Transcript System improvement by competency assessment

Medication Errors
&
IT
Gillian Cavell
Department of Health
&
King’s College Hospital
Introduction
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“Physicians should never again write a
prescription”
“Prescribing the old-fashioned way with pen
and pad is prone to mistakes”
“-medication errors the majority of which can
could be prevented with computerised
systems”(Schiff & Rucker JAMA 1998)
“Can automation… eliminate virtually all
medication errors or will it instill a false sense
of security?”(ISMP, 2000)
A Spoonful of Sugar
Automated dispensary systems
 Standard national system for coding
medicines and bar codes
 Central guidance on systems
specification
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What is a medication error?
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a preventable event that may cause or lead to
inappropriate medication use or patient harm while
the medication is in the control of the health care
professional, patient or consumer. Such events may
be related to professional practice, health care
products, procedures and systems including;
prescribing, order communication, product labelling,
packaging and nomenclature; compounding,
dispensing, distribution, administration, education,
monitoring and use
Prescribing
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What is a safe
prescription?
- appropriate drug
- appropriate dose
- appropriate time(s)
- appropriate route
- communicated via a
legible prescription
- all details correct
Prescribing
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What to choose?
Contraindications?
What dose?
What formulation?
Will anyone read my
writing?
HELP!!
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IS THIS SAFE?
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Electronic Prescribing
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Choice of drug
Contraindications
Choice of dose
Linked to formulation
It will be legible
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THIS MUST BE SAFER
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Where is the evidence?
81% reduction in non-missed-dose error rate.
from 142 / 1,000 pt-days to 26.6 per 1000 ptdays
86% reduction in non-intercepted serious
medication errors.
from 7.6 / 1000 pt-days to 1.1 per 1000 ptdays
All main error types reduced; dose, frequency,
route, substitution, allergies
(Bates et al. J. Am.Med. Inform. Assoc.1999)
Where is the evidence?
55% reduction in non-intercepted serious
medication errors
from 10.7 / 1,000 pt-days to 4.86 per 1000 ptdays
84% reduction in non-intercepted potential
adverse events
from 5.99 / 1000 pt-days to 0.98 per 1000 ptdays
Error types reduced; dose errors, known allergy
errors
(Bates et al. JAMA.1998)
Where is the evidence?
Meta-analysis of comparative studies
18 studies
Advice given on dosing of drugs
Pharmacokinetic models used to predict dose
Higher blood concentrations
Reduced time to therapeutic control
Total dose unchanged
Fewer unwanted effects
5/6 studies showed outcome benefit
(Walton et al BMJ 1999)
Where is the evidence?
Legibility & completeness
Improved completeness of demographic data
(100%)
Improved legibility of drug name (100%)
Administration times present (100%)
Prescriber ‘signed’ (100%)
Dosing units standardised (mg/micrograms)
Use of abbreviations reduced
(data from Wirral Hospital )
Dispensing
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Pharmacy staff
interprets the prescription
confirms appropriateness
produces label
selects container
affixes label
gives to patient
Dispensing
Errors can occur with interpretation
 Lack of availability of information
 Transcription
 Label generation
 Product selection
 Wrong patient errors
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Dispensing
Direct transmission of the prescription
 Integration of Pharmacy systems with
electronic patient records
 Robotic dispensing systems
reduced error rate
2.9%-0.6% (US data)
19 - 7 per 100,000 items (UK)
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Administration
5 (6) ‘rights’
right drug, right dose, (right
formulation), right patient, right route,
right time
 Errors do occur
 Estimated at 5% of oral doses due
(including omissions) (Barber & Dean 2000)
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Automated drug administration
Automated bedside ‘dispensing’
machine reduced error rates from
15.9% to 10.6%
 Wrong time errors were most common
 Omissions were reduced(Barker et al. AJHP 1984)
 Extra dose, wrong dose and wrong
route errors increased
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Bar Coding drug administration
Reduces errors to 1/6 of those with
keyboard entry
 Less stressful
 Concord Hospital - 80% fall in
medication errors (unpublished)
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Monitoring and use
Adverse event detection
 Longitudinal medication summaries with
clinical and lab. events
 compliance monitoring
 medication review
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Barriers
Lack of research
 Limited funding
 Lack of demand from healthcare
industry
 Safety has not been a high priority
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Conclusions
Several IT developments have been
shown to improve safety
 Electronic prescribing appears to be
most beneficial
 Dispensing and administration may be
safer if electronically linked
 Professional rewards
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