Behavioral Economics Interventions to Improve Outpatient Antibiotic Prescribing for Acute Respiratory Infections: a Cost-Effectiveness Analysis

Abstract

Background: Behavioral economics interventions have been shown to effectively reduce the rates of inappropriate antibiotic prescriptions for acute respiratory infections (ARIs).

Objective: To determine the cost-effectiveness of three behavioral economic interventions designed to reduce inappropriate antibiotic prescriptions for ARIs.

Design: Thirty-year Markov model from the US societal perspective with inputs derived from the literature and CDC surveillance data.

Subjects: Forty-five-year-old adults with signs and symptoms of ARI presenting to a healthcare provider.

Interventions: (1) Provider education on guidelines for the appropriate treatment of ARIs; (2) Suggested Alternatives, which utilizes computerized clinical decision support to suggest non-antibiotic treatment choices in lieu of antibiotics; (3) Accountable Justification, which mandates free-text justification into the patient's electronic health record when antibiotics are prescribed; and (4) Peer Comparison, which sends a periodic email to prescribers about his/her rate of inappropriate antibiotic prescribing relative to clinician colleagues.

Main measures: Discounted costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios.

Key results: Each intervention has lower costs but higher QALYs compared to provider education. Total costs for each intervention were $178.21, $173.22, $172.82, and $172.52, and total QALYs were 14.68, 14.73, 14.74, and 14.74 for the control, Suggested Alternatives, Accountable Justification, and Peer Comparison groups, respectively. Results were most sensitive to the quality-of-life of the uninfected state, and the likelihood and costs for antibiotic-associated adverse events.

Conclusions: Behavioral economics interventions can be cost-effective strategies for reducing inappropriate antibiotic prescriptions by reducing healthcare resource utilization.

Trial registration: ClinicalTrials.gov NCT01454947.

Keywords: cost-effectiveness; healthcare administration; infectious disease; physician behavior.

Figure 1

Markov Model Structure. Figure 1depicts the Markov framework. “U_” and “V_” designate unvaccinated (UNVACC) and vaccinated (VACC) individuals, respectively, while “s” and “r” subscripts represent carriers of susceptible or resistant bacterial strains. As individuals get vaccinated over time, they move from the UNVACC to the VACC pool. An individual may contract one of three types of infections: viral acute respiratory infection (VARI), susceptible bacterial acute respiratory infection (BARIs), or resistant bacterial acute respiratory infection (BARIr). For VARI, treatment is either over-the-counter and symptomatic treatment (VOTC), or inappropriate antibiotics (VABX), which may lead to an adverse drug reaction (VADR) and possible emergency department visit (VED) and/or anaphylactic death (VDEATH). Otherwise, the infection will resolve (VRESOLVED) and patients return to the pool of unvaccinated/vaccinated individuals. For BARI, all individuals should receive antibiotics (BABX), which may also lead to subsequent adverse drug reaction (ADR) and emergency visit (BED). In addition, the infection may become severe requiring inpatient hospitalization (BHOSP) and possible infectious and hospitalization complications (BCOMP). Not shown is background mortality, which assumes that individuals may exit the model at any state due to death from natural causes.

Figure 2

Cost-Effectiveness Plane. The cost-effectiveness plane depicts the incremental costs and quality-adjusted life years of each intervention relative to the control group. The further down the X and Y -axes the intervention is, the more cost-effective it is relative to the control.

Figure 3

One-Way Sensitivity Analysis, Suggested Alternatives. One-way sensitivity analyses yielded similar trends for each intervention, with results most sensitive to the utility of the uninfected health state, followed by the likelihood and costs associated with adverse events due to antibiotics. Therefore, we have not shown a tornado diagram for each intervention evaluated. Results have been transformed into net monetary benefits as even in one-way sensitivity analyses, the interventions remained dominant over the control group, therefore yielding negative ICERs. Ranges for each parameter varied in sensitivity analysis are shown in Table 1 .

Figure 4

Net Monetary Benefits. Net monetary benefits indicate that all BEARI interventions provide greater benefit than the control group. Note that the lines depicting each intervention are essentially overlapping. The axis and graph have been scaled for graphical clarity.