Safety and Quality of Prescribing by
Medical Residents: Implications for
Electronic Prescribing
Darren Triller, Pharm D
Senior Director
Health Care Quality Improvement
IPRO
Introduction/ Background
• Medication-related problems are major contributors to
avoidable morbidity and mortality, and unique
environmental and system factors may increase the risk of
patients encountering problems with prescriptions
originating from academic medical centers and issued by
medical residents.
• While emerging electronic prescribing technology has the
potential to eliminate some types of prescribing problems, it
is unclear whether existing e-prescribing technology has the
ability to address problem types most commonly associated
with prescriptions issued at large academic medical centers.
2
Study Goals
• Quantify & characterize problems identified with
prescriptions presented to pharmacies in close
proximity to academic medical centers
• Evaluate whether problems are more prevalent with
“Resident-issued” prescriptions
• Determine whether existing electronic prescribing
technology has the potential to address identified
problem types
3
Methods
• The study utilized a technical expert panel (TEP) to develop and
test data collection process and tools
•Collected real-time data from a representative sample of
pharmacies in close proximity to large academic centers across the
state.
4
Methods Cont.
Using Google Maps®, pharmacies with proximity to the largest
academic medical centers were recruited for voluntary
participation in the study.
5
Methods Cont.
• Pharmacies were approached
in descending order of program
size and in increasing order of
distance from the medical center
• Goal of recruiting 2-3
pharmacies in proximity to each
of six targeted residency
programs from across the state
• 15 pharmacies were
successfully recruited
6
Academic Program Size
Program Size (# of total
residents)
Hospital Name
Region
# of participating
pharmacies
556
Mount Sinai Hospital
NYC
3
526
Strong Memorial Hospital
Upstate
2
443
New York Presbyterian
Hospital (Weill)
NYC
1
381
SUNY University Hospital
(Stony Brook)
Long Island
1
333
Maimonides Medical
Center
NYC
1
331
Long Island Jewish
Medical Center
NYC
1
303
Kings County Hospital
Center
NYC
1
219
SVCMC-St. Vincent’s
Manhattan
NYC
1
206
*Brooklyn Hospital
NYC
1
76
*Metropolitan Hospital
NYC
1
60
*Rochester General
Hospital
Upstate
2
7
Methods Cont.
•Study staff, trained pharmacists or pharmacy
students collected the data. (training video)
• All problems were tracked for 24 hours & then
considered “Timed out/ not resolved” if there was
no resolution documented by that time.
Day 1
Document
problems
associated with
new prescriptions
received.
Day 2
Collect data on
resolving problems
from day 1 &
document problems
associated with new
prescriptions
received.
Day 3
Collect data on
resolving
problems from
day 2
8
Methods Cont.
• A documented “problem” was any instance
in which a pharmacist, when presented with a
newly issued prescription, could not continue
the dispensing process without rectifying
some component of the prescription.
Categories of problems
associated with prescriptions
• All such instances inherently contribute to
delays in medication procurement by the
patient, which, in and of themselves, may
contribute to adverse outcomes.
9
Methods Cont.
•Data from participating pharmacies was aggregated and analyzed
to quantify the rate of problems and the characteristics of the most
common problem types.
•Additional analysis compared rates of problems by prescriber
type and intake type.
•The incidence of unsafe prescriptions was assessed via query of
clinical members of the TEP using Survey Monkey® for both the
clinical impact of the delay in patient care and the potential
severity of prescriptions that were identified as clinical problems.
10
Results
11
Results Cont.
4.6% of new prescriptions received on study days
contained problems. (203 out of 4,452)
12
Results Cont.
Problem rate by prescription intake
Rx intake
Total
Scripts
Problem
Scripts
Problem
Rate
e-Rx
435
14
3.2%
Faxed
391
36
9.2%
Phoned
926
21
2.2%
Written
2321
132
5.7%
p<0.05
13
Results Cont.
p<0.05
14
Post-Hoc Analysis Rationale
•To determine whether practices within pharmacies (e.g. attributing
prescriptions written by residents to their attending physicians) might
unintentionally bias the results against residents by deflating the
denominator in rate calculations.
Post-Hoc
Original
Pharmacy
Resident
Attending
Resident
Attending
A
0
270
26
244
B
2
121
1
122
C
27
330
54
303
7.5% of Attending prescriptions were actually written by Residents
15
Post-Hoc Analysis Results
p<0.05
16
Results Cont.
Drug Category
Antibiotic
% of all problems
11.17%
Narcotic
9.22%
Antidepressant / antipsychotic
5.83%
Proton Pump Inhibitor
5.34%
Steroid
5.34%
Benzodiazepine
3.88%
Statin
3.88%
Supplies (first-aid)
3.40%
Vitamin
3.40%
Beta Blocker
2.91%
17
Results Cont.
18
Results: Clinical Impact of Delayed
Prescriptions
• 25.1% of problem prescriptions “timed-out” (n=51)
• TEP Survey Results:
• 60% considered to be highly likely/likely to cause a worsening
or prolongation in symptoms.
• Ex: narcotic pain relievers, antibiotics, topical steroids,
antiemetics, etc.
• 20% considered highly likely/likely to cause a worsening or
progression in disease state.
•Ex: antibiotics, insulin, antihistamine, etc.
19
Results: Potential Severity Classification
of Clinical Problem Prescriptions
•11.3% of Problems were deemed “clinical” in nature by data
collector
•11 of 27 clinical problems were selected to rank their potential
severity to the patient assuming the order was filled/taken as
originally written.
•TEP Survey Results:
• Four (36.4%) of the cases presented were ranked by the TEP as
Potentially Significant.
• Ex: Inappropriate dose, Inappropriate quantity, etc.
• Three (27.3%) of the cases presented were ranked by the TEP as
Potentially Fatal/Severe.
• Ex: Drug-drug interaction, inappropriate dose, severe overdose, etc.
20
Impact of E-Prescribing Methods
•The TEP was queried using Survey Monkey® to ascertain the
potential ability to diminish or avoid such problems using
existing e-rx technology
•asked to review each problem subtype and rank the
likelihood that e-rx features could address that problem
type
•asked to identify specific e-rx applications that presently
include the required features
•staff evaluated identified applications to verify the
availability of necessary features
•The presence of an available feature was then assumed to
have the potential to avoid/rectify related problem subtypes.
Final summary estimates reflect the percentage of problem
prescriptions potentiallty avoidable using e-rx technology.
21
Clerical Total (n=100) 41.8%
Distribution of
Problem Types
% of all Problems
Systems
Referenced
Electronic feature
available &
confirmed by
vendor (Y/N)
Drug not available/not
in stock (In US)
10%
Yes
Yes
Drug not available/not
in stock (In specific
pharmacy)
No
Missing/Illegible
patient info
7.5%
Yes
Yes* Interface to
PMS $300 or
$1500
Missing/Illegible
prescription/drug info
7.1%
Yes
Yes
Missing/Illegible
prescriber info
4.2%
Yes
Yes
Prescription not
dated
2.9%
Yes
Yes
22
Insurance Total (n=112) 46.9%
Distribution of
Problem Types
% of all Problems
Systems
Referenced
Electronic feature
available &
confirmed by
vendor (Y/N)
Drug not covered
13%
Yes
Yes
Invalid Date
10.9%
No
No
Prior authorization
needed
8.8%
No
Yes
Patient not
covered
2.1%
Yes
Yes
Invalid qty
prescribed
2.1%
Yes
Yes
Patient could not
afford
1.7%
No
Yes* Depending on
plan
23
Clinical Total (n=27) 11.3%
Distribution of Problem
Types
% of all Problems
Systems Referenced
Electronic feature
available & confirmed
by vendor (Y/N)
Inappropriate QTY
2.9%
Yes
Yes
Inappropriate Dose
2.5%
Yes
Yes
Inappropriate Form
1.3%
Yes
Yes
Drug-drug interaction
1.3%
Yes
Yes
Inappropriate
Frequency
0.8%
Yes
Yes
Contraindication
0%
Yes
Yes
Duplicate Therapy
0.8%
Allergy
0%
Yes
Yes
Inappropriate Drug for
dz/condition
0%
Yes
Yes
Inappropriate duration
0%
Yes
Yes
Yes
24
Result Summary
• Problems with prescriptions are still
unacceptably common, and adversely affect
patient care
• Prescriptions written by residents appear to
have a higher rate of problems than other
prescribers
• E-Prescribing has the potential to reduce
69% of the problems encountered at
pharmacies.
25
Limitations
• Pharmacy recruitment was difficult, and
other pharmacy practices and may have
biased or otherwise affected data
• Capture of event data on the pharmacy side
“diluted” the volume of prescriptions issued
by residents.
• Despite the large number of total
prescriptions involved, the relatively small
sample of identified problems limited the
ability to analyze potentially contributing
variables
26
Conclusion
•Prescriptions issued by residents appear to be more prone to
problems, suggesting that educational interventions may
improve quality.
•Existing e-rx technology has the potential to reduce or eliminate
many types of problems, and should be considered for
implementation in academic medical center environments as a
means of improving quality and safety.
27
Special Acknowledgements
The Project is a part of a state-wide Medication Safety Initiative funded by
the New York State Attorney General’s settlement with Cardinal Health,
Inc. and administered by Health Research Inc. (HRI)
•Project Assistance:
Derik Wandell, PharmD
Tina Fan, MD
Tierney Clark, PharmD Candidate
•Special thanks to all participating pharmacies.
For More Information
Project Director: Darren Triller, Pharm D
(518) 426-3300 x125
[email protected]
Project Coordinator: Stephanie Cannoe-Petersen, MA
(518) 426-3300 x144
[email protected]