Assessing the conversion of electronic medical record data into antibiotic stewardship indicators.

Renggli, L; Plüss-Suard, C; Gasser, M; Sonderegger, B; Kronenberg, A (2023). Assessing the conversion of electronic medical record data into antibiotic stewardship indicators. The journal of antimicrobial chemotherapy, 78(9), pp. 2297-2305. Oxford University Press 10.1093/jac/dkad235

[img]
Preview
Text
dkad235.pdf - Published Version
Available under License Creative Commons: Attribution-Noncommercial (CC-BY-NC).

Download (524kB) | Preview

BACKGROUND

Measuring the appropriateness of antibiotic use is crucial for antibiotic stewardship (ABS) programmes to identify targets for interventions.

OBJECTIVES

To assess the technical feasibility of converting electronic medical record (EMR) data into ABS indicators.

METHODS

In this observational feasibility study covering a period of 2 years, the EMRs of patients hospitalized at a large non-university hospital network and receiving at least one dose of a systemic antibiotic were included. ABS indicators measuring steps in the process of antibiotic prescription proposed by the literature were collected and rephrased or defined more specifically to be calculable if needed. Algorithms were programmed in R to convert EMR data into ABS indicators. The indicators were visualized in an interactive dashboard and the plausibility of each output value was assessed.

RESULTS

In total, data from 25 337 hospitalizations from 20 723 individual patients were analysed and visualized in an interactive dashboard. Algorithms could be programmed to compute 89% (25/28) of all pre-selected indicators assessing treatment decisions automatically out of EMR data, with good data quality for 46% (13/28) of these indicators. According to the data quality observed, the most important issues were (i) missing or meaningless information on indication (e.g. 'mild infection') and (ii) data processing issues such as insufficiently categorized metadata.

CONCLUSIONS

The calculation of indicators assessing treatment decisions from EMRs was feasible. However, better data structure and processing within EMR systems are crucial for improving the validity of the results.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Service Sector > Institute for Infectious Diseases

UniBE Contributor:

Renggli, Luzia Sonja, Plüss, Catherine, Gasser, Michael, Kronenberg, Andreas Oskar

Subjects:

600 Technology > 610 Medicine & health
500 Science > 570 Life sciences; biology
300 Social sciences, sociology & anthropology > 360 Social problems & social services

ISSN:

1460-2091

Publisher:

Oxford University Press

Language:

English

Submitter:

Pubmed Import

Date Deposited:

02 Aug 2023 09:56

Last Modified:

06 Sep 2023 00:15

Publisher DOI:

10.1093/jac/dkad235

PubMed ID:

37527399

BORIS DOI:

10.48350/185176

URI:

https://boris.unibe.ch/id/eprint/185176

Actions (login required)

Edit item Edit item
Provide Feedback