Date of Award
Open Access Thesis
Medical Doctor (MD)
Hospital-at-Home (HaH) is a unique care model that allows for the provision of inpatient level care in the patient’s home. HaH has been used to facilitate early discharge from inpatient care or to substitute entirely for an inpatient admission. Hospital-at-Home has been shown to have similar clinical outcomes to inpatient care, while reducing cost and complications associated with inpatient admission. Application of the HaH model to patients with oncologic disease is a promising avenue to reduce healthcare costs while improving patients’ quality of life by increasing time spent at home. A major challenge to implementing a Hospital-at-Home program for cancer patients is the lack of validated criteria to inform the selection of admissions most suitable for home-based hospital level care.
Methods and Results:
Admissions to the Yale New Haven Smilow Cancer Hospital’s medical oncology floor in New Haven from Jan 2015- Jun 2019 were included in the analysis (N=3,322). The analysis focused entirely on patients with solid tumors hospitalized for unplanned admissions. The definition of suitability for HaH was based on a substitutive model and identified admissions that did not receive any services that would be difficult to deliver or were inconsistent with safe care in the home. Twenty-seven-point-three percent of admissions were identified as suitable for HaH, accounting for 908 admissions during the study period. Admissions that were suitable for HaH were shorter in duration (2.79 vs 6.41 days), more likely to result in discharge home rather than to other healthcare facility (87.5% vs 69.5%), and less likely to be readmitted in the following 30 days (25.3% vs 31.5%). A predictive logistic model constructed using a purposeful selection process identified 13 statistically significant predictors for suitability for HaH: Black/African American race (vs all other), observation status, patient evaluated in the emergency department (ED) or oncology extended care center (vs admitted directly from clinic), primary admission diagnosis of secondary malignancy, primary admission diagnosis of fever, primary admission diagnosis of digestive diseases, oncology diagnosis of secondary or unknown malignancy, initial pre-admission respiratory rate >20 breaths/min, final pre-admission systolic blood pressure <100 mmHg, final pre-admission temperature >100o F, Sodium < 135 mmol/L, hemoglobin <10 g/dL and ED visit in the previous 90 days. The predictive model had moderate discrimination (c-statistic 0.686) and was well calibrated in the validation cohort (Hosmer-Lemeshow P-value >0.05).
We describe the first predictive model of suitability for Hospital-at-Home in oncology patients. This model serves as a starting point to creating selection criteria and can be further refined and tested in prospective validation and pilot studies. The modest discrimination of the model indicates that much of the variability that allows for accurate prediction is still unaccounted for and would benefit from larger studies and inclusion of clinician judgement.
Desai, Keval Niraj, "Development And Validation Of A Predictive Model For Oncology Hospital-At-Home" (2020). Yale Medicine Thesis Digital Library. 3894.
This Article is Open Access