Impact of Clinical Decision Support on Antibiotic Prescribing for Acute Respiratory Infections: a Cluster Randomized Implementation Trial.

Autor: Mann D; New York University School of Medicine, New York, NY, USA. Devin.Mann@nyulangone.org., Hess R; University of Utah School of Medicine, Salt Lake City, UT, USA., McGinn T; Hofstra Northwell School of Medicine, New York, NY, USA., Richardson S; Hofstra Northwell School of Medicine, New York, NY, USA., Jones S; New York University School of Medicine, New York, NY, USA., Palmisano J; Boston University, Boston, MA, USA., Chokshi SK; New York University School of Medicine, New York, NY, USA., Mishuris R; Boston University, Boston, MA, USA., McCullagh L; Hofstra Northwell School of Medicine, New York, NY, USA., Park L; University of Wisconsin School of Medicine and Public Health, Madison, WI, USA., Dinh-Le C; New York University School of Medicine, New York, NY, USA., Smith P; University of Wisconsin School of Medicine and Public Health, Madison, WI, USA., Feldstein D; University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Jazyk: angličtina
Zdroj: Journal of general internal medicine [J Gen Intern Med] 2020 Nov; Vol. 35 (Suppl 2), pp. 788-795. Date of Electronic Publication: 2020 Sep 01.
DOI: 10.1007/s11606-020-06096-3
Abstrakt: Background: Clinical decision support (CDS) is a promising tool for reducing antibiotic prescribing for acute respiratory infections (ARIs).
Objective: To assess the impact of previously effective CDS on antibiotic-prescribing rates for ARIs when adapted and implemented in diverse primary care settings.
Design: Cluster randomized clinical trial (RCT) implementing a CDS tool designed to guide evidence-based evaluation and treatment of streptococcal pharyngitis and pneumonia.
Setting: Two large academic health system primary care networks with a mix of providers.
Participants: All primary care practices within each health system were invited. All providers within participating clinic were considered a participant. Practices were randomized selection to a control or intervention group.
Interventions: Intervention practice providers had access to an integrated clinical prediction rule (iCPR) system designed to determine the risk of bacterial infection from reason for visit of sore throat, cough, or upper respiratory infection and guide evidence-based evaluation and treatment.
Main Outcome(s): Change in overall antibiotic prescription rates.
Measure(s): Frequency, rates, and type of antibiotics prescribed in intervention and controls groups.
Results: 33 primary care practices participated with 541 providers and 100,573 patient visits. Intervention providers completed the tool in 6.9% of eligible visits. Antibiotics were prescribed in 35% and 36% of intervention and control visits, respectively, showing no statistically significant difference. There were also no differences in rates of orders for rapid streptococcal tests (RR, 0.94; P = 0.11) or chest X-rays (RR, 1.01; P = 0.999) between groups.
Conclusions: The iCPR tool was not effective in reducing antibiotic prescription rates for upper respiratory infections in diverse primary care settings. This has implications for the generalizability of CDS tools as they are adapted to heterogeneous clinical contexts.
Trial Registration: Clinicaltrials.gov (NCT02534987). Registered August 26, 2015 at https://clinicaltrials.gov.
Databáze: MEDLINE
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