Predicting return visits to the emergency department for pediatric patients: Applying supervised learning techniques to the Taiwan National Health Insurance Research Database

2017 ◽  
Vol 144 ◽  
pp. 105-112 ◽  
Author(s):  
Ya-Han Hu ◽  
Chun-Tien Tai ◽  
Solomon Chih-Cheng Chen ◽  
Hai-Wei Lee ◽  
Sheng-Feng Sung
Keyword(s):  
Emergency Department ◽  
Health Insurance ◽  
Supervised Learning ◽  
National Health Insurance ◽  
National Health ◽  
Pediatric Patients ◽  
Research Database ◽  
Learning Techniques ◽  
Taiwan National Health Insurance ◽  
Return Visits

scholarly journals Predicting Unscheduled Emergency Department Return Visits Among Older Adults: Population-Based Retrospective Study (Preprint)

2020 ◽  
Author(s):  
Rai-Fu Chen ◽  
Kuei-Chen Cheng ◽  
Yu-Yin Lin ◽  
I-Chiu Chang ◽  
Cheng-Han Tsai
Keyword(s):  
Older Adults ◽  
Emergency Department ◽  
Health Insurance ◽  
Chronic Illness ◽  
Length Of Stay ◽  
Prediction Model ◽  
Older Adult ◽  
National Health Insurance ◽  
Research Database ◽  
Return Visits

BACKGROUND Unscheduled emergency department return visits (EDRVs) are key indicators for monitoring the quality of emergency medical care. A high return rate implies that the medical services provided by the emergency department (ED) failed to achieve the expected results of accurate diagnosis and effective treatment. Older adults are more susceptible to diseases and comorbidities than younger adults, and they exhibit unique and complex clinical characteristics that increase the difficulty of clinical diagnosis and treatment. Older adults also use more emergency medical resources than people in other age groups. Many studies have reviewed the causes of EDRVs among general ED patients; however, few have focused on older adults, although this is the age group with the highest rate of EDRVs. OBJECTIVE This aim of this study is to establish a model for predicting unscheduled EDRVs within a 72-hour period among patients aged 65 years and older. In addition, we aim to investigate the effects of the influencing factors on their unscheduled EDRVs. METHODS We used stratified and randomized data from Taiwan’s National Health Insurance Research Database and applied data mining techniques to construct a prediction model consisting of patient, disease, hospital, and physician characteristics. Records of ED visits by patients aged 65 years and older from 1996 to 2010 in the National Health Insurance Research Database were selected, and the final sample size was 49,252 records. RESULTS The decision tree of the prediction model achieved an acceptable overall accuracy of 76.80%. Economic status, chronic illness, and length of stay in the ED were the top three variables influencing unscheduled EDRVs. Those who stayed in the ED overnight or longer on their first visit were less likely to return. This study confirms the results of prior studies, which found that economically underprivileged older adults with chronic illness and comorbidities were more likely to return to the ED. CONCLUSIONS Medical institutions can use our prediction model as a reference to improve medical management and clinical services by understanding the reasons for 72-hour unscheduled EDRVs in older adult patients. A possible solution is to create mechanisms that incorporate our prediction model and develop a support system with customized medical education for older patients and their family members before discharge. Meanwhile, a reasonably longer length of stay in the ED may help evaluate treatments and guide prognosis for older adult patients, and it may further reduce the rate of their unscheduled EDRVs.

Identifying Renal Dysfunction in Stroke Patients Using Diagnostic Codes in the Taiwan National Health Insurance Research Database

2014 ◽  
Vol 10 (1) ◽  
pp. E5-E5 ◽  
Author(s):  
Cheng-Yang Hsieh ◽  
Ching-Lan Cheng ◽  
Edward Chia-Cheng Lai ◽  
Ming-Cheng Wang ◽  
Chih-Hung Chen ◽  
...  
Keyword(s):  
Health Insurance ◽  
Renal Dysfunction ◽  
National Health Insurance ◽  
National Health ◽  
Research Database ◽  
Stroke Patients ◽  
Diagnostic Codes ◽  
Taiwan National Health Insurance

scholarly journals Is Fibromyalgia Risk Higher Among Male and Young Inflammatory Bowel Disease Patients? Evidence from a Taiwan Cohort of One Million

2018 ◽  
Vol 1 (21;1) ◽  
pp. E257-E277
Author(s):  
Chun-Hung Tseng
Keyword(s):  
Inflammatory Bowel Disease ◽  
Health Insurance ◽  
National Health Insurance ◽  
National Health ◽  
Bowel Disease ◽  
Cox Regression ◽  
Research Database ◽  
Gender And Age ◽  
Taiwan National Health Insurance ◽  
Inflammatory Bowel

Background: Prior literatures have shown inflammatory bowel disease (IBD) could increase fibromyalgia (FM) risk. However, studies about gender and age distributions of FM risk among patients with IBD are rare. With large study samples, this study aimed to evaluate the FM risk among IBD patients with different gender and different age. Objective: We aim to estimate the FM risk among male and younger IBD patients with a large patient sample. Study Design: A retrospective cohort study was arranged in this research. Setting: The data used in this research were selected from the Taiwan National Health Insurance Research Database (NHIRD). Methods: From the Taiwan NHIRD, we selected 4,510 patients with IBD and 18,040 randomly gender- and age-matched patients without a history of IBD from the beginning of 2000 to the end of 2005 to analyze the development of FM over a 12-year follow-up period (2000– 2011). The Cox regression model was used to assess the effects of IBD on the risk of FM by adjusting for gender, age, and comorbidities, including hypertension, diabetes, hyperlipidemia, depression, anxiety, and sleep disorder. Results: After adjusting suitable covariates, the IBD patients had a greater FM risk (adjusted hazard ratio [aHR] 1.70, 95% confidence interval [CI] 1.59–1.83) than the controls. Male IBD patients had a higher FM risk than female IBD patients did (aHR 2.00, 95% CI 1.79–2.23 and aHR 1.52, 95% CI 1.38–1.67, respectively). The greatest age-specific FM risk occurred in the youngest IBD subgroup (≤ 39 years old) (aHR 1.92, 95% CI 1.68–2.19). Limitations: The information about personal behaviors was unobtainable in the Taiwan NHIRD. Other risk factors for cardiovascular disease that might augment FM cannot be excluded entirely in this study. Conclusion: IBD is disclosed to be correlated with an enhanced risk to develop FM, particularly in male and younger IBD patients. For preventing FM, it is necessary to pay more attention to the management of the IBD patients. Future researches are needed to further confirm the findings in this study. Key words: Inflammation, inflammatory bowel disease, fibromyalgia, Taiwan National Health Insurance Research Database

scholarly journals Predicting Unscheduled Emergency Department Return Visits Among Older Adults: Population-Based Retrospective Study

10.2196/22491 ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. e22491
Author(s):  
Rai-Fu Chen ◽  
Kuei-Chen Cheng ◽  
Yu-Yin Lin ◽  
I-Chiu Chang ◽  
Cheng-Han Tsai
Keyword(s):  
Older Adults ◽  
Emergency Department ◽  
Health Insurance ◽  
Chronic Illness ◽  
Length Of Stay ◽  
Prediction Model ◽  
Older Adult ◽  
National Health Insurance ◽  
Research Database ◽  
Return Visits

Background Unscheduled emergency department return visits (EDRVs) are key indicators for monitoring the quality of emergency medical care. A high return rate implies that the medical services provided by the emergency department (ED) failed to achieve the expected results of accurate diagnosis and effective treatment. Older adults are more susceptible to diseases and comorbidities than younger adults, and they exhibit unique and complex clinical characteristics that increase the difficulty of clinical diagnosis and treatment. Older adults also use more emergency medical resources than people in other age groups. Many studies have reviewed the causes of EDRVs among general ED patients; however, few have focused on older adults, although this is the age group with the highest rate of EDRVs. Objective This aim of this study is to establish a model for predicting unscheduled EDRVs within a 72-hour period among patients aged 65 years and older. In addition, we aim to investigate the effects of the influencing factors on their unscheduled EDRVs. Methods We used stratified and randomized data from Taiwan’s National Health Insurance Research Database and applied data mining techniques to construct a prediction model consisting of patient, disease, hospital, and physician characteristics. Records of ED visits by patients aged 65 years and older from 1996 to 2010 in the National Health Insurance Research Database were selected, and the final sample size was 49,252 records. Results The decision tree of the prediction model achieved an acceptable overall accuracy of 76.80%. Economic status, chronic illness, and length of stay in the ED were the top three variables influencing unscheduled EDRVs. Those who stayed in the ED overnight or longer on their first visit were less likely to return. This study confirms the results of prior studies, which found that economically underprivileged older adults with chronic illness and comorbidities were more likely to return to the ED. Conclusions Medical institutions can use our prediction model as a reference to improve medical management and clinical services by understanding the reasons for 72-hour unscheduled EDRVs in older adult patients. A possible solution is to create mechanisms that incorporate our prediction model and develop a support system with customized medical education for older patients and their family members before discharge. Meanwhile, a reasonably longer length of stay in the ED may help evaluate treatments and guide prognosis for older adult patients, and it may further reduce the rate of their unscheduled EDRVs.

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