Spatial Analysis of Elderly Access to Primary Care Services: Informing the Debate on Physician Shortage in the U.S.
- Presenter:
Chair: Willard Manning; Discussant: TBA Tue June 6, 2006 15:30-17:00 Room 226
High rates of admissions for Ambulatory Care Sensitive Conditions (ACSCs) are signals of poor preventive care utilization. This paper examines the influence of geographic or market-level supply and demand factors on market-level rates of ACSC admissions among Original Medicare (FFS) beneficiaries in the latter nineties (1998-2000). This period follows implementation of the Balanced Budget Act of 1997, which reduced the level of prospective payments and introduced limits to home health care visits and other aspects of preventive care services for the elderly.
The conceptual model assumes that local area market conditions, serving as interventions along the pathways to healthcare utilization, can impact outcomes. Using natural markets defined by The Health Resources and Services Administration’s Primary Care Service Area (PCSA) Project, spatial regression is used to analyze admission rates for Ambulatory Care Sensitive Conditions (ACSCs) among all elderly FFS beneficiaries 1998-2000, controlling for disease severity using detailed information from the MEDPAR claims.
A spatial spillovers model is estimated to account for endogenous provider and beneficiary behavior across Primary Care Service Areas. Spatial multiplier effects are found to be quite large, suggesting that OLS estimates of marginal impacts from explanatory variables would be overstated by about 50 percent in magnitude of effect. GeoDa and R spatial analysis software, with additional code written in PYTHON, are used to estimate an instrumental variables version of the spatial lag model and conduct mis-specification and goodness-of-fit tests. R and Python are required to obtain robust estimates of parameters because the dependent variable does not meet the assumptions under the Maximum Likelihood estimation done in GeoDa (the dependent variable is highly skewed). Reported standard errors are robust to heteroskedasticity.
Our evidence suggests that elderly living in impoverished rural areas, or in sprawling suburban places, are about equally more likely to be admitted for ACSCs. Greater availability of physicians does not seem to matter, but greater prevalence of non-physician clinicians and international medical graduates, relative to traditional physicians, does seem to reduce ACSC admissions, especially in poor rural areas. The relative importance of these non-traditional physician groups in providing primary care in areas of greatest need can inform the ongoing debate regarding whether there is an impending shortage of physicians in the US.
