Use of behavioral economics and social psychology to improve treatment of acute respiratory infections (BEARI): rationale and design of a cluster randomized controlled trial [1RC4AG039115-01] - study protocol and baseline practice and provider characteristics

Background: Inappropriate antibiotic prescribing for nonbacterial infections leads to increases in the costs of care, antibiotic resistance among bacteria, and adverse drug events. Acute respiratory infections (ARIs) are the most common reason for inappropriate antibiotic use. Most prior efforts to decrease inappropriate antibiotic prescribing for ARIs (e.g., educational or informational interventions) have relied on the implicit assumption that clinicians inappropriately prescribe antibiotics because they are unaware of guideline recommendations for ARIs. If lack of guideline awareness is not the reason for inappropriate prescribing, educational interventions may have limited impact on prescribing rates. Instead, interventions that apply social psychological and behavioral economic principles may be more effective in deterring inappropriate antibiotic prescribing for ARIs by well-informed clinicians. Methods/design The Application of Behavioral Economics to Improve the Treatment of Acute Respiratory Infections (BEARI) Trial is a multisite, cluster-randomized controlled trial with practice as the unit of randomization. The primary aim is to test the ability of three interventions based on behavioral economic principles to reduce the rate of inappropriate antibiotic prescribing for ARIs. We randomized practices in a 2 × 2 × 2 factorial design to receive up to three interventions for non-antibiotic-appropriate diagnoses: 1) Accountable Justifications: When prescribing an antibiotic for an ARI, clinicians are prompted to record an explicit justification that appears in the patient electronic health record; 2) Suggested Alternatives: Through computerized clinical decision support, clinicians prescribing an antibiotic for an ARI receive a list of non-antibiotic treatment choices (including prescription options) prior to completing the antibiotic prescription; and 3) Peer Comparison: Each provider’s rate of inappropriate antibiotic prescribing relative to top-performing peers is reported back to the provider periodically by email. We enrolled 269 clinicians (practicing attending physicians or advanced practice nurses) in 49 participating clinic sites and collected baseline data. The primary outcome is the antibiotic prescribing rate for office visits with non-antibiotic-appropriate ARI diagnoses. Secondary outcomes will examine antibiotic prescribing more broadly. The 18-month intervention period will be followed by a one year follow-up period to measure persistence of effects after interventions cease. Discussion The ongoing BEARI Trial will evaluate the effectiveness of behavioral economic strategies in reducing inappropriate prescribing of antibiotics. Trials registration ClinicalTrials.gov: NCT0145494

Behavioral interventions to reduce inappropriate antibiotic prescribing: a randomized pilot trial

Background: Clinicians frequently prescribe antibiotics inappropriately for acute respiratory infections (ARIs). Our objective was to test information technology-enabled behavioral interventions to reduce inappropriate antibiotic prescribing for ARIs in a randomized controlled pilot test trial. Methods: Primary care clinicians were randomized in a 2 × 2 × 2 factorial experiment with 3 interventions: 1) Accountable Justifications; 2) Suggested Alternatives; and 3) Peer Comparison. Beforehand, participants completed an educational module. Measures included: rates of antibiotic prescribing for: non-antibiotic-appropriate ARI diagnoses, acute sinusitis/pharyngitis, all other diagnoses/symptoms of respiratory infection, and all three ARI categories combined. Results: We examined 3,276 visits in the pre-intervention year and 3,099 in the intervention year. The antibiotic prescribing rate fell for non-antibiotic-appropriate ARIs (24.7 % in the pre-intervention year to 5.2 % in the intervention year); sinusitis/pharyngitis (50.3 to 44.7 %); all other diagnoses/symptoms of respiratory infection (40.2 to 25.3 %); and all categories combined (38.7 to 24.2 %; all p < 0.001). There were no significant relationships between any intervention and antibiotic prescribing for non-antibiotic-appropriate ARI diagnoses or sinusitis/pharyngitis. Suggested Alternatives was associated with reduced antibiotic prescribing for other diagnoses or symptoms of respiratory infection (odds ratio [OR], 0.62; 95 % confidence interval [CI], 0.44–0.89) and for all ARI categories combined (OR, 0.72; 95 % CI, 0.54–0.96). Peer Comparison was associated with reduced prescribing for all ARI categories combined (OR, 0.73; 95 % CI, 0.53–0.995). Conclusions: We observed large reductions in antibiotic prescribing regardless of whether or not study participants received an intervention, suggesting an overriding Hawthorne effect or possibly clinician-to-clinician contamination. Low baseline inappropriate prescribing may have led to floor effects. Trial Registration ClinicalTrials.gov: NCT01454960. Electronic supplementary material The online version of this article (doi:10.1186/s12879-016-1715-8) contains supplementary material, which is available to authorized users

When are person tradeoffs valid?

The person tradeoff (PTO) is commonly used in health economic applications. However, to date it has no theoretical basis. The purpose of this paper is to provide this basis from a set of assumptions that together justify the most common applications of the PTO method. Our analysis identifies the central assumptions in PTO measurements. We test these assumptions in an experiment, but find only limited support for the validity of the PTO.Person tradeoff Utility theory Social welfare

Using Social Media, Online Social Networks, and Internet Search as Platforms for Public Health Interventions: A Pilot Study

ObjectiveTo pilot public health interventions at women potentially interested in maternity care via campaigns on social media (Twitter), social networks (Facebook), and online search engines (Google Search).Data sources/study settingPrimary data from Twitter, Facebook, and Google Search on users of these platforms in Los Angeles between March and July 2014.Study designObservational study measuring the responses of targeted users of Twitter, Facebook, and Google Search exposed to our sponsored messages soliciting them to start an engagement process by clicking through to a study website containing information on maternity care quality information for the Los Angeles market.Principal findingsCampaigns reached a little more than 140,000 consumers each day across the three platforms, with a little more than 400 engagements each day. Facebook and Google search had broader reach, better engagement rates, and lower costs than Twitter. Costs to reach 1,000 targeted users were approximately in the same range as less well-targeted radio and TV advertisements, while initial engagements-a user clicking through an advertisement-cost less than $1 each.ConclusionsOur results suggest that commercially available online advertising platforms in wide use by other industries could play a role in targeted public health interventions