scholarly journals Appropriateness of emergency care use: a retrospective observational study based on professional versus patients’ perspectives in Taiwan

BMJ Open ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. e033833
Author(s):  
Chih-Yuan Lin ◽  
Yue-Chune Lee
Keyword(s):  
Emergency Department ◽  
New York ◽  
Health Insurance ◽  
Characteristic Curve ◽  
Estimating Equation ◽  
Equation Model ◽  
Sensitivity Analyses ◽  
New York University ◽  
Single Payer ◽  
Explicit Process

ObjectiveThe objectives of this study are to refine the measurement of appropriate emergency department (ED) use and to provide a natural observation of appropriate ED use rates based on professional versus patient perspectives.SettingTaiwan has a population of 23 million, with one single-payer universal health insurance scheme. Taiwan has no limitations on ED use, and a low barrier to ED use may be a surrogate for natural observation of users’ perspectives in ED use.ParticipantsIn 7 years, there were 1 835 860 ED visits from one million random samples of the National Health Insurance Database.MeasuresAppropriate ED use was determined according to professional standards, measured by the modified Billings New York University Emergency Department (NYU-ED) algorithm, and further analysed after the addition of prudent patient standards, measured by explicit process-based and outcome-based criteria.Statistical analysesThe area under the receiver operating characteristic curve (AUC) was used to reflect the performance of appropriate ED use measures, and sensitivity analyses were conducted using different thresholds to determine the appropriateness of ED use. The generalised estimating equation model was used to measure the associations between appropriate ED use based on process and outcome criteria and covariates including sex, age, occupation, health status, place of residence, medical resources area, date and income level.ResultsAppropriate ED use based on professional criteria was 33.5%, which increased to 63.1% when patient criteria were added. The AUC, which combines both professional and patient criteria, was high (0.85).ConclusionsThe appropriate ED use rate nearly doubled when patient criteria were added to professional criteria. Explicit process-based and outcome-based criteria may be used as a supplementary measure to the implicit modified Billings NYU-ED algorithm when determining appropriate ED use.

scholarly journals An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Farah E. Shamout ◽  
Yiqiu Shen ◽  
Nan Wu ◽  
Aakash Kaku ◽  
Jungkyu Park ◽  
...  
Keyword(s):  
Neural Network ◽  
Emergency Department ◽  
New York ◽  
Deep Neural Network ◽  
Characteristic Curve ◽  
Gradient Boosting ◽  
New York University ◽  
X Ray ◽  
Intelligence System ◽  
Chest X Ray

AbstractDuring the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. We propose a data-driven approach for automatic prediction of deterioration risk using a deep neural network that learns from chest X-ray images and a gradient boosting model that learns from routine clinical variables. Our AI prognosis system, trained using data from 3661 patients, achieves an area under the receiver operating characteristic curve (AUC) of 0.786 (95% CI: 0.745–0.830) when predicting deterioration within 96 hours. The deep neural network extracts informative areas of chest X-ray images to assist clinicians in interpreting the predictions and performs comparably to two radiologists in a reader study. In order to verify performance in a real clinical setting, we silently deployed a preliminary version of the deep neural network at New York University Langone Health during the first wave of the pandemic, which produced accurate predictions in real-time. In summary, our findings demonstrate the potential of the proposed system for assisting front-line physicians in the triage of COVID-19 patients.

scholarly journals NYU-EDA in modelling the effect of COVID-19 on patient volumes in a Finnish emergency department

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jalmari Tuominen ◽  
Ville Hällberg ◽  
Niku Oksala ◽  
Ari Palomäki ◽  
Timo Lukkarinen ◽  
...  
Keyword(s):  
Emergency Department ◽  
New York ◽  
Care Hospital ◽  
New York University ◽  
State Of Emergency ◽  
National State ◽  
Point Reduction ◽  
Ed Visits ◽  
Novel Coronavirus ◽  
The Impact

Abstract Background Emergency departments (EDs) worldwide have been in the epicentre of the novel coronavirus disease (COVID-19). However, the impact of the pandemic and national emergency measures on the number of non-COVID-19 presentations and the assessed acuity of those presentations remain uncertain. Methods We acquired a retrospective cohort containing all ED visits in a Finnish secondary care hospital during years 2018, 2019 and 2020. We compared the number of presentations in 2020 during the national state of emergency, i.e. from March 16 to June 11, with numbers from 2018 and 2019. Presentations were stratified using localized New York University Emergency Department Algorithm (NYU-EDA) to evaluate changes in presentations with different acuity levels. Results A total of 27,526 presentations were observed. Compared to previous two years, total daily presentations were reduced by 23% (from 113 to 87, p < .001). In NYU-EDA classes, Non-Emergent visits were reduced the most by 42% (from 18 to 10, p < .001). Emergent presentations were reduced by 19 to 28% depending on the subgroup (p < .001). Number of injuries were reduced by 25% (from 27 to 20, p < .001). The NYU-EDA distribution changed statistically significantly with 4% point reduction in Non-Emergent visits (from 16 to 12%, p < .001) and 0.9% point increase in Alcohol-related visits (from 1.6 to 2.5%, p < .001). Conclusions We observed a significant reduction in total ED visits in the course of national state of emergency. Presentations were reduced in most of the NYU-EDA groups irrespective of the assessed acuity. A compensatory increase in presentations was not observed in the course of the 3 month lockdown. This implies either reduction in overall morbidity caused by decreased societal activity or widespread unwillingness to seek required medical advice.

Evaluating the utility of rule OP-35 to define preventability of ED visits for oncology patients at an academic cancer center.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 272-272
Author(s):  
Steven Manobianco ◽  
Zachary L. Quinn ◽  
Valerie Pracilio Csik ◽  
Adam F Binder ◽  
Nathan Handley
Keyword(s):  
Emergency Department ◽  
New York ◽  
Outpatient Setting ◽  
Cancer Center ◽  
New York University ◽  
Timely Manner ◽  
Oncology Patients ◽  
Outpatient Chemotherapy ◽  
Treatment Models ◽  
Ed Visits

272 Background: Rule OP-35, which characterizes treatment-related complications of patients receiving outpatient chemotherapy that result in a potentially avoidable emergency department (ED) visit or hospitalization, was developed to encourage practices to build treatment models that reduce such events. However, defining visits as potentially avoidable based on symptoms may not capture the complexity of caring for oncology patients. We aim to evaluate the effectiveness of OP-35 in identifying preventable ED visits by real world standards at an academic institution. Methods: A retrospective analysis was performed reviewing ED visits at the Sidney Kimmel Cancer Center (SKCC) at Thomas Jefferson University for oncology patients from 10/1/2020 to 1/31/2021. Each patient received care at SKCC had received intravenous or oral chemotherapy in the preceding 30 days, and each encounter was classified as potentially avoidable by OP-35 criteria. Two investigators independently conducted chart reviews to determine whether these visits were potentially avoidable, recording whether the patient attempted to contact their care team prior to the ED encounter and assessing if the concern could have been managed in a timely manner in an outpatient setting. The two records were then compared, and the principal investigator served as an arbiter for determining if a visit was potentially avoidable in instances where the investigators disagreed. Results: We reviewed 144 total encounters and excluded events from patients with either acute leukemia or breast cancer on hormone therapy only, leaving 107 encounters for analysis. After evaluating the clinical circumstances, we determined that 29% of these ED encounters were potentially avoidable. Applying New York University Emergency Department Algorithm (NYU-EDA) criteria, 69% of encounters were considered potentially avoidable. Patients called for advice before seeking ED care in 53% of unavoidable encounters compared to 26% of potentially avoidable encounters. An additional 14% of visits deemed unavoidable were from patients sent directly from clinic. For potentially avoidable encounters, 60% of patients were discharged directly from the ED. In comparison, 8% of unavoidable encounters led to discharge from the ED. Pain was the most common reason for encounters and 53% of these visits were considered potentially avoidable. Conclusions: We found that approximately 30% of ED encounters deemed avoidable by OP-35 criteria were considered potentially avoidable following clinician review. In the majority of cases patients were referred to the ED following initial outpatient attempts at management. NYU-EDA criteria for preventability did not correlate with OP-35 nor clinician consensus regarding potentially avoidable encounters. More work remains in refining tools to identify potentially avoidable ED visits for oncology patients.

scholarly journals NYU-EDA in Modelling the Effect of COVID-19 on Patient Volumes in A Finnish Emergency Department

2020 ◽  
Author(s):  
Jalmari Tuominen ◽  
Ville Hällberg ◽  
Niku Oksala ◽  
Ari Palomäki ◽  
Timo Lukkarinen ◽  
...  
Keyword(s):  
Emergency Department ◽  
New York ◽  
Care Hospital ◽  
New York University ◽  
State Of Emergency ◽  
National State ◽  
Point Reduction ◽  
Ed Visits ◽  
Novel Coronavirus ◽  
The Impact

Abstract Background: Emergency departments (EDs) worldwide have been in the epicentre of the novel coronavirus disease (COVID-19). However, the impact of the pandemic and national emergency measures on the number of non-COVID-19 presentations and the assessed acuity of those presentations remain uncertain. Methods: We acquired a retrospective cohort containing all ED visits in a Finnish secondary care hospital during years 2018, 2019 and 2020. We compared the number of presentations in 2020 during the national state of emergency, i.e. from March 16 to June 11, with numbers from 2018 and 2019. Presentations were stratified by New York University Emergency Department Algorithm (NYU-EDA) in order to evaluate changes in presentations with different acuity levels.Results: A total of 27,526 presentations were observed. Compared to previous two years, total daily presentations were reduced by 23 % (from 113 to 87, p<.001). In NYU-EDA classes, Non-Emergent visits were reduced the most by 42 % (from 18 to 10, p<.001). Emergent presentations were reduced by 19 to 28 % depending on the subgroup (p<.001). Number of injuries were reduced by 25 % (from 27 to 20, p<.001). The NYU-EDA distribution changed statistically significantly with 4 percent point reduction in Non-Emergent visits (from 16 % to 12 %, p<.001) and 0.9 percent point increase in Alcohol-related visits (from 1.6 % to 2.5 %, p<.001).Conclusions: We observed a significant reduction in total ED visits in the course of national state of emergency. Presentations were reduced in most of the NYU-EDA groups irrespective of the assessed acuity. A compensatory increase in presentations was not observed in the course of the 3 month lockdown. This implies either reduction in overall morbidity caused by decreased societal activity or widespread unwillingness to seek required medical advice.

Patricia H. Labalme, ed., Beyond their sex New York and London : New York University Press, 1980. xx-188 pp. $ 21.90

Moreana ◽  
1982 ◽  
Vol 19 (Number 74) (2) ◽  
pp. 105-106
Author(s):  
Patricia Delendick ◽  
Germain Marc’hadour
Keyword(s):  
New York ◽  
New York University
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