A Symptom-Based Natural Language Processing Surveillance Pipeline for Post-COVID-19 Patients.

Post-acute sequelae of SARS CoV-2 (PASC) are a group of conditions in which patients previously infected with COVID-19 experience symptoms weeks/months post-infection. PASC has substantial societal burden, including increased healthcare costs and disabilities. This study presents a natural language processing (NLP) based pipeline for identification of PASC symptoms and demonstrates its ability to estimate the proportion of suspected PASC cases. A manual case review to obtain this estimate indicated our sample incidence of PASC (13%) was representative of the estimated population proportion (95% CI: 19±6.22%). However, the high number of cases classified as indeterminate demonstrates the challenges in classifying PASC even among experienced clinicians. Lastly, this study developed a dashboard to display views of aggregated PASC symptoms and measured its utility using the System Usability Scale. Overall comments related to the dashboard's potential were positive. This pipeline is crucial for monitoring post-COVID-19 patients with potential for use in clinical settings.

Re-Aiming Equity Evaluation in Clinical Decision Support: A Scoping Review of Equity Assessments in Surgical Decision Support Systems.

OBJECTIVE: We critically evaluated the surgical literature to explore the prevalence and describe how equity assessments occur when using clinical decision support systems. BACKGROUND: Clinical decision support (CDS) systems are increasingly used to facilitate surgical care delivery. Despite formal recommendations to do so, equity evaluations are not routinely performed on CDS systems and underrepresented populations are at risk of harm and further health disparities. We explored surgical literature to determine frequency and rigor of CDS equity assessments and offer recommendations to improve CDS equity by appending existing frameworks. METHODS: We performed a scoping review up to Augus 25, 2021 using PubMed and Google Scholar for the following search terms: clinical decision support, implementation, RE-AIM, Proctor, Proctor's framework, equity, trauma, surgery, surgical. We identified 1415 citations and 229 abstracts met criteria for review. A total of 84 underwent full review after 145 were excluded if they did not assess outcomes of an electronic CDS tool or have a surgical use case. RESULTS: Only 6% (5/84) of surgical CDS systems reported equity analyses, suggesting that current methods for optimizing equity in surgical CDS are inadequate. We propose revising the RE-AIM framework to include an Equity element (RE 2 -AIM) specifying that CDS foundational analyses and algorithms are performed or trained on balanced datasets with sociodemographic characteristics that accurately represent the CDS target population and are assessed by sensitivity analyses focused on vulnerable subpopulations. CONCLUSION: Current surgical CDS literature reports little with respect to equity. Revising the RE-AIM framework to include an Equity element (RE 2 -AIM) promotes the development and implementation of CDS systems that, at minimum, do not worsen healthcare disparities and possibly improve their generalizability.

Combined Expert and User-Driven Usability Assessment of Trauma Decision Support Systems Improves User-Centered Design.

BACKGROUND: Trauma clinical decision support systems improve adherence with evidence-based practice but suffer from poor usability and the lack of a user-centered design. The objective of this study was to compare the effectiveness of user and expert-driven usability testing methods to detect usability issues in a rib fracture clinical decision support system and identify guiding principles for trauma clinical decision support systems. METHODS: A user-driven and expert-driven usability investigation was conducted using a clinical decision support system developed for patients with rib fractures. The user-driven usability evaluation was as follows: 10 clinicians were selected for simulation-based usability testing using snowball sampling, and each clinician completed 3 simulations using a video-conferencing platform. End-users participated in a novel team-based approach that simulated realistic clinical workflows. The expert-driven heuristic evaluation was as follows: 2 usability experts conducted a heuristic evaluation of the clinical decision support system using 10 common usability heuristics. Usability issues were identified, cataloged, and ranked for severity using a 4-level ordinal scale. Thematic analysis was utilized to categorize the identified usability issues. RESULTS: Seventy-nine usability issues were identified; 63% were identified by experts and 48% by end-users. Notably, 58% of severe usability issues were identified by experts alone. Only 11% of issues were identified by both methods. Five themes were identified that could guide the design of clinical decision support systems-transparency, functionality and integration into workflow, automated and noninterruptive, flexibility, and layout and appearance. Themes were preferentially identified by different methods. CONCLUSION: We found that a dual-method usability evaluation involving usability experts and end-users drastically improved detection of usability issues over single-method alone. We identified 5 themes to guide trauma clinical decision support system design. Performing usability testing via a remote video-conferencing platform facilitated multi-site involvement despite a global pandemic.

Field-Triage, Hospital-Triage and Triage-Assessment: A Literature Review of the Current Phases of Adult Trauma Triage.

ABSTRACT: Despite major improvements in the United States trauma system over the past two decades, prehospital trauma triage is a significant challenge. Undertriage is associated with increased mortality, and overtriage results in significant resource overuse. The American College of Surgeons Committee on Trauma benchmarks for undertriage and overtriage are not being met. Many barriers to appropriate field triage exist, including lack of a formal definition for major trauma, absence of a simple and widely applicable triage mode, and emergency medical service adherence to triage protocols. Modern trauma triage systems should ideally be based on the need for intervention rather than injury severity. Future studies should focus on identifying the ideal definition for major trauma and creating triage models that can be easily deployed. This narrative review article presents challenges and potential solutions for prehospital trauma triage.

The Effect of Organ System Surgery on Intensive Care Unit Mortality in a Cohort of Critically Ill Surgical Patients.

BACKGROUND: The critical illness burden in the United States is growing with an aging population obtaining surgical intervention despite age-related comorbidities. The effect of organ system surgical intervention on intensive care units (ICUs) mortality is unknown. METHODS: We performed an 8-year retrospective analysis of surgical ICU patients. Poisson regression analysis was performed assessing the relative risk of in-hospital mortality based on surgical intervention. RESULTS: Of 468 000 ICU patients included, 97 968 (20.9%) were surgical admissions and 97 859 (99.9%) had complete outcomes data. Nonsurvivors were older (68.8 ± 15.4 vs. 62.7 ± 15.8 years, P < .001) with higher Acute Physiology, Age, Chronic Health Evaluation (APACHE) III Scores (81.4 ± 33.6 vs. 46.7 ± 20.1, P < .001. Patients with gastrointestinal (GI) (n = 1,558, 7.8%), musculoskeletal (n = 277, 5.5%), and neurological (n = 884, 4.6%) system operations had the highest mortality. Upon Poisson regression model, patients undergoing emergent operative interventions on the neurologic system (RR 1.86, 95% CI 1.67-2.07, P < .001) had increased relative risk of mortality when compared to emergent operative interventions on the cardiovascular system after controlling for pertinent covariates. Elective operative interventions on the respiratory (RR 2.39, 95% CI 2.03-2.80, P < .001), GI (RR 2.34, 95% CI 2.10-2.61, P < .001), and skin and soft tissue (RR 2.26, 95% CI 1.77-2.89, P < .001) systems had increased risk of mortality when compared to elective cardiovascular system surgery after controlling for pertinent covariates. CONCLUSION: We found significant differences in the risk of mortality based on organ system of operative intervention. The prognostication of critically ill patients undergoing surgical intervention is currently not accounted for in prognostic scoring systems.

Racial Disparities at Mixed-Race and Minority Hospitals : Treatment of African American Males With High-Grade Splenic Injuries.

INTRODUCTION: Racial and socioeconomic disparities in health access and outcomes for many conditions is well known. However, for time-sensitive high-acuity diseases such as traumatic injuries, disparities in access and outcomes should be significantly diminished. Our primary objective was to characterize racial disparities across majority, mixed-race, and minority hospitals for African American ([AA] vs White) males with high-grade splenic injuries. METHODS: Data from the National Trauma Data Bank were utilized from 2007 to 2015; 24 855 AA or White males with high-grade splenic injuries were included. Multilevel mixed-effects regression analysis was used to evaluate disparities in outcomes and resource allocation. RESULTS: Mortality was significantly higher for AA males at mixed-race (OR 1.6; 95% CI 1.3-2.1; P < .001) and minority (OR 2.1; 95% CI 1.5-3.0; P < .001) hospitals, but not at majority hospitals. At minority hospitals, AA males were significantly less likely to be admitted to the intensive care unit (OR 0.7; 95% CI, 0.49-0.97; P = .04) and experienced a significantly longer time to surgery (IRR 1.5; P = .02). Minority hospitals were significantly more likely to have failures from angiographic embolization requiring operative intervention (OR 2.2, P = .009). At both types of nonmajority hospitals, AA males with penetrating injuries were more likely to be managed with angiography (mixed-race hospitals: OR 1.7; P = .046 vs minority hospitals: OR 1.6; P = .08). DISCUSSION: While multiple studies have shown that minority hospitals have increased mortality compared to majority hospitals, this study found this disparity only existed for AAs.

Racial/Ethnic Disparities in Hospital Admissions from COVID-19 and Determining the Impact of Neighborhood Deprivation and Primary Language.

Background Despite past and ongoing efforts to achieve health equity in the United States, persistent disparities in socioeconomic status along with multilevel racism maintain disparate outcomes and appear to be amplified by COVID-19. Objective Measure socioeconomic factors and primary language effects on the risk of COVID-19 severity across and within racial/ethnic groups. Design Retrospective cohort study. Setting Health records of 12 Midwest hospitals and 60 clinics in the U.S. between March 4, 2020 to August 19, 2020. Patients PCR+ COVID-19 patients. Exposures Main exposures included race/ethnicity, area deprivation index (ADI), and primary language. Main Outcomes and Measures The primary outcome was COVID-19 severity using hospitalization within 45 days of diagnosis. Logistic and competing-risk regression models (censored at 45 days and accounting for the competing risk of death prior to hospitalization) assessed the effects of neighborhood-level deprivation (using the ADI) and primary language. Within race effects of ADI and primary language were measured using logistic regression. Results 5,577 COVID-19 patients were included, 866 (n=15.5%) were hospitalized within 45 days of diagnosis. Hospitalized patients were older (60.9 vs. 40.4 years, p<0.001) and more likely to be male (n=425 [49.1%] vs. 2,049 [43.5%], p=0.002). Of those requiring hospitalization, 43.9% (n=381), 19.9% (n=172), 18.6% (n=161), and 11.8% (n=102) were White, Black, Asian, and Hispanic, respectively. Independent of ADI, minority race/ethnicity was associated with COVID-19 severity; Hispanic patients (OR 3.8, 95% CI 2.72-5.30), Asians (OR 2.39, 95% CI 1.74-3.29), and Blacks (OR 1.50, 95% CI 1.15-1.94). ADI was not associated with hospitalization. Non-English speaking (OR 1.91, 95% CI 1.51-2.43) significantly increased odds of hospital admission across and within minority groups. Conclusions Minority populations have increased odds of severe COVID-19 independent of neighborhood deprivation, a commonly suspected driver of disparate outcomes. Non-English-speaking accounts for differences across and within minority populations. These results support the continued concern that racism contributes to disparities during COVID-19 while also highlighting the underappreciated role primary language plays in COVID-19 severity across and within minority groups.

Racial Disparities at Mixed-Race and Minority Hospitals: Treatment of African American Males With High-Grade Splenic Injuries.

INTRODUCTION: Racial and socioeconomic disparities in health access and outcomes for many conditions are well known. However, for time-sensitive high-acuity diseases such as traumatic injuries, disparities in access and outcomes should be significantly diminished. Our primary objective was to characterize racial disparities across majority, mixed-race, and minority hospitals for African American (AA) versus white males with high-grade splenic injuries. METHODS: Data from the National Trauma Data Bank was utilized from 2007 to 2015. A total of 24 855 AA or white males with high-grade splenic injuries were included. Multilevel mixed effects regression analysis was used to evaluate disparities in outcomes and resource allocation. RESULTS: Mortality was significantly higher for AA males at mixed-race (odds ratio [OR] 1.6; 95% CI 1.3-2.1; P < .001) and minority (OR 2.1; 95% CI 1.5-3.0; P < .001) hospitals, but not at majority hospitals. At minority hospitals, AA males were significantly less likely to be admitted to the intensive care unit (OR 0.7; 95% CI 0.49-0.97; P = .04) and experienced a significantly longer time to surgery (IRR 1.5; P = .02). Minority hospitals were significantly more likely to have failures from angiographic embolization requiring operative intervention (OR 2.2; P = .009). At both types of nonmajority hospitals, AA males with penetrating injuries were more likely to be managed with angiography (mixed-race hospitals: OR 1.7; P = .046 vs minority hospitals: OR 1.6; P = .08). DISCUSSION: While multiple studies have shown that minority hospitals have increased mortality compared to majority hospitals, this study found this disparity only existed for AAs.

Predictors of Change in Code Status from Time of Admission to Death in Critically Ill Surgical Patients.

Racial and gender disparities in end-of-life decision-making practices have not been well described in surgical patients. We performed an eight-year retrospective analysis of surgical patients within the Cerner Acute Physiology and Chronic Health Evaluation Outcomes database. ICU patients with documented admission code status, and death or ICU discharge code status, respectively, were included. Logistic regression analysis was performed to assess change in code status. Of 468,000 ICU patients, 97,968 (20.9%) were surgical, 63,567 (95%) survived, and 3,343 (5%) died during their hospitalization. Of those, 50,915 (80.1%) and 2,625 (78.5%) had complete code status data on admission and discharge or death, respectively. Women were less likely than men to remain full code at ICU discharge and death (n = 20,940, 95.6% and n = 141, 11.9% vs n = 29,320, 97.4% and n = 233, 16.3%, P < 0.001). Compared with whites, blacks and other minorities had a 0.46 odds (95% confidence interval [CI]: 0.33-0.64, P < 0.001) and 0.54 odds (95% CI: 0.34-0.85, P = 0.01) of changing from full code status before death, respectively. Before ICU discharge, blacks and other minorities had a 0.56 odds of changing from full code status when compared with whites (95% CI: 0.40-0.79, P < 0.001 vs 95% CI: 0.36-0.87, P = 0.01, respectively). Women were more likely to be discharged or die after a change in code status from full code (odds ratio 1.27, 95% CI: 1.06-1.07, P < 0.001; odds ratio 1.39, 95% CI: 1.09-1.79, P = 0.009). Men and minorities are more likely to be discharged from the ICU or die with a full code status designation.

Are Predictive Energy Expenditure Equations in Ventilated Surgery Patients Accurate?

BACKGROUND:: While indirect calorimetry (IC) is the gold standard used to calculate specific calorie needs in the critically ill, predictive equations are frequently utilized at many institutions for various reasons. Prior studies suggest these equations frequently misjudge actual resting energy expenditure (REE) in medical and mixed intensive care unit (ICU) patients; however, their utility for surgical ICU (SICU) patients has not been fully evaluated. Therefore, the objective of this study was to compare the REE measured by IC with REE calculated using specific calorie goals or predictive equations for nutritional support in ventilated adult SICU patients. MATERIALS AND METHODS:: A retrospective review of prospectively collected data was performed on all adults (n = 419, 18-91 years) mechanically ventilated for >24 hours, with an Fio2 ≤ 60%, who met IC screening criteria. Caloric needs were estimated using Harris-Benedict equations (HBEs), and 20, 25, and 30 kcal/kg/d with actual (ABW), adjusted (ADJ), and ideal body (IBW) weights. The REE was measured using IC. RESULTS:: The estimated REE was considered accurate when within ±10% of the measured REE by IC. The HBE, 20, 25, and 30 kcal/kg/d estimates of REE were found to be inaccurate regardless of age, gender, or weight. The HBE and 20 kcal/kg/d underestimated REE, while 25 and 30 kcal/kg/d overestimated REE. Of the methods studied, those found to most often accurately estimate REE were the HBE using ABW, which was accurate 35% of the time, and 25 kcal/kg/d ADJ, which was accurate 34% of the time. This difference was not statistically significant. CONCLUSION:: Using HBE, 20, 25, or 30 kcal/kg/d to estimate daily caloric requirements in critically ill surgical patients is inaccurate compared to REE measured by IC. In SICU patients with nutrition requirements essential to recovery, IC measurement should be performed to guide clinicians in determining goal caloric requirements.

The effect of residual Ca2+ on the stochastic gating of Ca2+-regulated Ca2+ channel models.

Single-channel models of intracellular Ca(2+) channels such as the inositol 1,4,5-trisphosphate receptor and ryanodine receptor often assume that Ca(2+)-dependent transitions are mediated by a constant background [Ca(2+)] as opposed to a dynamic [Ca(2+)] representing the formation and collapse of a localized Ca(2+) domain. This assumption neglects the fact that Ca(2+) released by open intracellular Ca(2+) channels may influence subsequent gating through the processes of Ca(2+)-activation or -inactivation. We study the effect of such "residual Ca(2+)" from previous channel opening on the stochastic gating of minimal and realistic single-channel models coupled to a restricted cytoplasmic compartment. Using Monte Carlo simulation as well as analytical and numerical solution of a system of advection-reaction equations for the probability density of the domain [Ca(2+)] conditioned on the state of the channel, we determine how the steady-state open probability (p(open)) of single-channel models of Ca(2+)-regulated Ca(2+) channels depends on the time constant for Ca(2+) domain formation and collapse. As expected, p(open) for a minimal model including Ca(2+) activation increases as the domain time constant becomes large compared to the open and closed dwell times of the channel, that is, on average the channel is activated by residual Ca(2+) from previous openings. Interestingly, p(open) for a channel model that is inactivated by Ca(2+) also increases as a function of the domain time constant when the maximum domain [Ca(2+)] is fixed, because slow formation of the Ca(2+) domain attenuates Ca(2+)-mediated inactivation. Conversely, when the source amplitude of the channel is fixed, increasing the domain time constant leads to elevated domain [Ca(2+)] and decreased open probability. Consistent with these observations, a realistic De Young-Keizer-like IP(3)R model responds to residual Ca(2+) with a steady-state open probability that is a monotonic function of the domain time constant, though minimal models that include both Ca(2+)-activation and -inactivation show more complex behavior. We show how the probability density approach described here can be generalized for arbitrarily complex channel models and for any value of the domain time constant. In addition, we present a comparatively simple numerical procedure for estimating p(open) for models of Ca(2+)-regulated Ca(2+) channels in the limit of a very fast or very slow Ca(2+) domain. When the ordinary differential equation for the [Ca(2+)] in a restricted cytoplasmic compartment is replaced by a partial differential equation for the buffered diffusion of intracellular Ca(2+) in a homogeneous isotropic cytosol, we find the dependence of p(open) on the buffer time constant is qualitatively similar to the above-mentioned results.