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Filename: drivers/Session_files_driver.php
Line Number: 177
Backtrace:
File: /var/www/html/index.php
Line: 316
Function: require_once
Severity: Warning
Message: session_start(): Failed to read session data: user (path: /var/lib/php/sessions)
Filename: Session/Session.php
Line Number: 137
Backtrace:
File: /var/www/html/index.php
Line: 316
Function: require_once
Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1057
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3175
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
A core performance target for the English National Health Service (NHS) concerns waiting times at Emergency Departments (EDs), with the aim of minimising long waits. We investigate the drivers of long waits. We analyse weekly data for all major EDs in England from April 2011 to March 2016. A Poisson model with ED fixed effects is used to explore the impact on long (> 4 h) waits of variations in demand (population need and patient case-mix) and supply (emergency physicians, introduction of a Minor Injury Unit (MIU), inpatient bed occupancy, delayed discharges and long-term care). We assess overall ED waits and waits on a trolley (gurney) before admission. We also investigate variation in performance among EDs. The rate of long overall waits is higher in EDs serving older patients (4.2%), where a higher proportion of attendees leave without being treated (15.1%), in EDs with a higher death rate (3.3%) and in those located in hospitals with greater bed occupancy (1.5%). These factors are also significantly associated with higher rates of long trolley waits. The introduction of a co-located MIU is significantly and positively associated with long overall waits, but not with trolley waits. There is substantial variation in waits among EDs that cannot be explained by observed demand and supply characteristics. The drivers of long waits are only partially understood but addressing them is likely to require a multi-faceted approach. EDs with high rates of unexplained long waits would repay further investigation to ascertain how they might improve.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7072048 | PMC |
http://dx.doi.org/10.1007/s10198-019-01121-7 | DOI Listing |
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