Kevin Chen1,2, Keval Desai1, Soundari Sureshanand3,4, Kerin Adelson1,5, Jeremy I Schwartz1, Cary P Gross1,2, Sarwat I Chaudhry1,2. 1. Section of General Internal Medicine, Yale School of Medicine, New Haven, CT. 2. National Clinician Scholars Program, Yale School of Medicine and VA Connecticut Healthcare System, New Haven, CT. 3. Joint Data Analytics Team, Yale University, New Haven, CT. 4. Yale Center for Clinician Investigation, New Haven, CT. 5. Smilow Cancer Hospital at Yale New Haven Health, New Haven, CT.
Abstract
PURPOSE: Hospital at home (HaH) is a means of providing inpatient-level care at home. Selection of admissions potentially suitable for HaH in oncology is not well studied. We sought to create a predictive model for identifying admissions of patients with cancer, specifically solid-tumor malignancies, potentially suitable for HaH. METHODS: In this observational study, we analyzed admissions of patients with solid-tumor malignancies and unplanned admissions (January 1, 2015, to June 12, 2019) at an academic, urban cancer hospital. Potential suitability for HaH was the primary outcome. Admissions were considered potentially suitable if they did not involve escalation of care, rapid response evaluation, in-hospital death, telemetry, surgical procedure, consultation to a procedural service, advanced imaging, transfusion, restraints, and nasogastric tube placement. Admission source, patient demographics, vital signs, laboratory test results, comorbidities, admission and active cancer diagnoses, and recent hospital utilization were included as candidate variables in a multivariable logistic regression model. RESULTS: Of 3,322 admissions, 905 (27.2%) patients were potentially suitable for HaH. After variable selection in the derivation cohort (n = 1,097), thirteen factors predicted potential suitability: admission source; temperature and respiratory rate at presentation; hemoglobin; breast cancer, GI cancer, or malignancy of secondary or ill-defined origin; admission for genitourinary, musculoskeletal, or neurologic symptoms, intestinal obstruction or ileus, or evaluation of secondary malignancy; and emergency department visit in prior 90 days. Model c-statistics were 0.71 (95% CI, 0.68 to 0.75) and 0.63 (0.59 to 0.67) in the derivation and validation (n = 1,095) cohorts. CONCLUSION: Hospital admissions of patients potentially suitable for HaH may be identifiable using data available at admission.
PURPOSE: Hospital at home (HaH) is a means of providing inpatient-level care at home. Selection of admissions potentially suitable for HaH in oncology is not well studied. We sought to create a predictive model for identifying admissions of patients with cancer, specifically solid-tumor malignancies, potentially suitable for HaH. METHODS: In this observational study, we analyzed admissions of patients with solid-tumor malignancies and unplanned admissions (January 1, 2015, to June 12, 2019) at an academic, urban cancer hospital. Potential suitability for HaH was the primary outcome. Admissions were considered potentially suitable if they did not involve escalation of care, rapid response evaluation, in-hospital death, telemetry, surgical procedure, consultation to a procedural service, advanced imaging, transfusion, restraints, and nasogastric tube placement. Admission source, patient demographics, vital signs, laboratory test results, comorbidities, admission and active cancer diagnoses, and recent hospital utilization were included as candidate variables in a multivariable logistic regression model. RESULTS: Of 3,322 admissions, 905 (27.2%) patients were potentially suitable for HaH. After variable selection in the derivation cohort (n = 1,097), thirteen factors predicted potential suitability: admission source; temperature and respiratory rate at presentation; hemoglobin; breast cancer, GI cancer, or malignancy of secondary or ill-defined origin; admission for genitourinary, musculoskeletal, or neurologic symptoms, intestinal obstruction or ileus, or evaluation of secondary malignancy; and emergency department visit in prior 90 days. Model c-statistics were 0.71 (95% CI, 0.68 to 0.75) and 0.63 (0.59 to 0.67) in the derivation and validation (n = 1,095) cohorts. CONCLUSION: Hospital admissions of patients potentially suitable for HaH may be identifiable using data available at admission.
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