Strategies to Improve AAA Screening Rates in Primary Care Ethan Zimmerman, MD Nellis Air Force Base Las Vegas, NV

Background AAA screening beneficial Screening rate ≈ 26% USPSTF (B recommendation) RRR: 11-66% Cost effective: $14-20K per life-year gained Screening rate ≈ 26% How can screening rates be improved? AAA screening is unanimously endorsed…at least on this continent. RRR is for screened vs unscreened population. Compares favorably to colon (A) and breast (B) cancer screening. Despite this, eligible patients remain largely unscreened. While the need for screening is not in dispute, we are still uncertain as to the best way to raise screening rates. This is the question we endeavored to answer.

Methods Study Design: 4-arm prospective cohort study Setting: primary care clinics at a military medical center Participants: enrolled males 65-75 IM and FM—including residency clinic

eligible for screening Patient Selection 1,651 enrolled men age 65-75 Excluded 102 already diagnosed with AAA 1,549 eligible for screening Excluded 672 with recent abdominal imaging 877 due for screening “recent abd imaging” = within last 5 yrs that would have detected AAA (i.e. ultrasonography, computed tomography, magnetic resonance imaging or aortography) IM = internal medicine Divided into cohort by assigned clinic 365 IM clinic 106 Stealth clinic 187 Raptor clinic 219 Phantom clinic

Patient Assignment Cohort (n) Intervention strategy Internal med (365) Point-of-care reminders Stealth clinic, FMR (106) Telephone reminders Raptor clinic, FM (187) Mailed reminders Phantom clinic, FM (219) Control (usual care) FMR = family medicine residency FM = family medicine Remember we recruited regardless of smoking history, hence needed to weed out

Point-of-Care Staff education EMR reminder AAA screening flyers posted Providers quizzed on USPSTF, then educated Nurses, medical assistants informed EMR reminder AAA added to prev med tracker MA’s updated at each clinic visit AAA screening flyers posted Provider orders during visit if indicated

Telephone Call made by nurse, standard text used Age, gender verified Required in-service Age, gender verified Smoking history confirmed EMR note with U/S order sent to provider for signature No answer? Up to 3 calls on 3 separate days Then letter asking for return phone call Std text = “You have been identified as meeting criteria for abdominal aortic aneurysm screening. It’s a routine screening ultrasound recommended for all males age 65-75 who have ever smoked more than 100 cigarettes in their lifetime.”

Mail Clarifies USPSTF, age, male, smoking history Encourages screening “5% of adults have AAA…risk for rupture” “early detection and treatment…quality of life” “offering a cost free screening ultrasound” Patient instructed to call clinic Provider orders U/S Letter stuffed/sent by med assistant

Screening trends *prevalence of AAA was 6% Note these are not “true” screening rates…consider adding actual abd U/S screening rate Evident from this plot that the screening rates pre-study as well as the final screening rates were dis-similar. Within each of the pre-study and post-intervention samples, the proportions of patients screened or diagnosed were not equal among intervention methods (p <0.0001). Further analysis revealed the point-of-care intervention method had a higher proportion of patients being screened/diagnosed than the mail intervention method within both the pre-study and post-intervention samples (p <0.0001 and p = 0.007 respectively). *prevalence of AAA was 6%

Pre-study vs Post-study

Statistical Analysis Cohort (n) Screening rates (%) P-value* Pre-study Post-intervention Telephone (182) 42 57 0.92 Mail (320) 53 0.35 Control (364) 40 47 <0.05 Point of care (785) 54 62 <0.0001 Total (1651) 56 <0.0001† Control and point of care intervention methods improved screening rates (p < 0.05 and p < 0.0001 respectively), but the mail and telephone intervention methods did not (p = 0.354 and p  0.918 respectively)…2x2 Contingency Table chi square using McNemar method (matched samples). The proportions of patients screened or diagnosed and those who are not in the paired pre-study and post-intervention samples were not equal when controlled for intervention method; intervention may be concluded to have improved screening/diagnosis without respect to intervention method. *McNemar chi square †Cochran–Mantel–Haenszel chi square

Conclusions Sample-wide impact was significant when controlled for intervention method Point-of-care intervention appeared to have had greatest impact but requires further study Significant change seen in control group also No change in mail and telephone cohorts It’s possible that the impact of point-of-care interventions is not superior to no intervention at all (control group).

Limitations Single center Baseline cohort screening rates differed Non-randomized Baseline screening rates dissimilar Across disciplines (academic, clinical) Across specialties (FM, IM) Interventions assumed to be labor-equivalent Lack of generalizability associated with non-randomized structure across clinics of heterogeneous specialty (FM/IM)

Future Considerations More in-depth data analysis Better comparison of differences among interventions Convert to quality improvement process PDSA…next step cross-over Extrapolation to other screening services Are efforts misplaced? Do reminders make a difference? Compare clinic-based interventions to public awareness campaigns