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
An interdisciplinary team developed, implemented, and evaluated a standardized structure and process for an electronic apparent cause analysis (eACA) tool that includes principles of high reliability, human factors engineering, and Just Culture. Steps include assembling a team, describing what happened, determining why the event happened, determining how defects might be fixed, and deciding which defects will be fixed. The eACA is an intuitive tool for identifying defects, apparent causes of those defects, and the strongest corrective actions. Moreover, the eACA facilitates system learning by aggregating apparent causes and corrective action trends to prioritize and implement system change(s).
Download full-text PDF |
Source |
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http://dx.doi.org/10.1016/j.jcjq.2024.05.009 | DOI Listing |
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