Virtual Transition of Care Clinics and Associated Readmission Rates: 3-Year Retrospective Cohort Study

Introduction

Unexpected return to the hospital reflects systemic challenges in health care delivery and places a financial strain on the nation’s health system [1]. Postdischarge follow-ups within 7 days is a well-established protective mechanism to reduce the risk of readmission and mitigate health care disparities but are limited by access challenges and physician shortages [2-5]. Transitions of care clinics have shown benefit in readmission reduction but may be cost prohibitive and logistically challenging [4,5]. Virtual postdischarge clinics may achieve similar benefits with fewer costs and present an opportunity to enhance postdischarge access [6].

Methods

Overview

At the University of California, San Diego Health, we implemented a hospital medicine physician-led virtual transitions of care (VToC) clinic, focused on postdischarge clinical management, medication reconciliation, primary care provider (PCP) repatriation, and specialty care navigation, with the aim of reducing repeat hospitalization.

Based on internal pilot data showing a favorable readmission impact for patients with moderate risk of readmission, we created a criteria-based order to trigger referral for patients (aged 18 years and older) discharged from the hospital medicine service line. The discharging providers were automatically prompted at discharge to refer patients to the clinic if patients had a LACE+ index (a readmission risk prediction index based on length of stay, acuity of admission, comorbidities, and emergency department visit history) between 50 and 75 [7]. Patients with LACE+ scores outside this range could be referred at provider discretion. Patients were excluded from appointment scheduling if they were discharged to a care facility or hospice or had an existing PCP appointment within 7 days of discharge.

The virtual clinic was supported by 12 hospitalists, 2 medical assistants, 1 pharmacist and an on-demand interpreter service. Medical assistants contacted eligible patients to schedule web-based video visits. VToC visits were occasionally converted to telephone encounters when patients faced technical barriers, which occurred in fewer than 5% of cases and thus were not considered a distinct comparison group for analysis. Patients received phone call reminders 1 business day prior to scheduled appointments. Pharmacists conducted previsit medication reviews to identify fill history gaps, dosing inconsistencies, and potential drug-drug interactions. Note templates guided VToC providers in addressing medication management, social determinants of health, barriers to follow-up, and care coordination. A standardized electronic handoff was routed to the patient’s PCP and relevant specialists summarizing the reason for hospitalization, follow-up needs, and timing recommendations. Additionally, post-VToC visit communication was sent to the discharging hospitalist to highlight potential care lapses and support quality improvement efforts.

Data were collected from the electronic health records using standard SQL queries. These included demographics (ages grouped as <45, 45-64, and ≥65 years; sex; and race and ethnicity); VToC status (yes or no); PCP (University of California San Diego or other); LACE+ score (<50, 50-75, or >75); and 30-day all-cause readmission. Patient characteristics were analyzed by VToC status (yes or no). A VToC status of “no” indicates patients who were discharged from the medicine service line to home and not seen in our clinic (because they did not meet eligibility criteria or could not be reached). Patients were excluded from analysis if they had missing demographic or clinical data. Readmission rates were analyzed for VToC status and by LACE+ score. Chi-square analysis was used to compare characteristics by VToC status with a P<.05 considered significant. Readmission rates (%) by VToC status stratified by LACE+ decile are reported. Error bars were calculated using 95% CIs. A multivariable logistic regression analysis was performed to assess independent associations with unplanned hospital readmission. Variables included in the model included age group, sex, race and ethnicity, PCP affiliation (UCSD versus non-UCSD), LACE+ score, and VToC enrollment. All analyses were conducted using the SPSS Statistics software suite (version 27.0; IBM Corporation).

Ethical Considerations

This study was conducted in an Institutional Review Board–exempt fashion in accordance with the ethical standards of the University of California San Diego Human Research Protection Program and the Office for Human Research Protections and adhered to the Helsinki Declaration of 1975, as revised in 2000.

Results

There were 25,970 patients identified for the study period of September 1, 2021, through September 17, 2024. A total of 527 (0.02%) patients had missing data and were excluded from the analysis. Of the 25,443 patients included in the study, 2314 (9.1%) were seen in VToC after discharge and 23,129 (90.9%) had standard of care follow-up. Table 1 shows the demographic comparisons of patients who were seen in VToC versus those who were not for the same time period.

The overall 30-day readmission rate for patients seen in the VToC clinic was 14.9% (344/2314) compared to 20.1% (4659/23,129) in the benchmark group (Table 1; P<.001). In the regression model, the absence of a VToC clinic was independently associated with increased odds of readmission (odds ratio 1.37; 95% CI 1.21-1.54; P<.001). In the multivariable regression analysis, younger age, female sex, non-Hispanic Asian race or ethnicity, higher LACE+ scores, and non-participation in the VToC program were each independently associated with increased odds of hospital readmission." should be changed to "In the multivariable regression analysis, younger age, female sex, Hispanic and Non Hispanic Black/African American race or ethnicity, higher LACE+ scores, and nonparticipation in the VToC program were each independently associated with increased odds of hospital readmission. This analysis is available in Multimedia Appendix 1. Decile matching was performed to account for the difference in distribution of LACE+ in the VToC and non-VToC groups. Analysis of LACE+ decile groups revealed that the impact of readmission reduction was most prominent among patients with LACE+ scores ranging between 50-75; however, across most groups VTOC performed better than non-VToC (Figure 1).

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Discussion

Here we present a hospitalist-led postdischarge virtual clinic aimed at improving transitions of care for patients. For patients at moderate risk, a VToC visit was associated with a significantly lower rate of readmission. Notably, our intervention group had a higher proportion of female and Hispanic patients, both of which were associated with increased odds of readmission in regression analyses.

This observational study is subject to selection bias, as clinic attendance could be influenced by patient-specific factors that influence readmission. Approximately 13% of patients referred to the VToC were not reached, which may introduce additional bias, as these individuals may differ in ways that influence outcomes. While we did not capture detailed data on patient acceptance, we addressed this limitation by matching the comparator group on readmission risk to reduce confounding. However, the stratified analysis according to the LACE+ index provides strong evidence in support of the impact of the program, and the positive impact observed is consistent with broader evidence that timely postdischarge access reduces readmission risk. VToC clinics address a critical gap in the care continuum while also providing the inherent benefits of telemedicine [6,8].

Results from this initiative are promising for the feasibility of telemedicine-based transitional care programs to promote the quadruple aim of improving population health, enhancing the care experience, reducing cost, and advancing care equity [9].