Dataset Information

Application of time series analysis in modelling and forecasting emergency department visits in a medical centre in Southern Taiwan.

ABSTRACT: OBJECTIVE:Emergency department (ED) overcrowding is acknowledged as an increasingly important issue worldwide. Hospital managers are increasingly paying attention to ED crowding in order to provide higher quality medical services to patients. One of the crucial elements for a good management strategy is demand forecasting. Our study sought to construct an adequate model and to forecast monthly ED visits. METHODS:We retrospectively gathered monthly ED visits from January 2009 to December 2016 to carry out a time series autoregressive integrated moving average (ARIMA) analysis. Initial development of the model was based on past ED visits from 2009 to 2016. A best-fit model was further employed to forecast the monthly data of ED visits for the next year (2016). Finally, we evaluated the predicted accuracy of the identified model with the mean absolute percentage error (MAPE). The software packages SAS/ETS V.9.4 and Office Excel 2016 were used for all statistical analyses. RESULTS:A series of statistical tests showed that six models, including ARIMA (0, 0, 1), ARIMA (1, 0, 0), ARIMA (1, 0, 1), ARIMA (2, 0, 1), ARIMA (3, 0, 1) and ARIMA (5, 0, 1), were candidate models. The model that gave the minimum Akaike information criterion and Schwartz Bayesian criterion and followed the assumptions of residual independence was selected as the adequate model. Finally, a suitable ARIMA (0, 0, 1) structure, yielding a MAPE of 8.91%, was identified and obtained as Visitt=7111.161+(at+0.37462 at-1). CONCLUSION:The ARIMA (0, 0, 1) model can be considered adequate for predicting future ED visits, and its forecast results can be used to aid decision-making processes.

SUBMITTER: Juang WC

PROVIDER: S-EPMC5719313 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Application of time series analysis in modelling and forecasting emergency department visits in a medical centre in Southern Taiwan.

Juang Wang-Chuan WC Huang Sin-Jhih SJ Huang Fong-Dee FD Cheng Pei-Wen PW Wann Shue-Ren SR

BMJ open 20171201 11

<h4>Objective</h4>Emergency department (ED) overcrowding is acknowledged as an increasingly important issue worldwide. Hospital managers are increasingly paying attention to ED crowding in order to provide higher quality medical services to patients. One of the crucial elements for a good management strategy is demand forecasting. Our study sought to construct an adequate model and to forecast monthly ED visits.<h4>Methods</h4>We retrospectively gathered monthly ED visits from January 2009 to De ...[more]

PMID: 29196487

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Project description:ImportanceRelatively little is known about the association of the Medicaid eligibility expansion under the Patient Protection and Affordable Care Act with emergency department (ED) visits categorized by medical urgency.ObjectiveTo estimate the association between state Medicaid expansions and ED visits by the urgency of presenting conditions.Design, setting, and participantsThis cross-sectional study used the Healthcare Cost and Utilization Project State Emergency Department Databases from January 2011 to December 2017 for 2 states that expanded Medicaid in 2014 (New York and Massachusetts) and 2 states that did not (Florida and Georgia). Difference-in-differences regression models were used to estimate the changes in ED visits overall and further stratified by the urgency of the conditions using an updated version of the New York University ED algorithm between the states that expanded Medicaid and those that did not, before and after the expansion. Data were analyzed between June 7 and December 12, 2021.ExposureState-level Medicaid eligibility expansion.Main outcomes and measuresEmergency department visits per 1000 population overall and stratified by medical urgency of the conditions.ResultsIn total, 80.6 million ED visits by 26.0 million individuals were analyzed. Emergency department visits were concentrated among women (59.3%), non-Hispanic Black individuals (28.3%), non-Hispanic White individuals (47.8%), and those aged 18 to 34 years (47.5%) and 35 to 44 years (20.4%). The rates of ED visits increased by a mean of 2.4 visits in nonexpansion states and decreased by a mean of 2.2 visits in expansion states after 2014, resulting in a significant regression-adjusted decrease of 4.7 visits per 1000 population (95% CI, -7.7 to -1.5; P = .003) in expansion states. Most of this decrease was associated with decreases in ED visits by conditions classified as not emergent (-1.5 visits; 95% CI, -2.4 to -0.7; P < .001), primary care treatable (-1.1 visits; 95% CI, -1.6 to -0.5; P < .001), and potentially preventable (-0.3 visits; 95% CI, -0.5 to -0.1; P = .02). No significant changes were observed for ED visits related to injuries and conditions classified as not preventable (-1.4; 95% CI, -3.1 to 0.3; P = .10), as well as for substance use and mental health disorders (0.0; 95% CI, -0.2 to 0.2; P = .94).Conclusions and relevanceThe findings of this study suggest that Medicaid expansion was associated with decreases in ED visits, for which decreases in ED visits for less medically emergent ED conditions may have been a factor.

Project description:Background and objectivesIn 2011, there were approximately 131 million visits to an emergency department in the United States. Emergency department visits have increased over time, far outpacing growth of the general population. There is a paucity of data evaluating emergency department visits among kidney transplant recipients. We sought to evaluate the incidence and risk factors for emergency department visits after initial hospital discharge after transplantation in the United States.Design, setting, participants, & measurementsWe identified 10,533 kidney transplant recipients from California, New York, and Florida between 2009 and 2012 using the State Inpatient and Emergency Department Databases included in the Healthcare Cost and Utilization Project. We used multivariable Poisson and Cox proportional hazard models to evaluate adjusted incidence rates and time to emergency department visits after transplantation.ResultsThere were 17,575 emergency department visits over 13,845 follow-up years (overall rate =126.9/100 patient-years; 95% confidence interval, 125.1 to 128.8). The cumulative incidences of emergency department visits at 1, 12, and 24 months were 12%, 40%, and 57%, respectively, with median time =19 months; 48% of emergency department visits led to hospital admission. Risk factors for higher emergency department rates included younger age, women, black and Hispanic race/ethnicity, public insurance, depression, diabetes, peripheral vascular disease, and emergency department use before transplant. There was wide variation in emergency department visits by individual transplant center (10th percentile =70.0/100 patient-years; median =124.6/100 patient-years; and 90th percentile =187.4/100 patient-years).ConclusionsThe majority of kidney transplant recipients will visit an emergency department in the first 2 years post-transplantation, with significant variation by patient characteristics and individual centers. As such, coordination of care through the emergency department is a critical component of post-transplant management, and specific acumen of transplant-related care is needed among emergency department providers. Additional research assessing best processes of care for post-transplant management and health care expenditures and outcomes associated with emergency department visits for transplant recipients are warranted.

Dataset Information

Application of time series analysis in modelling and forecasting emergency department visits in a medical centre in Southern Taiwan.

Publications

Application of time series analysis in modelling and forecasting emergency department visits in a medical centre in Southern Taiwan.

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