title: Longitudinal study of health maintenance organization efficiency.
abstract: Longitudinal studies looking at health maintenance organization (HMO) efficiency in the United States have not been performed before this study--previously there have only been small inter-group studies comparing efficiencies. The objectives here were twofold: to analyse HMO efficiency longitudinally, using a data envelopment analysis (DEA) model; and to compare the various types of HMOs and their efficiency using DEA. A cohort of HMOs was followed longitudinally and a number of variables measuring efficiency were studied. Data were derived from the HMO database survey (HCIA Inc.) for 1993-1997. Thirty-six HMOs were followed over a five-year period, and baseline input and output variables were collected. These measures are proxies for efficiency using the DEA methodology. Over all, using the DEA model it was demonstrated that HMOs tended to improve efficiency over time. Independent Practice Association HMOs appeared to show the highest level of improved efficiency. HMO type, profit status, federal eligibility and age were predictive variables for efficiency. Results of this study demonstrate that HMOs are improving efficiency longitudinally, and in general, certain specific models are longitudinally more efficient than others. Moreover, attributes of efficient HMOs have been identified. For policy-makers looking at efficiency, this information can be used to determine which HMO models are more appropriate when trying to achieve cost containment and effectiveness.
authors.affiliation: Department of Health Administration, Virginia Commonwealth University, Grant House, 1008 East Clay Street, PO Box 980203, Richmond, Virginia 23298-0203, USA.
authors.forename: J
authors.initials: J
authors.lastname: Rollins
authors.forename: K
authors.initials: K
authors.lastname: Lee
authors.forename: Y
authors.initials: Y
authors.lastname: Xu
authors.forename: Y A
authors.initials: YA
authors.lastname: Ozcan
mesh_terms: D019985:Benchmarking; D017598:Efficiency, Organizational / Q000706:statistics & numerical data* / Q000639:trends; D006279:Health Maintenance Organizations / Q000458:organization & administration* / Q000639:trends; D008137:Longitudinal Studies; D017146:Models, Organizational; D014481:United States