Mammography Use in California: The Relative Importance of Supply, Demand, and Local Impedance Factors

This paper examines a myriad of factors that can influence whether healthcare is utilized by insured elderly individuals. We estimate a robust, binary probit model of the mammography utilization outcome for about 160,800 women in California over the period 2002-2003. California is rich in heterogeneous socio-economic and socio-cultural factors, and heterogeneous urbanization with dense traffic congestion and commuter intensity in some places, flanked by rural locales with isolated providers. The sample is convenient, drawn from the linked SEER cancer registry and a 5% random sample of Medicare fee-for-service beneficiary files. A lot of attention has been paid to 'access' to healthcare, i.e. "Is the service I need conveniently available?" Distance to provider has been found extremely important in many studies of healthcare outcomes. In these data, we do not have the actual street address for people or their providers, so distance is approximated 'as the crow flies' between the geographic centroids of their respective ZIP codes. We find that over half of women reside in the same ZIP code as a mammography center, and only about 3% are located more than 10 miles from a center. However, despite the apparent proximity of service centers, only about half of the women in the sample received a mammogram in 2002-2003. We look at 2-year use because national health guidelines recommend a mammogram every other year from women age 40 or older, and this fee-for-service population has coverage available if they purchase Part B Medicare (for outpatient services). Less attention has been paid to the questions "Can I get there?" or "Am I interested in obtaining the service?". Apart from service proximity, there are many other factors, both socio-economic and socio-cultural, that might impact one's decision about seeking mammography. We explore these factors, using a comprehensive contextual model of health care utilization to guide development of many geo-spatial contextual variables. We find that personal factors, such as health-investment behavior (obtaining annual flu shot), age (diminishing marginal returns to screening), ability to pay (Part B or Medicaid coverage), disability, or cancer therapy (mammography use associated with cancer diagnosis) are predictors of why women USE mammography. Contextual factors from the local markets in which they live are better predictors of why women DON'T USE mammography (commuter intensity, racial/ethnic isolation/segregation, impoverished elderly community, English language ability, land use mix). We find that availability of health care professionals (doctors, nurses, physician assistants, nurse practitioners) does not significantly impact use. The model residuals, as well as many contextual variables, exhibit a large degree of spatial autocorrelation. In ongoing work, we estimate a spatial probit version of the model, accounting for the lack of independence across observations using spatial econometrics. This approach yields robust standard errors and robust spatial impact parameter estimates. After this stage of the analysis, we can identify regions with particular combinations of factors, or particularly low unexplained use rates, for focused investigation or targeted intervention by policy analysts in comprehensive cancer control roles.