Amber E Barnato1, Elan D Cohen2, Keili A Mistovich3, Chung-Chou H Chang4. 1. Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA; Department of Health Care Policy and Management, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania, USA. Electronic address: barnae@upmc.edu. 2. Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA. 3. Children's Hospital of the University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA. 4. Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA; Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania, USA.
Abstract
CONTEXT: Hospitals vary substantially in their end-of-life (EOL) treatment intensity. It is unknown if patterns of EOL treatment intensity are consistent across conditions. OBJECTIVES: To explore the relationship between hospitals' cancer- and non-cancer-specific EOL treatment intensity. METHODS: We conducted a retrospective cohort analysis of Pennsylvania acute care hospital admissions for either cancer or congestive heart failure (CHF) and/or chronic obstructive pulmonary disease (COPD) between 2001 and 2007, linked to vital statistics through 2008. We calculated Bayes's shrunken case-mix standardized (observed-to-expected) ratios of intensive care and life-sustaining treatment use among two EOL cohorts: those prospectively identified at high probability of dying on admission and those retrospectively identified as terminal admissions (decedents). We then summed these to create a hospital-specific prospective and retrospective overall EOL treatment intensity index for cancer vs. CHF/COPD. RESULTS: The sample included 207,523 admissions with 15% or greater predicted probability of dying on admission among 172,041 unique adults and 120,372 terminal admissions at 166 hospitals; these two cohorts overlapped by 52,986 admissions. There was substantial variation between hospitals in their standardized EOL treatment intensity ratios among cancer and CHF/COPD admissions. Within hospitals, cancer- and CHF/COPD-specific standardized EOL treatment intensity ratios were highly correlated for intensive care unit (ICU) admission (prospective ρ = 0.81; retrospective ρ = 0.78), ICU lengths of stay (ρ = 0.76; 0.64), mechanical ventilation (ρ = 0.73; 0.73), and hemodialysis (ρ = 0.60; 0.71) and less highly correlated for tracheostomy (ρ = 0.43; 0.53) and gastrostomy (ρ = 0.29; 0.30). Hospitals' overall EOL intensity index for cancer and CHF admissions were correlated (prospective ρ = 0.75; retrospective ρ = 0.75) and had equal group means (P-value = 0.631; 0.699). CONCLUSION: Despite substantial difference between hospitals in EOL treatment intensity, within-hospital homogeneity in EOL treatment intensity for cancer- and non-cancer populations suggests the existence of condition-insensitive institutional norms of EOL treatment.
CONTEXT: Hospitals vary substantially in their end-of-life (EOL) treatment intensity. It is unknown if patterns of EOL treatment intensity are consistent across conditions. OBJECTIVES: To explore the relationship between hospitals' cancer- and non-cancer-specific EOL treatment intensity. METHODS: We conducted a retrospective cohort analysis of Pennsylvania acute care hospital admissions for either cancer or congestive heart failure (CHF) and/or chronic obstructive pulmonary disease (COPD) between 2001 and 2007, linked to vital statistics through 2008. We calculated Bayes's shrunken case-mix standardized (observed-to-expected) ratios of intensive care and life-sustaining treatment use among two EOL cohorts: those prospectively identified at high probability of dying on admission and those retrospectively identified as terminal admissions (decedents). We then summed these to create a hospital-specific prospective and retrospective overall EOL treatment intensity index for cancer vs. CHF/COPD. RESULTS: The sample included 207,523 admissions with 15% or greater predicted probability of dying on admission among 172,041 unique adults and 120,372 terminal admissions at 166 hospitals; these two cohorts overlapped by 52,986 admissions. There was substantial variation between hospitals in their standardized EOL treatment intensity ratios among cancer and CHF/COPD admissions. Within hospitals, cancer- and CHF/COPD-specific standardized EOL treatment intensity ratios were highly correlated for intensive care unit (ICU) admission (prospective ρ = 0.81; retrospective ρ = 0.78), ICU lengths of stay (ρ = 0.76; 0.64), mechanical ventilation (ρ = 0.73; 0.73), and hemodialysis (ρ = 0.60; 0.71) and less highly correlated for tracheostomy (ρ = 0.43; 0.53) and gastrostomy (ρ = 0.29; 0.30). Hospitals' overall EOL intensity index for cancer and CHF admissions were correlated (prospective ρ = 0.75; retrospective ρ = 0.75) and had equal group means (P-value = 0.631; 0.699). CONCLUSION: Despite substantial difference between hospitals in EOL treatment intensity, within-hospital homogeneity in EOL treatment intensity for cancer- and non-cancer populations suggests the existence of condition-insensitive institutional norms of EOL treatment.
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