| LDR | | 02684nam u200421 4500 |
| 001 | | 000000420670 |
| 005 | | 20190215164648 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438062818 |
| 035 | |
▼a (MiAaPQ)AAI10786495 |
| 035 | |
▼a (MiAaPQ)unc:17594 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 610.73 |
| 100 | 1 |
▼a Linthicum, Benjamin Ovitt. |
| 245 | 10 |
▼a Improving Emergency Department Throughput by Adoption of an Admissions Predictor Tool at Triage. |
| 260 | |
▼a [S.l.]:
▼b The University of North Carolina at Chapel Hill.,
▼c 2018. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
| 300 | |
▼a 79 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B. |
| 500 | |
▼a Adviser: Debbie Travers. |
| 502 | 1 |
▼a Thesis (D.N.P.)--The University of North Carolina at Chapel Hill, 2018. |
| 520 | |
▼a Emergency departments are increasingly busier and busier. An area of concern for many hospitals is how to deal with the resulting overcrowding and related throughput problems. This is because delayed throughput is seen as a measure of quality d |
| 520 | |
▼a In this quality improvement project I sought to use an admissions predictor tool at triage to improve emergency department throughput by changing the process by which patients are identified and then processed for admissions. A new process was p |
| 520 | |
▼a A second goal for the project was to add to the collective evidence regarding the use of an admission predictor tool. This includes the practicality of its use as well as potential ways in which the tool could be improved upon or otherwise used |
| 520 | |
▼a I found the admissions process to be much more complex than initially anticipated and due to this complexity only one patient out of 281 patients screened underwent the new early bed request process. I found that in order to successfully use the |
| 520 | |
▼a I was able to find a new use for the predictor tool. By calculating an admissions probability on all patients in the emergency department, not already identified for admission, the tool was used to predict bed needs for the whole department at |
| 590 | |
▼a School code: 0153. |
| 650 | 4 |
▼a Nursing. |
| 690 | |
▼a 0569 |
| 710 | 20 |
▼a The University of North Carolina at Chapel Hill.
▼b Nursing. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-10B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0153 |
| 791 | |
▼a D.N.P. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997357
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a ***1012033 |