TY - JOUR
T1 - Predictors of unplanned hospitalizations in patients with nonmetastatic lung cancer during chemotherapy
AU - Fessele, Kristen L.
AU - Hayat, Matthew Jason
AU - Atkins, Robert L.
N1 - Funding Information:
Fessele is a scientific project leader at Flatiron Health in New York, NY; Hayat is an associate professor in the School of Public Health at Georgia State University in Atlanta; and Atkins is an associate professor and director of the New Jersey Health Initiatives–Robert Wood Johnson Foundation at Rutgers University in Camden.
Funding Information:
During the writing of this article, Fessele was supported, in part, by a postdoctoral fellowship award (T32NR013456) at the University of Utah from the National Institute of Nursing Research of the National Institutes of Health. This research was conducted as Fessele’s dissertation work in partial fulfillment of the requirements for the PhD degree at Rutgers University. This study used the linked Surveillance, Epidemiology, and End Results (SEER)– Medicare database. The interpretation and reporting of these data are the sole responsibility of the authors. The authors acknowledge the efforts of the National Cancer Institute; the Office of Research, Development, and Information (Centers for Medicare and Medicaid Services); Information Management Services, Inc.; and the SEER Program tumor registries in the creation of the SEER–Medicare database.
Publisher Copyright:
© 2017 by the Oncology Nursing Society.
PY - 2017/9
Y1 - 2017/9
N2 - Purpose/Objectives: To determine predictors of unplanned hospitalizations in patients with lung cancer to receive chemotherapy in the outpatient setting and examine the potential financial burden of these events. Design: Retrospective, longitudinal cohort study. Setting: The National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database. Sample: Of 104,388 incident cases of lung cancer diagnosed from 2005-2009, 2,457 cases of patients with lung cancer who received outpatient chemotherapy were identified. Patients were aged 66 years or older at diagnosis, had uninterrupted Medicare Part A and B coverage with no health maintenance organization enrollment, and received IV chemotherapy at least once. Methods: Generalized estimating equations was used. Main Research Variables: Patient age, sex, race, marital status, degree of residential urbanization, median income, education level, stage, receipt of radiation therapy, and comorbidities. Findings: Younger age, non-White race, lower education, higher income, receipt of radiation therapy, and lack of preexisting comorbidity were significant predictors of the likelihood of an initial unplanned hospitalization for lung cancer. Non-White race, receipt of radiation therapy, and comorbidity were factors associated with an increased number of hospitalizations. Conclusions: Unplanned hospitalizations are frequent, disruptive, and costly. This article defines areas for further exploration to identify patients at high risk for unexpected complications. Implications for Nursing: This article represents a foundation for development of risk models to enable nursing evaluation of patient risk for chemotherapy treatment interruption and unplanned hospitalization.
AB - Purpose/Objectives: To determine predictors of unplanned hospitalizations in patients with lung cancer to receive chemotherapy in the outpatient setting and examine the potential financial burden of these events. Design: Retrospective, longitudinal cohort study. Setting: The National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database. Sample: Of 104,388 incident cases of lung cancer diagnosed from 2005-2009, 2,457 cases of patients with lung cancer who received outpatient chemotherapy were identified. Patients were aged 66 years or older at diagnosis, had uninterrupted Medicare Part A and B coverage with no health maintenance organization enrollment, and received IV chemotherapy at least once. Methods: Generalized estimating equations was used. Main Research Variables: Patient age, sex, race, marital status, degree of residential urbanization, median income, education level, stage, receipt of radiation therapy, and comorbidities. Findings: Younger age, non-White race, lower education, higher income, receipt of radiation therapy, and lack of preexisting comorbidity were significant predictors of the likelihood of an initial unplanned hospitalization for lung cancer. Non-White race, receipt of radiation therapy, and comorbidity were factors associated with an increased number of hospitalizations. Conclusions: Unplanned hospitalizations are frequent, disruptive, and costly. This article defines areas for further exploration to identify patients at high risk for unexpected complications. Implications for Nursing: This article represents a foundation for development of risk models to enable nursing evaluation of patient risk for chemotherapy treatment interruption and unplanned hospitalization.
KW - Chemotherapy
KW - Comorbidity
KW - Hospitalization
KW - Lung neoplasms
KW - SEER-medicare
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U2 - 10.1188/17.ONF.E203-E212
DO - 10.1188/17.ONF.E203-E212
M3 - Article
C2 - 28820513
AN - SCOPUS:85028304629
SN - 0190-535X
VL - 44
SP - E203-E212
JO - Oncology nursing forum
JF - Oncology nursing forum
IS - 5
ER -