Hospitalization Rates and Predictors of Rehospitalization Among Individuals With Advanced Cancer in the Year After Diagnosis

Abstract

Purpose Among individuals with advanced cancer, frequent hospitalization increasingly is viewed as a hallmark of poor-quality care. We examined hospitalization rates and individual- and hospital-level predictors of rehospitalization among individuals with advanced cancer in the year after diagnosis. Methods Individuals diagnosed with advanced breast, colorectal, non-small-cell lung, or pancreatic cancer from 2009 to 2012 (N = 25,032) were identified with data from the California Cancer Registry (CCR). After linkage with inpatient discharge data, multistate and log-linear Poisson regression models were used to calculate hospitalization rates and to model rehospitalization in the year after diagnosis, accounting for survival. Results In the year after diagnosis, 71% of individuals with advanced cancer were hospitalized, 16% had three or more hospitalizations, and 64% of hospitalizations originated in the emergency department. Rehospitalization rates were significantly associated with black non-Hispanic (incidence rate ratio [IRR], 1.29; 95% CI, 1.17 to 1.42) and Hispanic (IRR, 1.11; 95% CI, 1.03 to 1.20) race/ethnicity; public insurance (IRR, 1.37; 95% CI, 1.23 to 1.47) and no insurance (IRR, 1.17; 95% CI, 1.02 to 1.35); lower socioeconomic status quintiles (IRRs, 1.09 to 1.29); comorbidities (IRRs, 1.13 to 1.59); and pancreatic (IRR, 2.07; 95% CI, 1.95 to 2.20) and non-small-cell lung (IRR, 1.69; 95% CI, 1.54 to 1.86) cancers versus colorectal cancer. Rehospitalization rates were significantly lower after discharge from a hospital that had an outpatient palliative care program (IRR, 0.90; 95% CI, 0.83 to 0.97) and were higher after discharge from a for-profit hospital (IRR, 1.33; 95% CI, 1.14 to 1.56). Conclusion Individuals with advanced cancer experience a heavy burden of hospitalization in the year after diagnosis. Efforts to reduce hospitalization and provide care congruent with patient preferences might target individuals at higher risk. Future work might explore access to palliative care in the community and related health care use among individuals with advanced cancer.

Figures

Fig 1.

Multistate model to describe all possible states and between-state transitions.