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Validation of an algorithm to evaluate the appropriateness of outpatient antibiotic prescribing using big data of Chinese diagnosis text.
- Source :
-
BMJ open [BMJ Open] 2020 Mar 19; Vol. 10 (3), pp. e031191. Date of Electronic Publication: 2020 Mar 19. - Publication Year :
- 2020
-
Abstract
- Objective: We aimed to evaluate the validity of an algorithm to classify diagnoses according to the appropriateness of outpatient antibiotic use in the context of Chinese free text.<br />Setting and Participants: A random sample of 10 000 outpatient visits was selected between January and April 2018 from a national database for monitoring rational use of drugs, which included data from 194 secondary and tertiary hospitals in China.<br />Research Design: Diagnoses for outpatient visits were classified as tier 1 if associated with at least one condition that 'always' justified antibiotic use; as tier 2 if associated with at least one condition that only 'sometimes' justified antibiotic use but no conditions that 'always' justified antibiotic use; or as tier 3 if associated with only conditions that never justified antibiotic use, using a tier-fashion method and regular expression (RE)-based algorithm.<br />Measures: Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the classification algorithm, using classification made by chart review as the standard reference, were calculated.<br />Results: The sensitivities of the algorithm for classifying tier 1, tier 2 and tier 3 diagnoses were 98.2% (95% CI 96.4% to 99.3%), 98.4% (95% CI 97.6% to 99.1%) and 100.0% (95% CI 100.0% to 100.0%), respectively. The specificities were 100.0% (95% CI 100.0% to 100.0%), 100.0% (95% CI 99.9% to 100.0%) and 98.6% (95% CI 97.9% to 99.1%), respectively. The PPVs for classifying tier 1, tier 2 and tier 3 diagnoses were 100.0% (95% CI 99.1% to 100.0%), 99.7% (95% CI 99.2% to 99.9%) and 99.7% (95% CI 99.6% to 99.8%), respectively. The NPVs were 99.9% (95% CI 99.8% to 100.0%), 99.8% (95% CI 99.7% to 99.9%) and 100.0% (95% CI 99.8% to 100.0%), respectively.<br />Conclusions: The RE-based classification algorithm in the context of Chinese free text had sufficiently high validity for further evaluating the appropriateness of outpatient antibiotic prescribing.<br />Competing Interests: Competing interests: None declared.<br /> (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Details
- Language :
- English
- ISSN :
- 2044-6055
- Volume :
- 10
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- BMJ open
- Publication Type :
- Academic Journal
- Accession number :
- 32198296
- Full Text :
- https://doi.org/10.1136/bmjopen-2019-031191