Evaluation of the Clinical Impact of Different Telemedicine Practices in Intensive Care Units

Telemedicine, Critical Care, Intensive Care Units

Telemedicine, Critical care, Intensive care units

The objective of this study is to assess whether an intervention package via telemedicine consisting of daily multidisciplinary rounds with a specialist in intensive care medicine, an intervention package provided by a specialized multiprofessional team (nursing, physical therapy and clinical pharmacy) and a management intervention package, focused on quality and safety, reduces the length of stay in ICU patients in Brazil. Our hypothesis is that the intervention package via telemedicine has the potential to decrease the length of stay in ICU patients in Brazil. The study provides for the implementation of three interventions in association via telemedicine. * Daily multidisciplinary rounds conducted by a physician specialized in intensive care medicine * Intervention package by specialized multidisciplinary team (nursing, physiotherapy and clinical pharmacy). * Management intervention package (quality and safety). The main questions it aims to answer are: * Length of stay in ICU * ICU mortality. * In-hospital mortality. * Ventilator-free days during the first 28 days. * ICU readmission within 48 hours. * Early reintubation (\<48h after elective extubation). * Ventilator-associated events. * Accidental extubation rate. * Patient Mobilization Density. * Adherence to maintaining the head-of-bed elevation. * Adequate prevention of venous thromboembolism. * Rate of patient-days under adequate sedation. * Rate of patients-days with oral or enteral nutrition. * Rate of patients with adequate glycemic control. * Rate of patients-days within normoxemia. * Rate of central venous catheter use. * Central venous catheter dwell time. * Rate of indwelling urinary catheter use. * Indwelling urinary catheter dwell time. * Standard resource use. * Standardized mortality rate.

BACKGROUND: ICU beds represent a scarce and high cost resource. This scenario is aggravated by the scarcity and heterogeneous distribution of specialists in intensive care medicine in Brazil. Telemedicine is an innovative and promising technology, with the possibility of making the daily multidisciplinary round accessible with the presence of intensive care medicine specialists throughout the national territory. In a previous study (Telescope Trial I), it was demonstrated that daily multidisciplinary round conducted via telemedicine by a remotely located medical specialist is a safe and feasible practice. However, little is known about different modalities of telemedicine care in the ICU environment, more specifically, about the impact of interventions performed by a multidisciplinary team (non-medical) and management interventions (quality and safety). SAMPLE SIZE CALCULATION: A total sample size of 18,750 to 25,000 patients will be considered to detect a reduction in the length of stay in the ICU on a logarithmic scale of 0.1479 (equivalent to a 1.1-day reduction compared to the baseline), resulting from the intervention package with a significance level of 5% and a minimum power of 95%. This variation in total sample size is due to different estimates of patients per period in the 25 Brazilian ICUs in question. It is estimated that there will be a variation of 30 to 40 patients recruited per month per ICU. PRIMARY OUTCOME: The primary outcome of this trial at the patient level is ICU length of stay (LOS) defined as the time interval in hours between patients' ICU admission and the moment of ICU physical discharge times (i.e., transfer to another care facility or another hospital) or ICU death, as defined by the hospital's system date and time. Date and time will be entered by the health care worker responsible for data collection. ICU LOS will be derived in 24 hours periods with decimal place. SECONDARY OUTCOMES: The secondary outcomes of this study include assessing the impact of interventions implemented through telemedicine compared with a control period in the following outcomes: * ICU mortality. * In-hospital mortality. * Ventilator-free days during the first 28 days. * ICU readmission within 48 hours. * Early reintubation (\<48h after elective extubation). * Ventilator-associated events. * Accidental extubation rate. Process-of-care and quality indicators * Patient mobilization density in the ICU. * Adherence to maintaining the head-of-bed elevation (30°-45°). * Adequate prevention of venous thromboembolism. * Rate of patient-days under adequate sedation \[defined by Richmond agitation and sedation scale (RASS) = -3 to +1\]. * Rate of patients-days with oral or enteral nutrition. * Rate of patients with adequate glycemic control (defined as blood glucose = 70 to 180mg/dL). * Rate of patients-days within normoxemia (defined as peripheral oxygen saturation = 92 to 96%). * Rate of central venous catheter use. * Central venous catheter dwell time. * Rate of indwelling urinary catheter use. * Indwelling urinary catheter dwell time. Unit-level organizational outcomes • Classification of the unit according to the profiles defined by standard resource use (SRU) and standardized mortality rate (SMR). SRU reflects the observed-to-expected rate of resource utilization, estimated as ICU LOS for surviving patients and adjusted for the patient's severity of illness. SMR reflects the observed / expected rate, according to acute physiology score (SAPS 3) of hospital deaths. The profiles are a combination of SMR (above or below median) and SRU (above or below median): Each unit can be assigned to one of four groups: 'most efficient' (SMR and SRU \<median); 'least efficient' (SMR, SRU \>median); 'overachieving' (low SMR, high SRU), 'underachieving' (high SMR, low SRU). STATISTICAL ANALYSIS: All analyses will be described in detail in a statistical analysis plan, which will be finalized and submitted for publication before the database is closed and analyses begin. The primary statistical analyses will be conducted according to the intention-to-treat principle. Since ICUs will be randomized (not patients) and outcomes will be measured at the patient level, all analyses will be adjusted for clustering of data. The primary outcome, length of ICU stay, will be analyzed at the individual level using a generalized linear mixed model, including as fixed effect the group, and considering distributions that can fit an expected right skewness (such as truncated Poisson, Gamma or inverse Gaussian distribution, etc.), choosing the best fit according to model parameters. The goal of the mixed model is to be able to fit random vectors, taking into account the correlation of the observations of individuals in the same cluster. Thus, the model will have as random effect an intercept for each unit. To consider an eventual lack of balance, we will adjust the analysis model for the factors used in the stratification and for the outcome value at the unit level in the pre-randomization period (i.e., mean length of stay in the ICU of each unit), as suggested by the literature. Additionally, we will adjust for factors that have a correlation with length of stay, aiming to decrease variability between units, thus impacting intra cluster correlation and increasing the power of the study. The adjustment factors will be defined after the pre-randomization period data collection, and reported in a statistical analysis plan, published before closing the study database, as specified above. These factors are about severity (SAPS 3) and clinical or surgical profile. In the event of a significant amount of missing data on the primary endpoint, the analysis will be re-evaluated after using multiple imputation with chained equations, assuming that the data will be missing at random. Data collected during the transition period will not be analyzed for primary, secondary or exploratory endpoints. Sensitivity analyses and subgroups for the primary outcome: We will define, a priori, the following subgroups for analysis of the primary outcome: A - ICU length of stay stratified by clinical vs elective surgical and emergency surgical patients. B - Length of stay in ICU stratified by three groups (lower, middle and upper thirds) of severity determined by SAPS 3 score. C - ICU length of stay stratified by mechanically ventilated patients on admission (invasive mechanical ventilation). Similarly, in all other analyses, generalized linear mixed models will be used. Analyses of the pre-specified secondary outcomes and subgroup analyses will not be adjusted for multiple comparisons, thus should be interpreted as exploratory. Due to the importance of the SAPS 3 severity score, we will evaluate the calibration of the model with data from the pre-randomization period. If necessary, we will recalibrate the model for the study population. The significance level for all endpoints will be 0.05. All analyses will be performed with R software (version 4.2.0, the version will be updated at the time of the analysis). REGULATORY STATUS: The study will be conducted in accordance with the principles of the Declaration of Helsinki and in accordance with the Medical Research Involving Humans Act. APPROVAL FROM ETHICS AND REGULATORY AUTHORITIES: The study will be performed according to the national and international guidelines. The Institutional Review Board of the Hospital Israelita Albert Einstein has approved this study (CAAE: 69575123.0.1001.0071). The participating centers will not initiate the study until they have obtained approval from their respective local Institutional Review Boards. The need for informed consent is determined by the Institutional Review Board of each participating center.

Brazil