Optimizing Hospital-wide Patient Scheduling (Record no. 50930)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03209nam a22005655i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-319-04066-0 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20200420211745.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 150523s2014 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783319040660 |
| -- | 978-3-319-04066-0 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 658.40301 |
| 100 1# - AUTHOR NAME | |
| Author | Gartner, Daniel. |
| 245 10 - TITLE STATEMENT | |
| Title | Optimizing Hospital-wide Patient Scheduling |
| Sub Title | Early Classification of Diagnosis-related Groups Through Machine Learning / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XIV, 119 p. 22 illus. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Lecture Notes in Economics and Mathematical Systems, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Introduction -- Machine learning for early DRG classification -- Scheduling the hospital-wide flow of elective patients -- Experimental analyses -- Conclusion. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Diagnosis-related groups (DRGs) are used in hospitals for the reimbursement of inpatient services. The assignment of a patient to a DRG can be distinguished into billing- and operations-driven DRG classification. The topic of this monograph is operations-driven DRG classification, in which DRGs of inpatients are employed to improve contribution margin-based patient scheduling decisions. In the first part, attribute selection and classification techniques are evaluated in order to increase early DRG classification accuracy. Employing mathematical programming, the hospital-wide flow of elective patients is modelled taking into account DRGs, clinical pathways and scarce hospital resources. The results of the early DRG classification part reveal that a small set of attributes is sufficient in order to substantially improve DRG classification accuracy as compared to the current approach of many hospitals. Moreover, the results of the patient scheduling part reveal that the contribution margin can be increased as compared to current practice. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-319-04066-0 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2014. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
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| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
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| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Business. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Operations research. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Decision making. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Health care management. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Health services administration. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Health informatics. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Management science. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Business and Management. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Operation Research/Decision Theory. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Health Informatics. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Health Informatics. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Operations Research, Management Science. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Health Care Management. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 0075-8442 ; |
| 912 ## - | |
| -- | ZDB-2-SBE |
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