Effect of a voice recognition system on paediatric outpatient medication errors
Date of Award
Master of Medicine (MMed)
Paediatrics and Child Health (East Africa)
Background: Medication errors have potential to cause harm and death; especially children who are three times more vulnerable than adults. Risk of medication errors is higher in out- patient settings due to a stressful work environment with less familiarity of individual patients. This problem in sub-Saharan Africa is however largely undetermined. A Voice Recognition System that converts verbal messages into text and stores it in a database in a retrievable format could impact on reduction of medication errors.
Objectives: The primary objective was to compare medication prescription and dispensing errors in written prescriptions with those from a Voice Recognition System. Secondary objectives were to determine the types and frequency of medication errors, determinants of medication errors and acceptability of routine use of a Voice Recognition System to make medication prescriptions.
Study design: A before -after Intervention study to determine the impact of introduction of a Voice Recognition System on the occurrence of medication errors.
Methods: Prescriptions issued from the Paediatric Accident and Emergency Department at Aga Khan University Hospital Nairobi over a six month period were randomly selected and analyzed for errors. Patient‟s bio-data, diagnosis, prescriber‟s specialization and time of prescription were retrieved from outpatient medical records and documented in a standard study tool.
A Voice Recognition System was installed and doctors and pharmacists consenting to use Voice Recognition were trained to enhance proficiency in its use. During consultations, doctors enrolled patients who provided written informed consent to have their prescriptions made using Voice Recognition. Prescription and dispensing records were analysed to determine the occurrence of medication errors. Questionnaires were issued to pharmacists and doctors to rate the use of Voice Recognition in the medication process.
Results: During the VRS phase the proportion of female patients reviewed were 56.9% compared to 40% in the pre VRS phase. (OR= 0.5 (95% CI 0.37-0.69), P<0.001). The top five conditions diagnosed at the pediatric A&E department were upper respiratory tract infections, urinary tract infections, tonsillitis, pharyngitis and gastroenteritis. Incidence was similar in both pre VRS and VRS phases. (51.5% and 58.3% OR=0.74 (95% CI 0.53-1.01), P=0.063.)
Overall, there was a 19.5% reduction in prescription errors from 86.1% in the pre Voice Recognition phase to 69.3% in the Voice Recognition phase (P<0.001). Among prescription errors analysed, there was a 31.9% reduction in omitted drug route (P <0.001) and a 64.8 % reduction in incorrect drug dose (P<0.001). Analysis of dispensing errors revealed the greatest error being omission in drug duration whose proportion increased fivefold from 16.5% in pre Voice Recognition to 83.7% in Voice Recognition phase (P< 0.001).
During the Voice Recognition phase healthcare providers were least likely to make medication errors during the afternoon shift (Odds Ratio 0.72, 95% CI: 0.5-1.03, P <0.001). Among the top five medications prescribed antihistamines were less likely to have errors (OR 0.48, 95% CI: 0.13-1.8) while topical medications were more likely to have errors (OR 1.64, 95%, CI: 1.07-2.52). Residents were more likely to make medication errors than other healthcare providers (OR 4.08, 95% CI: 2.95-5.66, p< 0.001).
Fifty eight percent of healthcare providers opted to continue using the Voice Recognition System.
Conclusion: Overall there was a 19.1% reduction in medication errors following introduction of the Voice Recognition. The greatest impact of Voice Recognition introduction was a 31.9% reduction in omitted drug route and 64.8% reduction in incorrect drug dose among prescription records. However, there was a fivefold increase in omission of drug duration among dispensing records from 16.5 % to 83.7%.
Migowa, A. N. (2013). Effect of a voice recognition system on paediatric outpatient medication errors (Unpublished master's dissertation). Aga Khan University, East Africa.