Acute Respiratory Infections (ARIs) Clinical Trial
Official title:
Use of Behavioral Economics to Improve Treatment of Acute Respiratory Infections (Main Study)
Bacteria resistant to antibiotic therapy are a major public health problem. The evolution of
multi-drug resistant pathogens may be encouraged by provider prescribing behavior.
Inappropriate use of antibiotics for nonbacterial infections and overuse of broad spectrum
antibiotics can lead to the development of resistant strains. Though providers are
adequately trained to know when antibiotics are and are not comparatively effective, this
has not been sufficient to affect critical provider practices.
The intent of this study is to apply behavioral economic theory to reduce the rate of
antibiotic prescriptions for acute respiratory diagnoses for which guidelines do not call
for antibiotics. Specifically targeted are infections that are likely to be viral.
The objective of this study is to improve provider decisions around treatment of acute
respiratory infections.
The participants are practicing attending physicians or advanced practice nurses (i.e.
providers) at participating clinics who see acute respiratory infection patients. A maximum
of 550 participants will be recruited for this study.
Providers consenting to participate will fill out a baseline questionnaire online.
Subsequent to baseline data collection and enrollment, participating clinic sites will be
randomized to the study arms, as described below.
There will be a control arm, with clinic sites randomized in a multifactorial design to up
to three interventions that leverage the electronic medical record: Order Sets that are
triggered by EHR workflow containing exclusively guideline concordant choices (AP, for
Alternative Prescriptions); Justification Alerts triggered by discordant prescriptions that
populate the note with provider's rationale for guideline exceptions (JA); and performance
feedback that benchmarks providers' own performance to that of their peers (SN, for social
norms).
The outcomes of interest are antibiotic prescribing patterns, including prescribing rates
and changes in prescribing rates over time.
The intervention period will be over one year, with a one-year follow up period to measure
persistence of the effect after EHR features are returned to the original state and
providers no longer receive email alerts.
Each consented provider will be randomized to 1 of 8 cells in a factorial design with equal
probability. If results of retrospective data analysis imply that design will be improved by
stratification, randomization will be stratified by factors that could influence outcomes.
Data will be collected from the clinics' Enterprise Data Warehouses which store copies of
data recorded in the electronic health record. Data elements from qualifying office visits
will be collected from coded portions of the electronic health record.
An encounter is eligible for intervention if the patient's diagnosis is in the selected
group of acute respiratory infections. The intervention EHR functions will be triggered when
clinicians initiate an antibiotic prescription or enter a diagnosis for an acute respiratory
infection that has a defined Order Set. If an antibiotic from a list of frequently
misprescribed antibiotics is ordered and a diagnosis has not yet been entered, providers
will be prompted to enter a diagnosis. If the diagnosis entered is acute nasopharyngitis;
acute laryngopharyngitis/acute upper respiratory infection; acute bronchitis; bronchitis not
specified as acute or chronic; or flu; the interventions will be triggered. The
diagnosis-appropriate order set will pop-up for providers in the AP arm, while clinicians
randomized to the justification arm will receive an alert and be required to enter a brief
statement justifying their antibiotic prescription if antibiotics are not indicated for the
diagnosis entered. This note will then be added to the patient's medical record.
Clinicians randomized to the social norm condition will receive email updates about their
antibiotic prescribing practices relative to other clinicians in their practice.
;
Allocation: Randomized, Intervention Model: Factorial Assignment, Masking: Single Blind (Subject), Primary Purpose: Treatment
| Status | Clinical Trial | Phase | |
|---|---|---|---|
| Completed |
NCT01454960 -
Use of Behavioral Economics to Improve Treatment of Acute Respiratory Infections (Pilot Study)
|
N/A | |
| Active, not recruiting |
NCT01767064 -
Nudging Guideline-concordant Antibiotic Prescribing Using Public Commitments
|
N/A |