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Electronic Prescribing: Friend or Foe? An audit of prescribing errors after the introduction of an electronic prescribing system in neonates and children. Maria O’Meara, Kings College Hospital Electronic Prescribing : Friend or Foe? Marie O’Meara Paediatric Liver Pharmacist King’s College Hospital NHS Foundation Trust Honorary Clinical Lecturer KCL & Naumann Shaheen University College London Background • Variety Children’s Hospital, 100 bed paediatric centre. National, tertiary and local services • Numerous Strategies to reduce medication errors • Paediatric prescribing error rates 5-27% (Miller et al 2007) • 8 studies investigating the effect of Electronic prescribing on prescribing error rates in children Electronic Prescribing & Medicines Administration System (EPMA) • EPMA- commercially available system produced by iSOFT PLC • No Clinical Decision support systems (CDSS) • First introduced at KCH in 2009 • Rollout to Women’s & children’s services Oct 2012 • Staggered, completed Jan 2013 EPMA in Paediatrics • Separate paediatric drug catalogue adapted from the adult catalogue. Choice of drugs available limited • Paediatric specific order sets for complex patient groups • All staff had mandatory training prior to the implementation • 24 hour support available during rollout period Aims and Objectives • To audit the number and rate of prescribing errors over a two week period • To identify the common types of prescribing errors • To assess the clinical significance of the errors • To compare the rate, nature and clinical significance of prescribing errors to the previous year (paper) to ascertain the impact of EP. • To make recommendations based on results obtained. Definition of a prescribing error • ‘A clinically meaningful prescribing error occurs when, as a result of a prescribing decision or prescription writing process, there is an unintentional significant (1) reduction in the probability of treatment being timely and effective or (2) increase in the risk of harm when compared with generally accepted practice’ -Dean et al. Methods • Prescribing errors, prospectively recorded pharmacists (n=5) & technicians (n=1) on ward rounds/visits over 2 weeks • Neonates excluded, PICU- Metavision • Each error allocated a code, corresponding to one of 33 scenarios -Ghaleb et al 2005 • Clinical significance determined using a validated method. 4 healthcare professionals (1 consultant, 2 pharmacists and 1 nurse) -Dean & Barber 1999 • Data were analysed using Microsoft Excel Results 2012 (pre EPMA) • Error rate – 1117 medication orders – 95 errors – Error rate 8.5% 2013 (post EPMA) • Error rate – 1147 medication orders – 180 errors – Error rate 15.7% • Clinical significance • Clinical significance – Minor 18.6% – Moderate 80.4% – Severe 1% – Minor 26.6% – Moderate 73.4% – Severe 0% Change in pattern of errors Error type ↑post EPMA • Prescribing dose/frequency that is not recommended for the formulation prescribed • Continuing a prescription for longer than necessary • Unintentionally not prescribing a drug for a condition for which the drug is indicated • Duplication • Formulation Error type ↓ /omitted post EPMA • Writing Illegibly • Misspelling a drug name • Omission of the prescribers signature • Writing a drug name using abbreviations • Dose written as mg/kg rather than final dose • Prescribing a prn drug without a max daily dose • Allergy status ommitted Drugs most associated with errors 2012 Drug (%) 2013 Drug (%) • • • • • • • • • • Paracetamol (17.9) Gentamicin (3.2) Morphine (7.4) Tacrolimus (4.2) Ursodeoxycholic acid (3.2) Morphine (7.2) Methylprednisolone (4.4) Paracetamol (3.9) Hydrocortisone (3.3) Phenobarbitone (3.3) Limitations • Voluntary reporting? Under reporting prior, inconsistent with literature • Snapshot (2 weeks) • EPMA – newly introduced • Point in prescribers rotation • Detail not always sufficient to rate significance Post audit implementation & Future work • • • • • Policy for weaning introduced Frequency & routes rationalised Upgrade of system 2014, ↑CDSS Large multicentre study required Electronic Prescribing in Pediatrics: Toward Safer and More Effective Medication Management Johnson et al Pediatrics 2013;131;e1350 – Paediatric requirements for safe and effective electronic prescribing • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • TABLE 1 Pediatric Requirements for Safe and Effective Electronic Prescribing Category Pediatric Requirements Patient information Date of birth or age in units more specific than years Weight in kg Height in cm Any history of intolerable adverse effects or allergy to medications Medication information Indication-based dosing and individual and daily dose alerts, using mg/kg per day or mg/m2 per day formula, unless inappropriate Weight-based dosing calculations All available formulations, including liquid formulations that may be specific brands Common formulations requiring extemporaneous compounding or combinations of active ingredients Cognitive support Dose range checking (minimum and maximum amount per dose, amount per day based on weight, surface area, and total dose) Automatic strength to volume conversions for liquid medications Adverse-effect warnings specific to pediatric populations Alternative therapies based on ameliorable adverse effects Tall-man lettering to reduce medication selection errors Medication-specific indications to reduce ordering of sound-alike drugs Pharmacy information Pharmacies that will create extemporaneous compounds Data transmission Use of messaging standards for data transmission to pharmacies that include the patient’s weight and notes pertaining to weight-based calculations Transmission of strength, concentration, and dose volume labeled in metric units for liquid medications