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
Purpose Of Review: While randomized controlled trials have historically served as the gold standard for shaping guideline recommendations, real-world data are increasingly being used to inform clinical decision-making. We describe ways in which healthcare systems are generating real-world data related to dyslipidemia and how these data are being leveraged to improve patient care.
Recent Findings: The electronic medical record has emerged as a major source of clinical data, which alongside claims and pharmacy dispending data is enabling healthcare systems the ability to identify care gaps (underdiagnosis and undertreatment) in patients with dyslipidemia. Availability of this data also allows healthcare systems the ability to test and deliver interventions at the point-of-care. Real-world data possess great potential as a complement to randomized controlled trials. Healthcare systems are uniquely positioned to not only define care gaps and areas of opportunity, but to also to leverage tools (e.g., clinical decision support, case identification) aimed at closing them.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1007/s11886-022-01767-5 | DOI Listing |
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