Unplanned 30-Day Readmissions in a General Internal Medicine Hospitalist Service at a Comprehensive Cancer Center

Abstract

Purpose: Hospital readmissions are considered by the Centers for Medicare and Medicaid as a metric for quality of health care delivery. Robust data on the readmission profile of patients with cancer are currently insufficient to determine whether this measure is applicable to cancer hospitals as well. To address this knowledge gap, we estimated the unplanned readmission rate and identified factors influencing unplanned readmissions in a hospitalist service at a comprehensive cancer center. Methods:We retrospectively analyzed unplanned 30-day readmission of patients discharged from the General Internal Medicine Hospitalist Service at a comprehensive cancer center between April 1, 2012, and September 30, 2012. Multiple independent variables were studied using univariable and multivariable logistic regression models, with generalized estimating equations to identify risk factors associated with readmissions. Results:We observed a readmission rate of 22.6% in our cohort. The median time to unplanned readmission was 10 days. Unplanned readmission was more likely in patients with metastatic cancer and those with three or more comorbidities. Patients discharged to hospice were less likely to be readmitted (all P values Ͻ .01). Conclusion:We observed a high unplanned readmission rate among our population of patients with cancer. The risk factors identified appear to be related to severity of illness and open up opportunities for improving coordination with primary care physicians, oncologists, and other specialists to manage comorbidities, or perhaps transition appropriate patients to palliative care. Our findings will be instrumental for developing targeted interventions to help reduce readmissions at our hospital. Our data also provide direction for appropriate application of readmission quality measures in cancer hospitals.

Symptoms of posttraumatic stress disorder among hospitalized patients with cancer

“…For purposeful selection, we included covariates that were associated at a significance level < .10 and any confounders (defined as any variable that changed the parameter estimate of another variable by >20% when removed from the model) in the final model. To examine relationships between continuous PTSD symptoms and patients' physical and psychological symptom burden, we used linear regression models adjusted for potential confounders, including age, sex, marital status, education level, comorbidities (Charlson Comorbidity Index), cancer type, presence of incurable cancer, and time since cancer diagnosis . We also used Fisher's exact test to compare the rates of moderate/severe ESAS symptoms for patients with and without a positive screen for PTSD symptoms.…”

“…We also used Fisher's exact test to compare the rates of moderate/severe ESAS symptoms for patients with and without a positive screen for PTSD symptoms. To investigate the relationships between continuous PTSD symptoms and time to hospital readmission within 90 days, we used Cox proportional hazards regression models adjusted for potential confounders, including age, sex, marital status, education level, comorbidities, cancer type, presence of incurable cancer, time since cancer diagnosis, length of stay during the index hospital admission, PHQ‐4 depression symptoms, PHQ‐4 anxiety symptoms, and ESAS physical symptoms . All reported P values are 2‐sided, with P < .05 considered statistically significant.…”

An ED pilot intervention to facilitate outpatient acute care for cancer patients

“…Based on prior research indicating that approximately 1 in 5 hospital admissions among patients with cancer may be avoidable, [3][4][5] we created and pilot-tested a pragmatic intervention to reduce hospital admissions among patients with solid-tumor malignancies. We hypothesized that embedding a medical oncologist in the ED would increase outpatient discharges in cancer A C C E P T E D M A N U S C R I P T…”

“…Approximately 1 in 5 of these hospitalizations may be avoidable, as evaluated by various criteria [3][4][5]. The majority of unplanned hospitalizations in cancer patients transit through the ED, a clinical environment where high patient acuity, inconsistent access to outpatient resources, and the absence of longitudinal patient relationships all create barriers to outpatient discharge plans.…”

Geriatric assessment factors are associated with mortality after hospitalization in older adults with cancer

“…Readmission related to cancer is common and occurs for new diagnoses, symptoms from cancer progression, and complications of procedures [31,32]. We recently identified dependence on IADLs, use of potentially inappropriate medications, and higher risk reasons for index admission to be associated with readmission [33].…”