Language

English

Publication Date

11-14-2023

Journal

BMC Medical Informatics and Decision Making

DOI

10.1186/s12911-023-02368-0

PMID

37964232

PMCID

PMC10644670

PubMedCentral® Posted Date

11-14-2023

PubMedCentral® Full Text Version

Post-print

Abstract

Background: Overprescribing of antibiotics for acute respiratory infections (ARIs) remains a major issue in outpatient settings. Use of clinical prediction rules (CPRs) can reduce inappropriate antibiotic prescribing but they remain underutilized by physicians and advanced practice providers. A registered nurse (RN)-led model of an electronic health record-integrated CPR (iCPR) for low-acuity ARIs may be an effective alternative to address the barriers to a physician-driven model.

Methods: Following qualitative usability testing, we will conduct a stepped-wedge practice-level cluster randomized controlled trial (RCT) examining the effect of iCPR-guided RN care for low acuity patients with ARI. The primary hypothesis to be tested is: Implementation of RN-led iCPR tools will reduce antibiotic prescribing across diverse primary care settings. Specifically, this study aims to: (1) determine the impact of iCPRs on rapid strep test and chest x-ray ordering and antibiotic prescribing rates when used by RNs; (2) examine resource use patterns and cost-effectiveness of RN visits across diverse clinical settings; (3) determine the impact of iCPR-guided care on patient satisfaction; and (4) ascertain the effect of the intervention on RN and physician burnout.

Discussion: This study represents an innovative approach to using an iCPR model led by RNs and specifically designed to address inappropriate antibiotic prescribing. This study has the potential to provide guidance on the effectiveness of delegating care of low-acuity patients with ARIs to RNs to increase use of iCPRs and reduce antibiotic overprescribing for ARIs in outpatient settings.

Keywords

Humans, Anti-Bacterial Agents, Decision Support Systems, Clinical, Nurse's Role, Respiratory Tract Infections, Electronic Health Records, Practice Patterns, Physicians', Randomized Controlled Trials as Topic, Integrated clinical prediction rules, EHR, Implementation, Acute respiratory infections, Antibiotics, RCT

Comments

Trial registration: ClinicalTrials.gov Identifier: NCT04255303, Registered February 5 2020, https://clinicaltrials.gov/ct2/show/NCT04255303 .

Published Open-Access

yes

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