AIM and Patient Safety

Patient safety has constituted a huge public health concern for a long period of time. The focus of safety in the healthcare context is around reducing preventable harms, such as medical errors and treatment-related injuries. COVID-19 pandemic, if anything, has act as a wake-up call for health experts to address latent safety problems. Advancements in the field of artificial intelligence have highlighted the use of intelligent systems as a proven means of improving patient safety and enhancing quality of care. This chapter explores trends in quality and safety research, the use of machine learning and natural language processing in the context of improving patient safety and outcomes, the use of patient safety databases as a source of data for machine learning, and the future of artificial intelligence in quality and safety. © Springer Nature Switzerland AG 2022.

Angiopoietin-Like4 Is a Novel Marker of COVID-19 Severity.

Vascular dysfunction and capillary leak are common in critically ill COVID-19 patients, but identification of endothelial pathways involved in COVID-19 pathogenesis has been limited. Angiopoietin-like 4 (ANGPTL4) is a protein secreted in response to hypoxic and nutrient-poor conditions that has a variety of biological effects including vascular injury and capillary leak. OBJECTIVES: To assess the role of ANGPTL4 in COVID-19-related outcomes. DESIGN SETTING AND PARTICIPANTS: Two hundred twenty-five COVID-19 ICU patients were enrolled from April 2020 to May 2021 in a prospective, multicenter cohort study from three different medical centers, University of Washington, University of Southern California and New York University. MAIN OUTCOMES AND MEASURES: Plasma ANGPTL4 was measured on days 1, 7, and 14 after ICU admission. We used previously published tissue proteomic data and lung single nucleus RNA (snRNA) sequencing data from specimens collected from COVID-19 patients to determine the tissues and cells that produce ANGPTL4. RESULTS: Higher plasma ANGPTL4 concentrations were significantly associated with worse hospital mortality (adjusted odds ratio per log2 increase, 1.53; 95% CI, 1.17-2.00; p = 0.002). Higher ANGPTL4 concentrations were also associated with higher proportions of venous thromboembolism and acute respiratory distress syndrome. Longitudinal ANGPTL4 concentrations were significantly different during the first 2 weeks of hospitalization in patients who subsequently died compared with survivors (p for interaction = 8.1 × 10-5). Proteomics analysis demonstrated abundance of ANGPTL4 in lung tissue compared with other organs in COVID-19. ANGPTL4 single-nuclear RNA gene expression was significantly increased in pulmonary alveolar type 2 epithelial cells and fibroblasts in COVID-19 lung tissue compared with controls. CONCLUSIONS AND RELEVANCE: ANGPTL4 is expressed in pulmonary epithelial cells and fibroblasts and is associated with clinical prognosis in critically ill COVID-19 patients.

Perceived Hospital Stress, Severe Acute Respiratory Syndrome Coronavirus 2 Activity, and Care Process Temporal Variance During the COVID-19 Pandemic.

OBJECTIVES: The COVID-19 pandemic threatened standard hospital operations. We sought to understand how this stress was perceived and manifested within individual hospitals and in relation to local viral activity. DESIGN: Prospective weekly hospital stress survey, November 2020-June 2022. SETTING: Society of Critical Care Medicine's Discovery Severe Acute Respiratory Infection-Preparedness multicenter cohort study. SUBJECTS: Thirteen hospitals across seven U.S. health systems. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We analyzed 839 hospital-weeks of data over 85 pandemic weeks and five viral surges. Perceived overall hospital, ICU, and emergency department (ED) stress due to severe acute respiratory infection patients during the pandemic were reported by a mean of 43% ( sd , 36%), 32% (30%), and 14% (22%) of hospitals per week, respectively, and perceived care deviations in a mean of 36% (33%). Overall hospital stress was highly correlated with ICU stress (ρ = 0.82; p < 0.0001) but only moderately correlated with ED stress (ρ = 0.52; p < 0.0001). A county increase in 10 severe acute respiratory syndrome coronavirus 2 cases per 100,000 residents was associated with an increase in the odds of overall hospital, ICU, and ED stress by 9% (95% CI, 5-12%), 7% (3-10%), and 4% (2-6%), respectively. During the Delta variant surge, overall hospital stress persisted for a median of 11.5 weeks (interquartile range, 9-14 wk) after local case peak. ICU stress had a similar pattern of resolution (median 11 wk [6-14 wk] after local case peak; p = 0.59) while the resolution of ED stress (median 6 wk [5-6 wk] after local case peak; p = 0.003) was earlier. There was a similar but attenuated pattern during the Omicron BA.1 subvariant surge. CONCLUSIONS: During the COVID-19 pandemic, perceived care deviations were common and potentially avoidable patient harm was rare. Perceived hospital stress persisted for weeks after surges peaked.

An Electronic Data Capture Tool for Data Collection During Public Health Emergencies: Development and Usability Study.

BACKGROUND: The Discovery Critical Care Research Network Program for Resilience and Emergency Preparedness (Discovery PREP) partnered with a third-party technology vendor to design and implement an electronic data capture tool that addressed multisite data collection challenges during public health emergencies (PHE) in the United States. The basis of the work was to design an electronic data capture tool and to prospectively gather data on usability from bedside clinicians during national health system stress queries and influenza observational studies. OBJECTIVE: The aim of this paper is to describe the lessons learned in the design and implementation of a novel electronic data capture tool with the goal of significantly increasing the nation's capability to manage real-time data collection and analysis during PHE. METHODS: A multiyear and multiphase design approach was taken to create an electronic data capture tool, which was used to pilot rapid data capture during a simulated PHE. Following the pilot, the study team retrospectively assessed the feasibility of automating the data captured by the electronic data capture tool directly from the electronic health record. In addition to user feedback during semistructured interviews, the System Usability Scale (SUS) questionnaire was used as a basis to evaluate the usability and performance of the electronic data capture tool. RESULTS: Participants included Discovery PREP physicians, their local administrators, and data collectors from tertiary-level academic medical centers at 5 different institutions. User feedback indicated that the designed system had an intuitive user interface and could be used to automate study communication tasks making for more efficient management of multisite studies. SUS questionnaire results classified the system as highly usable (SUS score 82.5/100). Automation of 17 (61%) of the 28 variables in the influenza observational study was deemed feasible during the exploration of automated versus manual data abstraction. The creation and use of the Project Meridian electronic data capture tool identified 6 key design requirements for multisite data collection, including the need for the following: (1) scalability irrespective of the type of participant; (2) a common data set across sites; (3) automated back end administrative capability (eg, reminders and a self-service status board); (4) multimedia communication pathways (eg, email and SMS text messaging); (5) interoperability and integration with local site information technology infrastructure; and (6) natural language processing to extract nondiscrete data elements. CONCLUSIONS: The use of the electronic data capture tool in multiple multisite Discovery PREP clinical studies proved the feasibility of using the novel, cloud-based platform in practice. The lessons learned from this effort can be used to inform the improvement of ongoing global multisite data collection efforts during the COVID-19 pandemic and transform current manual data abstraction approaches into reliable, real time, and automated information exchange. Future research is needed to expand the ability to perform automated multisite data extraction during a PHE and beyond.

Critical Care Response During the COVID-19 Pandemic.

Hospitals and health care systems with active critical care organizations (CCOs) that unified ICU units before the onset of the COVID-19 Pandemic were better positioned to adapt to the demands of the pandemic, due to their established standardization of care and integration of critical care within the larger structure of the hospital or health care system. CCOs should continue to make changes, based on the real experience of COVID-19 that would lead to improved care during the ongoing pandemic, and beyond.

Firm partisan positioning, polarization, and risk communication: Examining voluntary disclosures on COVID-19.

Research Summary: The COVID-19 pandemic will rank among the greatest challenges many executives will have faced and not only due to the operational challenges it posed. Upon entering the U.S. context, the disease was immediately politically polarized, with clear partisan splits forming in risk perceptions of the disease unrelated to science. We exploit this context to examine whether firms' partisan positioning affects whether and how they communicate risk to their investors on a polarized public policy issue. To do so, we examine the covariation between firms' disclosure of COVID-19 risks and the partisanship of their political giving. Our analysis of earnings call and campaign contribution data for the S&P 500 reveals a positive association between a firm's contributions to Democrats and its disclosure of COVID-19 risks. Managerial Summary: From its onset in the United States, attitudes toward and discourse around the COVID-19 pandemic was heavily politicized and perceptions of the disease's risks were seen as more serious by Democratic-identifying individuals than Republican identifiers. In this study, we examine whether this pattern also holds for U.S. publicly traded firms, who can also stake out a political position through their corporate political action committee campaign contributions. In analyses of earnings call transcripts from the first quarter of 2020, we show that the more Republican-leaning (Democrat-leaning) a firm's campaign contributions are, the less (more) likely it was to voluntarily disclose risks related to COVID-19. We argue that these findings hold implications for parties interested in interpreting firm's risk disclosures on politically polarized issues.