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 Medical Event Reporting System for Transfusion Medicine (MERS-TM) collects, classifies, and analyzes events that potentially could compromise the safety of transfused blood to facilitate system improvement. This system is designed to collect data on near misses as well as actual events. Near-miss events are a valuable source of data because they occur more frequently than, but share many characteristics and causes of, actual events. Further, although most current reporting efforts describe only what has occurred with little attention to what caused the event, MERS-TM includes a standardized method of causal analysis. The standardization provided by MERS allows users to compare their experience with that of other organizations, which speeds learning across the entire transfusion medicine community. Important features of the MERS-TM system are that it is able to capture threats, hazards, near misses, injuries, and deaths; characterizes failures and recoveries systematically; identifies and provides causal codes for the entire range of system defects including technical, organizational, cultural, and human factors; raises staff awareness about error management; is easily integrated with existing quality assurance programs; has a consistent and straightforward classification method; enables compliance with mandatory Food and Drug Administration reporting and accreditation requirements; has features to deal with a high volume of reports; supplies Web-based training, data entry, and analysis; and provides comparative benchmarks from comparable institutions.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1053/tmrv.2002.31459 | DOI Listing |
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