Impact of early telemedicine follow-up on 30-Day hospital readmissions.

INTRODUCTION: Telemedicine is increasing in popularity but the impact of this shift on patient outcomes has not been well described. Prior data has shown that early post-discharge office visits can reduce readmissions. However, it is unknown if routine use of telemedicine visits for this purpose is similarly beneficial. MATERIALS AND METHODS: We conducted a retrospective observational study using electronic health records data to assess if the rate of 30-day hospital readmissions differed between modality of visit for primary care or cardiology post-discharge follow-up visits. RESULTS: Compared to discharges with completed in-person follow-up visits, the adjusted odds of readmission for those with telemedicine follow-up visits was not significantly different (odds ratio [OR] 0.96, 95% confidence interval [CI] 0.61 to 1.51, P = 0.86). CONCLUSIONS: Our study showed that 30-day readmission rate did not differ significantly according to the modality of visit. These results provide reassurance that telemedicine visits are a safe and viable alternative for primary care or cardiology post-hospitalization follow-up.

Telemedicine is associated with reduced socioeconomic disparities in outpatient clinic no-show rates.

INTRODUCTION: The global pandemic caused by coronavirus (COVID-19) sped up the adoption of telemedicine. We aimed to assess whether factors associated with no-show differed between in-person and telemedicine visits. The focus is on understanding how social economic factors affect patient no-show for the two modalities of visits. METHODS: We utilized electronic health records data for outpatient internal medicine visits at a large urban academic medical center, from February 1, 2020 to December 31, 2020. A mixed-effect logistic regression was used. We performed stratified analysis for each modality of visit and a combined analysis with interaction terms between exposure variables and visit modality. RESULTS: A total of 111,725 visits for 72,603 patients were identified. Patient demographics (age, gender, race, income, partner), lead days, and primary insurance were significantly different between the two visit modalities. Our multivariable regression analyses showed that the impact of sociodemographic factors, such as Medicaid insurance (OR 1.23, p < 0.01 for in-person; OR 1.03, p = 0.57 for telemedicine; p < 0.01 for interaction), Medicare insurance (OR 1.11, p = 0.04 for in-person; OR 0.95, p = 0.32 for telemedicine; p = 0.03 for interaction) and Black race (OR 1.36, p < 0.01 for in-person; OR 1.20, p < 0.01 for telemedicine; p = 0.03 for interaction), on increased odds of no-show was less for telemedicine visits than for in-person visits. In addition, inclement weather and younger age had less impact on no-show for telemedicine visits. DISCUSSION: Our findings indicated that if adopted successfully, telemedicine had the potential to reduce no-show rate for vulnerable patient groups and reduce the disparity between patients from different socioeconomic backgrounds.

The Promise of Remote Patient Monitoring: Lessons Learned During the COVID-19 Surge in New York City.

The coronavirus pandemic catalyzed a digital health transformation, placing renewed focus on using remote monitoring technologies to care for patients outside of hospitals. At NewYork-Presbyterian, the authors expanded remote monitoring infrastructure and developed a COVID-19 Hypoxia Monitoring program-a critical means through which discharged COVID-19 patients were followed and assessed, enabling the organization to maximize inpatient capacity at a time of acute bed shortage. The pandemic tested existing remote monitoring efforts, revealing numerous operating challenges including device management, centralized escalation protocols, and health equity concerns. The continuation of these programs required addressing these concerns while expanding monitoring efforts in ambulatory and transitions of care settings. Building on these experiences, this article offers insights and strategies for implementing remote monitoring programs at scale and improving the sustainability of these efforts. As virtual care becomes a patient expectation, the authors hope hospitals recognize the promise that remote monitoring holds in reenvisioning health care delivery.

Hospital Readmissions After Implementation of a Discharge Care Program for Patients with COVID-19 Illness.

BACKGROUND: The surge of coronavirus 2019 (COVID-19) hospitalizations in New York City required rapid discharges to maintain hospital capacity. OBJECTIVE: To determine whether lenient provisional discharge guidelines with remote monitoring after discharge resulted in safe discharges home for patients hospitalized with COVID-19 illness. DESIGN: Retrospective case series SETTING: Tertiary care medical center PATIENTS: Consecutive adult patients hospitalized with COVID-19 illness between March 26, 2020, and April 8, 2020, with a subset discharged home INTERVENTIONS: COVID-19 Discharge Care Program consisting of lenient provisional inpatient discharge criteria and option for daily telephone monitoring for up to 14 days after discharge MEASUREMENTS: Fourteen-day emergency department (ED) visits and hospital readmissions RESULTS: Among 812 patients with COVID-19 illness hospitalized during the study time period, 15.5% died prior to discharge, 24.1% remained hospitalized, 10.0% were discharged to another facility, and 50.4% were discharged home. Characteristics of the 409 patients discharged home were mean (SD) age 57.3 (16.6) years; 245 (59.9%) male; 27 (6.6%) with temperature ≥ 100.4 °F; and 154 (37.7%) with oxygen saturation < 95% on day of discharge. Over 14 days of follow-up, 45 patients (11.0%) returned to the ED, of whom 31 patients (7.6%) were readmitted. Compared to patients not referred, patients referred for remote monitoring had fewer ED visits (8.3% vs 14.1%; OR 0.60, 95% CI 0.31-1.15, p = 0.12) and readmissions (6.9% vs 8.3%; OR 1.15, 95% CI 0.52-2.52, p = 0.73). LIMITATIONS: Single-center study; assignment to remote monitoring was not randomized. CONCLUSIONS: During the COVID-19 surge in New York City, lenient discharge criteria in conjunction with remote monitoring after discharge were associated with a rate of early readmissions after COVID-related hospitalizations that was comparable to the rate of readmissions after other reasons for hospitalization before the COVID pandemic.

Psychological distress, coping behaviors, and preferences for support among New York healthcare workers during the COVID-19 pandemic.

OBJECTIVE: The mental health toll of COVID-19 on healthcare workers (HCW) is not yet fully described. We characterized distress, coping, and preferences for support among NYC HCWs during the COVID-19 pandemic. METHODS: This was a cross-sectional web survey of physicians, advanced practice providers, residents/fellows, and nurses, conducted during a peak of inpatient admissions for COVID-19 in NYC (April 9th-April 24th 2020) at a large medical center in NYC (n = 657). RESULTS: Positive screens for psychological symptoms were common; 57% for acute stress, 48% for depressive, and 33% for anxiety symptoms. For each, a higher percent of nurses/advanced practice providers screened positive vs. attending physicians, though housestaff's rates for acute stress and depression did not differ from either. Sixty-one percent of participants reported increased sense of meaning/purpose since the COVID-19 outbreak. Physical activity/exercise was the most common coping behavior (59%), and access to an individual therapist with online self-guided counseling (33%) garnered the most interest. CONCLUSIONS: NYC HCWs, especially nurses and advanced practice providers, are experiencing COVID-19-related psychological distress. Participants reported using empirically-supported coping behaviors, and endorsed indicators of resilience, but they also reported interest in additional wellness resources. Programs developed to mitigate stress among HCWs during the COVID-19 pandemic should integrate HCW preferences.