1. Preventive Health Care Use in Elderly Uterine Cancer Survivors Division of Health Policy and Management School of Public Health University of Minnesota June 27, 2006 AcademyHealth Annual Research Meeting Xinhua Yu, M.B., PhD A. Marshall McBean, MD, MSc

2. Rationale & Purpose > 80% of uterine cancer patients survive for 5 years Cancer survivors should receive the same rates of preventive services as women with no history of cancer Using SEER-Medicare linked data  Compare the rates of utilization of recommended preventive care services in the population of survivors with the rates in a matched sample of persons with no history of cancer

3. Theoretical Framework Persons with a chronic disease such as cancer would be more likely to be screened or provided other preventive or healthcare services (Feinstein, 1970) The “competing demands model” (Jaen, et al. 1994), suggests that persons with chronic diseases might receive fewer recommended health care services than persons without chronic diseases Empirical evidence supports both positions

4. Conflicting Evidence Earle, et al. (2003) – Breast cancer survivors were more likely than those without cancer to receive influenza vaccine, mammograms, and other cancer screening Earle and Neville (2004) – Colorectal cancer survivors were less likely than those without cancer to receive influenza vaccine, mammograms, and hemoglobin A1c tests to monitor diabetes

5. Study Cohorts Data source: Linked SEER-Medicare database (2003 batch) Case identification – Incident uterine cancer 1973- 1993; survived > 5 years (to 12/31/98); > 65 years old on 1/1/97; no end-stage renal disease; no additional cancer Restrict to those who had complete claim history  had both Medicare Part A and Part B, and not in managed care Comparison cohort – women with no history of cancer

6. Outcome Measures Biannual mammography Quadrennial colorectal cancer screening Annual influenza immunization Biannual bone density testing

7. Independent Variables Age on 1/1/1999 Race/ethnicity Zip code median income (2000 census) Rural residence During 1997 and1998: Hospitalization, and if in a teaching hospital Comorbidities – Charlson score Specialty of treating physicians Number of physician visits (excludes physician visits during hospitalization)

8. Medical Specialty Primary care only: primary care physicians including internal medicine and geriatric medicine Gynecologist: at least one visit to gynecologist or gynecologic oncologist Primary care + oncologist: at least one visit of other type of oncologists Other: other physicians not included in the above or no physician visit

9. Statistical Analysis Propensity score matching Bivariate and multivariate analyses  Logistic regression on the matched data

10. Counterfactual matching to ensure the comparability between cancer survivors and those non-cancer controls Propensity of having or not having cancer was predicted using logistic regression The dependent variable was cancer (yes/no). The predictors were all the covariables Each cancer survivor was matched with an elderly woman with no history of any type of cancer living in the same SEER Registry area whose propensity score was the nearest to that of the cancer survivor psmatch2 module in Stata 9.1 Ref: E. Leuven and B. Sianesi. (2003). "PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing" Propensity Score Matching

11. Results

12. Matched Cohort Characteristics

14. Age-adjusted Rates and Adjusted Odds Ratios of Preventive Service Use Preventive service Uterine cancer survivors No history of cancer Adjusted Odds Ratios (95% CI) Mammography56.0% 49.6% ## 1.39 (1.27-1.51) Colorectal cancer screening21.3% 19.6% # 1.11 (1.04-1.19) Influenza vaccination52.7%52.6%1.00 (0.95-1.05) Bone density testing19.5%19.8%0.97 (0.91-1.05) Cancer survivors vs. no history of cancer: # = 0.01<p<0.05; ## = p<0.01

15. Age-adjusted Rates of Mammography and Colorectal Cancer Screening by Medical Specialty among Uterine Cancer Survivors

16. Age-adjusted Rates of Mammography and Colorectal Cancer Screening by Physician Visits among Uterine Cancer survivors

17. medical specialtyMammography Colorectal Cancer Screening Influenza Vaccination Bone Density Testing Primary careReference Oncologist + Primary care 1.29 (1.05-1.58) 1.10 (0.96-1.26) 0.96 (0.87-1.06) 1.04 (0.90-1.20) Gynecologist 3.18 (2.83-3.59) 1.52 (1.37-1.70) 1.16 (1.11-1.20) 1.79 (1.66-1.93) Other0.30 (0.23-0.38) 0.51 (0.41-0.63) 0.33 (0.29-0.37) 0.49 (0.41-0.58) Adjusted Odds Ratios of Preventive Service Use by Medical Specialty Model includes cancer (yes/no), age, race, rural residence, zip code median income, hospitalization, comorbidities, medical specialty, and physician visits

18. Adjusted Odds Ratios of Preventive Service Use by Physician Visits Physician VisitsMammography Colorectal Cancer Screening Influenza Vaccination Bone Density Testing 0—4reference 5—9 2.65 (2.39-2.93) 1.83 (1.73-1.94) 1.90 (1.65-2.19) 1.80 (1.69-1.91) 10—14 3.39 (2.95-3.91) 2.20 (1.93-2.52) 2.29 (1.99-2.63) 2.09 (1.92-2.27) >=15 4.04 (3.71-4.41) 2.45 (2.21-2.71) 2.52 (2.21-2.88) 2.64 (2.44-2.85) Model includes cancer (yes/no), age, race, rural residence, zip code median income, hospitalization, comorbidities, medical specialty, and physician visits

19. Conclusions Women who survived five or more years after the diagnosis of uterine cancer received higher rates of cancer screening services than women having no history of cancer The rates of influenza vaccination and bone density testing were equal Receiving care by gynecologists or gynecologic oncologists was associated with the greatest use of these preventive services Those who had more than 5 physician visits were more likely to receive the preventive services

20. Acknowledgement Research group  A. Marshall McBean, M.D.,M.Sc.  Xinhua Yu, M.B., PhD,  Beth A. Virnig, PhD, MPH Research Data Assistance Center (ResDAC) at the University of Minnesota Supported by R01 AG025079, R01 CA098974