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

2. 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.

3. 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

4. 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

5. 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

6. 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

7. 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 who have ever smoked more than 100 cigarettes in their lifetime.”

8. 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

9. 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 < and p = respectively).
*prevalence of AAA was 6%

10. Pre-study vs Post-study

11. 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 < respectively), but the mail and telephone intervention methods did not (p = and p  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

12. 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).

13. 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)

14. 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