ICU Utilization After Implementation of Minor Severe Pneumonia Criteria in Real-Time Electronic Clinical Decision Support.

OBJECTIVES: To determine if the implementation of automated clinical decision support (CDS) with embedded minor severe community-acquired pneumonia (sCAP) criteria was associated with improved ICU utilization among emergency department (ED) patients with pneumonia who did not require vasopressors or positive pressure ventilation at admission. DESIGN: Planned secondary analysis of a stepped-wedge, cluster-controlled CDS implementation trial. SETTING: Sixteen hospitals in six geographic clusters from Intermountain Health; a large, integrated, nonprofit health system in Utah and Idaho. PATIENTS: Adults admitted to the hospital from the ED with pneumonia identified by: 1) discharge International Classification of Diseases , 10th Revision codes for pneumonia or sepsis/respiratory failure and 2) ED chest imaging consistent with pneumonia, who did not require vasopressors or positive pressure ventilation at admission. INTERVENTIONS: After implementation, patients were exposed to automated, open-loop, comprehensive CDS that aided disposition decision (ward vs. ICU), based on objective severity scores (sCAP). MEASUREMENTS AND MAIN RESULTS: The analysis included 2747 patients, 1814 before and 933 after implementation. The median age was 71, median Elixhauser index was 17, 48% were female, and 95% were Caucasian. A mixed-effects regression model with cluster as the random effect estimated that implementation of CDS utilizing sCAP increased 30-day ICU-free days by 1.04 days (95% CI, 0.48-1.59; p < 0.001). Among secondary outcomes, the odds of being admitted to the ward, transferring to the ICU within 72 hours, and receiving a critical therapy decreased by 57% (odds ratio [OR], 0.43; 95% CI, 0.26-0.68; p < 0.001) post-implementation; mortality within 72 hours of admission was unchanged (OR, 1.08; 95% CI, 0.56-2.01; p = 0.82) while 30-day all-cause mortality was lower post-implementation (OR, 0.71; 95% CI, 0.52-0.96; p = 0.03). CONCLUSIONS: Implementation of electronic CDS using minor sCAP criteria to guide disposition of patients with pneumonia from the ED was associated with safe reduction in ICU utilization.

Implementation of Lung-Protective Ventilation in Patients With Acute Respiratory Failure.

OBJECTIVES: We implemented a computerized protocol for low tidal volume ventilation (LTVV) to improve management and outcomes of mechanically ventilated patients with, and without, the acute respiratory distress syndrome (ARDS). DESIGN: Pragmatic, nonrandomized stepped wedge type II hybrid implementation/effectiveness trial. SETTING: Twelve hospitals in an integrated healthcare system over a 2-year period. PATIENTS: Patients greater than or equal to 18 years old who had initiation of mechanical ventilation in the emergency department or ICU. We excluded patients who died or transitioned to comfort care on the day of admission to the ICU. We defined a subgroup of patients with ARDS for analysis. INTERVENTIONS: Implementation of ventilator protocols for LTVV in the ICU. MEASUREMENTS AND MAIN RESULTS: Our primary clinical outcome was ventilator-free days (VFDs) to day 28. Our primary process outcome was median initial set tidal volume. We included 8,692 mechanically ventilated patients, 3,282 (38%) of whom had ARDS. After implementation, set tidal volume reported as mL/kg predicted body weight decreased from median 6.1 mL/kg (interquartile range [IQR], 6.0-6.8 mL/kg) to 6.0 mL/kg (IQR, 6.0-6.6 mL/kg) ( p = 0.009). The percent of patients receiving LTVV (tidal volume ≤ 6.5 mL/kg) increased from 69.8% ( n = 1,721) to 72.5% ( n = 1,846) ( p = 0.036) after implementation. The percent of patients receiving greater than 8 mL/kg initial set tidal volume was reduced from 9.0% ( n = 222) to 6.7% ( n = 174) ( p = 0.005) after implementation. Among patients with ARDS, day 1 positive end-expiratory pressure increased from 6.7 to 8.0 cm H 2 O ( p < 0.001). We observed no difference in VFD (adjusted odds ratio, 1.06; 95% CI, 0.91-1.24; p = 0.44), or in secondary outcomes of length of stay or mortality, either within the main cohort or the subgroup of patients with ARDS. CONCLUSIONS: We observed improved adherence to optimal ventilator management with implementation of a computerized protocol and reduction in the number of patients receiving tidal volumes greater than 8 mL/kg. We did not observe improvement in clinical outcomes.

A Pragmatic, Stepped-Wedge, Cluster-controlled Clinical Trial of Real-Time Pneumonia Clinical Decision Support.

Rationale: Care of emergency department (ED) patients with pneumonia can be challenging. Clinical decision support may decrease unnecessary variation and improve care. Objectives: To report patient outcomes and processes of care after deployment of electronic pneumonia clinical decision support (ePNa): a comprehensive, open loop, real-time clinical decision support embedded within the electronic health record. Methods: We conducted a pragmatic, stepped-wedge, cluster-controlled trial with deployment at 2-month intervals in 16 community hospitals. ePNa extracts real-time and historical data to guide diagnosis, risk stratification, microbiological studies, site of care, and antibiotic therapy. We included all adult ED patients with pneumonia over the course of 3 years identified by International Classification of Diseases, 10th Revision discharge coding confirmed by chest imaging. Measurements and Main Results: The median age of the 6,848 patients was 67 years (interquartile range, 50-79), and 48% were female; 64.8% were hospital admitted. Unadjusted mortality was 8.6% before and 4.8% after deployment. A mixed effects logistic regression model adjusting for severity of illness with hospital cluster as the random effect showed an adjusted odds ratio of 0.62 (0.49-0.79; P < 0.001) for 30-day all-cause mortality after deployment. Lower mortality was consistent across hospital clusters. ePNa-concordant antibiotic prescribing increased from 83.5% to 90.2% (P < 0.001). The mean time from ED admission to first antibiotic was 159.4 (156.9-161.9) minutes at baseline and 150.9 (144.1-157.8) minutes after deployment (P < 0.001). Outpatient disposition from the ED increased from 29.2% to 46.9%, whereas 7-day secondary hospital admission was unchanged (5.2% vs. 6.1%). ePNa was used by ED clinicians in 67% of eligible patients. Conclusions: ePNa deployment was associated with improved processes of care and lower mortality. Clinical trial registered with www.clinicaltrials.gov (NCT03358342).

Learning from past respiratory failure patients to triage COVID-19 patient ventilator needs: A multi-institutional study.

BACKGROUND: Unlike well-established diseases that base clinical care on randomized trials, past experiences, and training, prognosis in COVID19 relies on a weaker foundation. Knowledge from other respiratory failure diseases may inform clinical decisions in this novel disease. The objective was to predict 48-hour invasive mechanical ventilation (IMV) within 48 h in patients hospitalized with COVID-19 using COVID-like diseases (CLD). METHODS: This retrospective multicenter study trained machine learning (ML) models on patients hospitalized with CLD to predict IMV within 48 h in COVID-19 patients. CLD patients were identified using diagnosis codes for bacterial pneumonia, viral pneumonia, influenza, unspecified pneumonia and acute respiratory distress syndrome (ARDS), 2008-2019. A total of 16 cohorts were constructed, including any combinations of the four diseases plus an exploratory ARDS cohort, to determine the most appropriate cohort to use. Candidate predictors included demographic and clinical parameters that were previously associated with poor COVID-19 outcomes. Model development included the implementation of logistic regression and three ensemble tree-based algorithms: decision tree, AdaBoost, and XGBoost. Models were validated in hospitalized COVID-19 patients at two healthcare systems, March 2020-July 2020. ML models were trained on CLD patients at Stanford Hospital Alliance (SHA). Models were validated on hospitalized COVID-19 patients at both SHA and Intermountain Healthcare. RESULTS: CLD training data were obtained from SHA (n = 14,030), and validation data included 444 adult COVID-19 hospitalized patients from SHA (n = 185) and Intermountain (n = 259). XGBoost was the top-performing ML model, and among the 16 CLD training cohorts, the best model achieved an area under curve (AUC) of 0.883 in the validation set. In COVID-19 patients, the prediction models exhibited moderate discrimination performance, with the best models achieving an AUC of 0.77 at SHA and 0.65 at Intermountain. The model trained on all pneumonia and influenza cohorts had the best overall performance (SHA: positive predictive value (PPV) 0.29, negative predictive value (NPV) 0.97, positive likelihood ratio (PLR) 10.7; Intermountain: PPV, 0.23, NPV 0.97, PLR 10.3). We identified important factors associated with IMV that are not traditionally considered for respiratory diseases. CONCLUSIONS: The performance of prediction models derived from CLD for 48-hour IMV in patients hospitalized with COVID-19 demonstrate high specificity and can be used as a triage tool at point of care. Novel predictors of IMV identified in COVID-19 are often overlooked in clinical practice. Lessons learned from our approach may assist other research institutes seeking to build artificial intelligence technologies for novel or rare diseases with limited data for training and validation.

Driving pressure is not associated with mortality in mechanically ventilated patients without ARDS.

BACKGROUND: In patients with acute respiratory distress syndrome (ARDS), low tidal volume ventilation has been associated with reduced mortality. Driving pressure (tidal volume normalized to respiratory system compliance) may be an even stronger predictor of ARDS survival than tidal volume. We sought to study whether these associations hold true in acute respiratory failure patients without ARDS. METHODS: This is a retrospectively cohort analysis of mechanically ventilated adult patients admitted to ICUs from 12 hospitals over 2 years. We used natural language processing of chest radiograph reports and data from the electronic medical record to identify patients who had ARDS. We used multivariable logistic regression and generalized linear models to estimate associations between tidal volume, driving pressure, and respiratory system compliance with adjusted 30-day mortality using covariates of Acute Physiology Score (APS), Charlson Comorbidity Index (CCI), age, and PaO2/FiO2 ratio. RESULTS: We studied 2641 patients; 48% had ARDS (n = 1273). Patients with ARDS had higher mean APS (25 vs. 23, p < .001) but similar CCI (4 vs. 3, p = 0.6) scores. For non-ARDS patients, tidal volume was associated with increased adjusted mortality (OR 1.18 per 1 mL/kg PBW increase in tidal volume, CI 1.04 to 1.35, p = 0.010). We observed no association between driving pressure or respiratory compliance and mortality in patients without ARDS. In ARDS patients, both ΔP (OR1.1, CI 1.06-1.14, p < 0.001) and tidal volume (OR 1.17, CI 1.04-1.31, p = 0.007) were associated with mortality. CONCLUSIONS: In a large retrospective analysis of critically ill non-ARDS patients receiving mechanical ventilation, we found that tidal volume was associated with 30-day mortality, while driving pressure was not.

Real-world use of nirmatrelvir-ritonavir in COVID-19 outpatients during BQ.1, BQ.1.1., and XBB.1.5 predominant omicron variants in three U.S. health systems: a retrospective cohort study.

Background: Ritonavir-boosted Nirmatrelvir (NMV-r), a protease inhibitor with in vitro activity against SARS-CoV-2, can reduce risk of progression to severe COVID-19 among high-risk individuals infected with earlier variants, but less is known about its effectiveness against omicron variants BQ.1/BQ.1.1/XBB.1.5. We sought to evaluate effectiveness of NMV-r in BQ.1/BQ.1.1/XBB.1.5 omicron variants by comparing hospitalisation rates to NMV-r treated patients during a previous omicron phase and to contemporaneous untreated patients. Methods: We conducted a retrospective observational cohort study of non-hospitalised adult patients with SARS-CoV-2 infection using real-world data from three health systems in Colorado and Utah, and compared hospitalisation rates in NMV-r-treated patients in a BA.2/BA.2.12.1/BA.4/BA.5 variant-predominant (first) phase (April 3, 2022-November 12, 2022), with a BQ.1/BQ.1.1/XBB.1.5 variant-predominant (second) phase (November 13, 2022-March 7, 2023). In the primary analysis, we used Firth logistic regression with a two-segment (phase) linear time model, and pre-specified non-inferiority bounds for the mean change between segments. In a pre-specified secondary analysis, we inferred NMV-r effectiveness in a cohort of treated and untreated patients infected during the second phase. For both analyses, the primary outcome was 28-day all-cause hospitalisation. Subgroup analyses assessed treatment effect heterogeneity. Findings: In the primary analysis, 28-day all-cause hospitalisation rates in NMV-r treated patients in the second phase (n = 12,061) were non-inferior compared to the first phase (n = 25,075) (198 [1.6%] vs. 345 [1.4%], adjusted odds ratio (aOR): 0.76 [95% CI 0.54-1.06]), with consistent results among secondary endpoints and key subgroups. Secondary cohort analyses revealed additional evidence for NMV-r effectiveness, with reduced 28-day hospitalisation rates among treated patients compared to untreated patients during a BQ.1/BQ.1.1/XBB.1.5 predominant phase (198/12,061 [1.6%] vs. 376/10,031 [3.7%], aOR 0.34 [95% CI 0.30-0.38), findings robust to additional sensitivity analyses. Interpretation: Real-world evidence from major US healthcare systems suggests ongoing NMV-r effectiveness in preventing hospitalisation during a BQ.1/BQ.1.1/XBB.1.5-predominant phase in the U.S, supporting its continued use in similar patient populations. Funding: U.S. National Institutes of Health.

Effectiveness and Safety of an Emergency Department Code Sepsis Protocol: A Pragmatic Clinical Trial.

Rationale: Sepsis care delivery-including the initiation of prompt, appropriate antimicrobials-remains suboptimal. Objectives: This study was conducted to determine direct and off-target effects of emergency department (ED) sepsis care reorganization. Methods: This pragmatic pilot trial enrolled adult patients who presented from November 2019 to February 2021 to an ED in Utah before and after implementation of a multimodal, team-based "Code Sepsis" protocol. Patients who presented to two other EDs where usual care was continued served as contemporaneous control subjects. The primary outcome was door-to-antimicrobial time among patients meeting Sepsis-3 criteria before ED departure. Secondary and safety outcomes included all-cause 30-day mortality, antimicrobial utilization and overtreatment, and antimicrobial-associated adverse events. Multivariable regression analyses used difference-in-differences methods to account for trends in outcomes unrelated to the studied intervention. Results: Code Sepsis protocol activation (N = 307) exhibited 8.5% sensitivity and 66% positive predictive value for patients meeting sepsis criteria before ED departure. Among 10,151 patients who met sepsis criteria during the study, adjusted difference-in-differences analysis demonstrated a 13-minute (95% confidence interval = 7-19) decrease in door-to-antimicrobial time associated with Code Sepsis implementation (P < 0.001). Mortality and clinical safety outcomes were unchanged, but Code Sepsis implementation was associated with increased false-positive presumptive infection diagnoses among patients who met sepsis criteria in the ED and increased antimicrobial utilization. Conclusions: Implementation of a team-based protocol for rapid sepsis evaluation and treatment during the coronavirus disease (COVID-19) pandemic's first year was associated with decreased ED door-to-antimicrobial time but also increased antimicrobial utilization. Measurement of both patient-centered and off-target effects of sepsis care improvement interventions is essential to comprehensive assessment of their value. Clinical trial registered with www.clinicaltrials.gov (NCT04148989).

Implementation of coordinated spontaneous awakening and breathing trials using telehealth-enabled, real-time audit and feedback for clinician adherence (TEACH): a type II hybrid effectiveness-implementation cluster-randomized trial.

BACKGROUND: Intensive care unit (ICU) patients on mechanical ventilation often require sedation and analgesia to improve comfort and decrease pain. Prolonged sedation and analgesia, however, may increase time on mechanical ventilation, risk for ventilator associated pneumonia, and delirium. Coordinated interruptions in sedation [spontaneous awakening trials (SATs)] and spontaneous breathing trials (SBTs) increase ventilator-free days and improve mortality. Coordination of SATs and SBTs is difficult with substantial implementation barriers due to difficult-to-execute sequencing between nurses and respiratory therapists. Telehealth-enabled remote care has the potential to overcome these barriers and improve coordinated SAT and SBT adherence by enabling proactive high-risk patient monitoring, surveillance, and real-time assistance to frontline ICU teams. METHODS: The telehealth-enabled, real-time audit and feedback for clinician adherence (TEACH) study will determine whether adding a telehealth augmented real-time audit and feedback to a usual supervisor-led audit and feedback intervention will yield higher coordinated SAT and SBT adherence and more ventilator-free days in mechanically ventilated patients than a usual supervisor-led audit and feedback intervention alone in a type II hybrid effectiveness-implementation cluster-randomized clinical trial in 12 Intermountain Health hospitals with 15 ICUs. In the active comparator control group (six hospitals), the only intervention is the usual supervisor-led audit and feedback implementation. The telehealth-enabled support (TEACH) intervention in six hospitals adds real-time identification of patients eligible for a coordinated SAT and SBT and consultative input from telehealth respiratory therapists, nurses, and physicians to the bedside clinicians to promote adherence including real-time assistance with execution. All intubated and mechanically ventilated patients ≥ 16 years of age are eligible for enrollment except for patients who die on the day of intubation or have preexisting brain death. Based on preliminary power analyses, we plan a 36-month intervention period that includes a 90-day run-in period. Estimated enrollment in the final analysis is up to 9900 mechanically ventilated patients over 33 months. DISCUSSION: The TEACH study will enhance implementation science by providing insight into how a telehealth intervention augmenting a usual audit and feedback implementation may improve adherence to coordinated SAT and SBT and increase ventilator-free days. TRIAL REGISTRATION: Clinicaltrials.gov, NCT05141396 , registered 12/02/2021.

Awakening and Breathing Coordination: A Mixed-Methods Analysis of Determinants of Implementation.

Rationale: Routine spontaneous awakening and breathing trial coordination (SAT/SBT) improves outcomes for mechanically ventilated patients, but adherence varies. Understanding barriers to and facilitators of consistent daily use of SAT/SBT (implementation determinants) can guide the development of implementation strategies to increase adherence to these evidence-based interventions. Objectives: We conducted an explanatory, sequential mixed-methods study to measure variation in the routine daily use of SAT/SBT and to identify implementation determinants that might explain variation in SAT/SBT use across 15 intensive care units (ICUs) in urban and rural locations within an integrated, community-based health system. Methods: We described the patient population and measured adherence to daily use of coordinated SAT/SBT from January to June 2021, selecting four sites with varied adherence levels for semistructured field interviews. We conducted key informant interviews with critical care nurses, respiratory therapists, and physicians/advanced practice clinicians (n = 55) from these four sites between October and December 2021 and performed content analysis to identify implementation determinants of SAT/SBT use. Results: The 15 sites had 1,901 ICU admissions receiving invasive mechanical ventilation (IMV) for ⩾24 hours during the measurement period. The mean IMV patient age was 58 years, and the median IMV duration was 5.3 days (interquartile range, 2.5-11.9). Coordinated SAT/SBT adherence (within 2 h) was estimated at 21% systemwide (site range, 9-68%). ICU clinicians were generally familiar with SAT/SBT but varied in their knowledge and beliefs about what constituted an evidence-based SAT/SBT. Clinicians reported that SAT/SBT coordination was difficult in the context of existing ICU workflows, and existing protocols did not explicitly define how coordination should be performed. The lack of an agreed-upon system-level measure for tracking daily use of SAT/SBT led to uncertainty regarding what constituted adherence. The effects of the COVID-19 pandemic increased clinician workloads, impacting performance. Conclusions: Coordinated SAT/SBT adherence varied substantially across 15 ICUs within an integrated, community-based health system. Implementation strategies that address barriers identified by this study, including knowledge deficits, challenges regarding workflow coordination, and the lack of performance measurement, should be tested in future hybrid implementation-effectiveness trials to increase adherence to daily use of coordinated SAT/SBT and minimize harm related to the prolonged use of mechanical ventilation and sedation.

Delivery of Lung-protective Ventilation for Acute Respiratory Distress Syndrome: A Hybrid Implementation-Effectiveness Trial.

Rationale: Lung-protective ventilation (LPV) improves outcomes for patients with acute respiratory distress syndrome (ARDS), but adherence remains inadequate. Objectives: To measure the process and clinical impacts of implementation of a science-based intervention to improve LPV adherence for patients with ARDS, in part by increased use of clinical decision support (CDS). Methods: We conducted a type III hybrid implementation/effectiveness pilot trial enrolling adult patients with ARDS admitted to three hospitals before and after the launch of a multimodal implementation intervention to increase the use of mechanical ventilation CDS and improve LPV adherence. The primary outcome was patients' percentage of time adherent to low tidal volume (⩽6.5 ml/kg predicted body weight) ventilation (LTVV). Secondary outcomes included adherence to prescribed oxygenation settings, the use of the CDS tool's independent oxygenation and ventilation components, ventilator-free days, and mortality. Analyses employed multivariable regression to compare adjusted pre- versus postintervention outcomes after the exclusion of a postintervention wash-in period. A sensitivity analysis measured process outcomes' level and trend change postintervention using segmented regression. Results: The 446 included patients had a mean age of 60 years, and 43% were female. Demographic and clinical characteristics were similar pre- versus postintervention. The adjusted proportion of adherent time increased postintervention for LTVV (9.2%; 95% confidence interval [CI], 3.8-14.5%) and prescribed oxygenation settings (11.9%; 95% CI, 7.2-16.5%), as did the probability patients spent ⩾90% of ventilated time on LTVV (adjusted odds ratio [aOR] 2.58; 95% CI, 1.64-4.10) and use of ventilation CDS (aOR, 41.3%; 95% CI, 35.9-46.7%) and oxygenation CDS (aOR, 54.3%; 95% CI, 50.9-57.7%). Ventilator-free days (aOR, 1.15; 95% CI, 0.81-1.62) and 28-day mortality (aOR, 0.78; 95% CI, 0.50-1.20) did not change significantly after intervention. Segmented regression analysis supported a causal relationship between the intervention and improved CDS usage but suggested trends before intervention rather than the studied intervention could explain increased LPV adherence after the intervention. Conclusions: In this pilot trial, a multimodal implementation intervention was associated with increased use of ventilator management CDS for patients with ARDS but was not associated with differences in clinical outcomes and may not have independently caused the observed postintervention improvements in LPV adherence. Clinical trial registered with www.clinicaltrials.gov (NCT03984175).

Prognostic Accuracy of Presepsis and Intrasepsis Characteristics for Prediction of Cardiovascular Events After a Sepsis Hospitalization.

OBJECTIVES: Sepsis survivors face increased risk for cardiovascular complications; however, the contribution of intrasepsis events to cardiovascular risk profiles is unclear. SETTING: Kaiser Permanente Northern California (KPNC) and Intermountain Healthcare (IH) integrated healthcare delivery systems. SUBJECTS: Sepsis survivors (2011-2017 [KPNC] and 2018-2020 [IH]) greater than or equal to 40 years old without prior cardiovascular disease. DESIGN: Data across KPNC and IH were harmonized and grouped into presepsis (demographics, atherosclerotic cardiovascular disease scores, comorbidities) or intrasepsis factors (e.g., laboratory values, vital signs, organ support, infection source) with random split for training/internal validation datasets (75%/25%) within KPNC and IH. Models were bidirectionally, externally validated between healthcare systems. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Changes to predictive accuracy (C-statistic) of cause-specific proportional hazards models predicting 1-year cardiovascular outcomes (atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation events) were compared between models that did and did not contain intrasepsis factors. Among 39,590 KPNC and 16,388 IH sepsis survivors, 3,503 (8.8%) at Kaiser Permanente (KP) and 600 (3.7%) at IH experienced a cardiovascular event within 1-year after hospital discharge, including 996 (2.5%) at KP and 192 (1.2%) IH with an atherosclerotic event first, 564 (1.4%) at KP and 117 (0.7%) IH with a heart failure event, 2,310 (5.8%) at KP and 371 (2.3%) with an atrial fibrillation event. Death within 1 year after sepsis occurred for 7,948 (20%) KP and 2,085 (12.7%) IH patients. Combined models with presepsis and intrasepsis factors had better discrimination for cardiovascular events (KPNC C-statistic 0.783 [95% CI, 0.766-0.799]; IH 0.763 [0.726-0.801]) as compared with presepsis cardiovascular risk alone (KPNC: 0.666 [0.648-0.683], IH 0.660 [0.619-0.702]) during internal validation. External validation of models across healthcare systems showed similar performance (KPNC model within IH data C-statistic: 0.734 [0.725-0.744]; IH model within KPNC data: 0.787 [0.768-0.805]). CONCLUSIONS: Across two large healthcare systems, intrasepsis factors improved postsepsis cardiovascular risk prediction as compared with presepsis cardiovascular risk profiles. Further exploration of sepsis factors that contribute to postsepsis cardiovascular events is warranted for improved mechanistic and predictive models.

An alert tool to promote lung protective ventilation for possible acute respiratory distress syndrome.

Objective: Computer-aided decision tools may speed recognition of acute respiratory distress syndrome (ARDS) and promote consistent, timely treatment using lung-protective ventilation (LPV). This study evaluated implementation and service (process) outcomes with deployment and use of a clinical decision support (CDS) synchronous alert tool associated with existing computerized ventilator protocols and targeted patients with possible ARDS not receiving LPV. Materials and Methods: We performed an explanatory mixed methods study from December 2019 to November 2020 to evaluate CDS alert implementation outcomes across 13 intensive care units (ICU) in an integrated healthcare system with >4000 mechanically ventilated patients annually. We utilized quantitative methods to measure service outcomes including CDS alert tool utilization, accuracy, and implementation effectiveness. Attitudes regarding the appropriateness and acceptability of the CDS tool were assessed via an electronic field survey of physicians and advanced practice providers. Results: Thirty-eight percent of study encounters had at least one episode of LPV nonadherence. Addition of LPV treatment detection logic prevented an estimated 1812 alert messages (41%) over use of disease detection logic alone. Forty-eight percent of alert recommendations were implemented within 2 h. Alert accuracy was estimated at 63% when compared to gold standard ARDS adjudication, with sensitivity of 85% and positive predictive value of 62%. Fifty-seven percent of survey respondents observed one or more benefits associated with the alert. Conclusion: Introduction of a CDS alert tool based upon ARDS risk factors and integrated with computerized ventilator protocol instructions increased visibility to gaps in LPV use and promoted increased adherence to LPV.

Evaluation of potential COVID-19 recurrence in patients with late repeat positive SARS-CoV-2 testing.

BACKGROUND: SARS-CoV-2 reinfection and reactivation has mostly been described in case reports. We therefore investigated the epidemiology of recurrent COVID-19 SARS-CoV-2. METHODS: Among patients testing positive for SARS-CoV-2 between March 11 and July 31, 2020 within an integrated healthcare system, we identified patients with a recurrent positive SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) assay ≥60 days after an initial positive test. To assign an overall likelihood of COVID-19 recurrence, we combined quantitative data from initial and recurrent positive RT-PCR cycle thresholds-a value inversely correlated with viral RNA burden- with a clinical recurrence likelihood assigned based on independent, standardized case review by two physicians. "Probable" or "possible" recurrence by clinical assessment was confirmed as the final recurrence likelihood only if a cycle threshold value obtained ≥60 days after initial testing was lower than its preceding cycle threshold or if the patient had an interval negative RT-PCR. RESULTS: Among 23,176 patients testing positive for SARS-CoV-2, 1,301 (5.6%) had at least one additional SARS-CoV-2 RT-PCRs assay ≥60 days later. Of 122 testing positive, 114 had sufficient data for evaluation. The median interval to the recurrent positive RT-PCR was 85.5 (IQR 74-107) days. After combining clinical and RT-PCR cycle threshold data, four patients (3.5%) met criteria for probable COVID-19 recurrence. All four exhibited symptoms at recurrence and three required a higher level of medical care compared to their initial diagnosis. After including six additional patients (5.3%) with possible recurrence, recurrence incidence was 4.3 (95% CI 2.1-7.9) cases per 10,000 COVID-19 patients. CONCLUSIONS: Only 0.04% of all COVID-19 patients in our health system experienced probable or possible recurrence; 90% of repeat positive SARS-CoV-2 RT-PCRs were not consistent with true recurrence. Our pragmatic approach combining clinical and quantitative RT-PCR data could aid assessment of COVID-19 reinfection or reactivation by clinicians and public health personnel.

Electronic pulmonary embolism clinical decision support and effect on yield of computerized tomographic pulmonary angiography: ePE-A pragmatic prospective cohort study.

OBJECTIVE: Multiple professional societies recommend pre-test probability (PTP) assessment prior to imaging in the evaluation of patients with suspected pulmonary embolism (PE), however, PTP testing remains uncommon, with imaging occurring frequently and rates of confirmed PE remaining low. The goal of this study was to assess the impact of a clinical decision support tool embedded into the electronic health record to improve the diagnostic yield of computerized tomography pulmonary angiography (CTPA) in suspected patients with PE in the emergency department (ED). METHODS: Between July 24, 2014 and December 31, 2016, 4 hospitals from a healthcare system embedded an optional electronic clinical decision support system to assist in the diagnosis of pulmonary embolism (ePE). This system employs the Pulmonary Embolism Rule-out Criteria (PERC) and revised Geneva Score (RGS) in series prior to CT imaging. We compared the diagnostic yield of CTPA) among patients for whom the physician opted to use ePE versus the diagnostic yield of CTPA when ePE was not used. RESULTS: During the 2.5-year study period, 37,288 adult patients were eligible and included for study evaluation. Of eligible patients, 1949 of 37,288 (5.2%) were enrolled by activation of the tool. A total of 16,526 CTPAs were performed system-wide. When ePE was not engaged, CTPA was positive for PE in 1556 of 15,546 scans for a positive yield of 10.0%. When ePE was used, CTPA identified PE in 211 of 980 scans (21.5% yield) (P < 0.001). CONCLUSIONS: ePE significantly increased the diagnostic yield of CTPA without missing 30-day clinically overt PE.

Diagnostic yield of pulmonary embolism testing in patients presenting to the emergency department with syncope.

BACKGROUND: Syncope occurs in 1 in 4 people during their lifetime and accounts for 1% to 1.5% of emergency department (ED) visits. Most causes of syncope are benign, but syncope may be caused by life-threatening conditions including pulmonary embolism (PE) in up to 2% of cases. A recent publication reported the prevalence of PE in patients with syncope to be over 17%. AIMS: We sought to determine the frequency and diagnostic yield of testing for PE in patients presenting to the ED with syncope in our large, integrated health care system. METHODS: We performed a retrospective, longitudinal cohort study of patients who presented with syncope to EDs within a 21-hospital integrated health care system from 2010 to 2015 to find the frequency and diagnostic yield of testing for PE in patients with syncope at index ED visit and within 180 days afterward. RESULTS: We screened 2 749 371 ED encounters to find 32 440 (1.2%) with syncope. Median age was 52 (interquartile range, 31-71), 57.5% were female, and 90% were Caucasian. PE was diagnosed on the index ED visit in 259 (0.8%; 95% confidence interval [CI], 0.7%-0.9%) cases. Assessment for suspected PE with D-dimer occurred in 5089 (15.7%) patients, and 2338 (7.2%) underwent computed tomography pulmonary angiography (CTPA). The yield of CTPA was 7.9%. PE was detected in 2.2% in whom a D-dimer was performed. From index visit to 180 days, 467 (1.4%; 95% CI, 1.3%-1.6%) patients were diagnosed with a PE, and 1051 (3.2%, 95% CI, 3.0%-3.4%) patients died. CONCLUSION: Diagnostic testing for PE is frequent in patients with syncope presenting to the EDs of a large, integrated health care system. The yield of diagnostic testing is low.