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Improving Drug Safety withthe use of Information
Technology
Dr. Pauline Lai Siew Mei
Department of Primary Care Medicine
Faculty of Medicine, University of Malaya
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Introduction Medication errors, adverse drug events, or
injuries due to drugs, occur more often than
necessaryLazarou J, et al. JAMA. 1998;279:1200 –1205
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Incidence Medication errors receive less public attention
compared to aeroplane and automobile crashes.
Overall incidence for serious adverse drug reactions
in hospitals is 6.7%
Between 28% and 56% of adverse drug events are
preventableBates DW, et al. JAMA. 1995;274:29 –34.
Lazarou J, et al. JAMA. 1998;279:1200 –1205
Leape LL, et al. N Engl J Med. 1991;324:377 –384.
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Role of automation in the medication
process
Source: BMJ. 2000 March 18; 320(7237): 788 –
791.
TranscriptionElectronic prescribing
DispensingRobots, bar coding,
Automated dispensing devices
Medication administration
Bar coding, automated dispensing devicesElectronic medicine administration
Monitoring ADR
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TranscriptionElectronic prescriptions
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Prescribing medications
Most common form of therapeutic interventionby Drs to influence patients’ health
Inappropriate prescribing:
Most common cause of iatrogenic disease
Frequent source of negligence claims against
Drs & healthcare providers
Maxwell & Walley, 2003
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“Forcing functions” of I.T. Prescriptions
prescribed
electronically can beforced to be legible
and complete
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Access the electronic PMR to obtain a
complete medication history
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Decision supportPerforms checks in real time
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Drug templatesProvides a guide to the clinician on the appropriate drug
dosage and route of administration
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Chemotherapy protocols
Each regime can be preset within the system
Ensures that the correct drug(s), dose and route of administration
is prescribed for that particular regime
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Assist with calculations
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Calculates the body surface area
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Displays calculation Asks if it is correct. The dose is then checked against a table of doses, withdaily and weekly limits. If a dose limit is exceeded the order can be rounded
down / suspended until it can be reviewed and approved
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Make knowledge more
readily accessible
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Providing access to drug information
Use of hand-held devices for rapid
and instant access will improve
safety
http://www.epocrates.com
http://www.unboundmedicine.com
http://www.micromedex.com
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Drug information sourcesWithin a clinical application
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Impact of the use of electronicprescribing in an outpatient
setting in the UMMCP.S.M. Lai1, S.S. Chua2, C.P.L. Tan3 1Pharmacy Unit, UMMC2
Dept of Pharmacy, University of Malaya3Dept of Primary Care Medicine, University of Malaya
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Objectives
To investigate any difference in
Doctors’ consultation time
Time taken for outpatient pharmacy to
dispense medications
before and after the implementationof e prescribing
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Methodology
Period of study:
Phase 1: 8 April – 6 May 2002
Implementation of e prescribing – May 2002
Phase 2: 2 Sept – 28 Sept 2002
Study site:
Primary Care Clinic, University Malaya Medical
Centre
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Sampling frame
Included
All patients attending the Primary Care Clinic
between 0800-1500 hours during the studyperiod
Excluded Patients prescribed non-formulary items
Patients admitted to the ward
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Data collected
Time taken by the doctor to see eachpatient
Time taken by the outpatient pharmacy todispense medications
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Demographic data
Phase 1 Phase 2
No. of patients 2663 1485
Mean age
(years)
43.50 22.00 49.25 19.40
Fewer patients were included in Phase 2 as not all
patients were prescribed electronically
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No. of diagnoses per patientNo. of diagnoses Phase 1 Phase 2
One 1792 (67.5%) 1124 (77.7%)
Two 817 (30.8%) 304 (21.0%)
Three 42 (1.6%) 17 (1.2%)
Four 2 (0.1%) 1 (0.1%)
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Waiting times
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Waiting times
Phase 1 Phase 2
Duration in Dr’s room (mins) Min 2.00 1.00
Max 415.00 216.00
p=0.669 Mean 22.2 32.4 22.7 31.0
Pharmacy waiting time* (mins) Min 1.00 1.00
Max 222.00 128.00
*p<0.001 Mean 27.6 18.7 7.2 11.2
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No. of items dispensed & not
dispensedPhase 1 Phase 2
No. of items received 5093 4020
No. of items not dispensed 179 3
% of items not dispensed*
(*p<0.001)
3.51 0.07
Mean no. of items per
prescription (p=0.617)
2.63 1.33 2.71 1.53
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No. of prospective pharmacy
interventions Phase 1 Phase 2
Sample size 1926 1485
No. of prescriptions
intervened* (p<0.001)
263 (13.6%) 3 (0.2%)
No. of prospective
problems detected
402 3
Total no. of drugsprescribed 5093 4020
Drugs not available 179 0
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Electronic prescribing
Reduced patient frustration
Caused by delays
Not being told in advance to pay the full costof the drug
Medication is ready before the patientarrives in pharmacy
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Prescribing electronically
A prescription for a single item took slightly
more time to enter electronically than to write by
hand
Prescriptions for multiple medications took less
time
Doctors became more proficient in using the
system as time went onBates DW et al, 1994:996 Abstract from 18th Annual Symposium on Computer
Applications in Medical Care
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Conclusion
Electronic prescribing
Simplified the dispensing process & reduced
pharmacy waiting time by about 4x
Did not increase doctors’ consultation time
Improved the efficiency of the prescribing
process through online drug availability &
formulary benefits at the optimal point
between the doctor & patient
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DispensingRobots
Bar-coding
Automated dispensing devices
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Robots for filling prescriptions
May reduce error rates
Used in some large hospitals especially in the
outpatient setting
One unpublished study: robot decreased the
dispensing error rate from 2.9% to 0.6%
Pharmacy Robot in Scotland saved their Trust
£700,000 http://www.bbc.co.uk/news/health-
11562928
PE Weaver and VJ Perini, American Society of Health System Pharmacists, 1998
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Bar-coding of medications
Ensures that drug at hand is the intended one
Used to record who is giving and receiving it
Can record various time intervals
May reduce error rates to about 1/6 to keyboard entry
Less stressful to workers
Major barrier to implementation: drug manufacturers not able
to agree on a common approach (to be legislated?)
Concord Hospital, New Hampshire, USA
80% fall in medication administration errorsD DePiero, personal communication
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Baxa compounderInterfaced with a Pharmacy Information System
Automated Total Parenteral Nutrition
Compounder
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CytoCare™
Automates the compounding of hazardous
IVs, used for chemotherapy, monoclonal
antibody therapy, and genetic therapy
Improves accuracy, efficiency and pharmacist
safety
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http://www.devonrobotics.com/cytocare/tv /
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AdministrationBar-coded patient identification
Automated dispensing devices
Automated medication administration record
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Bar coded patient identification
Designed to prevent
accidents, such as the
performance in one
patient of a procedureintended for another
patient
Verification of the
correct drug for the
correct patient
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Automated dispensing devices
Can be used to hold drugs at a location
& dispense only to a specific patient
If linked with bar coding & interfacedwith hospital information systems and
electronic prescribing can decrease
medication error rates substantially
Without these links, effect is unclear:
one study showed an increase in
medication errors
Barker KN et al. Am J Hosp Pharm. 1984;41:1352 –1358
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Electronic medication
administration
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Touch-screen administration application. List of doses due for administration for the patient.
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Full details of the dose selected
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Non-administration reasons may be recorded
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When recording administration, the current date and time
defaults in but can be over-ridden
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The updated administration record confirming
that the erythromycin has been administered
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An intravenous infusion is selected for administration
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Entering the batch number and expiry date
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Entering password of second checker (if required)
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Batch number and second check confirmed
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Heparin infusion now in progress
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Administration history desktop
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Report for the ward manager of doses overdue on the
ward. Used at nursing shift handover
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Monitoring ADR
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Monitoring
Boring & not performed well by humans
Data collected hard to sift through to detect problems
If monitoring of information is computerized,
applications can perform this task, looking for
relations & trends & highlighting them, whichpermits clinicians to intervene before an adverse
outcome occurs.
R id t & t ki f
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Rapid response to & tracking of
adverse events
I.T. can be used with electronic medical records to identify,
intervene early in, and track the frequency of adverse events
Combing clinical data bases to detect signals that suggest thepresence of an adverse drug event (e.g. use of an antidote).
This approach identified 81x as many events as did
spontaneous reporting
Such tools may be useful both for the improvement of care
and for research.
Classen DC et al. JAMA. 1991;266:2847 –2851
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Other ways that I.T. can
improve drug safety
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Improving communication
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Improve exchange of information
Computerized coverage systems for signing
out
Hand-held personal digital assistants
Wireless access to electronic medical records
Especially if links b/w various applications &
a common clinical data base are in place
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Urgent action
Serious laboratory abnormalities: hypokalemia
Require urgent action when clinician is not around
Such results can be “lost” amid less critical data.
Information systems: identify & rapidly communicate these
problems to clinicians automatically
This approach reduced the time to the administration of
appropriate treatment by 11% & reduced the duration of
dangerous conditions in patients by 29%
Kuperman GJ et al. J Am Med Inform Assoc 1999;6:512-522
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“Corollary orders”
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“Corollary orders”
An action may imply that another should be taken
Prescribing bed rest would trigger the suggestion of initiating
prophylaxis against deep venous thrombosis
Targets errors of omission
Resulted in a change in behavior in 46% vs 22% of the
intervention & control group, respectively, with regard to a
broad range of actions
Overhage JM, et al. J Am Med Inform Assoc 1997;4:364-375
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Barriers to the use of I.T.
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Financial barriers
Investment costs can be high
Doolan DF & Bates DW. Health Aff (Millwood) 2002;21:180-188.
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Lack of standards
Quality of the decision support remains highly variable
Lack a single standard for clinical data, procedures,medications, laboratory data
Most applications do not communicate well, w/in
organizations, & costs of interfaces are high
Some important types of data are privately held.
Metzger J & Turisco F. (Accessed 8 Sept, 2010, athttp://www.leapfroggroup.org/CPOE/CPOE%20Guide.pdf .)
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Personnel barriers
“Paradigm shift” of the older generation
Cultural values of I.T. being impersonal
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Summary Although I.T. has been used widely in hospitals,
relatively few data are available regarding their impacton the safety of the process of giving drugs
Exceptions: electronic prescribing & decision support:which have been found to improve drug safety
Robots to fill prescriptions, bar-coding, automateddispensing devices, and computerisation of the
medication administration record, though less studied,should all eventually reduce error rates
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Thank you
