Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&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
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Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
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Function: require_once
Background: The Aston Medication Adherence Study was designed to examine non-adherence to prescribed medicines within an inner-city population using general practice (GP) prescribing data.
Objective: To examine non-adherence patterns to prescribed oral medications within three chronic disease states and to compare differences in adherence levels between various patient groups to assist the routine identification of low adherence amongst patients within the Heart of Birmingham teaching Primary Care Trust (HoBtPCT).
Setting: Patients within the area covered by HoBtPCT (England) prescribed medication for dyslipidaemia, type-2 diabetes and hypothyroidism, between 2000 and 2010 inclusively. HoBtPCT's population was disproportionately young, with seventy per cent of residents from Black and Minority Ethnic groups.
Method: Systematic computational analysis of all medication issue data from 76 GP surgeries dichotomised patients into two groups (adherent and non-adherent) for each pharmacotherapeutic agent within the treatment groups. Dichotomised groupings were further analysed by recorded patient demographics to identify predictors of lower adherence levels. Results were compared to an analysis of a self-report measure of adherence [using the Modified Morisky Scale(©) (MMAS-8)] and clinical value data (cholesterol values) from GP surgery records.
Main Outcome: Adherence levels for different patient demographics, for patients within specific longterm treatment groups.
Results: Analysis within all three groups showed that for patients with the following characteristics, adherence levels were statistically lower than for others; patients: younger than 60 years of age; whose religion is coded as "Islam"; whose ethnicity is coded as one of the Asian groupings or as "Caribbean", "Other Black" and "African"; whose primary language is coded as "Urdu" or "Bengali"; and whose postcodes indicate that they live within the most socioeconomically deprived areas of HoBtPCT. Statistically significant correlations between adherence status and results from the selfreport measure of adherence and of clinical value data analysis were found.
Conclusion: Using data from GP prescribing systems, a computerised tool to calculate individual adherence levels for oral pharmacotherapy for the treatment of diabetes, dyslipidaemia and hypothyroidism has been developed. The tool has been used to establish nonadherence levels within the three treatment groups and the demographic characteristics indicative of lower adherence levels, which in turn will enable the targeting of interventional support within HoBtPCT.
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http://dx.doi.org/10.1007/s11096-013-9896-3 | DOI Listing |
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