Effect of behavioral intervention on inappropriate antibiotic prescribing among primary care practices: a randomized clinical trial

Sylvia Okoma, Mercer University College of Pharmacy

The United Kingdom’s Review on Antimicrobial Resistance and the United States Federal Government Taskforce for Combating Antibiotic Resistant Bacteria both emphasize the importance of working to reduce the rise of resistant bacteria by changing antibiotic prescribing patterns.   [1, 2]

However, it has been identified that inappropriate antibiotic prescribing habits continue to be threat for the development of antimicrobial resistance.   [3, 4]

Title: Effect of Behavioral Intervention on Inappropriate Antibiotic Prescribing Among Primary Care Practices: A Randomized Clinical Trial [5]
Design Cluster, randomized clinical trial; N = 31,712
Objective To assess the effects of behavioral interventions in prescribing patterns and the rate of inappropriate, not guideline concordant antibiotic prescribing during ambulatory visits for acute respiratory tract infections
Study Groups Visits during the intervention period (n = 16, 959) that can be further divided by number of interventions: zero interventions (n = 2,095); one intervention (n = 6,462); two interventions (n = 6,385); three interventions (n = 2,492)
Methods There were 47 primary care practices in Boston and Los Angeles that participated and enrolled 248 clinicians who were randomized to receive zero, one, two, or three interventions over an eighteen month period.  All clinicians were educated on the antibiotic prescribing guidelines prior to enrollment and received incentives for enrollment in the study.  Three behavioral interventions were used and were implemented alone or in combination at the primary care practices.  Accountable justification prompted clinicians to provide a free-text justification for prescribing antibiotics and this was recorded in the patients’ electronic health records.  Peer comparison utilized emails that were sent to clinicians and provided a comparison of the antibiotic prescribing rates of the prescriber with the lowest inappropriate prescribing rates, called “top performers”.  Suggested alternatives used electronic order sets that suggested non-antibiotic treatments for select physician encounters.
Duration November 1, 2011 to April 1, 2014
Primary Outcome Measure Antibiotic prescribing for antibiotic-inappropriate diagnoses, namely nonspecific upper respiratory tract infections, acute bronchitis, and influenza, from 18 months of the pre-intervention period to 18 months after the intervention period.
Baseline Characteristics Overall
Clinician type, n (%)
Internal medicine 150 (60)
Family medicine 32 (13)
Number of clinicians by region, n (%)
Massachusetts 171 (69)
Southern California 77 (31)
Patient Characteristics
Age, mean (SD), y 48 (17)
Men, n (%) 5,567 (33)
Race, n (%)
White 14,415 (87)
Hispanic or Latino 5,383 (32)
Insurance type, n (%)
Medicare 2,340 (14)
State or country subsidized 3,894 (24)
Private 9,737 (59)
Results The mean incidences of inappropriate antibiotic prescribing rates changed from 24.1% when the intervention started to 13.1% 18 months later for the baseline control group (no p value reported).

 

For the suggested alternatives group it changed from 22.1% to 6.1% with a variation in difference of -5.0% [95% confidence interval (CI), -7.8% to 0.1%, p = 0.66].

 

In the accountable justification group, there was a change from 23.2% to 5.2% with a variation in difference of -7.0% [95% CI, -9.1% to -2.9%, p < 0.001].

 

Lastly, a change from 19.9% to 3.7% was noted for the peer comparison group with a variation in difference of -5.2% [95% CI, -6.9% to -1.6%, p < 0.001].

Adverse Events Common Adverse Events: acute respiratory tract infection in patients who did not receive antibiotics in the control practices (0.43%) and accountable justification and peer comparison groups (1.41%)
Serious Adverse Events: None reported
Percentage that Discontinued due to Adverse Events: N/A
Study Author Conclusions Peer influenced and socially motivated comparison interventions, namely accountable justification and peer comparison groups, performed more favorably in comparison with traditional audit-and-feedback method used with the suggested alternatives group.  In addition, the accountable justification and peer comparison methods of behavioral intervention resulted in lower rates of inappropriate antibiotic prescribing for acute respiratory tract infections.

It has been proposed that the peer comparison intervention would provide the simplest and most practical intervention because it does not require modification of the electronic health record (EHR).  However, the accountable justification intervention could easily be applied to clinical decision making.   Future efforts to reduce the impact of antimicrobial resistance in healthcare practice should focus on the influences of behavioral science by focusing on efforts to reduce the disruption of clinicians’ workflow while appealing to their pride in performance.

 

References

  1. O’Neill, Jim.   Antimicrobial resistance: tackling a crisis for the health and wealth of nations.   The Review of Antimicrobial Resistance, Dec 2014.   http://amr-review.org/sites/default/files/AMR%20Review%20Paper%20-%20Tackling%20a%20crisis%20for%20the%20health%20and%20wealth%20of%20nations_1.pdf  Accessed 11 Feb 2016.
  2. Office of the Press Secretary, The White House.  Executive order-combating antibiotic-resistant bacteria.   Whitehouse.gov, Sep 2014.   https://www.whitehouse.gov/the-press-ofice/2014/09/18/executive-order-combating-antibiotic-resistant-bacteria  Accessed 11 Feb 2016.
  3.  Steinman, MA, R.  Gonzales, JA Linder, and CS Landefeld.   Changing use of antibiotics in community-based outpatient practice, 1991-1999.   Annals of Internal Medicine, 138 (7):525-533; 2003.   Accessed 11 Feb 2016.
  4. Linder, JA.   Antibiotic prescribing for acute respiratory infections-success that’s way off the mark: comment on “A cluster randomized trial of decision support strategies for reducing antibiotic use in acute bronchitis”.  JAMA Internal Medicine, 173(4):273-275; 2013.  Accessed 11 Feb 2016.
  5.  Meeker, D., J.  Linder, C.  Fox, M.  Friedberg, et al.  Effect of behavioral interventions on inappropriate antibiotic prescribing among primary care practices: a randomized clinical trial.   JAMA 315(6): 562-579, 9 Feb 2016.   Accessed 10 Feb 2016.
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