Clinical Decision Support System Based on Hybrid Knowledge Modeling
A Case Study of Chronic Kidney Disease-Mineral and Bone Disorder Treatment
Bibliographic Data
| ID | 15474342 |
|---|---|
| Authors | Syed Imran Ali (0000-0001-6056-4746, Kyung Hee University), Su Woong Jung (0000-0002-9053-924X, Kyung Hee University Hospital at Gangdong, corresponding author), Hafiz Syed Muhammad Bilal (0000-0002-8920-4231, Kyung Hee University), Sang Ho Lee (0000-0002-4634-4904, Kyung Hee University), Sang-Ho Lee (0000-0002-7572-5706, Department of Internal Medicine, Division of Nephrology, Kyung Hee University Hospital at Gangdong, Seoul 05278, Korea), Jamil Hussain (0000-0003-3862-8787, Sejong University), Muhammad Afzal (0000-0003-2570-3223, Sejong University), Maqbool Hussain (0000-0002-1663-1718, Sejong University), Taqdir Ali (0000-0002-4684-5960, University of British Columbia), TaeChoong Chung (Kyung Hee University, corresponding author), Sungyoung Lee (0000-0002-5962-1587, Kyung Hee University, corresponding author) |
| Year | 2021 |
| Volume | 19 |
| Issue | 1 |
| Pages | 226-226 |
| Publication date | 2021-12-26 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph19010226 |
| PMID | 35010486 |
| OpenAlex | W4200515998 |
| Language | EN |
| References cited | 52 |
Clinical decision support systems (CDSSs) represent the latest technological transformation in healthcare for assisting clinicians in complex decision-making. Several CDSSs are proposed to deal with a range of clinical tasks such as disease diagnosis, prescription management, and medication ordering. Although a small number of CDSSs have focused on treatment selection, areas such as medication selection and dosing selection remained under-researched. In this regard, this study represents one of the first studies in which a CDSS is proposed for clinicians who manage patients with end-stage renal disease undergoing maintenance hemodialysis, almost all of whom have some manifestation of chronic kidney disease-mineral and bone disorder (CKD-MBD). The primary objective of the system is to aid clinicians in dosage prescription by levering medical domain knowledge as well existing practices. The proposed CDSS is evaluated with a real-world hemodialysis patient dataset acquired from Kyung Hee University Hospital, South Korea. Our evaluation demonstrates overall high compliance based on the concordance metric between the proposed CKD-MBD CDSS recommendations and the routine clinical practice. The concordance rate of overall medication dosing selection is 78.27%. Furthermore, the usability aspects of the system are also evaluated through the User Experience Questionnaire method to highlight the appealing aspects of the system for clinicians. The overall user experience dimension scores for pragmatic, hedonic, and attractiveness are 1.53, 1.48, and 1.41, respectively. A service reliability for the Cronbach's alpha coefficient greater than 0.7 is achieved using the proposed system, whereas a dependability coefficient of the value 0.84 reveals a significant effect
Clinical decision support system · Concordance · Cronbach's alpha · Data mining · Decision support system · Hemodialysis · Intensive care medicine · Kidney disease · Medical physics · Medical prescription · Psychometrics · Usability · Artificial Intelligence in Healthcare · Blood Pressure and Hypertension Studies · Clinical Psychology · Computer Science · Machine Learning in Healthcare · Medicine · Nursing · Internal Medicine
| Citation velocity | historical |
|---|---|
| Highly cited | No |