Duke 2008 | ASHE | Equity and Efficiency in Health and Healthcare

Objective and rationale: This study brings together two major, prominent strands of research on variation in health care utilization that have not previously been combined -- small-area variation (SAV), and physician financial self-interest (FSI). SAV research finds that moving the entire U.S. to the health care patterns of low-utilization areas would save up to $600 billion annually without adverse effects on outcomes, quality, or access. However, very little is known regarding the causes of utilization variation. The FSI research, which is most developed for imaging, has shown that FSI is associated with individual-physician-level utilization 2-4 times as high as without FSI, but this research has not quantified the aggregate effect of FSI.

The general hypothesis we will investigate is that SAV in the proportion of care provided by physicians with FSI accounts for much of SAV in utilization.

Methodology: We investigate the hypothesis (i) for total imaging, (ii) more narrowly, for each imaging modality (CT, MR, etc.) separately, and (iii) more broadly, by studying the relation of FSI in imaging to total healthcare costs.

Data from Medicare's 5% Research Identifiable Files for 2005 (latest available) will be used. The small areas will be the 3,436 hospital service areas (HSAs) from the Dartmouth Atlas of Healthcare. Because FSI can be difficult to identify unambiguously, four alternative criteria will be used to identify it.

Multivariable regression will used to measure the contribution of FSI to SAV in per beneficiary utilization or costs of various types of care in HSAs. Characteristics (age, morbidities, etc.) of beneficiaries in the HSA will be controls.

Preliminary Results: For 2004 Medicare data, we find substantial variability among counties and states in imaging utilization, overall and for individual modalities. The systematic component of variation (SCV) is 330 to 489 for counties and 22 to 66 for states. For comparison, the SCV for a variety of surgical procedures is 11 to 128 at the level of HRRs, of which there are 306 in the U.S. For all four definitions of FSI, there was similarly large variation across counties in the proportion of imaging performed by physicians with FSI (CVs ranging from 31.68 to 91.91).

At the county level, for all four definitions, we found the percent of treating physicians with FSI is positively and statistically significantly correlated with images per 1000 beneficiaries for total imaging (correlation coefficients of 0.13-0.19 across definitions) and for ultrasound (correlation coefficient 0.2-0.33), but for only two definitions for CT In multivariable regression (in a simple form at the state level), we find no significant effect of radiologists per 1,000 Medicare enrollees on total imaging utilization, but a statistically significant effect of percent of imaging referred by treating physicians with FSI in imaging.

HSA-level analysis is still to be performed.

Conclusions: If our findings support our hypothesis, we will have a potential strategy for cutting costs and achieving the savings suggested by the SAV research. Having ways to cut costs identified in advance will abet change when, as periodically happens, deteriorating finances facilitate action.