Transforming Transitional Care: Early Hospital Discharge through the Care at Home Program

Every year, thousands of patients face the challenging transition from hospital to home, resulting in high readmission rates and excessive resource use. Our telemedicine-based Care at Home (CaH) program, which facilitates early discharge, was assessed for its impact on 30-day readmissions, length of hospital stay (LoS), and total charges.

Retrospective cohort study comparing standard inpatient care with the CaH program, which features telemedicine support and continuous monitoring provided by nurses, paramedics, and physicians after early hospital discharge. This program prioritizes patients at higher risk for readmission.

Data were derived from 2866 hospital admissions covering select diagnostic-related groups (DRGs) between January and December 2023. Of these, 215 patients were enrolled in CaH and 2651 received standard inpatient care.

We analyzed 30-day readmission rates, LoS, and total charges. Categorical variables were evaluated using χ² tests, and the Mann-Whitney U (MWU) test was applied for skewed continuous variables. A Cox proportional hazards model assessed time to readmission, using a 1.15 noninferiority margin.

The 30-day readmission rate was 11.2% in the CaH group and 12.8% in the control group (P = .57). Hazard ratios (HRs) favored CaH but exceeded the 1.15 noninferiority margin (adjusted HR, 0.82; 95% CI, 0.54-1.24; P = .35). CaH did achieve significantly lower LoS (mean 4.7 vs 7.7 days; MWU P < .001) and total charges (mean $54,491 vs $84,245; MWU P < .001). DRG-specific analyses revealed variable readmission outcomes but consistent reductions in LoS and costs across most DRGs for patients in CAH.

CaH yielded comparable 30-day readmission rates while significantly lowering LoS and total costs, although it did not achieve the predefined noninferiority margin. Potential selection bias and differences in patient acuity may have influenced these findings. Further research should focus on refining patient selection, developing condition-specific protocols, and examining broader applications of telemedicine-driven early discharge models.