A Large-Scale Multicenter Retrospective Study on Nephrotoxicity Associated With Empiric Broad-Spectrum Antibiotics in Critically Ill Patients.

BACKGROUND: Evidence regarding acute kidney injury associated with concomitant administration of vancomycin and piperacillin-tazobactam is conflicting, particularly in patients in the ICU. RESEARCH QUESTION: Does a difference exist in the association between commonly prescribed empiric antibiotics on ICU admission (vancomycin and piperacillin-tazobactam, vancomycin and cefepime, and vancomycin and meropenem) and acute kidney injury? STUDY DESIGN AND METHODS: This was a retrospective cohort study using data from the eICU Research Institute, which contains records for ICU stays between 2010 and 2015 across 335 hospitals. Patients were enrolled if they received vancomycin and piperacillin-tazobactam, vancomycin and cefepime, or vancomycin and meropenem exclusively. Patients initially admitted to the ED were included. Patients with hospital stay duration of < 1 h, receiving dialysis, or with missing data were excluded. Acute kidney injury was defined as Kidney Disease: Improving Global Outcomes stage 2 or 3 based on serum creatinine component. Propensity score matching was used to match patients in the control (vancomycin and meropenem or vancomycin and cefepime) and treatment (vancomycin and piperacillin-tazobactam) groups, and ORs were calculated. Sensitivity analyses were performed to study the effect of longer courses of combination therapy and patients with renal insufficiency on admission. RESULTS: Thirty-five thousand six hundred fifty-four patients met inclusion criteria (vancomycin and piperacillin-tazobactam, n = 27,459; vancomycin and cefepime, n = 6,371; vancomycin and meropenem, n = 1,824). Vancomycin and piperacillin-tazobactam was associated with a higher risk of acute kidney injury and initiation of dialysis when compared with that of both vancomycin and cefepime (Acute kidney injury: OR, 1.37 [95% CI, 1.25-1.49]; dialysis: OR, 1.28 [95% CI, 1.14-1.45]) and vancomycin and meropenem (Acute kidney injury: OR, 1.27 [95%, 1.06-1.52]; dialysis: OR, 1.56 [95% CI, 1.23-2.00]). The odds of acute kidney injury developing was especially pronounced in patients without renal insufficiency receiving a longer duration of vancomycin and piperacillin-tazobactam therapy compared with vancomycin and meropenem therapy. INTERPRETATION: VPT is associated with a higher risk of acute kidney injury than both vancomycin and cefepime and vancomycin and meropenem in patients in the ICU, especially for patients with normal initial kidney function requiring longer durations of therapy. Clinicians should consider vancomycin and meropenem or vancomycin and cefepime to reduce the risk of nephrotoxicity for patients in the ICU.

Improving ICU Risk Predictive Models Through Automation Designed for Resiliency Against Documentation Bias.

OBJECTIVES: Electronic health records enable automated data capture for risk models but may introduce bias. We present the Philips Critical Care Outcome Prediction Model (CCOPM) focused on addressing model features sensitive to data drift to improve benchmarking ICUs on mortality performance. DESIGN: Retrospective, multicenter study of ICU patients randomized in 3:2 fashion into development and validation cohorts. Generalized additive models (GAM) with features designed to mitigate biases introduced from documentation of admission diagnosis, Glasgow Coma Scale (GCS), and extreme vital signs were developed using clinical features representing the first 24 hours of ICU admission. SETTING: eICU Research Institute database derived from ICUs participating in the Philips eICU telecritical care program. PATIENTS: A total of 572,985 adult ICU stays discharged from the hospital between January 1, 2017, and December 31, 2018, were included, yielding 509,586 stays in the final cohort; 305,590 and 203,996 in development and validation cohorts, respectively. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Model discrimination was compared against Acute Physiology and Chronic Health Evaluation (APACHE) IVa/IVb models on the validation cohort using the area under the receiver operating characteristic (AUROC) curve. Calibration assessed by actual/predicted ratios, calibration-in-the-large statistics, and visual analysis. Performance metrics were further stratified by subgroups of admission diagnosis and ICU characteristics. Historic data from two health systems with abrupt changes in Glasgow Coma Scale (GCS) documentation were assessed in the year prior to and after data shift. CCOPM outperformed APACHE IVa/IVb for ICU mortality (AUROC, 0.925 vs 0.88) and hospital mortality (AUROC, 0.90 vs 0.86). Better calibration performance was also attained among subgroups of different admission diagnoses, ICU types, and over unique ICU-years. The CCOPM provided more stable predictions compared with APACHE IVa within an external cohort of greater than 120,000 patients from two health systems with known changes in GCS documentation. CONCLUSIONS: These mortality risk models demonstrated excellent performance compared with APACHE while appearing to mitigate bias introduced through major shifts in GCS documentation at two large health systems. This provides evidence to support using automated capture rather than trained personnel for capture of GCS data used in benchmarking ICUs on mortality performance.

Implementing and Optimizing Inpatient Access to Dermatology Consultations via Telemedicine: An Experiential Study.

Background/Introduction: In-house dermatology consultation services for hospitalized patients are not universally available in acute care hospitals. We encountered an unanticipated access gap for in-person dermatology consultations in our tertiary care hospital that routinely cares for complex high acuity patients with multiple comorbidities. To bridge this gap in specialist expertise in a timely manner, we expeditiously designed and implemented a telemedicine-supported inpatient dermatology consultation service. Methods: We conducted a retrospective review of 155 teledermatology consultations conducted between November 2017 and March 2019 as well as periodic prospective multidisciplinary process improvement meetings to optimize service-associated process maps and workflows. Results: Teledermatology consultations changed the working diagnosis of the primary team in 52.3% of cases and most commonly recommended medical management (61.9% of cases). In total 100% of patients accepted telemedicine support and rated their experience as positive. The first three periodic process improvement meetings led to significant improvements in teledermatology-related process maps and workflows. Discussion: Diagnostic concordance rates between the primary team and the teledermatologist were similar to those reported in the literature for in-person dermatology consultations. Important process improvements include establishing central responsibility of preparing and overseeing the consultation process, mandating the presence of a primary team representative during consultation and patient chart review by the teledermatologist before teleconsultation. Conclusion: Inpatient teledermatology consultation services can be instituted timely and continuously improved to reliably and effectively bridge access gaps, improve diagnostic accuracy and differentiate therapeutic approaches while maintaining patient satisfaction.

Acute Cerebrovascular Disorders and Vasculopathies Associated with Significant Mortality in SARS-CoV-2 Patients Admitted to The Intensive Care Unit in The New York Epicenter.

The current Coronavirus pandemic due to the novel SARS-Cov-2 virus has proven to have systemic and multi-organ involvement with high acuity neurological conditions including acute ischemic strokes. We present a case series of consecutive COVID-19 patients with cerebrovascular disease treated at our institution including 3 cases of cerebral artery dissection including subarachnoid hemorrhage. Knowledge of the varied presentations including dissections will help treating clinicians at the bedside monitor and manage these complications preemptively.

ICU Telemedicine Implementation and Risk-Adjusted Mortality Differences Between Daytime and Nighttime Coverage.

BACKGROUND: ICU telemedicine augmentation has been associated with improvements in clinical and financial outcomes in many cases, but not all. Understanding this discrepancy is of interest given the clinical impact and intervention cost. A recent meta-analysis noted an association with mortality reduction and standardized mortality ratio (SMR) before ICU telemedicine implementation of > 1. RESEARCH QUESTION: Does ICU telemedicine implementation affect adjusted mortality outcomes? If so, in what context? STUDY DESIGN AND METHODS: We performed a retrospective pre-post analysis comparing before vs after ICU telemedicine implementation on the outcome of risk-adjusted ICU mortality during am vs pm admissions as well as other objective measures of ICU telemedicine involvement. RESULTS: One thousand five hundred eighty-one patient-stays and 14,584 patient-stays were available for analysis in the implementation period before vs after ICU telemedicine implementation, respectively. The average Acute Physiology and Chronic Health Evaluation (APACHE) IVa score was 46.6 vs 54.8 (P < .01) in the am group before ICU telemedicine implementation vs the am group after ICU telemedicine implementation, respectively. The average APACHE IVa score was 47.2 vs 56.3 (P < .01) in the pm group before ICU telemedicine implementation vs the pm group after ICU telemedicine implementation, respectively. Overall, the risk-adjusted ICU mortality was 8.7% before ICU telemedicine implementation vs 6.5% (P < .01) after implementation. When stratified by am and pm admission groups, no significant difference in risk-adjusted ICU mortality was seen in the am stratum. In the pm stratum, risk-adjusted mortality was 10.8% before ICU telemedicine implementation vs 7.0% (P < .01) after ICU telemedicine implementation. The preimplementation SMR in the am admission stratum was 0.95 vs 1.30 in the pm stratum. INTERPRETATION: We found a reduction in risk-adjusted ICU mortality with implementation of ICU telemedicine driven predominantly within the pm admission group. The pm admission SMR was 1.30, which may suggest an association with SMR of > 1 before ICU telemedicine implementation and mortality reduction. Future studies should seek to confirm this finding and should explore other important ICU telemedicine outcomes in the context of observed-to-expected ratios.

Rapid Implementation and Adaptation of a Telehospitalist Service to Coordinate and Optimize Care for COVID-19 Patients.

Background/Introduction: The COVID-19 pandemic poses enormous resource challenges to hospitals. Telemedicine is increasingly recognized as an attractive tool to alleviate resource strains. Herein we describe the rapid implementation and sequential process improvement (PI) of a centralized telehospitalist service to coordinate and optimize management of large number of COVID-19 patients in a tertiary and quaternary care hospital very close to the New York City epicenter. Methods: Prospective multidisciplinary PI meetings were held weekly between March 23 and May 10, 2020, and consensus service modifications were implemented for the following week. Inpatient census data, telehospitalist intervention volumes, and service utilization statistics were collected. Results/Discussion: Between March 23 and May 10, 2020, a total of 745 COVID-19 patients were admitted to the general medical wards. The telehospitalist service performed 1,136 audiovisual (AV) patient assessments, 379 best practice interventions, cohorted 108 patients, and conducted 170 remote family conversations. During the consecutive PI cycles, a number of adaptations in AV setup, care standardization, patient logistics, communication, and consultative functions were made to load balance the bedside hospitalist teams. As the COVID-19 hospital census increased to peak levels, the most value was added through facilitation of communication and collaboration between the bedside clinical teams, the infection prevention and control teams, and patient logistics team. Conclusions: A telehospitalist service can be rapidly implemented with basic telemedicine equipment. Processes/this functions can be sequentially adapted to quickly changing needs during conditions such as the COVID-19 pandemic that very quickly can place extraordinary strains on hospital resources.

Effects of Telemedicine ICU Intervention on Care Standardization and Patient Outcomes: An Observational Study.

OBJECTIVES: Given the numerous recent changes in ICU practices and protocols, we sought to confirm whether favorable effects of telemedicine ICU interventions on ICU mortality and length of stay can be replicated by a more recent telemedicine ICU intervention. DESIGN SETTING AND PATIENTS: Observational before-after telemedicine ICU intervention study in seven adult ICUs in two hospitals. The study included 1,403 patients in the preintervention period (October 2014 to September 2015) and 14,874 patients in the postintervention period (January 2016 to December 2018). INTERVENTION: Telemedicine ICU implementation. MEASUREMENTS AND MAIN RESULTS: ICU and hospital mortality and length of stay, best practice adherence rates, and telemedicine ICU performance metrics. Unadjusted ICU and hospital mortality and lengths of stay were not statistically significantly different. Adjustment for Acute Physiology and Chronic Health Evaluation Version IVa score, ICU type, and ICU admission time via logistic regression yielded significantly lower ICU and hospital mortality odds ratios of 0.58 (95% CI, 0.45-0.74) and 0.66 (95% CI, 0.54-0.80), respectively. When adjusting for acuity by comparing observed-over-expected length of stay ratios through Acute Physiology and Chronic Health Evaluation IVa methodology, we found significantly lower ICU and hospital length of stay in the postintervention group. ICU mortality improvements were driven by nighttime ICU admissions (odds ratio 0.45 [95% CI, 0.33-0.61]) as compared to daytime ICU admissions (odds ratio 0.81 [95% CI, 0.55-1.20]), whereas hospital mortality improvements were seen in both subgroups but more prominently in nighttime ICU admissions (odds ratio 0.57 [95% CI, 0.44-0.74]) as compared to daytime ICU admissions (odds ratio 0.73 [95% CI, 0.55-0.97]), suggesting that telemedicine ICU intervention can effectively supplement low intensity bedside staffing hours (nighttime). CONCLUSIONS: In this pre-post observational study, telemedicine ICU intervention was associated with improvements in care standardization and decreases in ICU and hospital mortality and length of stay. The mortality benefits were mediated in part through telemedicine ICU supplementation of low intensity bedside staffing hours.

Hyperglycemia in Medically Critically Ill Patients: Risk Factors and Clinical Outcomes.

BACKGROUND: We aimed to robustly categorize glycemic control in our medical intensive care unit (ICU) as either acceptable or suboptimal based on time-weighted daily blood glucose averages of <180 mg/dL or >180 mg/dL; identify clinical risk factors for suboptimal control; and compare clinical outcomes between the 2 glycemic control categories. METHODS: This was a retrospective cohort study in an academic tertiary and quaternary medical ICU. RESULTS: Out of total of 974 unit stays over a 2-year period, 920 had complete data sets available for analysis. Of unit stays 63% (575) were classified as having acceptable glycemic control and the remaining 37% were classified (345) as having suboptimal glycemic control. Adjusting for covariables, the odds of suboptimal glycemic control were highest for patients with diabetes mellitus (odds ratio [OR] 5.08, 95% confidence interval [CI] 3.72-6.93), corticosteroid use during the ICU stay (OR 4.50, 95% CI 3.21-6.32), and catecholamine infusions (OR 1.42, 95% CI 1.04-1.93). Adjusting for acuity, acceptable glycemic control was associated with decreased odds of hospital mortality but not ICU mortality (OR 0.65, 95% CI 0.48-0.88 and OR 0.81, 95% CI 0.55-1.17, respectively). Suboptimal glycemic control was associated with increased odds of longer-than-predicted ICU and hospital stays (OR 1.76, 95% CI 1.30-2.38 and OR 1.50, 95% CI 1.12-2.01, respectively). CONCLUSIONS: In our high-acuity medically critically ill patient population, achieving time-weighted average daily blood glucose levels <180 mg/dL reliably while in the ICU significantly decreased the odds of subsequent hospital mortality. Suboptimal glycemic control during the ICU stay, on the other hand, significantly increased the odds of longer-than-predicted ICU and hospital stay.

Global health, global surgery and mass casualties: II. Mass casualty centre resources, equipment and implementation.

Trauma/stroke centres optimise acute 24/7/365 surgical/critical care in high-income countries (HICs). Concepts from low-income and middle-income countries (LMICs) offer additional cost-effective healthcare strategies for limited-resource settings when combined with the trauma/stroke centre concept. Mass casualty centres (MCCs) integrate resources for both routine and emergency care-from prevention to acute care to rehabilitation. Integration of the various healthcare systems-governmental, non-governmental and military-is key to avoid both duplication and gaps. With input from LMIC and HIC personnel of various backgrounds-trauma and subspecialty surgery, nursing, information technology and telemedicine, and healthcare administration-creative solutions to the challenges of expanding care (both daily and disaster) are developed. MCCs are evolving initially in Chile and Pakistan. Technologies for cost-effective healthcare in LMICs include smartphone apps (enhance prehospital care) to electronic data collection and analysis (quality improvement) to telemedicine and drones/robots (support of remote regions and resource optimisation during both daily care and disasters) to resilient, mobile medical/surgical facilities (eg, battery-operated CT scanners). The co-ordination of personnel (within LMICs, and between LMICs and HICs) and the integration of cost-effective advanced technology are features of MCCs. Providing quality, cost-effective care 24/7/365 to the 5 billion who lack it presently makes MCCs an appealing means to achieve the healthcare-related United Nations Sustainable Development Goals for 2030.

Machine Learning and Artificial Intelligence in Neurocritical Care: a Specialty-Wide Disruptive Transformation or a Strategy for Success.

PURPOSE OF REVIEW: Neurocritical care combines the complexity of both medical and surgical disease states with the inherent limitations of assessing patients with neurologic injury. Artificial intelligence (AI) has garnered interest in the basic management of these complicated patients as data collection becomes increasingly automated. RECENT FINDINGS: In this opinion article, we highlight the potential AI has in aiding the clinician in several aspects of neurocritical care, particularly in monitoring and managing intracranial pressure, seizures, hemodynamics, and ventilation. The model-based method and data-driven method are currently the two major AI methods for analyzing critical care data. Both are able to analyze the vast quantities of patient data that are accumulated in the neurocritical care unit. AI has the potential to reduce healthcare costs, minimize delays in patient management, and reduce medical errors. However, these systems are an aid to, not a replacement for, the clinician's judgment.

Legal Perspectives on Telemedicine Part 2: Telemedicine in the Intensive Care Unit and Medicolegal Risk.

Tele-intensive care unit (tele-ICU) implementation has been shown to improve clinical and financial outcomes. The expansion of this new care delivery model has outpaced the development of its accompanying regulatory framework. In the first part of this commentary we discussed legal and regulatory issues of telemedicine in general and expanded on tele-ICU implementation in particular. Major legal and regulatory barriers to expansion remain, including uncertainty regarding license portability and reimbursement. In this second part we discuss the effects of telemedicine implementation on the various aspects of medicolegal risk and risk mitigation, with a particular focus on tele-ICU. There is a paucity of legal data regarding the effect of tele-ICU implementation on medicolegal risk. We will therefore systematically discuss the effects of tele-ICU on the various root causes of medical error. Given the substantial capital and operational investment that must be undertaken to build and run a tele-ICU, any reduction in risk adds to the financial return on investment and further decreases barriers to implementation.

Legal Perspectives on Telemedicine Part 1: Legal and Regulatory Issues.

Telemedicine is defined as the remote delivery of clinical care services through audio-visual conferencing technology. A shortage of care practitioners combined with an aging population with disproportionately increasing care utilization patterns has created a "perfect storm," which since the late 1990s has propelled telemedicine as a potential solution to bridge this supply/demand and access gap. In critical care approximately 20% of nonfederal adult intensive care unit (ICU) beds in the US today are supported by some form of tele-ICU coverage. The literature has shown with increasing clarity during the last decade that correct tele-ICU implementation improves outcomes and has the potential to significantly improve the financial performance of health care systems. As is often the case in technology-driven innovations, the legal and regulatory framework has been moving slower than the clinical adoption of this new care delivery model, which is true not just in critical care, but in other medical specialties as well. This 2-part series focuses on legal perspectives on telemedicine. The first part discusses legal and regulatory challenges of telemedicine in general, with a more in-depth focus on tele-ICU. The second part will discuss the effects of telemedicine implementation on medicolegal risk, using the litigious critical care environment as an example.

Artificial intelligence in neurocritical care.

BACKGROUND: Neurocritical care combines the management of extremely complex disease states with the inherent limitations of clinically assessing patients with brain injury. As the management of neurocritical care patients can be immensely complicated, the automation of data-collection and basic management by artificial intelligence systems have garnered interest. METHODS: In this opinion article, we highlight the potential artificial intelligence has in monitoring and managing several aspects of neurocritical care, specifically intracranial pressure, seizure monitoring, blood pressure, and ventilation. RESULTS: The two major AI methods of analytical technique currently exist for analyzing critical care data: the model-based method and data driven method. Both of these methods have demonstrated an ability to analyze vast quantities of patient data, and we highlight the ways in which these modalities of artificial intelligence might one day play a role in neurocritical care. CONCLUSIONS: While none of these artificial intelligence systems are meant to replace the clinician's judgment, these systems have the potential to reduce healthcare costs and errors or delays in medical management.

Telemedicine in the ICU: clinical outcomes, economic aspects, and trainee education.

PURPOSE OF REVIEW: The evidence base for telemedicine in the ICU (tele-ICU) is rapidly expanding. The last 2 years have seen important additions to our understanding of when, where, and how telemedicine in the ICU adds value. RECENT FINDINGS: Recent publications and a recent meta-analysis confirm that tele-ICU improves core clinical outcomes for ICU patients. Recent evidence further demonstrates that comprehensive tele-ICU programs have the potential to quickly recuperate their implementation and operational costs and significantly increase case volumes and direct contribution margins particularly if additional logistics and care standardization functions are embedded to optimize ICU bed utilization and reduce complications. Even though the adoption of tele-ICU is increasing and the vast majority of today's medical graduates will regularly use some form of telemedicine and/or tele-ICU, telemedicine modules have not consistently found their way into educational curricula yet. Tele-ICU can be used very effectively to standardize supervision of medical trainees in bedside procedures or point-of-care ultrasound exams, especially during off-hours. Lastly, tele-ICUs routinely generate rich operational data, as well as risk-adjusted acuity and outcome data across the spectrum of critically ill patients, which can be utilized to support important clinical research and quality improvement projects. SUMMARY: The value of tele-ICU to improve patient outcomes, optimize ICU bed utilization, increase financial performance and enhance educational opportunities for the next generation of providers has become more evident and differentiated in the last 2 years.

Evaluating Tele-ICU Implementation Based on Observed and Predicted ICU Mortality: A Systematic Review and Meta-Analysis.

OBJECTIVES: Past studies have examined numerous components of tele-ICU care to decipher which elements increase patient and institutional benefit. These factors include review of the patient chart within 1 hour, frequent collaborative data reviews, mechanisms for rapid laboratory/alert review, and interdisciplinary rounds. Previous meta-analyses have found an overall ICU mortality benefit implementing tele-ICU, however, subgroup analyses found few differences. The purpose of this systematic review and meta-analysis was to explore the effect of tele-ICU implementation with regard to ICU mortality and explore subgroup differences via observed and predicted mortality. DATA SOURCES: We searched PubMed, Cochrane Library, Embase, and European Society of Intensive Care Medicine for articles related to tele-ICU from inception to September 18, 2018. STUDY SELECTION: We included all trials meeting inclusion criteria which looked at the effect of tele-ICU implementation on ICU mortality. DATA EXTRACTION: We abstracted study characteristics, patient characteristics, severity of illness scores, and ICU mortality rates. DATA SYNTHESIS: We included 13 studies from 2,766 abstracts identified from our search strategy. The before-after tele-ICU implementation pooled odds ratio for overall ICU mortality was 0.75 (95% CI, 0.65-0.88; p < 0.001). In subgroup analysis, the pooled odds ratio for ICU mortality between the greater than 1 versus less than 1 observed to predicted mortality ratios was 0.64 (95% CI, 0.52-0.77; p < 0.001) and 0.98 (95% CI, 0.81-1.18; p = 0.81), respectively. Test for interaction was significant (p = 0.002). CONCLUSIONS: After evaluating all included studies, tele-ICU implementation was associated with an overall reduction in ICU mortality. Subgroup analysis suggests that publications exhibiting observed to predicted ICU mortality ratios of greater than 1 before tele-ICU implementation was associated with a reduction in ICU mortality after tele-ICU implementation. No significant ICU mortality reduction was noted in the subgroup of observed to predicted ICU mortality ratio less than 1 before tele-ICU implementation. Future studies should confirm this finding using patient-level data.

Global health, global surgery and mass casualties. I. Rationale for integrated mass casualty centres.

It has been well-documented recently that 5 billion people globally lack surgical care. Also well-documented is the need to improve mass casualty disaster response. Many of the United Nations (UN) Sustainable Development Goals (SDGs) for 2030-healthcare and economic milestones-require significant improvement in global surgical care, particularly in low-income and middle-income countries. Trauma/stroke centres evolved in high-income countries with evidence that 24/7/365 surgical and critical care markedly improved morbidity and mortality for trauma and stroke and for cardiovascular events, difficult childbirth, acute abdomen. Duplication of emergency services, especially civilian and military, often results in suboptimal, expensive care. By combining all healthcare resources within the ongoing healthcare system, more efficient care for both individual emergencies and mass casualty situations can be achieved. We describe progress in establishing mass casualty centres in Chile and Pakistan. In both locations, planning among the stakeholders (primarily civilian and military) indicates the feasibility of such integrated surgical and emergency care. We also review other programmes and initiatives to provide integrated mass casualty disaster response. Integrated mass casualty centres are a feasible means to improve both day-to-day surgical care and mass casualty disaster response. The humanitarian aspect of mass casualty disasters facilitates integration among stakeholders-from local healthcare systems to military resources to international healthcare organisations. The benefits of mass casualty centres-both healthcare and economic-can facilitate achieving the 2030 UN SDGs.

Optimizing Tele-ICU Operational Efficiency Through Workflow Process Modeling and Restructuring.

Little is known on how to best prioritize various tele-ICU specific tasks and workflows to maximize operational efficiency. We set out to: 1) develop an operational model that accurately reflects tele-ICU workflows at baseline, 2) identify workflow changes that optimize operational efficiency through discrete-event simulation and multi-class priority queuing modeling, and 3) implement the predicted favorable workflow changes and validate the simulation model through prospective correlation of actual-to-predicted change in performance measures linked to patient outcomes. SETTING: Tele-ICU of a large healthcare system in New York State covering nine ICUs across the spectrum of adult critical care. PATIENTS: Seven-thousand three-hundred eighty-seven adult critically ill patients admitted to a system ICU (1,155 patients pre-intervention in 2016Q1 and 6,232 patients post-intervention 2016Q3 to 2017Q2). INTERVENTIONS: Change in tele-ICU workflow process structure and hierarchical process priority based on discrete-event simulation. MEASUREMENTS AND MAIN RESULTS: Our discrete-event simulation model accurately reflected the actual baseline average time to first video assessment by both the tele-ICU intensivist (simulated 132.8 ± 6.7 min vs 132 ± 12.2 min actual) and the tele-ICU nurse (simulated 128.4 ± 7.6 min vs 123 ± 9.8 min actual). For a simultaneous priority and process change, the model simulated a reduction in average TVFA to 51.3 ± 1.6 min (tele-ICU intensivist) and 50.7 ± 2.1 min (tele-ICU nurse), less than the added simulated reductions for each change alone, suggesting correlation of the changes to some degree. Subsequently implementing both changes simultaneously resulted in actual reductions in average time to first video assessment to values within the 95% CIs of the simulations (50 ± 5.5 min for tele-intensivists and 49 ± 3.9 min for tele-nurses). CONCLUSIONS: Discrete-event simulation can accurately predict the effects of contemplated multidisciplinary tele-ICU workflow changes. The value of workflow process and task priority modeling is likely to increase with increasing operational complexities and interdependencies.

Low Risk Monitoring in Neurocritical Care.

Background/Rationale: Patients are admitted to Intensive care units (ICUs) either because they need close monitoring despite a low risk of hospital mortality (LRM group) or to receive ICU specific active treatments (AT group). The characteristics and differential outcomes of LRM patients vs. AT patients in Neurocritical Care Units are poorly understood. Methods: We classified 1,702 patients admitted to our tertiary and quaternary care center Neuroscience-ICU in 2016 and 2017 into LRM vs. AT groups. We compared demographics, admission diagnosis, goal of care status, readmission rates and managing attending specialty extracted from the medical record between groups. Acute Physiology, Age and Chronic Health Evaluation (APACHE) IVa risk predictive modeling was used to assess comparative risks for ICU and hospital mortality and length of stay between groups. Results: 56.9% of patients admitted to our Neuroscience-ICU in 2016 and 2017 were classified as LRM, whereas 43.1% of patients were classified as AT. While demographically similar, the groups differed significantly in all risk predictive outcome measures [APACHE IVa scores, actual and predicted ICU and hospital mortality (p < 0.0001 for all metrics)]. The most common admitting diagnosis overall, cerebrovascular accident/stroke, was represented in the LRM and AT groups with similar frequency [24.3 vs. 21.3%, respectively (p = 0.15)], illustrating that further differentiating factors like symptom duration, neurologic status and its dynamic changes and neuro-imaging characteristics determine the indication for active treatment vs. observation. Patients with intracranial hemorrhage/hematoma were significantly more likely to receive active treatments as opposed to having a primary focus on monitoring [13.6 vs. 9.8%, respectively (p = 0.017)]. Conclusion: The majority of patients admitted to our Neuroscience ICU (56.9%) had <10% hospital mortality risk and a focus on monitoring, whereas the remaining 43.1% of patients received active treatments in their first ICU day. LRM Patients exhibited significantly lower APACHE IVa scores, ICU and hospital mortality rates compared to AT patients. Observed-over-expected ICU and hospital mortality ratios were better than predicted by APACHE IVa for low risk monitored patients and close to prediction for actively treated patients, suggesting that at least a subset of LRM patients may safely and more cost effectively be cared for in intermediate level care settings.