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: 3122
Function: getPubMedXML
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
Objective: Identify potential negative impacts arising from implementing an electronic medical record system, classify them according to the level of criticality, and analyze method's effectiveness after implementation.
Methods: The research involved identifying the negative impacts, classifying them according to the criteria for criticality, stratifying them as high, medium, or low severity, and finally, analyzing the effectiveness of the identification and classification methods.
Results: Findings confirmed that 89.20% of identified impacts occurred as predicted, and 88.94% of impacts had a level of criticality compatible with the severity of the problem.
Conclusion: Predicting and classifying negative impacts are important stages in implementing electronic health records in hospitals. The method for identification and classification of impacts were, in most cases, considered effective.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11634333 | PMC |
http://dx.doi.org/10.31744/einstein_journal/2024AO0916 | DOI Listing |
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