Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
The high costs of building, equipping, and staffing critical care beds, coupled with more restrictive reimbursement policies, are forcing hospital administrators to seek ways for determining accurately the number of critical care beds needed. Existing critical care bedsizing models do not capture the complexity of today's critical care environment, nor have they been formally validated using actual hospital performance data. The study described herein was designed to address these needs. A GPSS/H simulation model was developed and validated, and includes the flow of patients through the study hospital's operating rooms, post-anesthesia recovery unit, three intensive care units, and two intermediate care (stepdown) units.
Download full-text PDF |
Source |
---|
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!