TY - JOUR
T1 - Clinical Verification of A Clinical Decision Support System for Ventilator Weaning
AU - Hsu, Jiin Chyr
AU - Chen, Yung Fu
AU - Chung, Wei Sheng
AU - Tan, Tan Hsu
AU - Chen, Tainsong
AU - Chiang, John Y.
N1 - Funding Information:
This article was funded in part by the National Science Council of Taiwan under grants NSC96-2912-I-039-001, NSC97-2912-I-039-001, and NSC100-2410-H-166-007-MY3. This article has been published as part of BioMedical Engineering OnLine Volume 12 Supplement 1, 2013: Selected articles from the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Workshop on Current Challenging Image Analysis and Information Processing in Life Sciences. The full contents of the supplement are available online at http://www.biomedical-engineering-online.com/supplement/12/S1 1Institute of Biomedical Engineering, National Cheng Kung University, Tainan, Taiwan. 2Department of Internal Medicine, Taoyuan General Hospital, Ministry of Health and Welfare, Taoyuan, Taiwan. 3Department of Healthcare Administration, Central Taiwan University of Science and Technology, Taichung, Taiwan. 4Department of Health Services Administration, China Medical University, Taichung, Taiwan. 5Department of Internal Medicine, Taichung Hospital, Ministry of Health and Welfare, Taichung, Taiwan. 6Department of Electrical Engineering, National Taipei University of Technology, Taipei, Taiwan. 7Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan.
PY - 2013/12/9
Y1 - 2013/12/9
N2 - Background: Weaning is typically regarded as a process of discontinuing mechanical ventilation in the daily practice of an intensive care unit (ICU). Among the ICU patients, 39%-40% need mechanical ventilator for sustaining their lives. The predictive rate of successful weaning achieved only 35-60% for decisions made by physicians. Clinical decision support systems (CDSSs) are promising in enhancing diagnostic performance and improve healthcare quality in clinical setting. To our knowledge, a prospective study has never been conducted to verify the effectiveness of the CDSS in ventilator weaning before. In this study, the CDSS capable of predicting weaning outcome and reducing duration of ventilator support for patients has been verified. Methods: A total of 380 patients admitted to the respiratory care center of the hospital were randomly assigned to either control or study group. In the control group, patients were weaned with traditional weaning method, while in the study group, patients were weaned with CDSS monitored by physicians. After excluding the patients who transferred to other hospitals, refused further treatments, or expired the admission period, data of 168 and 144 patients in the study and control groups, respectively, were used for analysis. Results: The results show that a sensitivity of 87.7% has been achieved, which is significantly higher (p<0.01) than the weaning determined by physicians (sensitivity: 61.4%). Furthermore, the days using mechanical ventilator for the study group (38.41 ± 3.35) is significantly (p<0.001) shorter than the control group (43.69 ± 14.89), with a decrease of 5.2 days in average, resulting in a saving of healthcare cost of NT$45,000 (US$1,500) per patient in the current Taiwanese National Health Insurance setting. Conclusions: The CDSS is demonstrated to be effective in identifying the earliest time of ventilator weaning for patients to resume and sustain spontaneous breathing, thereby avoiding unnecessary prolonged ventilator use and decreasing healthcare cost.
AB - Background: Weaning is typically regarded as a process of discontinuing mechanical ventilation in the daily practice of an intensive care unit (ICU). Among the ICU patients, 39%-40% need mechanical ventilator for sustaining their lives. The predictive rate of successful weaning achieved only 35-60% for decisions made by physicians. Clinical decision support systems (CDSSs) are promising in enhancing diagnostic performance and improve healthcare quality in clinical setting. To our knowledge, a prospective study has never been conducted to verify the effectiveness of the CDSS in ventilator weaning before. In this study, the CDSS capable of predicting weaning outcome and reducing duration of ventilator support for patients has been verified. Methods: A total of 380 patients admitted to the respiratory care center of the hospital were randomly assigned to either control or study group. In the control group, patients were weaned with traditional weaning method, while in the study group, patients were weaned with CDSS monitored by physicians. After excluding the patients who transferred to other hospitals, refused further treatments, or expired the admission period, data of 168 and 144 patients in the study and control groups, respectively, were used for analysis. Results: The results show that a sensitivity of 87.7% has been achieved, which is significantly higher (p<0.01) than the weaning determined by physicians (sensitivity: 61.4%). Furthermore, the days using mechanical ventilator for the study group (38.41 ± 3.35) is significantly (p<0.001) shorter than the control group (43.69 ± 14.89), with a decrease of 5.2 days in average, resulting in a saving of healthcare cost of NT$45,000 (US$1,500) per patient in the current Taiwanese National Health Insurance setting. Conclusions: The CDSS is demonstrated to be effective in identifying the earliest time of ventilator weaning for patients to resume and sustain spontaneous breathing, thereby avoiding unnecessary prolonged ventilator use and decreasing healthcare cost.
UR - https://www.scopus.com/pages/publications/84889679964
UR - https://www.scopus.com/pages/publications/84889679964#tab=citedBy
U2 - 10.1186/1475-925X-12-S1-S4
DO - 10.1186/1475-925X-12-S1-S4
M3 - Article
C2 - 24565021
AN - SCOPUS:84889679964
SN - 1475-925X
VL - 12
JO - Biomedical engineering online
JF - Biomedical engineering online
IS - SUPPL 1
M1 - S4
ER -