Risk Stratification in Medication
Reconciliation and ADE Screening:
A Demonstration Project
June 6th, 2011
Medication Reconciliation:
Connecting Sectors and Sparking Action
Corinne M.
M Hohl,
Hohl MD,
MD FRCP(C),
FRCP(C) MHSc
Emergency Physician, Vancouver General Hospital
Assistant Professor, University of British Columbia
Scientist, Centre for Clinical Epidemiology and Evaluation
Clinician Scientist, Vancouver Coastal Health Research Institute
Acknowledgements
Riyad Abu-Laban
Gary Andolfatto
Jeff Brubacher
Linda Dempster
Garth Hunte
Susanne Moadebi
Fruzsina
i Pataki
ki
Sam Sheps
Joel Singer
Boris Sobolev
Ruth Tsang
Matthew Wiens
Eugenia Yu
UBC Dept of Emergency Medicine
Objectives:
• Cases
• What we have learned
• Frequency in ED
• Patient Outcomes
• Attribution
• Potential solution
• Clinical Decision Rule
• Demonstration Project
• Future Directions
Case 1
Mrs. J.: 82 yr old female
• Presentation #1 to the ED:
• Labored breathing
breathing, drowsiness and refusing intake for 48h
48h.
Diagnosed with dehydration, renal failure and a possible UTI.
• 5-day admission to Internal Medicine.
• Discharge home in improved condition
condition.
• Addition of ciprofloxacin for UTI the only medication change.
• Presentation #2 to the ED:
• R
Returned
t
d 5d llater
t ffor llabored
b db
breathing,
thi iincreasing
i
drowsiness, decreased intake and now unresponsive.
• Her daughter: “She looks exactly the same as when I brought
her here the first time.
time ”
Case 1
Mrs. J.: 82 yr old female
• Presentation #2 to the ED (cont):
{ HR 70, BP 152/70,
/ RR 18-24, Temp 37.3, O2 sat
99%, Glu 4.5
{ Drowsy
y and confused.
{ Physical exam normal.
{ Lab values: Bicarb=14, Creatinine=99, K=3.1
{ Blood
l d gas: 7.48/17/92/12/-10 Æ Mixed acid base disorder
{ Urine culture: negative from first admission.
Æ Chronic Salicylate poisoning: ASA
ASA=5.4
5.4 (0.3
(0.3-2.1)
2.1)
Case 1
Diagnosis of
Mrs. J.: 82 yr old female
ADE was
• Presentation #1 to the ED:
missed
inforthe
• Labored breathing,
g, drowsiness and refusing
g food or drink
2 days. Diagnosed with dehydration, acute ED
renal failure
and
a
and
on
possible UTI.
• 5-day admission to Internal Medicine.
the ward
• Discharge home to the community in improved condition
condition.
• Addition of CIPROFLOXACIN for UTI is the only medication
change.
• Presentation #2 to the ED:
• Returned 5days later for “labored breathing”, increasing
drowsiness, decreased intake and now unresponsive.
• Her daughter: “She looks exactly the same as when I brought
h h
her
here th
the fi
firstt ti
time”>
”
Case 1
• Aspirin poisoning caused:
• Two acute care ED visits.
• Two acute care hospital admissions.
• Dialysis candidate on second admission.
• Preventable:
• Second ED visit ($)
• Second acute care hospital admission ($$).
• Patient and family suffering
suffering.
Case 2
Mr. S.: 90 gentleman, living independently
• Presentation #1 to the ED:
• H
Heartt Att
Attackk Æ Cardiac
C di cath
th llab
b ffor PCI and
d stent.
t t
• Started on aspirin and clopidogrel for stent, and warfarin
for low ejection fraction post heart attack
• Discharged
Di h
dh
home to the
h community.
i
• Presentation #2 to the ED:
•
•
•
•
Started bleedingg from his nose 5 wks later.
Took 8h to control the bleeding.
INR=6.2, and Hb=78 (prior 128).
Discharged home.
home
Case 2
• Presentation #3 to the ED:
• Presented to the ED several hours later for chest pain “just
like my heart attack before Christmas.
Christmas ”
• Diagnosed with recurrent heart attack requiring
readmission to hospital.
• INR>9.0, Hb=68
Case 2
Mr. S.: 90 gentleman, living independently
• Presentation #1 to the ED:
• H
Heartt Att
Attackk Æ Cardiac
C di cath
th llab
b ffor PCI and
d stent.
t t
• Started on aspirin and clopidogrel for stent,
and warfarin of
Diagnosis
for low ejection fraction post heart attack
ADE was
• Discharged
Di h
dh
home to the
h community.
i
missed in the
Started bleedingg from his nose 5 wks later.
ED.
• Presentation #2 to the ED:
•
• Took 8h to control the bleeding.
• INR=6.2, and Hb=78 (prior 128).
home
• Discharged home.
Case 2
• Adverse drug event to Warfarin, aspirin and
clopidogrel:
• Two acute care ED visits.
• One acute care hospital admission.
• Preventable:
• One ED visit ($).
• One
O acute
t care h
hospital
it l admission
d i i ($$)
($$).
• Patient and family suffering.
Do we have a problem?
DRV Study:
How manyy patients
p
present
p
to tertiaryy care EDs
because of an adverse drug event?
DRV Study:
How manyy patients
p
present
p
to tertiaryy care EDs
because of an adverse drug event?
We learned that:
• ADEs are responsible for the patient’s chief complaint
in 12% or - one in nine - ED visits.
• Extrapolated nationally
nationally: ~1
~1.7
7 million ED visits/year
visits/year.
• 68% were retrospectively deemed to have been
preventable.
• The odds of being admitted was double (OR 2.18) for
patients presenting with adverse drug events.
DRV Study:
What types
yp of events?
• 39% due to adverse drug reactions
• 28% due to non-adherence
What types of drugs?
•
•
•
•
•
•
Opioid-containing analgesics (11%)
Antipsychotics (10%)
Benzodiazepines (6%)
Diuretics (6%)
Beta-lactam antibiotics (6%)
NSAIDs (5%)
DRV Study:
Extrapolated
p
to where I work:
–
–
–
–
We see 75,000 visits annually.
9 000 are due
9,000
d to
t adverse
d
d
drug
events.
t
6,000 are due to preventable adverse drug events.
Over 60% off p
patients with adverse drug
g events
were discharged back home and most (90%)
would not have seen a pharmacist in the current
standard off care.
Patient Outcomes:
How do p
patients p
presentingg with Adverse Drugg
Events do?
Patient Outcomes
Mortality
o ta ty
• 6-month mortality of patients presenting with an adverse
drug reaction 14.6%.
• 6-month mortality of patients presenting without a
medication-related problem 5.9% (p-value not significant).
Patient Outcomes
Adjusted
j
for age,
g ggender, number of co-morbid
conditions, presence of GP and illicit drug use:
• Adjusted odds of spending one additional day in hosp/mo:
{ OR 1.51 (95%CI
(
1.41–1.61, p<0.001))
• Adjusted rate of outpatient health care encounters:
{ RR 1.24 (95% CI 1.07–1.44, p=0.005)
• Adjusted median monthly cost of care:
{ 1.88 times higher (95%CI 1.16–3.05, p=0.01)
Patient Outcomes:
Extrapolated
p
to the patients
p
we see with ADEs
at our hospital:
– The 9
9,000
000 who presented with adverse drug
events each spent 2.4 to 7.8 additional days in
the hospital during the 6-month follow-up period
compared
d with
i h patients
i
presenting
i to the
h ED ffor
other reasons.
– For VGH ((955-bed hospital)
p ) alone: 21,000-70,000
,
,
acute care bed-days.
Attribution Study:
Do emergency
g y physicians
p y
recognize
g
these
presentations?
Attribution Study:
Do emergency physicians recognize these
presentations?
i ?
We learned that:
•
Emergency physicians attribute ~37% of presentations deemed
medication-related to a non medication-related cause Æ in over
1/3 of cases we are uncertain or miss the ADE.
•
This figure is the same regardless of how you define an
ADE(adverse drug reactions, nonadherence, dosing problems).
•
Greater patient age was associated with lack of attribution.
Provider factors were not associated. Limited ability to study this
because of sample size.
Attribution Study:
Extrapolated
p
to myself:
y
– I see ~2,600 patients in the ED annually.
– I see 315 patients with an ADE.
– I correctly attribute ~196, and miss the ADE or am
uncertain in ~119
119.
I do around 25% of my shifts during business hours
hours,
so only 25% of these patients stand a chance to see
our ED pharmacist – and most will never…
Do we have a problem?
To add insult to injury:
• Aging
g g patient
p
population
p p
• Increasing medication use for chemoprevention
p
of new drugs
g
• Development
ÆThe problem is here to stay.
ÆNational and Provincial focus on:
Æ Medication reconciliation
Æ Reduction in drug
drug-related
related morbidity
Æ Better evaluation of real-world effectiveness/safety of drugs.
What could solutions looks like?
• Pharmacists to screen all ED patients?
• We cannot get people to work
harder/faster/more.
• How can you deliver an improved service
within the fiscal and manpower constraints
we face?
• Can we be smarter?
Can we use existing resources
better or improve one area and
disinvest from another?
Risk Stratification
using Clinical Decision Rules.
For other problems
C-spine injuries
Subarachnoid hemorrhage
Knee/Ankle Rules
Head injuries
Chest Pain
Syncope
The rules can be implemented using existing
resource because they are based on
information already collected during the
clinical encounter.
Clinical Decision Rule Derivation:
Can we derive a clinical decision rule that
accurately stratifies ED patients into high and
low-risk groups so that we can limit the
pharamcist resources required to capture a
high proportion of events.
– >95%
– >90%
Clinicians in
the ED miss
over 1/3 of
ADEs – they do
not know who
these patients
are!
Clinical Decision Rule Derivation:
• Factors that associated with ADEs with good interrater
t agreement:
t
presence of comorbid conditions
Recent medication changes
arrival by ambulance
recent hospital admission
use of >3 medications
antibiotic use
age
triage acuity
renal failure
• Clinical Decision Rule (CDR) that identifies highrisk pts with high sensitivity and low specificity:
• improves the pick
pick-up
up rate of ADEs: 62% Æ >90%.
>90%
• reduces the need to have a pharmacist evaluate each
patient: 100% Æ 26%.
Adverse Drug Reaction Rule
• We can reliably detect the low-risk
low risk
patients and exclude them from
screening – no lethal or severe
events missed in derivation set.
• Refinements may lead to greater
specificity (age vs
hypertensives/diuretics).
hypertensives/diuretics)
Adverse Drug Reaction Rule
Extrapolated
p
to our situation:
• The pharmacists do not need to screen
75 000 pts to increase the recognition
75,000
rate of these events.
• They can ignore all low risk patients.
patients
• They evaluate high-risk patients only, in
whom an investment is more likely to
pay off. They now screen ~28% of
patients.
BC HSPO Proposal
• Patient-focused fundingg model in BC.
• Purpose: to procure services using a funding
model that will encourage improvement and
create a competitive environment.
• Patient-Focused Funding Model to incent:
•
•
•
•
Quality
Efficiency
Access
Volume
Proposal
• To implement
p
a two-step
pp
process in the ED:
• Initial triage screen of patients using the clinical
decision rule Æ results in high/low risk flag.
• Pharmacists perform medication reconciliation and
ADE screening on all high-risk patients.
• Document all ADEs found on a provincial platform
th t can b
that
be accessed
d iin th
the community
it
(PharmaNet).
• Communicates ADEs found back to community and
treating MDs
MDs.
• Incorporate continuous quality improvement and
data quality check.
Other Benefits
• Work with PharmaNet & Excelleris to enable the data
platform for ADE documentation in the ED.
Æ Enhanced communication throughout healthcare
sectors.
Æ Patients with severe ADEs are referred into EDs to
access care, 85% of ADEs are moderate and severe
(don’tt want to capture mild ADEs).
(don
Æ Concept of ADE surveillance regionally
Æ Data capture on ADEs: allows us to propose
better prescribing practices and evaluate them to
see what makes a difference.
Future Directions
Post-market surveillance
• “…monitor[ing] the safety, efficacy and quality of health
products after they have reached the marketplace.”
• “This
“Thi … iis essential
ti l tto maintaining
i t i i th
the b
balance
l
b
between
t
the health benefits and risks posed by all health products.”
ED Based ADE Surveillance
ED-Based
• Aggregate feedback to prescribers about practices.
• Aggregate
gg g feedback about new drugs.
g
• Better use of drugs and better use of our $$.
Lessons
• Dauntingg problem
p
• Making people work harder, faster to achieve
better quality is not likely feasible.
• There are efficiencies that can be gained, and
there are areas where we will notice an impact
probably more than others.
Questions?
Thank you!