• Internal medicine journal · Oct 2020

    Clinical decision support in a hospital electronic prescribing system informed by local data: experience at a tertiary New Zealand centre.

    • Chin Paul K L PKL https://orcid.org/0000-0002-5470-5191 Department of Medicine, University of Otago, Christchurch, New Zealand. , QianYi Chuah, Amanda M Crawford, Olivia R Clendon, Philip G Drennan, Judith M Dalrymple, Murray L Barclay, and Matthew P Doogue.
    • Department of Medicine, University of Otago, Christchurch, New Zealand.
    • Intern Med J. 2020 Oct 1; 50 (10): 1225-1231.

    BackgroundAn electronic prescribing and administration (ePA) system has been progressively rolled out to Canterbury District Health Board (CDHB, Christchurch, New Zealand) public hospitals since 2014, and is currently used for around 1300 tertiary beds. ePA data can be used to monitor user behaviour, and to evaluate and inform the local customisation of clinical decision support (CDS) tools within the ePA system.AimsTo describe retrospectively illustrative vignettes of CDHB ePA analyses that have been used for CDS.MethodsAlerts were developed according to a set of common principles agreed upon by the CDHB CDS Working Group. Alerts were informed and evaluated by extracting and parsing data for various time periods during 2016 to 2018 from the CDHB ePA database.ResultsThere was a median of 74 000 prescriptions a month. After examining 525 spironolactone prescriptions, the high dose alert threshold was set at 100 mg with an expected alert burden of 3%. The presence of a ceftriaxone shortage prescribing alert for 1 week was associated with a prescribing rate that was lower than 95% of the preceding 52 weeks. Following review of 367 fentanyl patch alerts, revision of the alert led to false positives falling from 43% to 3% (P < 0.0001). At the point of firing, 6% of antithrombotic drug interactions alerts led to immediate changes in prescriptions (94% overridden), and a further 22% were changed within 30 min after the alert.ConclusionsLocal data extracts from ePA systems can inform iterative configuration of the software and monitor user behaviour.© 2019 Royal Australasian College of Physicians.

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