Address correspondence to Daniel Polsky, Ph.D., Division of General Internal Medicine, University of Pennsylvania, 423 Guardian Drive, Blockley Hall 12th Floor, Philadelphia, PA 19104. Katrina A. Armstrong, M.D., is with the Division of General Internal Medicine, Philadelphia, PA. Thomas C. Randall, M.D., is with the Department of Obstetrics & Gynecology, University of Pennsylvania, Philadelphia, PA. Richard N. Ross, M.S., Orit Even-Shoshan, M.S., and Jeffrey H. Silber, M.D., Ph.D., are with the Center for Outcomes Research, Children's Hospital of Philadelphia, Philadelphia, PA. Paul R. Rosenbaum, Ph.D., is with the Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA.
Variation in Chemotherapy Utilization in Ovarian Cancer: The Relative Contribution of Geography
Article first published online: 6 JUL 2006
Health Services Research
Volume 41, Issue 6, pages 2201–2218, December 2006
How to Cite
Polsky, D., Armstrong, K. A., Randall, T. C., Ross, R. N., Even-Shoshan, O., Rosenbaum, P. R. and Silber, J. H. (2006), Variation in Chemotherapy Utilization in Ovarian Cancer: The Relative Contribution of Geography. Health Services Research, 41: 2201–2218. doi: 10.1111/j.1475-6773.2006.00596.x
- Issue published online: 6 JUL 2006
- Article first published online: 6 JUL 2006
- Geographic variations;
- chemotherapy treatment;
- ovarian cancer
Objective. This study investigates geographic variation in chemotherapy utilization for ovarian cancer in both absolute and relative terms and examines area characteristics associated with this variation.
Data Sources. Surveillance, Epidemiology, and End Results (SEER) Medicare data from 1990 to 2001 for Medicare patients over 65 with a diagnosis of ovarian cancer between 1990 and 1999. Chemotherapy within a year of diagnosis was identified by Medicare billing codes. The hospital referral region (HRR) represents the geographic unit of analysis.
Study Design. A logit model predicting the probability of receiving chemotherapy by each of the 39 HRRs. Control variables included medical characteristics (patient age, stage, year of diagnosis, and comorbidities) and socioeconomic characteristics (race, income, and education). The variation among HRRs was tested by the χ2 statistic, and the relative contribution was measured by the ω statistic. HHR market characteristic are then used to explain HRR-level variation.
Principal Findings. The average chemotherapy rate was 56.6 percent, with a range by HRR from 33 percent to 67 percent. There were large and significant differences in chemotherapy use between HRRs, reflected by a χ2 for HRR of 146 (df=38, p<.001). HRR-level variation in chemotherapy use can be partially explained by higher chemotherapy rates in HRRs with a higher percentage of hospitals with oncology services. However, an ω analysis indicates that, by about 15 to one, the variation between patients in use of chemotherapy reflects variations in patient characteristics rather than unexplained variation among HRRs.
Conclusions. While absolute levels of chemotherapy variation between geographic areas are large and statistically significant, this analysis suggests that the role of geography in determining who gets chemotherapy is small relative to individual medical characteristics. Nevertheless, while variation by medical characteristics can be medically justified, the same cannot be said for geographic variation. Our finding that density of oncology hospitals predicts chemotherapy use suggests that provider supply is positively correlated with geographic variation.