical data; D006273:Health Facility Merger / Q000706:statistics & numerical data*; D006279:Health Maintenance Organizations / Q000191:economics* / Q000706:statistics & numerical data; D016015:Logistic Models; D018803:Models, Economic; D012308:Risk Management / Q000191:economics / Q000458:organization & administration / Q000706:statistics & numerical data; D013997:Time Factors; D014481:United States