Trend analysis of emergency department malpractice claims in the Netherlands

Abstract Background Emergency department (ED) visits show a high volatility over time. Therefore, EDs are likely to be crowded at peak-volume moments. ED crowding is a widely reported problem with negative consequences for patients as well as staff. Previous studies on the predictive value of weather variables on ED visits show conflicting results. Also, no such studies were performed in the Netherlands. Therefore, we evaluated prediction models for the number of ED visits in our large the Netherlands teaching hospital based on calendar and weather variables as potential predictors. Methods Data on all ED visits from June 2016 until December 31, 2019, were extracted. The 2016–2018 data were used as training set, the 2019 data as test set. Weather data were extracted from three publicly available datasets from the Royal Netherlands Meteorological Institute. Weather observations in proximity of the hospital were used to predict the weather in the hospital’s catchment area by applying the inverse distance weighting interpolation method. The predictability of daily ED visits was examined by creating linear prediction models using stepwise selection; the mean absolute percentage error (MAPE) was used as measurement of fit. Results The number of daily ED visits shows a positive time trend and a large impact of calendar events (higher on Mondays and Fridays, lower on Saturdays and Sundays, higher at special times such as carnival, lower in holidays falling on Monday through Saturday, and summer vacation). The weather itself was a better predictor than weather volatility, but only showed a small effect; the calendar-only prediction model had very similar coefficients to the calendar+weather model for the days of the week, time trend, and special time periods (both MAPE’s were 8.7%). Conclusions Because of this similar performance, and the inaccuracy caused by weather forecasts, we decided the calendar-only model would be most useful in our hospital; it can probably be transferred for use in EDs of the same size and in a similar region. However, the variability in ED visits is considerable. Therefore, one should always anticipate potential unforeseen spikes and dips in ED visits that are not shown by the model.

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No Evidence for a Sustained Increase in Sexually Transmitted Diseases Among Heterosexuals in Amsterdam, The Netherlands A 12-Year Trend Analysis at the Sexually Transmitted Disease Outpatient Clinic Amsterdam

Sexually Transmitted Diseases ◽

10.1097/01.olq.0000251230.62493.f3 ◽

2007 ◽

Vol 34 (7) ◽

pp. 461-467 ◽

Cited By ~ 7

Author(s):

Akke K. Van der Bij ◽

Ronald B. Geskus ◽

Han S. A. Fennema ◽

Karin Adams ◽

Roel A. Coutinho ◽

...

Keyword(s):

The Netherlands ◽

Sexually Transmitted Diseases ◽

Trend Analysis ◽

Outpatient Clinic ◽

Sexually Transmitted Disease ◽

Transmitted Disease ◽

Sexually Transmitted ◽

Sustained Increase

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Compliance With Imaging Guidelines for Workup of Transient Ischemic Attack

Stroke ◽

10.1161/strokeaha.120.029858 ◽

2020 ◽

Vol 51 (8) ◽

pp. 2563-2567

Author(s):

Vincent M. Timpone ◽

Alexandria Jensen ◽

Sharon N. Poisson ◽

Premal S. Trivedi

Keyword(s):

Emergency Department ◽

Trend Analysis ◽

Transient Ischemic Attack ◽

Emergency Departments ◽

Odds Ratio ◽

International Classification Of Diseases ◽

Multivariable Logistic Regression Analysis ◽

Primary Analysis ◽

Ischemic Attack ◽

Neurovascular Imaging

Background and Purpose: Multiple societal guidelines recommend urgent brain and neurovascular imaging in patients with transient ischemic attack (TIA) to identify and treat risk factors that may lead to future stroke. The purpose of this study was to evaluate whether national imaging utilization for workup of TIA complies with society guidelines. Methods: Analysis utilized the Nationwide Emergency Department Sample. Primary analysis was performed on a 2017 cohort, and secondary trend analysis was performed on cohorts from 2006 to2017. Patients diagnosed and discharged from emergency departments with TIA were identified using International Classification of Diseases, Ninth Revision and Tenth Revision codes. Brain and neurovascular imaging obtained during the encounter was identified using Current Procedural Terminology codes. Demographics, health insurance, patient income, and hospital-type covariates were analyzed using a hierarchical multivariable logistic regression analysis to identify predictors of obtaining neurovascular imaging during an emergency department encounter. Results: In 2017, there were 167 999 patients evaluated and discharged from emergency departments with TIA. The percentage of patients receiving brain and neurovascular imaging was 78.5% and 43.2%, respectively. The most common imaging workup utilized was a solitary computed tomography–brain without any neurovascular imaging (30.9% of encounters). Decreased odds of obtaining neurovascular imaging was observed in Medicaid patients (odds ratio, 0.65 [95% CI, 0.58–0.74]), rural hospitals (odds ratio, 0.26 [95% CI, 0.17–0.41]), nontrauma centers (odds ratio, 0.40 [95% CI, 0.21–0.74]), and weekend encounters (odds ratio, 0.91 [95% CI, 0.85–0.96]). Trend analysis demonstrated a steady rise in brain and neurovascular imaging in 2006 from 34.9% and 6.8% of encounters, respectively, to 78.5% and 43.2% of encounters in 2017. Conclusions: Compliance with imaging guidelines is improving; however, the majority of TIA patients discharged from the emergency department do not receive recommended neurovascular imaging during their encounter. Follow-up studies are needed to determine whether delayed or incomplete vascular screening increases the risk of future stroke.

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