title: Trends in end-of-life cancer care in the Medicare program.
abstract: OBJECTIVE
  To examine contemporary trends in end-of-life cancer care and geographic variation of end-of-life care aggressiveness among Medicare beneficiaries.
  
  
  METHODS
  Using the Surveillance, Epidemiology, and End Results-Medicare data, we identified 132,051 beneficiaries who died as a result of cancer in 2006-2011. Aggressiveness of end-of-life care was measured by chemotherapy received within 14 days of death, >1 emergency department (ED) visit within 30 days of death, >1 hospitalization within 30 days of death, ≥1 intensive care unit (ICU) admission within 30 days of death, in-hospital death, or hospice enrollment ≤3 days before death. Using hierarchical generalized linear models, we assessed potentially aggressive end-of-life care adjusting for patient demographics, tumor characteristics, and hospital referral region (HRR)-level market factors.
  
  
  RESULTS
  The proportion of beneficiaries receiving at least one potentially aggressive end-of-life intervention increased from 48.6% in 2006 to 50.5% in 2011 (P<.001). From 2006 to 2011, increases were apparent in repeated hospitalization (14.1% vs. 14.8%; P=.01), repeated ED visits (34.3% vs. 36.6%; P<.001), ICU admissions (16.2% vs. 21.3%; P<.001), and late hospice enrollment (11.2% vs. 12.9%; P<.001), whereas in-hospital death declined (23.5% vs. 20.9%; P<.001). End-of-life chemotherapy use (4.4% vs. 4.5%) did not change significantly over time (P=.12). The use of potentially aggressive end-of-life care varied substantially across HRRs, ranging from 40.3% to 58.3%. Few HRRs had a decrease in aggressive end-of-life care during the study period.
  
  
  CONCLUSIONS
  Despite growing focus on providing appropriate end-of-life care, there has not been an improvement in aggressive end-of-life cancer care in the Medicare program.
authors.affiliation: Department of Chronic Disease Epidemiology, Yale University School of Public Health, New Haven, CT, USA; Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA. Electronic address: shiyi.wang@yale.edu.
authors.forename: Shi-Yi
authors.initials: SY
authors.lastname: Wang
authors.affiliation: Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA.
authors.forename: Jane
authors.initials: J
authors.lastname: Hall
authors.affiliation: Department of Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors.forename: Craig E
authors.initials: CE
authors.lastname: Pollack
authors.affiliation: Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA; Section of Medical Oncology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA.
authors.forename: Kerin
authors.initials: K
authors.lastname: Adelson
authors.affiliation: Department of Health Policy and Management, Yale University School of Public Health, New Haven, CT, USA.
authors.forename: Elizabeth H
authors.initials: EH
authors.lastname: Bradley
authors.affiliation: Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA.
authors.forename: Jessica B
authors.initials: JB
authors.lastname: Long
authors.affiliation: Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, Yale Cancer Center, Yale University School of Medicine, New Haven, CT, USA; Section of General Internal Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA.
authors.forename: Cary P
authors.initials: CP
authors.lastname: Gross
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003430:Cross-Sectional Studies; D004358:Drug Therapy / Q000639:trends; D004636:Emergency Service, Hospital / Q000639:trends; D005260:Female; D017051:Hospice Care / Q000639:trends; D006760:Hospitalization / Q000639:trends; D006801:Humans; D007342:Insurance Benefits / Q000639:trends*; D016014:Linear Models; D008297:Male; D006278:Medicare / Q000639:trends*; D009369:Neoplasms / Q000628:therapy*; D018426:SEER Program; D013727:Terminal Care / Q000706:statistics & numerical data / Q000639:trends*; D014481:United States
keywords: End-of-life care; Geographic variation; Intensity