Transcript ppt med discrep

Measuring the Severity of Medication
Discrepancies:
A Community Pharmacy Perspective
Overview

Background

Introduction

Medication Discrepancies

Potential-to-harm scale

Data

Limitations

Conclusion
2
Background

The Journal of the American
Medical Association recently said
that if adverse reactions to
medications were classified as a
distinct disease, it would rank as
the 5th leading cause of death in
the USA.
3
Introduction
Modern Medicine = More Diagnoses
= More Treatment Options
= More Drugs Dispensed
However,
Increased Potential for Medication
Discrepancies
Increased Risk of Medication Errors
4
Introduction
What does this mean to pharmacists?
= The integrated management of
medication regimes to decrease the
number of medication discrepancies
5
Introduction
Our study sought to investigate the
prevalence of medication
discrepancies in two population
cohorts leaving hospital care for
either a:

Outpatient Renal Ward

Long Term Care Facility
6
Medication Discrepancy
Medication
discrepancies,
for
our
purposes, were taken to be any
discontinuity between the pharmacy
database and any other listing of the
patients' medications, e.g. hospital
records.
7
Methods



Each patient was interviewed about
his/her medication regimen.
Discrepancies were rated for potential
short and long term risks based upon
a novel potential-to-harm (PTH) scale
The PTH scale was devised to gauge
the severity of each discrepancy
8
Potential-to-Harm Scale


Categorical
assessments were
carried out by
pharmacists
Short Term Risk
S1 – Low risk of discomfort or harm
S2 – Intermediate risk of discomfort or harm
S3 – High risk of discomfort or harm
Potential risks in
both short and long
Long Term Risk
term were
L1 – Low risk of discomfort or harm
considered
L2 – Intermediate risk of discomfort or harm
L3 – High risk of discomfort or harm
9
Examples
Example:
Short
Term
Risk,
Low
Discomfort or Harm (S1):
Risk
of
Patient's community pharmacy list did
not include docusate sodium for
prevention of constipation secondary
to chronic narcotic use but patient is
using regularly.
10
Examples
Example:
Long Term Risk, High Risk of Discomfort
or Harm (L3):
Patient's community pharmacy list
included Warfarin 1mg OD but the
current dose was for 2.5mg OD.
11
Med Rev Form
12
Results – Analysis
Table 1. Demographic Data
Longterm Care
Cohort
(n = 29)
Renal Ward
Cohort
(n = 19)
Total
(N = 48)
82 (±9)
55
96
66 (±16)
21
81
76 (±14)
21
96
Male, No. (%)
14 (48.3)
11 (57.9)
25 (52.1)
Female, No. (%)
15 (51.7)
8 (42.1)
23 (47.9)
Mean age (±SD), y
Min age, y
Max age, y
13
Results – No. of Meds
35
30
25
20
# of Meds
15
10
5
0
10
20
30
40
50
60
70
80
90
100
110
Age at Assessment
14
Results – Analysis
Table 3. Potential-to-Harm Scale Observations
Short Term
Long Term
S1
S2
S3
L1
L2
L3
Longterm Care Cohort
(n = 29)
No. discrepancies by
severity class per 10
patients, Mean (±SD)
3 (±6)
5 (±12)
3 (±10)
5 (±7)
3 (±7)
3 (±10)
Renal Ward Cohort
(n = 19)
No. discrepancies by
severity class per 10
patients, Mean (±SD)
5 (±7)
15 (±27)
7 (±8)
16 (±17)
0
0
4(±7)
9 (±15)
5 (±10)
10 (±11)
2 (±6)
2 (±8)
Total (N = 48)
No.
discrepancies
severity class per
patients, Mean (±SD)
by
10
15
Results – Analysis
Table 2. Observed Discrepancies
No. Patients with
discrepancies (%)
No. recorded medications,
mean (±SD)
No. medication
discrepancies, mean
(±SD)
Relative No. of
discrepancies, mean %
(±SD%)
Longterm Care
Cohort
(n = 29)
Renal Ward
Cohort
(n = 19)
Total
(N = 48)
15 (51.7)
19 (100.0)
34 (70.8)
12 (±6)
15 (±4)
13 (±5)
3 (±4)
5 (±3)
3 (±4)
23 (35)
30 (20)
26 (29)
16
Limitations


The sample size for this study was
small, 48 patients, and therefore may
not be a true representation of the
population.
There is a degree of interviewer
subjectivity in performing the
medication reconciliations which may
influence the results.
17
Conclusion
Extrapolating from the data, we can
make the following conclusions and
observation:

Both populations displayed severe
risks resulting from medication
discrepancies.
18
Conclusion


Both populations displayed severe
risks resulting from medication
discrepancies.
Renal patients had more
discrepancies than long term care
patients. Possibly the more the
patient controls their own medication
the more problems that can arise.
19
Conclusion


Regular medication reconciliations
decrease the number of medication
discrepancies.
Medication reconciliations are an
important tool available to community
pharmacists and can be used to
improve the delivery of seamless
patient care.
20
Conclusion

By doing medication reconciliation we
have shown that it can improve
patient outcomes.
The data and results of this study
provide a stepping stone to further
study in regards to medication related
problems.
21
22