Proactive Recruitment Strategy for Patient Identification for Lung Cancer Screening.

PURPOSE: We assessed low-dose computed tomography (LDCT) screening for lung cancer using a proactive patient education/recruitment program. METHODS: We identified patients aged 55-80 years from a family medicine group. In the retrospective phase (March-August, 2019), patients were categorized as current/former/never smokers, and screening eligibility was determined. Patients who underwent LDCT in the past year, along with outcomes, were documented. In the prospective phase (2020), patients in the same cohort who did not undergo LDCT were proactively contacted by a nurse navigator to discuss eligibility and prescreening. Eligible and willing patients were referred to their primary care physician. RESULTS: In the retrospective phase, of 451 current/former smokers, 184 (40.8%) were eligible for LDCT, 104 (23.1%) were ineligible, and 163 (36.1%) had an incomplete smoking history. Of those eligible, 34 (18.5%) had LDCT ordered. In the prospective phase, 189 (41.9%) were eligible for LDCT (150 [79.4%] of whom had no prior LDCT or diagnostic CT), 106 (23.5%) were ineligible, and 156 (34.6%) had an incomplete smoking history. The nurse navigator identified an additional 56/451 (12.4%) patients as eligible after contacting patients with incomplete smoking history. In total, 206 patients (45.7%) were eligible, an increase of 37.3% compared with the retrospective phase (150). Of these, 122 (59.2%) verbally agreed to screening, 94 (45.6%) met with their physician, and 42 (20.4%) were prescribed LDCT. CONCLUSIONS: A proactive education/recruitment model increased eligible patients for LDCT by 37.3%. Proactive identification/education of patients desiring to pursue LDCT was 59.2%. It is essential to identify strategies that will increase and deliver LDCT screening among eligible and willing patients.

Point-of-Care Ultrasound and Procedural Instruction in the Family Medicine Clerkship: A CERA Study.

BACKGROUND AND OBJECTIVES: Point-of-care ultrasound (POCUS) education has become a mainstay in resident education in multiple specialties, including family medicine (FM), but literature regarding the use of POCUS during clinical medical student education is lacking. The purpose of this study was to investigate whether and how POCUS education is conducted in FM clerkships in the United States and Canada and how it compares to more traditional FM clinical procedural instruction. METHODS: As part of the 2020 Council of Academic Family Medicine's Educational Research Alliance survey of FM clerkship directors, we surveyed clerkship directors in the United States and Canada about whether and how POCUS education, as well as other procedural instruction in their institutions and FM clerkships, was conducted. We included questions regarding POCUS and other procedural use by preceptors and faculty. RESULTS: We found that 13.9% of clerkship directors reported structured POCUS education during clerkship, while 50.5% included other procedural training. The survey revealed that 65% of clerkship directors felt that POCUS was an important component of FM, but this was not a predictor of POCUS use in personal or preceptor practice nor of its inclusion in FM clerkship education. CONCLUSIONS: Structured POCUS education is a rare component of FM clerkship education; while more than half of clerkship directors felt that POCUS was important for FM, few used it personally or included it in clerkship education. As POCUS continues to be integrated into medical education in FM, the clerkship may represent an opportunity to expand POCUS exposure for students.

Simulation-Based Medical Education in Family Medicine Residencies: A CERA Study.

BACKGROUND AND OBJECTIVES: To better understand the current use of simulation and barriers to its use in family medicine resident education, we surveyed US family medicine residency (FMR) program directors (PDs) about opinions and use of simulation-based medical education (SBME) in their programs. A number of specialties have incorporated or required simulation-based educational techniques in residency education over the past 10 years, but little is known about the current use of SBME in family medicine graduate medical education. We also evaluated associations between program characteristics and the use of SBME in FMR education. METHODS: Questions were included on the 2019 Council of Academic Family Medicine Education Research Alliance (CERA) survey of US FMR PDs. The survey included questions regarding current use of SBME along with questions to identify barriers to its use in family medicine programs. RESULTS: Thirty-nine percent (n=250) of PDs completed the survey; 84.5% reported using simulation. PDs reporting they did not use simulation were less likely to view simulation as valuable for education or assessment. Unexpectedly, residency program size was not associated with simulation use or access to a dedicated location for SBME. DISCUSSION: Use of SBME in family medicine resident education has increased since 2011. PDs value simulation for education and remediation, and most programs have introduced some degree of simulation despite barriers. The results of this study can inform resources to support the continued integration of SBME into family medicine resident education.

Cognitive Component Structure of a Neuropsychological Battery Administered to Cognitively-Normal Adults in the SIU Longitudinal Cognitive Aging Study.

We used principal component analysis (PCA) to examine the component structure of a neuropsychological test battery administered to 943 cognitively-normal adults enrolled in the Southern Illinois University (SIU) Longitudinal Cognitive Aging Study (LCAS). Four components explaining the most variance (63.9%) in the dataset were identified: speed/cognitive flexibility, visuospatial skills, word-list learning/memory, and story memory. Regression analyses confirmed that increased age was associated with decreased component scores after controlling for gender and education. Our identified components differ slightly from previous studies using PCA on similar test batteries. Factors such as the demographic characteristics of the study sample, the inclusion of mixed patient and control samples, the inclusion of different test measures in previous studies, and the fact that many neuropsychological test measures assess multiple cognitive processes simultaneously, may help to explain these inconsistencies.