International Journal of Environmental Research and Public Health Article Predicting the 14-Day Hospital Readmission of Patients with Pneumonia Using Artificial Neural Networks (ANN) Shu-Farn Tey 1, Chung-Feng Liu 2, Tsair-Wei Chien 2,* , Chin-Wei Hsu 3, Kun-Chen Chan 4, Chia-Jung Chen 5, Tain-Junn Cheng 6 and Wen-Shiann Wu 7,8,* 1 Pulmonary Medicine, Chi-Mei Medical Center, Tainan 700, Taiwan;
[email protected] 2 Department of Medical Research, Chi-Mei Medical Center, Tainan 700, Taiwan;
[email protected] 3 Department of Pharmacy, Chi-Mei Medical Center, Tainan 700, Taiwan;
[email protected] 4 Division of Clinical Pathology, Chi-Mei Medical Center, Tainan 700, Taiwan;
[email protected] 5 Department of Information Systems, Chi-Mei Medical Center, Tainan 700, Taiwan;
[email protected] 6 Departments of Neurology and Occupational Medicine, Chi-Mei Medical Center, Tainan 700, Taiwan;
[email protected] 7 Division of Cardiovascular Medicine, Chi-Mei Medical Center, Tainan 700, Taiwan 8 Department of Pharmacy, Chia-Nan University of Pharmacy and Science, Tainan 700, Taiwan * Correspondence:
[email protected] (T.-W.C.);
[email protected] (W.-S.W.); Tel.: +886-62812811 (W.-S.W.) Abstract: Unplanned patient readmission (UPRA) is frequent and costly in healthcare settings. No indicators during hospitalization have been suggested to clinicians as useful for identifying patients at high risk of UPRA. This study aimed to create a prediction model for the early detection of 14-day UPRA of patients with pneumonia. We downloaded the data of patients with pneumonia as the Citation: Tey, S.-F.; Liu, C.-F.; Chien, primary disease (e.g., ICD-10:J12*-J18*) at three hospitals in Taiwan from 2016 to 2018.