Severe Acute Respiratory Syndrome–Associated Coronavirus 2 Infection and Organ Dysfunction in the ICU: Opportunities for Translational Research

OBJECTIVES: Since the beginning of the coronavirus disease 2019 pan-demic, hundreds of thousands of patients have been treated in ICUs across the globe. The severe acute respiratory syndrome–associated coronavirus 2 virus enters cells via the angiotensin-converting enzyme 2 receptor and activates several distinct inflammatory pathways, resulting in hematologic abnormalities and dysfunction in respiratory, cardiac, gastrointestinal renal, endocrine, dermatologic, and neurologic systems. This review summarizes the current state of research in coronavirus disease 2019 pathophysi-ology within the context of potential organ-based disease mechanisms and opportunities for translational research. DATA SOURCES: Investigators from the Research Section of the Society of Critical Care Medicine were selected based on expertise in specific organ systems and research focus. Data were obtained from searches conducted in Medline via the PubMed portal, Directory of Open Access Journals, Excerpta Medica database, Latin American and Caribbean Health Sciences Literature, and Web of Science from an initial search from December 2019 to October 15, 2020, with a revised search to February 3, 2021. The medRxiv, Research Square, and clinical trial registries preprint servers also were searched to limit publication bias. STUDY SELECTION: Content experts selected studies that included mechanism-based relevance to the severe acute respiratory syndrome–associated coronavirus 2 virus or coronavirus disease 2019 disease. DATA EXTRACTION: Not applicable. DATA SYNTHESIS: Not applicable. CONCLUSIONS: Efforts to improve the care of critically ill coronavirus disease 2019 patients should be centered on understanding how severe acute respiratory syndrome–associated coronavirus 2 infection affects organ function. This review articulates specific targets for further research. KEY WORDS: angiotensin-converting enzyme 2 receptor; coronavirus disease 2019; critical illness; pandemic; severe acute respiratory syndrome–associated coronavirus

Fulfilling the Promises of Health Information Technology: Are Metrics Measuring Our Delivered Care?

ICU utilization represents 13.4% of hospital cost, 4.1% of national health expenditures, and 0.66% of gross domestic product. With the high cost and utilization of intensive care, it is important to understand quality of care. Data must be analyzed to understand how we can prevent patient mortality and morbidity, predict patient risk, and make care more efficient overall. Our two objectives were to: 1) Assess if quality metrics and measures accurately reflect the clinical care provided in the ICU, and 2) Examine if publicly reported outcomes (metrics and measures) reflect the quality of care provided in the ICU. We will review the common validated predictive scoring systems, their uses in the ICU, relative advantages, and their comparative efficacy. While predictive scores are valuable to research comparative groups, e.g., comparing performance of two different ICU units, they offer no assistance to the management of individual patients. Hence, we will discuss dynamic scoring systems, which offer real-time data to predict patient status. Examples of typical ICU quality metrics and hospital benchmarks will also be reviewed. Taking into consideration predictive scoring, dynamic scoring, quality and benchmark metrics, measurement combined with public reporting metrics can draw attention to particular areas of concern and stimulate improvement efforts. However, we argue that our current measurement isn’t enough; instead, it is a simplistic approximation of what administrators, regulators, and patients believe represents high quality of care. Artificial intelligence, cost-effectiveness analyses, and a systems approach (i.e., “clinically meaningful measurement into care delivery at appropriate points of interaction with patients combined with specific actions to ensure delivery of optimal care”) could help us best understand the quality and efficiency of our care

Impact of Telemedicine on Mortality, Length of Stay, and Cost among Patients in Progressive Care Units: Experience from a Large Healthcare System

Utilizing a retrospective observational study design, this study aimed to determine whether telemedicine intervention can affect hospital mortality, length of stay, and direct costs for progressive care unit patients. Adult patients admitted to progressive care unit (PCU) as their primary admission in a large health care system between December 2011 and August 2016 (n = 16091). During the study period, PCU patients with telemedicine intervention (TPCU, n = 8091) and nontelemedicine (NTPCU, n = 8000) were compared concurrently. Primary outcome was PCU and hospital mortality. Secondary outcomes were hospital length of stay, PCU length of stay, and mean direct costs. The mean age NTPCU and TPCU patients were 63.4 years (95%CI, 62.9-63.8 yr) and 71.1 years (95% CI, 70.7-71.74 yr), respectively. All Patient Refined-Diagnosis Related Group Disease Severity (