東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

An algorithm for estimating the dura...

Lease, Mark Wayne.

FindBook

Google Book

Amazon

博客來

An algorithm for estimating the duration of a planned surgical procedure based on a historical database.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	An algorithm for estimating the duration of a planned surgical procedure based on a historical database./
作者:	Lease, Mark Wayne.
面頁冊數:	118 p.
附註:	Source: Dissertation Abstracts International, Volume: 63-08, Section: B, page: 3645.
Contained By:	Dissertation Abstracts International63-08B.
標題:	Health Sciences, Health Care Management. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3060842
ISBN:	0493764879

An algorithm for estimating the duration of a planned surgical procedure based on a historical database.
Lease, Mark Wayne.

An algorithm for estimating the duration of a planned surgical procedure based on a historical database. - 118 p.

Source: Dissertation Abstracts International, Volume: 63-08, Section: B, page: 3645.

Thesis (Ph.D.)--Texas A&M University, 2002.

The operating suites of a busy hospital will see over 15,000 surgeries per year. Between 50 and 100 surgeries will be performed per day, involving over 300 staff: physicians, nurses, surgical technicians, and other support personnel. A hospital's surgery schedule for a day is constantly being revised for many reasons: difficult procedures may take longer to complete than expected, emergencies may require reshuffling of rooms and personnel, and ambulatory patients may not arrive when scheduled. While there is an inherent element of unpredictability in estimating in advance a surgery schedule, having and maintaining an accurate schedule is still important for a number of reasons: every change to the schedule requires many people to change their plans, expensive surgical resources can be wasted, and patient satisfaction is adversely effected.

ISBN: 0493764879Subjects--Topical Terms:

1017922
Health Sciences, Health Care Management.

An algorithm for estimating the duration of a planned surgical procedure based on a historical database.
LDR:03184nmm 2200301 4500 001 1811204
005 20051203081804.5
008 130610s2002 eng d
020 $a 0493764879
035 $a (UnM)AAI3060842
035 $a AAI3060842
040 $a UnM $c UnM
100 1 $a Lease, Mark Wayne. $3 1900793
245 1 3 $a An algorithm for estimating the duration of a planned surgical procedure based on a historical database.
300 $a 118 p.
500 $a Source: Dissertation Abstracts International, Volume: 63-08, Section: B, page: 3645.
500 $a Chair: William M. Lively.
502 $a Thesis (Ph.D.)--Texas A&M University, 2002.
520 $a The operating suites of a busy hospital will see over 15,000 surgeries per year. Between 50 and 100 surgeries will be performed per day, involving over 300 staff: physicians, nurses, surgical technicians, and other support personnel. A hospital's surgery schedule for a day is constantly being revised for many reasons: difficult procedures may take longer to complete than expected, emergencies may require reshuffling of rooms and personnel, and ambulatory patients may not arrive when scheduled. While there is an inherent element of unpredictability in estimating in advance a surgery schedule, having and maintaining an accurate schedule is still important for a number of reasons: every change to the schedule requires many people to change their plans, expensive surgical resources can be wasted, and patient satisfaction is adversely effected.
520 $a This research makes two contributions: (1) a system for efficiently developing and executing a surgical schedule is described, and (2) an algorithm is described to estimate the surgery time of future surgeries by comparing the surgeon's descriptive coding of the proposed procedures against a historical database of similar procedures and it demonstrates that the implemented algorithm results in estimated surgery times that are statistically more accurate than the surgeons' estimates of the same surgeries.
520 $a The resulting algorithm uses a classification-tree approach modified to remove the computational intractability of the "classic" classification tree, and the modified approach provides an explanation of why the resulting surgery duration was chosen. As the size of the database containing the historical surgical information grows, the algorithm is well behaved---the size of the resulting classification tree, the computer time required to generate the tree, and the access time required to find the duration estimate from the tree all grow slightly faster than linearly. The algorithm can accommodate many years of surgical history with modest computer hardware resources. With a cumulative, absolute error rate of 28.3%, the algorithm proved to be more accurate in estimating the duration of 14,250 surgeries than the 33.0% error rate of the surgeons performing the surgery.
590 $a School code: 0803.
650 4 $a Health Sciences, Health Care Management. $3 1017922
650 4 $a Health Sciences, Medicine and Surgery. $3 1017756
690 $a 0769
690 $a 0564
710 2 0 $a Texas A&M University. $3 718977
773 0 $t Dissertation Abstracts International $g 63-08B.
790 1 0 $a Lively, William M., $e advisor
790 $a 0803
791 $a Ph.D.
792 $a 2002
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3060842