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
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
Introduction: Screening for colorectal cancer (CRC) is effective in reducing CRC burden. Primary care clinics have an important role in increasing screening. We investigated associations between clinic-level CRC screening rates of the clinics serving low income, medically underserved population, and clinic-level screening interventions, clinic characteristics and community contexts.
Methods: Using data (2015-16) from the Centers for Disease Control and Prevention's (CDC) Colorectal Cancer Control Program, we linked clinic-level data with county-level contextual data from external sources. Analysis variables included clinic-level CRC screening rates, four different evidence-based interventions (EBIs) intended to increase screening, clinic characteristics, and clinic contexts. In the analysis (2018), we used weighted ordinary least square multiple regression analyses to associate EBIs and other covariates with clinic-level screening rates.
Results: Clinics (N = 581) had an average screening rate of 36.3% (weighted. Client reminders had the highest association (5.6 percentage points) with screening rates followed by reducing structural barriers (4.9 percentage points), provider assessment and feedback (3.2 percentage points), and provider reminders (<1 percentage point). Increases in the number of EBIs was associated with steady increases in the screening rate (5.4 percentage points greater for one EBI). Screening rates were 16.4 percentage points higher in clinics with 4 EBIs vs. no EBI. Clinic characteristics, contexts (e.g. physician density), and context-EBI interactions were also associated with clinic screening rates.
Conclusions: These results may help clinics, especially those serving low income, medically underserved populations, select individual or combinations of EBIs suitable to their contexts while considering costs.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6904949 | PMC |
http://dx.doi.org/10.1016/j.ypmed.2019.105774 | DOI Listing |
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