Symptom-related emergency department visits and hospital admissions during ambulatory cancer treatment.
BACKGROUND
People with cancer experience symptoms related to the disease and treatments. Symptom distress has a negative impact on quality of life (QoL). Attending to symptoms and side effects of treatment promotes safe and effective delivery of therapies and may prevent or reduce emergency department visits (EDVs) and unplanned hospital admissions (HAs). There is limited evidence examining symptom-related EDVs or HAs (sx-EDV/HAs) and interventions in ambulatory oncology patients.


OBJECTIVE
To examine factors associated with sx-EDV/HAs in ambulatory oncology patients receiving chemotherapy and/or radiation.


METHODS
This secondary analysis used data from a randomized controlled trial of ambulatory oncology patients (n = 663) who received the web-based Electronic Self-Report Assessment – Cancer intervention (symptom self-monitoring, tailored education, and communication coaching) or usual care with symptom self-monitoring alone. Group differences were described by summary statistics and compared by t test. Factors associated with the odds of at least 1 sx-EDV/HA were modeled using logistic regression.


RESULTS
98 patients had a total of 171 sx-EDV/HAs with no difference between groups. Higher odds of at least 1 sx-EDV/HA were associated with socioeconomic and clinical factors. The multivariable model indicated that work status, education level, treatment modality, and on-treatment Symptom Distress Scale-15 scores were signifcantly associated with having at least 1 sx-EDV/HA.


CONCLUSIONS
This is a secondary analysis not sized to determine cause and effect. The results have limited generalizability.


CONCLUSIONS
Most patients did not experience a sx-EDV/HA. Demographic and clinical factors predicted a sx-EDV/HA.
Phyllis F Cantor Center, Harvard Medical School, Boston, Massachusetts. maryl_siefert@dfci.harvard.edu
Mary Lou
ML
Siefert
Biostatistics & Computational Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts.
Traci M
TM
Bonquist
Phyllis F Cantor Center, Department of Medicine, Harvard Medical School, Boston, Massachusetts.
Donna L
DL
Berry
Biostatistics & Computational Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts.
Fangxin
F
Hong