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
In light of the lack of integration between electronic health records and decision support, this research explores how semantic electronic health record technology, particularly openEHR, can be used to represent clinical practice guidelines (CPGs). We used the tool Visual Understanding Environment (VUE) to build a graphical representation of the European ischaemic stroke clinical management guidelines. We used openEHR archetypes to conceptually support this process and also to represent clinical concepts in stroke treatment compliance criteria. Our results show that, as an intermediate step in authoring computer-interpretable guidelines, an openEHR-based representation of CPGs and their compliance criteria supports the process of identifying the relevant knowledge and data elements in the care process to be modelled. It further eases the separation of the CPGs into data and logic components and is useful as a communication means for guideline verification by clinicians. Additionally, we retrieved existing and authored new openEHR archetypes for the acute stroke clinical management process. We conclude that openEHR-based guideline and compliance data representations may be a promising first step in building future decision support applications that are well connected to the electronic health record, can be useful in locating discrepancies between different sets of guidelines within the same care context and provide a helpful tool for driving the archetype authoring and review process.
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