Faculty Bibliography

OBJECTIVE:Increased utilization of CT pulmonary angiography (CTPA) for the evaluation of pulmonary embolism has been associated with decreasing diagnostic yields and rising concerns about the harms of unnecessary testing. The objective of this study was to determine whether clinical decision support (CDS) use would be associated with increased imaging yields after controlling for selection bias. METHODS:We performed a retrospective cohort study in the emergency departments of two tertiary care hospitals of all CTPAs performed between August 2015 and September 2018. Providers ordering a CTPA are routed to an optional CDS tool, which allows them to use Wells' Criteria for pulmonary embolism. After propensity score matching, CTPA yield was calculated for the CDS-use and CDS-dismissal groups and stratified by provider type. RESULTS:A total of 7,367 CTPAs were ordered during the study period. Of those, providers used the CDS tool in 2,568 (35%) cases and did not use the tool in 4,799 (65%) of cases. After propensity score matching, CTPA yield was 11.99% in the CDS-use group and 8.70% in the CDS-dismissal group (P < .001). Attending physicians, residents, and physician assistant CDS users demonstrated a 56.5% (P = .006), 38.7% (P = .01), and 16.7% (P = .03) increased yield compared with those who dismissed the tool, respectively. DISCUSSION/CONCLUSIONS:Diagnostic yield was 38% higher for CTPAs when the provider used the CDS tool, after controlling for selection bias. Yields were higher for every provider type. Further research is needed to discover successful strategies to increase provider use of these important tools.

BACKGROUND:Chinese studies reported predictors of severe disease and mortality associated with coronavirus disease 2019 (COVID-19). A generalizable and simple survival calculator based on data from US patients hospitalized with COVID-19 has not yet been introduced. OBJECTIVE:Develop and validate a clinical tool to predict 7-day survival in patients hospitalized with COVID-19. DESIGN/METHODS:Retrospective and prospective cohort study. SETTING/METHODS:Thirteen acute care hospitals in the New York City area. PARTICIPANTS/METHODS:Adult patients hospitalized with a confirmed diagnosis of COVID-19. The development and internal validation cohort included patients hospitalized between March 1 and May 6, 2020. The external validation cohort included patients hospitalized between March 1 and May 5, 2020. MEASUREMENTS/METHODS:Demographic, laboratory, clinical, and outcome data were extracted from the electronic health record. Optimal predictors and performance were identified using least absolute shrinkage and selection operator (LASSO) regression with receiver operating characteristic curves and measurements of area under the curve (AUC). RESULTS:The development and internal validation cohort included 11 095 patients with a median age of 65 years [interquartile range (IQR) 54-77]. Overall 7-day survival was 89%. Serum blood urea nitrogen, age, absolute neutrophil count, red cell distribution width, oxygen saturation, and serum sodium were identified as the 6 optimal of 42 possible predictors of survival. These factors constitute the NOCOS (Northwell COVID-19 Survival) Calculator. Performance in the internal validation, prospective validation, and external validation were marked by AUCs of 0.86, 0.82, and 0.82, respectively. LIMITATIONS/CONCLUSIONS:All participants were hospitalized within the New York City area. CONCLUSIONS:The NOCOS Calculator uses 6 factors routinely available at hospital admission to predict 7-day survival for patients hospitalized with COVID-19. The calculator is publicly available at https://feinstein.northwell.edu/NOCOS.

Behavioral interventions have been shown to have powerful effects on human behavior both outside of and within the context of health care. As organizations increasingly adopt behavioral architecture, care must be taken to consider its potential negative consequences. An evidenced-based approach is best, whereby interventions that might have a significant deleterious effect on patients' health outcomes are first tested and rigorously evaluated before being systematically rolled out. In the case of clinical decision support, brief and thorough instructions should be provided for use. Physician performance when using these systems is best measured relatively, in the context of peers with similar training. Responsibility for errors must be shared with clinical team members and system designers.

BACKGROUND:The benefits of computed tomography pulmonary angiography (CTPA) for pulmonary embolism (PE) diagnosis must be weighed against its risks, radiation-induced malignancy, and contrast-induced nephropathy. Appropriate use of CTPA can be assessed by monitoring yield, the percentage of tests positive for PE. We identify factors that are associated low CTPA yield, which may predict overtesting. METHODS:This was a retrospective cohort study of six emergency departments between June 2014 and February 2017. The electronic health record was queried for CTPAs ordered for adult patients in the emergency department. We assessed the following patient factors: age, gender, body mass index, number of comorbidities, race, and ethnicity, provider factors: type (resident, fellow, attending, physician assistant) and environment factors: test time of day, season of visit, and crowdedness of the department. RESULTS:A total of 14,782 CTPAs were reviewed, of which 1366 were found to be positive for PE, resulting in an overall CTPA yield of 9.24%. Provider type was not associated with a difference in yield. Testing was less likely to be positive in younger patients, females, those with lower body mass indexes and those identifying as Asian or Hispanic. Testing was also less likely to be positive when ordered during the overnight shift and during the winter and spring seasons. CONCLUSION:Our study identified several patient and environmental factors associated with low CTPA yield suggesting potential targets for overtesting. Targeting education and clinical decision support to assist providers in these circumstances may meaningfully improve yields.