• Anand Shah, Thomas J Polascik, Daniel J George, John Anderson, Terry Hyslop, Alicia M Ellis, Andrew J Armstrong, Michael Ferrandino, Glenn M Preminger, Rajan T Gupta, W Robert Lee, Nadine J Barrett, John Ragsdale, Coleman Mills, Devon K Check, Alireza Aminsharifi, Ariel Schulman, Christina Sze, Efrat Tsivian, Kae Jack Tay, Steven Patierno, Kevin C Oeffinger, and Kevin Shah.
• Duke University, Durham, NC, USA.
• J Gen Intern Med. 2021 Jan 1; 36 (1): 92-99.

BackgroundImplementation methods of risk-stratified cancer screening guidance throughout a health care system remains understudied.ObjectiveConduct a preliminary analysis of the implementation of a risk-stratified prostate cancer screening algorithm in a single health care system.DesignComparison of men seen pre-implementation (2/1/2016-2/1/2017) vs. post-implementation (2/2/2017-2/21/2018).ParticipantsMen, aged 40-75 years, without a history of prostate cancer, who were seen by a primary care provider.InterventionsThe algorithm was integrated into two components in the electronic health record (EHR): in Health Maintenance as a personalized screening reminder and in tailored messages to providers that accompanied prostate-specific antigen (PSA) results.Main MeasuresPrimary outcomes: percent of men who met screening algorithm criteria; percent of men with a PSA result. Logistic repeated measures mixed models were used to test for differences in the proportion of individuals that met screening criteria in the pre- and post-implementation periods with age, race, family history, and PSA level included as covariates.Key ResultsDuring the pre- and post-implementation periods, 49,053 and 49,980 men, respectively, were seen across 26 clinics (20.6% African American). The proportion of men who met screening algorithm criteria increased from 49.3% (pre-implementation) to 68.0% (post-implementation) (p < 0.001); this increase was observed across all races, age groups, and primary care clinics. Importantly, the percent of men who had a PSA did not change: 55.3% pre-implementation, 55.0% post-implementation. The adjusted odds of meeting algorithm-based screening was 6.5-times higher in the post-implementation period than in the pre-implementation period (95% confidence interval, 5.97 to 7.05).ConclusionsIn this preliminary analysis, following implementation of an EHR-based algorithm, we observed a rapid change in practice with an increase in screening in higher-risk groups balanced with a decrease in screening in low-risk groups. Future efforts will evaluate costs and downstream outcomes of this strategy.

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