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
Background: General practitioners (GPs) assess the existence of the patient's disease, decide whether the disease affects the patient's ability to work and if necessary, recommend sick leave. Our aim was to describe correlations in patients' sick leave between GP practices (GPPs) in a 5-year period.
Method: The study included 253 GPPs, from 2007 to 2011. The personal numbers of patients from each GPP were connected to DREAM, a registry at the Danish Ministry of Employment that includes social welfare payments, including sick leave benefits. We adjusted for patient age, gender, ethnicity and social differences. Spearman's rank correlation coefficients (2007 - 2011) were used for calculating the correlation in adjusted sick leave.
Results: The number of patient sick leave weeks between GPPs varied from 36 to 2,704 sick leave weeks per 1000 patients (18 - 65 years). The correlation coefficients for adjusted sick leave weeks varied from 0.90 to 0.94 (P < 0.05). Correlations for the 10 GPPs with the highest number of sick leave weeks and the 10 GPPs with the lowest number of sick leave weeks were almost as high as the correlations of the total population of GPPs.
Conclusions: The study showed great differences in sick leave between GPPS; however, significant correlation for adjusted sick leave in each GPP was demonstrated this may indicate that GPS play an important role in their patients' sick leave the study provides a method to distinguish between gpps with low patient sick leave and high patient sick leave in causal studies of sick leave differences among GPS.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1177/1403494814541019 | DOI Listing |
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