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Impact of Telemedicine Monitoring of Community ICUs on Interhospital Transfers.

ABSTRACT: OBJECTIVES:To study the effects of tele-ICU monitoring on interhospital transfers from community-based ICUs to the quaternary care hospital at Mayo Clinic, Rochester, MN. DESIGN:This is a retrospective review of data on interhospital transfers comparing trends prior to tele-ICU implementation to those following implementation. SETTING:Tele-ICU programs are increasingly utilized to fill resource gaps in caring for critically ill patients. How such programs impact population and bed management within a healthcare system are not known. Mayo Clinic serves as quaternary referral care center for hospitals in the region within the Mayo Clinic Health System. In August 2013, we implemented tele-ICU monitoring at six Mayo Clinic Health System hospital ICUs. SUBJECTS:All adult ICU admissions during the study period (preimplementation phase: January 1, 2012, to December 31, 2012; and postimplementation phase: January 1, 2014, to December 31, 2014) in any of the six specified community ICUs were included in the study. MEASUREMENTS AND MAIN RESULTS:Interhospital transfers significantly increased post institution of tele-ICU (p = 0.040) and was attributed primarily to transfer from less specialized ICUs (p = 0.037) as compared with more resource-intensive ICUs (p = 0.88). However, for such patient transfers, there were no significant differences before and after severity of illness scores, ICU mortality, or inhospital mortality. CONCLUSION:In a regional healthcare system, implementation of a tele-ICU program is associated with an increase in interhospital transfers from less resourced ICUs to the referral center, a trend that is not readily explained by increased severity of illness.

SUBMITTER: Pannu J

PROVIDER: S-EPMC5511079 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Impact of Telemedicine Monitoring of Community ICUs on Interhospital Transfers.

Pannu Jasleen J Sanghavi Devang D Sheley Todd T Schroeder Darrell R DR Kashyap Rahul R Marquez Alberto A Daniels Craig E CE Brown Daniel R DR Caples Sean M SM

Critical care medicine 20170801 8

<h4>Objectives</h4>To study the effects of tele-ICU monitoring on interhospital transfers from community-based ICUs to the quaternary care hospital at Mayo Clinic, Rochester, MN.<h4>Design</h4>This is a retrospective review of data on interhospital transfers comparing trends prior to tele-ICU implementation to those following implementation.<h4>Setting</h4>Tele-ICU programs are increasingly utilized to fill resource gaps in caring for critically ill patients. How such programs impact population ...[more]

PMID: 28481753

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Project description:ObjectivesThis quality improvement project sought to enhance clinical information sharing for interhospital transfers to an inpatient hepatology service comprised of internal medicine resident frontline providers (housestaff) with the specific aims of making housestaff aware of 100% of incoming transfers and providing timely access to clinical summaries.InterventionsIn February 2020, an email notification system to senior medicine residents responsible for patient triage shared planned arrival time for patients pending transfer. In July 2020, a clinical data repository ("Transfer Log") updated daily by accepting providers (attending physicians and subspecialty fellows) became available to senior medicine residents responsible for triage.MethodsLikert scale surveys were administered to housestaff before email intervention (pre) and after transfer log intervention (post). The time from patient arrival to team assignment (TTA) in the electronic medical record was used as a proxy for time to patient assessment and was measured pre- and postinterventions; >2 hours to TTA was considered an extreme delay.ResultsHousestaff reported frequency of access to clinical information as follows: preinterventions 4/31 (13%) sometimes/very often and 27/31 (87%) never/rarely; postinterventions 11/26 (42%) sometimes/very often and 15/26 (58%) never/rarely (p = 0.02). Preinterventions 12/39 (31%) felt "not at all prepared" versus 27/39 (69%) "somewhat" or "adequately"; postinterventions 2/24 (8%) felt "not at all prepared" versus 22/24 (92%) somewhat/adequately prepared (p = 0.06). There was a significant difference in mean TTA between pre- and posttransfer log groups (62 vs. 40 minutes, p = 0.01) and a significant reduction in patients with extreme delays in TTA post-email (18/180 pre-email vs. 7/174 post-email, p = 0.04).ConclusionEarly notification and increased access to clinical information were associated with better sense of preparedness for admitting housestaff, reduction in TTA, and reduced frequency of extreme delays in team assignment.

Project description:ImportanceStroke treatment is exquisitely time sensitive. The door-in-door-out (DIDO) time, defined as the total time spent in the emergency department (ED) at a transferring hospital, is an important quality metric for the care of acute stroke. However, little is known about the contributions of specific process steps to delays and disparities in DIDO time.ObjectiveTo quantify process steps and their association with DIDO times at transferring hospitals among patients with acute ischemic stroke (AIS).Design, setting, and participantsThis retrospective cohort study analyzed patients in the American Heart Association Get With the Guidelines-Stroke registry with AIS presenting between January 1, 2019, to December 31, 2021, and transferred from the presenting hospital ED to another acute care hospital for evaluation of thrombolytics, endovascular therapy, or postthrombolytic care. Data were analyzed from July 8 to October 13, 2023.ExposuresIntervals of ED care of ischemic stroke: door-to-imaging and imaging-to-door times.Main outcomes and measuresThe primary outcome was DIDO time. Multivariate generalized estimating equations regression models were performed to compare contributions of interval process times to explain variation in DIDO time, controlling for patient- and hospital-level characteristics.ResultsAmong 28 887 patients (50.5% male; mean [SD] age, 68.3 [14.8] years; 5.5% Hispanic, 14.7% non-Hispanic Black, and 73.2% non-Hispanic White), mean (SD) DIDO time was 171.4 (149.5) minutes, mean (SD) door-to-imaging time was 18.3 (34.1) minutes, and mean (SD) imaging-to-door time was 153.1 (141.5) minutes. In the model adjusting for door-to-imaging time, the following were associated with longer DIDO time: age 80 years or older (compared with 18-59 years; 5.97 [95% CI, 1.02-10.92] minutes), female sex (5.21 [95% CI, 1.55-8.87] minutes), and non-Hispanic Black race (compared with non-Hispanic White 10.09 [95% CI, 4.21-15.96] minutes). In the model including imaging-to-door time as a covariate, disparities in DIDO by age and female sex became nonsignificant, and the disparity by Black race was attenuated (2.32 [95% CI, 1.09-3.56] minutes).Conclusions and relevanceIn this national cohort study of interhospital transfer of patients with AIS, delays in DIDO time by Black race, older age (≥80 years), and female sex were largely explained by the imaging-to-door period, suggesting that future systems interventions should target this interval to reduce these disparities. While existing guidelines and care resources heavily focus on reducing door-to-imaging times, further attention is warranted to reduce imaging-to-door times in the management of patients with AIS who require interhospital transfer.

Project description:Background and objectiveThe Coronavirus Aid, Relief, and Economic Security Act led to the rapid implementation of telemedicine across health care office settings. Whether this transition to telemedicine has any impact on missed appointments is yet to be determined. This study examined the relationship between telemedicine usage and missed appointments during the COVID-19 pandemic.MethodThis retrospective study used appointment-level data from 55 Federally Qualified Health Centre clinics in Texas between March and November 2020. To account for the nested data structure of repeated appointments within each patient, a mixed-effects multivariable logistic regression model was used to examine associations between telemedicine use and missed appointments, adjusting for patient sociodemographic characteristics, geographic classification, past medical history, and clinic characteristics. The independent variable was having a telemedicine appointment, defined as an audiovisual consultation started and finalized via a telemedicine platform. The outcome of interest was having a missed appointment (yes/no) after a scheduled and confirmed medical appointment. Results from this initial model were stratified by appointment type (in-person vs. telemedicine).ResultsThe analytic sample included 278,171 appointments for 85,413 unique patients. The overall missed appointment rate was 18%, and 25% of all appointments were telemedicine appointments. Compared to in-person visits, telemedicine visits were less likely to result in a missed appointment (OR = 0.87, p < .001). Compared to Whites, Asians were less likely to have a missed appointment (OR = 0.82, p < .001) while African Americans, Hispanics, and American Indians were all significantly more likely to have missed appointments (OR = 1.61, p < .001; OR = 1.19, p = .01; OR = 1.22, p < .01, respectively). Those accessing mental health services (OR = 1.57 for in-person and 0.78 for telemedicine) and living in metropolitan areas (OR = 1.15 for in-person and 0.82 for telemedicine) were more likely to miss in-person appointments but less likely to miss telemedicine appointments. Patients with frequent medical visits or those living with chronic diseases were more likely to miss in-person appointments but less likely to miss telemedicine appointments.ConclusionsTelemedicine is strongly associated with fewer missed appointments. Although our findings suggest a residual lag in minority populations, specific patient populations, including those with frequent prior visits or chronic conditions, those seeking mental health services, and those living in metropolitan areas were less likely to miss telemedicine appointments than in-person visits. These findings highlight how telemedicine can enable effective and accessible care by reducing missed healthcare appointments.KEY MESSAGESTelemedicine was associated with 13% lower odds of missed appointments.Patients with frequent medical visits or those living with chronic diseases were less likely to miss telemedicine appointments but more likely to miss in-person appointments.Patients seeking mental health services were less likely to miss telemedicine appointments but more likely to miss in-person appointments.Similarly, those living in metropolitan areas were less likely to miss telemedicine appointments but more likely to miss in-person appointments.

Dataset Information

Impact of Telemedicine Monitoring of Community ICUs on Interhospital Transfers.

Publications

Impact of Telemedicine Monitoring of Community ICUs on Interhospital Transfers.

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