Family Perspectives on Aggressive Cancer Care Near the End of Life.

IMPORTANCE: Patients with advanced-stage cancer are receiving increasingly aggressive medical care near death, despite growing concerns that this reflects poor-quality care. OBJECTIVE: To assess the association of aggressive end-of-life care with bereaved family members' perceptions of the quality of end-of-life care and patients' goal attainment. DESIGN, SETTING, AND PARTICIPANTS: Interviews with 1146 family members of Medicare patients with advanced-stage lung or colorectal cancer in the Cancer Care Outcomes Research and Surveillance study (a multiregional, prospective, observational study) who died by the end of 2011 (median, 144.5 days after death; interquartile range, 85.0-551.0 days). EXPOSURES: Claims-based quality measures of aggressive end-of-life care (ie, intensive care unit [ICU] admission or repeated hospitalizations or emergency department visits during the last month of life; chemotherapy ≤2 weeks of death; no hospice or ≤3 days of hospice services; and deaths occurring in the hospital). MAIN OUTCOMES AND MEASURES: Family member-reported quality rating of "excellent" for end-of-life care. Secondary outcomes included patients' goal attainment (ie, end-of-life care congruent with patients' wishes and location of death occurred in preferred place). RESULTS: Of 1146 patients with cancer (median age, 76.0 years [interquartile range, 65.0-87.0 years]; 55.8% male), bereaved family members reported excellent end-of-life care for 51.3%. Family members reported excellent end-of-life care more often for patients who received hospice care for longer than 3 days (58.8% [352/599]) than those who did not receive hospice care or received 3 or fewer days (43.1% [236/547]) (adjusted difference, 16.5 percentage points [95% CI, 10.7 to 22.4 percentage points]). In contrast, family members of patients admitted to an ICU within 30 days of death reported excellent end-of-life care less often (45.0% [68/151]) than those who were not admitted to an ICU within 30 days of death (52.3% [520/995]) (adjusted difference, -9.4 percentage points [95% CI, -18.2 to -0.6 percentage points]). Similarly, family members of patients who died in the hospital reported excellent end-of-life care less often (42.2% [194/460]) than those who did not die in the hospital (57.4% [394/686]) (adjusted difference, -17.0 percentage points [95% CI, -22.9 to -11.1 percentage points]). Family members of patients who did not receive hospice care or received 3 or fewer days were less likely to report that patients died in their preferred location (40.0% [152/380]) than those who received hospice care for longer than 3 days (72.8% [287/394]) (adjusted difference, -34.4 percentage points [95% CI, -41.7 to -27.0 percentage points]). CONCLUSIONS AND RELEVANCE: Among family members of older patients with fee-for service Medicare who died of lung or colorectal cancer, earlier hospice enrollment, avoidance of ICU admissions within 30 days of death, and death occurring outside the hospital were associated with perceptions of better end-of-life care. These findings are supportive of advance care planning consistent with the preferences of patients.

Elderly breast and colorectal cancer patients' clinical course: patient and contextual influences.

BACKGROUND: The social and medical environments that surround people are each independently associated with their cancer course. The extent to which these characteristics may together mediate patients' cancer care and outcomes is not known. METHODS: Using multilevel methods and data, we studied elderly breast and colorectal cancer patients (level I) within urban social (level II: ZIP code tabulation area) and health care (level III: hospital service area) contexts. We sought to determine (1) which, if any, observable social and medical contextual attributes were associated with patient cancer outcomes after controlling for observable patient attributes, and (2) the magnitude of residual variation in patient cancer outcomes at each level. RESULTS: Numerous patient attributes and social area attributes, including poverty, were associated with unfavorable patient cancer outcomes across the full clinical cancer continuum for both cancers. Health care area attributes were not associated with patient cancer outcomes. After controlling for observable covariates at all 3 levels, there was substantial residual variation in patient cancer outcomes at all levels. CONCLUSIONS: After controlling for patient attributes known to confer risk of poor cancer outcomes, we find that neighborhood socioeconomic disadvantage exerts an independent and deleterious effect on residents' cancer outcomes, but the area supply of the specific types of health care studied do not. Multilevel interventions targeted at cancer patients and their social areas may be useful. We also show substantial residual variation in patient outcomes across social and health care areas, a finding potentially relevant to traditional small area variation research methods.

Insurer market structure and variation in commercial health care spending.

OBJECTIVE: To examine the relationship between insurance market structure and health care prices, utilization, and spending. DATA SOURCES: Claims for 37.6 million privately insured employees and their dependents from the Truven Health Market Scan Database in 2009. Measures of insurer market structure derived from Health Leaders Inter study data. METHODS: Regression models are used to estimate the association between insurance market concentration and health care spending, utilization, and price, adjusting for differences in patient characteristics and other market-level traits. RESULTS: Insurance market concentration is inversely related to prices and spending, but positively related to utilization. Our results imply that, after adjusting for input price differences, a market with two equal size insurers is associated with 3.9 percent lower medical care spending per capita (p = .002) and 5.0 percent lower prices for health care services relative to one with three equal size insurers (p < .001). CONCLUSION: Greater fragmentation in the insurance market might lead to higher prices and higher spending for care, suggesting some of the gains from insurer competition may be absorbed by higher prices for health care. Greater attention to prices and utilization in the provider market may need to accompany procompetitive insurance market strategies.