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Title: Dispensing errors in hospital pharmacy: incidence, causes and impact of automation
Author: James, Kathryn Lynette
ISNI:       0000 0004 2731 3381
Awarding Body: King's College London (University of London)
Current Institution: King's College London (University of London)
Date of Award: 2009
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Dispensing medication is inherently risky and errors are inevitable occurrences. Pharmacists are encouraged to monitor dispensing errors so that risk reduction strategies can be implemented. Automated dispensing systems (ADS) are advocated as a key error reduction strategy. However, little research has investigated the incidence, type and causes of dispensing errors in hospitals with ADS and manual dispensing systems. Analysis of dispensing error data, self-reported by hospitals using standardised definitions and a validated methodology, was undertaken. Prevented dispensing incidents (detected during dispensing) occurred more frequently than unprevented dispensing incidents (detected after issue of medication). However, automation had no significant effect on the unprevented dispensing incident rate. The most common dispensing error types reported were supply of the wrong drug, strength, form and printing the wrong directions/warnings on the label. The critical incident technique, employing self-reported incident forms, was used to investigate the causes of specific prevented dispensing incidents occurring at hospital pharmacies. These incidents were attributed to active failures (interchanging different formulations, computer and stock selection errors), error-producing conditions (high workload, complex prescriptions and interruptions) and latent conditions (inadequate staffing/skill mix, unclear drug computer selection lists and drug storage on dispensary shelves). Socio-technical theory was used to investigate the effect of dispensary workload and occupational stressors on prevented dispensing incidents in hospitals utilising ADS and manual dispensing. A strong positive relationship was identified between dispensary workload and prevented dispensing incidents. Workforce planning models were developed enabling determination of staffing levels required to maintain a safe permissible workload. Automation was associated with a higher workload, lower prevented dispensing incident rate and less job stress and overload. However, automation reduced staff autonomy, organisational commitment and job satisfaction. Improved workforce planning, staff training and design of pharmacy computer software are needed to reduce dispensing errors. Automation improves dispensing efficiency and safety. However, care must be taken to avoid an imbalance between technology and employee needs.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available