Transcript Paediatric Electronic Prescribing

Paediatric Electronic Prescribing
Dr David Terry
Director – Pharmacy Academic Practice Unit
Electronic Prescribing in Hospitals
Moving Forward
Thursday 6th October 2016
The Studio Conference Centre, Birmingham
Peaky
Blinders
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over 270,600 patient visits
every year
361 beds
43,151 inpatient admissions
each year
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Hand written drugcharts!
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Drug Errors
Prescribing errors occur in 1.5-9.2% of medication orders
written for hospital inpatients
Dispensing errors are identified in 0.02% of dispensed items
Medication administration errors occur in 3-8% of nonintravenous doses and about 50% of all intravenous doses
E-prescribing reduces error rates by 55% and serious
medication errors by 88%
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Changing doses
Unlicensed products
Variable strengths
Swallowing / formulations
Fewer decision support
tools
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Developing eRx’ing
EPMA – 5yrs
PICs
… built at UHB, but now
to include children.
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Prescribing Information
and Communications
System
Safety
Quality
Resources
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BDD
BCH Drug Database
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BDD
Drug
Indication
Route
Age
Dose
Terry D, Junaid E, Reynolds F, Sinclair A, Bugg N, Terry A, Terry J, Hussain A, Caffrey J, Burridge A.
Electronic prescribing: the development of a paediatric drug database. Arch Dis Child
2015;100:e1 doi:10.1136/archdischild-2015-308634.2
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Age ranges!
• Over 400 in a single text
• No consistency in terms
• Developed our own rules
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Drug
Indication
Route
Age
Dose
Drug
Indication
Route
Age
Dose
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55
8-12 years
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9-16 years
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Adult
58
All ages
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All ages (under 15 years)
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All ages except neonates
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All ages except premature babies
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All children > 1 month
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Birth-2 years
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Child 11-18 years
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Child 6-18 years
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Child 8-11 years
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Children
68
Children (all ages)
69
Children 13-16 years
70
Children over 12 years
71
Children over 2 years
72
Children over 4 weeks
73
Children over 5 years
75
Infants & Children
Drug
Indication
Route
Age
Dose
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Age ranges!
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age ranges should be mutually exclusive and coterminous;
age ranges should have precise upper and lower limits;
time units should be used in the expression of all age ranges;
acceptable time units are days, weeks, months and years;
the birth date is ‘day 0’ whatever time of day the child is born;
a ‘transition day’ is the day on which the child attains the next
significant age and is included in the upper limit of an age range;
• when a child reaches 18 years old the adult drug dictionary will apply.
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Age ranges!
• a neonate is a child of 0 days to 28 days;
• the first month of life is always 28 days,
• 2 months is 56 days,
• 3 months is 13 weeks (91 days);
• other than for the first 3 months of life in the period up to one year ‘a
month’=30 days;
• other than for children in the first 3 months of life age ranges in the period
up to 5 years are expressed in months;
• for ages over 5 years the limits are expressed in years.
RATIONALISATION OF PAEDIATRIC DRUG DOSING AGE RANGES: REDUCING CONFUSION
Alice Burridge, John Caffrey, Fiona Reynolds, David Terry, Akhmed Hussain,Emma Pring, Basheer Tharayil.
10.1136/archdischild-2015-308634.2
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BCH – current position
• Pilot ward go live January 2017
• Go live over a 6 month period?
• Dose ceilings – drug, age, route
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SPACER
Aims: To identify the benefits and disbenefits of EPMA
compared to paper-based system
Before and after study
3 years
3 strands
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SPACER
Ethnographic
Data Envelopment
Analysis
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Drugs Data Decisions (3D)
Ethnographic
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Data Envelopment
Analysis
Safety
Quality
Resources
Culture
Technology
Processes
Organisation structure
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Drugs Data Decisions (3D)
Strand A
Ethnographic strand
Mixed method – Qualitative
and Quantitative study
Observe the organisational
change, explore staff
perspectives of doctors, nurses
and pharmacists as eprescribing is implemented
Strand B Efficiency
– “DEA model”
strand
DEA – Data Envelopment
Analysis
What is the impact of eprescribing on the efficiency
of the services?
Strand C – 3D study –
Drugs, Data, Decisions
What Key Performance Measures
does the hospital measure before
implementation of e-prescribing,
how much resources are used to
generate it?
What will be measured during and
after implementation?
Safety
Pre-implementation
(year 1)
Quality
Resources
Culture
Peri-implementation
(year 2)
Technology
Post-implementation
(year 3)
Processes
Structure
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Strand B Efficiency
– “DEA model”
strand
DEA – Data Envelopment
Analysis
What is the impact of eprescribing on the efficiency
of the services?
• Benchmarking tool?
• Define areas – DMU
• Identify inputs & outputs
• Determine ‘efficiency’
• Identify changes over time
David RP Terry
Dr David Terry
Director – Pharmacy Academic Practice Unit
[email protected]
[email protected]
0121-204-3941
David RP Terry