Highly connected individuals disseminate information effectively within their social network. To apply this concept to inflammatory bowel disease (IBD) care and lay the foundation for network ...interventions to disseminate high-quality treatment, we assessed the need for improving the IBD practices of highly connected clinicians. We aimed to examine whether highly connected clinicians who treat IBD patients were more likely to provide high-quality treatment than less connected clinicians.
We used network analysis to examine connections among clinicians who shared patients with IBD in the Veterans Health Administration between 2015-2018. We created a network comprised of clinicians connected by shared patients. We quantified clinician connections using degree centrality (number of clinicians with whom a clinician shares patients), closeness centrality (reach via shared contacts to other clinicians), and betweenness centrality (degree to which a clinician connects clinicians not otherwise connected). Using weighted linear regression, we examined associations between each measure of connection and two IBD quality indicators: low prolonged steroids use, and high steroid-sparing therapy use.
We identified 62,971 patients with IBD and linked them to 1,655 gastroenterologists and 7,852 primary care providers. Clinicians with more connections (degree) were more likely to exhibit high-quality treatment (less prolonged steroids beta -0.0268, 95%CI -0.0427, -0.0110, more steroid-sparing therapy beta 0.0967, 95%CI 0.0128, 0.1805). Clinicians who connect otherwise unconnected clinicians (betweenness) displayed more prolonged steroids use (beta 0.0003, 95%CI 0.0001, 0.0006). The presence of variation is more relevant than its magnitude.
Clinicians with a high number of connections provided more high-quality IBD treatments than less connected clinicians, and may be well-positioned for interventions to disseminate high-quality IBD care. However, clinicians who connect clinicians who are otherwise unconnected are more likely to display low-quality IBD treatment. Efforts to improve their quality are needed prior to leveraging their position to disseminate high-quality care.
The COVID-19 pandemic placed considerable strain on critical care resources. How US hospitals responded to this crisis is unknown.
What actions did US hospitals take to prepare for a potential surge ...in demand for critical care services in the context of the COVID-19 pandemic?
From September to November 2020, the chief nursing officers of a representative sample of US hospitals were surveyed regarding organizational actions taken to increase or maintain critical care capacity during the COVID-19 pandemic. Weighted proportions of hospitals for each potential action were calculated to create estimates across the entire population of US hospitals, accounting for both the sampling strategy and nonresponse. Also examined was whether the types of actions taken varied according to the cumulative regional incidence of COVID-19 cases.
Responses were received from 169 of 540 surveyed US hospitals (response rate, 31.3%). Almost all hospitals canceled or postponed elective surgeries (96.7%) and nonsurgical procedures (94.8%). Few hospitals created new medical units in areas not typically dedicated to health care (12.9%), and almost none adopted triage protocols (5.6%) or protocols to connect multiple patients to a single ventilator (4.8%). Actions to increase or preserve ICU staff, including use of ICU telemedicine, were highly variable, without any single dominant strategy. Hospitals experiencing a higher incidence of COVID-19 did not consistently take different actions compared with hospitals facing lower incidence.
Responses of hospitals to the mass need for critical care services due to the COVID-19 pandemic were highly variable. Most hospitals canceled procedures to preserve ICU capacity and scaled up ICU capacity using existing clinical space and staffing. Future research linking hospital response to patient outcomes can inform planning for additional surges of this pandemic or other events in the future.
A growing number of Coronavirus Disease-2019 (COVID-19) survivors are affected by post-acute sequelae of SARS CoV-2 infection (PACS). Using electronic health record data, we aimed to characterize ...PASC-associated diagnoses and develop risk prediction models.
In our cohort of 63,675 patients with a history of COVID-19, 1724 (2.7%) had a recorded PASC diagnosis. We used a case-control study design and phenome-wide scans to characterize PASC-associated phenotypes of the pre-, acute-, and post-COVID-19 periods. We also integrated PASC-associated phenotypes into phenotype risk scores (PheRSs) and evaluated their predictive performance.
In the post-COVID-19 period, known PASC symptoms (e.g., shortness of breath, malaise/fatigue) and musculoskeletal, infectious, and digestive disorders were enriched among PASC cases. We found seven phenotypes in the pre-COVID-19 period (e.g., irritable bowel syndrome, concussion, nausea/vomiting) and sixty-nine phenotypes in the acute-COVID-19 period (predominantly respiratory, circulatory, neurological) associated with PASC. The derived pre- and acute-COVID-19 PheRSs stratified risk well, e.g., the combined PheRSs identified a quarter of the cohort with a history of COVID-19 with a 3.5-fold increased risk (95% CI: 2.19, 5.55) for PASC compared to the bottom 50%.
The uncovered PASC-associated diagnoses across categories highlighted a complex arrangement of presenting and likely predisposing features, some with potential for risk stratification approaches.
Abstract BACKGROUND: Variation in the use of ICUs for low-risk conditions contributes to health system inefficiency. We sought to examine the relationship between ICU use for patients with pulmonary ...embolism (PE) and cost, mortality, readmission, and procedure use. METHODS: We performed a retrospective cohort study including 61,249 adults with PE discharged from 263 hospitals in three states between 2007 and 2010. We generated hospital-specific ICU admission rate quartiles and used a series of multilevel models to evaluate relationships between admission rates and risk-adjusted in-hospital mortality, readmission, and costs and between ICU admission rates and several critical care procedures. RESULTS: Hospital quartiles varied in unadjusted ICU admission rates for PE (range, ≤ 15% to > 31%). Among all patients, there was a small trend toward increased use of arterial catheterization (0.6%-1.1%, P < .01) in hospital quartiles with higher levels of ICU admission. However, use of invasive mechanical ventilation (14.4%-7.9%, P < .01), noninvasive ventilation (6.6%-3.0%, P < .01), central venous catheterization (14.6%-11.3%, P < .02), and thrombolytics (11.0%-4.7%, P < .01) in patients in the ICU declined across hospital quartiles. There was no relationship between ICU admission rate and risk-adjusted hospital mortality, costs, or readmission. CONCLUSIONS: Hospitals vary widely in ICU admission rates for acute PE without a detectable impact on mortality, cost, or readmission. Patients admitted to ICUs in higher-using hospitals received many critical care procedures less often, suggesting that these patients may have had weaker indications for ICU admission. Hospitals with greater ICU admission may be appropriate targets for improving efficiency in ICU admissions.
The distinction between overuse and appropriate use of the ICU hinges on whether a patient would benefit from ICU care. We sought to test 1) whether physicians agree about which types of patients ...benefit from ICU care and 2) whether estimates of ICU benefit are influenced by factors unrelated to severity of illness.
Randomized study.
Online vignettes.
U.S. critical care physicians.
Physicians were provided with eight vignettes of hypothetical patients. Each vignette had a single patient or hospital factor randomized across participants (four factors related and four unrelated to severity of illness).
The primary outcome was the estimate of ICU benefit, assessed with a 4-point Likert-type scale. In total, 1,223 of 8,792 physicians volunteered to participate (14% recruitment rate). Physician agreement of ICU benefit was poor (mean intraclass correlation coefficient for each vignette: 0.06; range: 0-0.18). There were no vignettes in which more than two thirds of physicians agreed about the extent to which a patient would benefit from ICU care. Increasing severity of illness resulted in greater estimated benefit of ICU care. Among factors unrelated to severity of illness, physicians felt ICU care was more beneficial when told one ICU bed was available than if ICU bed availability was unmentioned. Physicians felt ICU care was less beneficial when family was present than when family presence was unmentioned. The patient's age, but not race/ethnicity, also impacted estimates of ICU benefit.
Estimates of ICU benefit are widely dissimilar and influenced by factors unrelated to severity of illness, potentially resulting in inconsistent allocation of ICU care.
Patients with severe coronavirus disease (COVID-19) meet clinical criteria for the acute respiratory distress syndrome (ARDS), yet early reports suggested they differ physiologically and clinically ...from patients with non-COVID-19 ARDS, prompting treatment recommendations that deviate from standard evidence-based practices for ARDS.
To compare respiratory physiology, clinical outcomes, and extrapulmonary clinical features of severe COVID-19 with non-COVID-19 ARDS.
We performed a retrospective cohort study, comparing 130 consecutive mechanically ventilated patients with severe COVID-19 with 382 consecutive mechanically ventilated patients with non-COVID-19 ARDS. Initial respiratory physiology and 28-day outcomes were compared. Extrapulmonary manifestations (inflammation, extrapulmonary organ injury, and coagulation) were compared in an exploratory analysis.
Comparison of patients with COVID-19 and non-COVID-19 ARDS suggested small differences in respiratory compliance, ventilatory efficiency, and oxygenation. The 28-day mortality was 30% in patients with COVID-19 and 38% in patients with non-COVID-19 ARDS. In adjusted analysis, point estimates of differences in time to breathing unassisted at 28 days (adjusted subdistributional hazards ratio, 0.98 95% confidence interval (CI), 0.77-1.26) and 28-day mortality (risk ratio, 1.01 95% CI, 0.72-1.42) were small for COVID-19 versus non-COVID-19 ARDS, although the confidence intervals for these estimates include moderate differences. Patients with COVID-19 had lower neutrophil counts but did not differ in lymphocyte count or other measures of systemic inflammation.
In this single-center cohort, we found no evidence for large differences between COVID-19 and non-COVID-19 ARDS. Many key clinical features of severe COVID-19 were similar to those of non-COVID-19 ARDS, including respiratory physiology and clinical outcomes, although our sample size precludes definitive conclusions. Further studies are needed to define COVID-19-specific pathophysiology before a deviation from evidence-based treatment practices can be recommended.
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