A descriptive analysis of average productivity among health maintenance organizations, 1985 to 2001

Abstract

This paper examines the evolution of average productivity among HMOs for 4,419 Health Maintenance Organizations (HMOs) from 1985 to 2001. For both IPA and non-IPA HMOs, HMO productivity increased from 1990 to 1996 and rapidly decreased from 1997 to 2001. In contrast to cost functions that show scale economies for IPA and non-IPA HMOs, production functions showed scale economies for IPA HMOs were constant and non-IPA HMOs having only slight scale economies. This suggests that much of the scale economies observed in cost functions are due to lower prices for resources used rather than improvements in production organization. Non-IPA HMOs and non-profit HMOs are more productive than IPA HMOs and for profit HMOs. Production organization for non-IPA HMOs appears to have improved over time, resulting in non-IPA HMOs being able to produce more member months of coverage with their production organization in 1997 to 2001 than they would have with their production organization in 1985 to 1990. Regulations requiring consumer involvement in HMO governance reduce productivity.

Revisiting the Relationship between Managed Care and Hospital Consolidation

“…The HMO data come from InterStudy census data (InterStudy 1985–1987, 1988–2001) and Group Health Association HMO Directories (Group Health Association of America 1989–1992). The InterStudy data are used to form county‐level measures of HMO penetration and the number of HMOs following the methodology of Wholey, Engberg, and Bryce (2006). County‐level market measures come from the Area Resource File (ARF, Bureau of Health Professions 1999).…”

“…The HMO data come from InterStudy census data (InterStudy 1985(InterStudy -1987(InterStudy , 1988(InterStudy -2001 and Group Health Association HMO Directories (Group Health Association of America 1989America -1992. The InterStudy data are used to form county-level measures of HMO penetration and the number of HMOs following the methodology of Wholey, Engberg, and Bryce (2006 HSA measures were constructed by first measuring HMO enrollment, ARF characteristics, and wage data at the county level. The ARF provided county-level measures of the number of primary care physicians, median percapita income, unemployment rate, population of the HSA, and percent of the population over 65 years of age.…”

The Changing Effect of HMO Market Structure: An Analysis of Penetration, Concentration, and Ownership Between 1994-2005

“…Schramm (2001) and Town et al (2004) both reported that conversion of HMO plans to for-profit status does not result in demonstrable economic efficiency in the health plans. Wholey et al (2006), in a descriptive analysis of HMO plans between 1985 and 2001, even found for-profit HMOs to be less productive than not-for-profit plans. Shen and Melnick (2004) directly tested whether for-profit HMOs exert more financial pressure than not-for-profit plans on hospital cost and revenue growth between 1989 and 1998.…”

Trends in Hospital Cost and Revenue, 1994–2005: How Are They Related to HMO Penetration, Concentration, and For‐Profit Ownership?

“…Some argue that FP health plans are no more effective than nonprofit plans at improving health system efficiency (Weisbrod 1988), which is empirically supported by Schramm (2001) and Town, Feldman, and Wholey (2004). Yet Wholey, Engberg, and Bryce (2006) found FP HMOs to be less productive than not‐FP plans between 1985 and 2001. Shen and Melnick (2004) found that, between 1989 and 1998, hospital costs and revenues grew at a slower rate in higher FP HMO share areas, especially in high HMO penetration areas.…”