Antimicrobial Resistance
Conditions
Brief summary
Interventions that are low-cost, do not add substantially to the physician workload, are consistent with good physician practices and WHO guidelines, and serve as a reminder on the risks of overprescribing antibiotics are critically needed. The overall goal of the proposed project is to test the effect of two behavioral interventions targeted to junior physicians-specifically, requiring them to specify the diagnosis in the prescription note and providing feedback-on their antibiotics prescription rate; examine the intervention's effects across gender and caste; and draw lessons for scaling up the intervention.
Detailed description
Antimicrobial resistance (AMR) is one of the top ten threats to global health. Limited existing evidence from Nepal, the site for the proposed study, suggests that physicians "err on the side of caution" by prescribing antibiotics even for viral conditions, which contributes to AMR. Interventions that are low-cost, do not add substantially to the physician workload, are consistent with good physician practices and WHO guidelines, and serve as a reminder on the risks of overprescribing antibiotics are critically needed. The overall goal of the proposed project is to test the effect of a behavioral intervention targeted to junior physicians-specifically, requiring them to specify the diagnosis in the prescription note and providing feedback-on their antibiotics prescription rate; examine the intervention's effects across gender and caste; and draw lessons for scaling up the intervention. The specific objectives are the following: Objective 1. Assess the effect of a behavioral intervention targeted to junior physicians on antibiotics prescription rate, including by caste and gender of the patient. A stepped-wedge randomized control trial (RCT) will be conducted among 60 junior physicians in five hospitals (1 government, 2 private teaching, and 2 community) in Nepal. The intervention will be rolled out sequentially across the hospitals and data will be collected from patients (n=3,600) both before and after the intervention. The intervention will consist of three components: (a) a Refresher Training on AMR, (b) a Diagnosis Mandate, and (c) an Individualized Feedback. Objective 2. Identify barriers to scaling up the intervention beyond the study's site and strategies for their mitigation. After preliminary analysis of the quantitative data, key informant interviews with national- and provincial- level health policy makers (n=5), and in-depth interviews with physicians (n=5) and hospital managers (n=5) will be conducted. Objective 3. Assess the extent to which physicians prescribe antibiotics correctly. From a subset of patients (n=120, i.e., 2 per physician), more detailed medical information will be collected and analyzed from their outpatient booklet. This registration is for objective 1. Therefore, only details pertaining to that objective will be provided here.
Interventions
BEHAVIORALDiagnosis Mandate
The intervention consists of: a) a Refresher Training on AMR, and (b) a Diagnosis Mandate.
BEHAVIORALIndividualized Feedback
Physicians receive a customized feedback on their prescription behavior, including antibiotics prescription rate.
Sponsors
Penn State University
Study design
Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
DOUBLE (Subject, Caregiver)
Intervention model description
This is a stepped-wedge randomized controlled trial
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
For physicians: Inclusion criteria: * age 18+ * working at an outpatient clinic in one of the participating hospitals.
Exclusion criteria
* \<18 years of age * working at more than one of the participating hospitals For patients: Inclusion criteria: * age 18+ * sought care at one of the outpatient clinics in the participating hospitals.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Antibiotics prescription rate | 1-3 months before the intervention and 3-5 months after the intervention, depending on the timing of the intervention which varies by hospital. | The number of patient visits in which antibiotics are prescribed by the total number of visits |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Differences in prescription rates by patient's gender | 1-3 months before the intervention and 3-5 months after the intervention, depending on the timing of the intervention which varies by hospital. | The number of patient visits in which antibiotics are prescribed by the total number of visits, by male and female |
| Differences in prescription rates by patient's ethnicity (advantaged versus disadvantaged) | 1-3 months before the intervention and 3-5 months after the intervention, depending on the timing of the intervention which varies by hospital. | The number of patient visits in which antibiotics are prescribed by the total number of visits, by advantaged and disadvantaged status |
Countries
Nepal, United States
Outcome results
None listed