Developing consensus on hospital prescribing indicators of potential harm for infants and children. (18th May 2016)

• Record Type: Journal Article
• Authors: Fox, Andy; Pontefract, Sarah; Brown, David; Portlock, Jane; Coleman, Jamie
• Is Part Of: British journal of clinical pharmacology. Volume 82:Number 2(2016:Aug.)
• Page Start: 451
• Page End: 460
• Publication Date: 2016-05-18
• Subjects: clinical decision support -- consensus -- medication errors -- paediatrics -- prescribing errors -- quality indicators; Pharmacology -- Periodicals; Drugs -- Periodicals; 615.1
• DOI: 10.1111/bcp.12954
• Languages: English
• ISSNs: 0306-5251

Abstract

Abstract : Aims: The aim of the study was to develop a list of hospital based paediatric prescribing indicators that can be used to assess the impact of electronic prescribing or clinical decision support tools on paediatric prescribing errors. Methods: Two rounds of an electronic consensus method (eDelphi) were carried out with 21 expert panellists from the UK. Panellists were asked to score each prescribing indicator for its likelihood of occurrence and severity of outcome should the error occur. The scores were combined to produce a risk score and a median score for each indicator calculated. The degree of consensus between panellists was defined as the proportion that gave a risk score in the same category as the median. Indicators were included if a consensus of 80% or higher was achieved and were in the high risk categories. Results: Each of the 21 panellists completed an exploratory round and two rounds of scoring. This identified 41 paediatric prescribing indicators with a high risk rating and greater than 80% consensus. The most common error type within the indicators was wrong dose ( n = 19) and the most common drug classes were antimicrobials ( n = 10) and cardiovascular ( n = 7). Conclusions: A set of 41 paediatric prescribing indicators describing potential harm for the hospital setting has been identified by an expert panel. The indicators provide a standardized method of evaluation of prescribing data on both paper and electronic systems. They can also be used to assess implementation of clinical decision support systems or other quality improvement initiatives.