Literature DB >> 28698381

Reasons for computerised provider order entry (CPOE)-based inpatient medication ordering errors: an observational study of voided orders.

Joanna Abraham1, Thomas G Kannampallil2, Alan Jarman1, Shivy Sharma1, Christine Rash3, Gordon Schiff4, William Galanter3,5,6.   

Abstract

OBJECTIVE: Medication voiding is a computerised provider order entry (CPOE)-based discontinuation mechanism that allows clinicians to identify erroneous medication orders. We investigated the accuracy of voiding as an indicator of clinician identification and interception of a medication ordering error, and investigated reasons and root contributors for medication ordering errors.
METHOD: Using voided orders identified with a void alert, we conducted interviews with ordering and voiding clinicians, followed by patient chart reviews. A structured coding framework was used to qualitatively analyse the reasons for medication ordering errors. We also compared clinician-CPOE-selected (at time of voiding), clinician-reported (interview) and chart review-based reasons for voiding.
RESULTS: We conducted follow-up interviews on 101 voided orders. The positive predictive value (PPV) of voided orders that were medication ordering errors was 93.1% (95% CI 88.1% to 98.1%, n=94). Using chart review-based reasons as the gold standard, we found that clinician-CPOE-selected reasons were less reflective (PPV=70.2%, 95% CI 61.0% to 79.4%) than clinician-reported (interview) (PPV=86.1%, 95%CI 78.2% to 94.1%) reasons for medication ordering errors. Duplicate (n=44) and improperly composed (n=41) ordering errors were common, often caused by predefined order sets and data entry issues. A striking finding was the use of intentional violations as a mechanism to notify and seek ordering assistance from pharmacy service. Nearly half of the medication ordering errors were voided by pharmacists. DISCUSSION: We demonstrated that voided orders effectively captured medication ordering errors. The mismatch between clinician-CPOE-selected and the chart review-based reasons for error emphasises the need for developing standardised operational descriptions for medication ordering errors. Such standardisation can help in accurately identifying, tracking, managing and sharing erroneous orders and their root contributors between healthcare institutions, and with patient safety organisations. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Entities:  

Keywords:  Medication Safety; Patient Safety; Qualitative Research

Mesh:

Year:  2017        PMID: 28698381     DOI: 10.1136/bmjqs-2017-006606

Source DB:  PubMed          Journal:  BMJ Qual Saf        ISSN: 2044-5415            Impact factor:   7.035


  5 in total

1.  Risk factors associated with medication ordering errors.

Authors:  Joanna Abraham; William L Galanter; Daniel Touchette; Yinglin Xia; Katherine J Holzer; Vania Leung; Thomas Kannampallil
Journal:  J Am Med Inform Assoc       Date:  2021-01-15       Impact factor: 4.497

2.  The Impact of Technology on Prescribing Errors in Pediatric Intensive Care: A Before and After Study.

Authors:  Moninne M Howlett; Eileen Butler; Karen M Lavelle; Brian J Cleary; Cormac V Breatnach
Journal:  Appl Clin Inform       Date:  2020-05-06       Impact factor: 2.342

3.  An Analysis of the Safety of Medication Ordering Using Typo Correction within an Academic Medical System.

Authors:  Alaina Brooks Darby; Brittany Lee Karas; Tina Wagner
Journal:  Appl Clin Inform       Date:  2021-08-02       Impact factor: 2.762

4.  Defining electronic-prescribing and infusion-related medication errors in paediatric intensive care - a Delphi study.

Authors:  Moninne M Howlett; Brian J Cleary; Cormac V Breatnach
Journal:  BMC Med Inform Decis Mak       Date:  2018-12-07       Impact factor: 2.796

5.  How do stakeholders experience the adoption of electronic prescribing systems in hospitals? A systematic review and thematic synthesis of qualitative studies.

Authors:  Albert Farre; Gemma Heath; Karen Shaw; Danai Bem; Carole Cummins
Journal:  BMJ Qual Saf       Date:  2019-07-29       Impact factor: 7.035

  5 in total

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