Effect of a voice recognition system on pediatric outpatient medication errors at a tertiary healthcare facility in

Angela N Migowa1, William M Macharia2, Pauline Samia2

  • 1Department of Pediatrics and Child Health, Aga Khan University, 3rd Parklands Avenue, PO Box 30270, Nairobi County 00100, Kenya.

Insights

Implementing a voice recognition system (VRS) significantly reduced medication errors in a Kenyan pediatric emergency department, particularly incorrect dosages. The technology was also found to be acceptable to healthcare providers.

Area of Science:

  • Health Informatics
  • Patient Safety
  • Clinical Pharmacy

Background:

  • Medication errors contribute significantly to mortality, with higher risks in pediatric populations.
  • Research on medication errors in sub-Saharan Africa is limited due to competing health priorities.
  • Voice recognition systems (VRS) offer a potential technological solution to improve prescription accuracy.

Purpose of the Study:

  • To evaluate the impact of introducing a voice recognition system (VRS) on medication error prevalence.
  • To characterize medication errors and assess the acceptability of VRS among healthcare providers.

Main Methods:

  • A before-and-after intervention study design was employed.
  • The study was conducted in a Pediatric Accident and Emergency Department in Kenya.
  • Prescription records were analyzed pre- and post-VRS implementation.

Main Results:

  • A reduction in medication prescription errors was observed after VRS implementation (74.3% pre-VRS vs. 65.7% post-VRS).
  • The greatest reduction was noted in incorrect medication dosages.
  • Over half (58%) of providers preferred VRS over handwritten prescriptions.

Conclusions:

  • Voice recognition systems effectively reduce medication prescription errors, especially dosage errors.
  • VRS technology is acceptable to physicians and pharmacists in a Kenyan tertiary care setting.
  • Further research on training, user experience, and software enhancement is recommended to further minimize errors.
Abstract

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