Che-Hung Tsai

Dr. Che-Hung Tsai

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Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2011 in Health Policy
Verified
Journal Article
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CTChe-Hung Tsai
Che-Hung Tsai
WCWen-Yi Chen
Wen-Yi Chen
YLYia-Wun Liang
Yia-Wun Liang

28 March 2020 in Healthcare
Verified
Journal Article
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CTChe-Hung Tsai
Che-Hung Tsai
SWShao-Jen Weng
Shao-Jen Weng
SLShih-Chia Liu
Shih-Chia Liu
YTYao-Te Tsai
Yao-Te Tsai
DGDonald Gotcher
Donald Gotcher
SKSeung-Hwan Kim
Seung-Hwan Kim
Study Objective: Overcrowding in emergency departments (ED) is an increasingly common problem in Taiwanese hospitals, and strategies to improve efficiency are in demand. We propose a bed resource allocation strategy to overcome the overcrowding problem. Method: We investigated ED occupancy using discrete-event simulation and evaluated the effects of suppressing day-to-day variations in ED occupancy by adjusting the number of empty beds per day. Administrative data recorded at the ED of Taichung Veterans General Hospital (TCVGH) in Taiwan with 1500 beds and an annual ED volume of 66,000 visits were analyzed. Key indices of ED quality in the analysis were the length of stay and the time in waiting for outward transfers to in-patient beds. The model is able to analyze and compare several scenarios for finding a feasible allocation strategy. Results: We compared several scenarios, and the results showed that by reducing the allocated beds for the ED by 20% on weekdays, the variance of daily ED occupancy was reduced by 36.25% (i.e., the percentage of reduction in standard deviation). Conclusions: This new allocation strategy was able to both reduce the average ED occupancy and maintain the ED quality indices.

31 October 2021 in Journal of Clinical Medicine
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Journal Article
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CTChe-Hung Tsai
Che-Hung Tsai
JMJen-Wen Ma
Jen-Wen Ma
SLShih-Chia Liu
Shih-Chia Liu
TLTzu-Chieh Lin
Tzu-Chieh Lin
SHSung-Yuan Hu
Sung-Yuan Hu
Background: This study was conducted to identify the predictive factors for survival and favorable neurological outcome in patients with emergency department cardiac arrest (EDCA). Methods: ED patients who suffered from in-hospital cardiac arrest (IHCA) from July 2014 to June 2019 were enrolled. The electronic medical records were retrieved and data were extracted according to the IHCA Utstein-style guidelines. Results: The cardiac arrest survival post-resuscitation in-hospital (CASPRI) score was associated with survival, and the CASPRI scores were lower in the survival group. Three components of the CASPRI score were associated with favorable neurological survival, and the CASPRI scores were lower in the favorable neurological survival group of patients who were successfully resuscitated. The independent predictors of survival were presence of hypotension/shock, metabolic illnesses, short resuscitation time, receiving coronary angiography, and TTM. Receiving coronary angiography and low CASPRI score independently predicted favorable neurological survival in resuscitated patients. The performance of a low CASPRI score for predicting favorable neurological survival was fair, with an AUROCC of 0.77. Conclusions: The CASPRI score can be used to predict survival and neurological status of patients with EDCA. Post-cardiac arrest care may be beneficial for IHCA, especially in patients with EDCA.

1 March 2014 in Journal of the Chinese Medical Association
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Journal Article
Closed access
CTChe-Hung Tsai
Che-Hung Tsai
SWShao-Jen Weng
Shao-Jen Weng
CHChin-Yin Huang
Chin-Yin Huang
DYDavid Hung-Tsang Yen
David Hung-Tsang Yen
HCHsiu-Ling Chen
Hsiu-Ling Chen
Isposition, insult, response, and organ dysfunction (PIRO) concept of sepsis can be used to predict the risk of unplanned ICU transfer after ED admission. Methods: The ICU transfer group included 313 patients with unplanned transfer to the ICU within 48 hours of ED admission, and the control (non-transfer) group included 736 randomly sampled patients who were not transferred to the ICU. Two-thirds of the total 1049 patients in this study were randomly assigned to a derivation group, which was used to develop the PIRO model, and the remaining patients were assigned to a validation group. Results: Independent predictors of deterioration within 48 hours after ED admission were identified by the PIRO concept. PIRO scores were higher in the ICU transfer group than in the non-transfer group, both in the derivation group [median (mean ± SD), 5 (5.7 ± 3.7) vs. 2 (2.5 ± 2.5); p < 0.001], and in the validation group [median (mean ± SD), 6 (6.0 ± 3.4) vs. 2 (2.4 ± 2.6); p < 0.001]. The proportion of ICU transfer patients with a PIRO score of 0–3, 4–6, 7–9, and ≥10 was 14.1%, 46.5%, 57.3%, and 83.8% in the derivation group (p < 0.001) and 12.8%, 37.3%, 68.2%, and 70.0% in the validation group (p < 0.001), respectively. The proportion of inpatient mortality in patients with a PIRO score of 0–3, 4–6, 7–9, and ≥10 was 2.6%, 10.1%, 23.2%, and 45.9% in the derivation group (p < 0.001) and 3.3%, 12.0%, 18.2%, and 20.5% in the validation group (p < 0.001), respectively. Conclusion: The PIRO concept of sepsis may be used in undifferentiated medical ED patients as a prediction system for unplanned ICU transfer after admission....

1 March 2020 in Artificial Intelligence in Medicine
Verified
Journal Article
Closed access
CCChun-An Chou
Chun-An Chou
QCQingtao Cao
Qingtao Cao
SWShao-Jen Weng
Shao-Jen Weng
CTChe-Hung Tsai
Che-Hung Tsai

1 January 2014 in The Scientific World Journal
Verified
Journal Article
Open access
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CTChe-Hung Tsai
Che-Hung Tsai
CCChing-Wan Cheng
Ching-Wan Cheng
SWShao-Jen Weng
Shao-Jen Weng
CHChin-Yin Huang
Chin-Yin Huang
DYDavid Hung-Tsang Yen
David Hung-Tsang Yen
HCHsiu-Ling Chen
Hsiu-Ling Chen
Background. The objectives of this study were to compare the risk factors for unplanned intensive care unit (ICU) transfer after emergency department (ED) admission in patients with infections and those without infections and to explore the feasibility of using risk stratification tools for sepsis to derive a prediction system for such unplanned transfer.Methods. The ICU transfer group included 313 patients, while the control group included 736 patients randomly selected from those who were not transferred to the ICU. Candidate variables were analyzed for association with unplanned ICU transfer in the 1049 study patients.Results. Twenty-four variables were associated with unplanned ICU transfer. Sixteen (66.7%) of these variables displayed association in patients with infections and those without infections. These common risk factors included specific comorbidities, physiological responses, organ dysfunctions, and other serious symptoms and signs. Several common risk factors were statistically independent.Conclusions. The risk factors for unplanned ICU transfer in patients with infections were comparable to those in patients without infections. The risk factors for unplanned ICU transfer included variables from multiple dimensions that could be organized according to the PIRO (predisposition, insult/infection, physiological response, and organ dysfunction) model, providing the basis for the development of a predictive system.