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Improving Cancer Screening Rates in Primary Care via Practice Facilitation and Academic Detailing: A Multi-PBRN
Christopher P Morley1, Laura A Schad1, Laurene M Tumiel-Berhalter2,3
1Department of Public Health and Preventive Medicine, State University of New York (SUNY) Upstate Medical University, Syracuse, NY.
Purpose:
In the United States, cancer screening rates are often below national targets. This project implemented practice facilitation and academic detailing aimed at increasing breast, cervical, and colorectal cancer screening rates in safety-net primary care practices.
Methods:
Three practice-based research networks across western and central New York State partnered to provide quality improvement strategies on breast, cervical, and colorectal cancer screening. Pre/postintervention screening rates for all participating practices were collected annually, as were means across all practices over 7 years. Simple ordinary least squares linear regression was used to calculate the trend for each cancer type and test for statistical significance (ie, P≤0.05), using the ordinal time point as a fixed effect.
Results:
An overall increase in mean screening rates was seen over the duration of this project for colorectal (24.6% preintervention to 48.0% in year 7 of intervention; P<0.001) and breast cancer (37.0% preintervention to 48.6% in year 7; P=0.460). Mean cervical cancer screening rates decreased (35.5% preintervention to 31.4% in year 7; P=0.209). Success in increasing screening rates varied across regions of New York State.
Conclusions:
Practice facilitation and academic detailing were successful in significantly increasing, on average, colorectal cancer screening rate. Cervical cancer screening showed an overall decrease, likely due to difficulties for primary care practices in tracking and implementation, as many patients seek this service at outside gynecology facilities. Regional differences, guideline changes, and practice reorganization each may have played a part in observed trends. A standardization of queries being used to pull screening rates is an important step in increasing the reliability of these data.
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