neurological conditions across the continuum of care
TRANSCRIPT
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Neurological Conditions Across the Continuum of Care: Using interRAI Instruments to Respond to the Needs of Special Populations
John P. Hirdes, PhD
Ontario Home Care Research & Knowledge Exchange Chair
Professor, School of Public Health and Health Systems
University of Waterloo
Twitter: @interRAI_Hirdes
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Innovations in Data, Evidence, and Applications for
Persons with Neurological Conditions
(ideas PNC)
• PI: Hirdes
• Co-PIs: Maxwell & Jetté
• Co-Is: Berg, Bronskill, Clarke,
Colantonio, Doran, Heckman,
Hogan, Kergoat, Marrie, Martin,
Mitchell, Patten, Postuma,
Pringsheim, Zygun
• Staff: Boyd, Caldarelli, Chen,
Curtin-Telegdi, Danila, Foebel,
Hsueh, Koreck, Vu
• Students: Cheng, Cooper,
Costa, Mathias, Neufeld,
Turcotte
• Consultants: Poss
Twitter: @interRAI_Hirdes
Funding: Public Health Agency of Canada
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Project Activities
A) Estimate prevalence of the neurological conditions across the
continuum of care
B) Develop detailed clinical profile of persons with 10 neurological
conditions in different care settings
C) Evaluate applicability of current interRAI care planning
approaches to persons with neurological conditions
D) Examine access to and utilization of health and social services by
persons with neurological conditions
E) Examine costs of care associated with neurological conditions
including both formal and informal sources
F) Identify approaches for performance measurement and develop
recommendations on reporting and risk adjustment methods
G) Examine experience of informal caregivers providing support,
including extent and type of care provided
Twitter: @interRAI_Hirdes
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Things designed for the “general”
population may not work so well for
“special” populations
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Implementation & Testing of interRAI Instruments:
A Unique Opportunity to Study Neurological Conditions Across the
Continuum of Care
RAI 2.0 RAI-HC RAI-MH interRAI CMH interRAI ESP interRAI PC interRAI ID interRAI ED/AC interRAI CA interRAI CHA interRAI AL interRAI SQoL
DB
Twitter: @interRAI_Hirdes
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Clinical Profiles of Persons with Neurological
Conditions in the Continuum of Care
Twitter: @interRAI_Hirdes
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About the Data
• CIHI’s interRAI data holdings • Complex Continuing Care (CCC) from CCRS - Apr 1996 to Mar 2011
• Nursing Homes/Long Term Care (LTC) from CCRS - Jun 2003 to Mar 2011
• Home Care Long Stay (HC) from OACCAC and HCRS - Jan 2002 to Dec 2010
• Mental Health (MH) from OMHRS - Oct 2005 to Mar 2010 (Ontario only)
• Linked data sets • CIHI RAI data linked to DAD, NACRS, NRS 2003-10
• ICES RAI data linked to DAD, ODB, physician billing (Ontario only)
• RAI-HC data linked to OACCAC admin database (Ontario only)
Twitter: @interRAI_Hirdes
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Sample sizes of the neurological conditions
within each care settings CCC LTC MH HC Long Stay
Non PHAC Neuro/Non Stroke 86,218 51,540 111,182 348,167
Any PHAC neurological conditions 47,945 119,687 3,576 142,090
ADRD 34,573 106,364 533 107,563
Epilepsy 8,061 9,132 1,372 3,324
Parkinson’s 6,372 12,132 771 20,388
Brain Injury 2,217 1,848 368 7,352
Multiple Sclerosis 1,981 2,409 268 6,412
Cerebral Palsy 600 1,021 184 2,369
ALS 367 240 7 1,561
Huntington's 158 413 139 185
Muscular Dystrophy 50 61 31 982
Spinal Cord Injury 19 23 16 2,208
Twitter: @interRAI_Hirdes
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Demographics
and Clinical Characteristics
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0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
CCC LTC MH HC
Age distribution of persons with brain injury by Care Setting, Ontario, 2010
age >85
age 75-85
age 65-75
age <65
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Cross-sector trajectories of change
Cognition and ADL
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HC Long Stay – ADL Self-performance Hierarchy
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 (independent) 1-2 3-4 5-6 (most impaired)
Twitter: @interRAI_Hirdes
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MH – ADL Self-performance Hierarchy
SCI, ALS groups n<30, thus not included
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 (independent) 1-2 3-4 5-6 (most impaired)
Twitter: @interRAI_Hirdes
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LTC - ADL Self-performance Hierarchy
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 (independent) 1-2 3-4 5-6 (most impaired)
SCI group n<30, thus not included
Twitter: @interRAI_Hirdes
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Use of interRAI Clinical Assessment
Protocols (CAPs) among Persons with
Neurological Conditions
Twitter: @interRAI_Hirdes
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MH – Falls CAP (Note: Only two levels shown - multiple falls not captured prior to 2009)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Triggered (Levels 1&2)
Not triggered
SCI, ALS groups n<30, thus not included
Twitter: @interRAI_Hirdes
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LTC – Falls CAP
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Triggered- High Risk Falls
Triggered- Med Risk Falls
Not triggered
SCI group n<30, thus not included
Twitter: @interRAI_Hirdes
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HC Long Stay – Falls CAP
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Triggered - High Risk Falls
Triggered - Med Risk Falls
Not triggered
Twitter: @interRAI_Hirdes
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Rates of falls at follow-up by baseline Fall CAP, home care client
prevalence samples (YT, Northern BC, WRHA, ON, NS) 2007 & 2010
0102030405060708090
Non P
HA
C n
eu
ro/n
on
stro
ke
SC
I
CP MD AD
RD
MS Stro
ke
He
ad
Tra
um
a
Epile
psy
ALS
Park
inso
ns
Huntin
gto
ns
%F
ell
at
Fo
llo
w-u
p
Not Triggered Medium Risk High Risk
Twitter: @interRAI_Hirdes
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www.interrai.org
Rates of falls at follow-up by baseline Fall CAP, home care client
prevalence samples (YT, Northern BC, WRHA, ON, NS) 2007 & 2010
0102030405060708090
Non P
HA
C n
eu
ro/n
on
stro
ke
SC
I
CP MD AD
RD
MS Stro
ke
He
ad
Tra
um
a
Epile
psy
ALS
Park
inso
ns
Huntin
gto
ns
%F
ell
at
Fo
llo
w-u
p
Not Triggered Medium Risk High Risk
Twitter: @interRAI_Hirdes
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www.interrai.org
Rates of falls at follow-up by baseline Fall CAP, home care client
prevalence samples (YT, Northern BC, WRHA, ON, NS) 2007 & 2010
0102030405060708090
Non P
HA
C n
eu
ro/n
on
stro
ke
SC
I
CP MD AD
RD
MS Stro
ke
He
ad
Tra
um
a
Epile
psy
ALS
Park
inso
ns
Huntin
gto
ns
%F
ell
at
Fo
llo
w-u
p
Not Triggered Medium Risk High Risk
Twitter: @interRAI_Hirdes
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Validation of Scales and Algorithms for
Persons with Neurological Conditions
MAPLe and CHESS
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Distribution of the Method for Assigning Priority Levels (MAPLe),
home care client prevalence samples (YT, Northern BC, WRHA, ON, NS)
2007 & 2010
0%
20%
40%
60%
80%
100%
Non PHACneuro/non
stroke
MS Stroke Parkinsons HeadTrauma
ADRD
Very High
High
Moderate
Mild
Low
Twitter: @interRAI_Hirdes
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Association of caregiver distress with MAPLe level, home care client
prevalence samples (YT, Northern BC, WRHA, ON, NS) 2007 & 2010
0
10
20
30
40
50
60
Low Mild Moderate High Very High
%C
lien
ts w
ith
Dis
tressed
C
are
giv
er
MAPLe Level
Non PHAC neuro/non stroke MS Stroke Parkinsons Head Trauma ADRD
Twitter: @interRAI_Hirdes
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Survival Analysis of Nursing Home Admissions by MAPLe
Level among Home Care Clients with Parkinson’s Disease,
ON&WRHA
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CHESS Scale
• Considers
• Changes in ADL and cognition
• Signs and symptoms (e.g., shortness of breath, weight loss)
• End-stage disease
• 0 – stable to 5 – highly unstable health
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6-month Survival among CCC Hospital
Patients with MS, by CHESS Score
Twitter: @interRAI_Hirdes
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Resource Use Among Persons with
Neurological Conditions
Twitter: @interRAI_Hirdes
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Formal and Informal Care Costs per Week
by Neurological Condition, Ontario 2009
0
100
200
300
400
Co
st/
week
Twitter: @interRAI_Hirdes
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• Data from interRAI assessments in Canada provide a
unique opportunity to understand the experience of special
populations across the continuum of care
• Getting diagnostic information complete and correct is
important
• interRAI instruments WORK as clinical tools for
• General population
• Special populations
Twitter: @interRAI_Hirdes
Concluding Comments
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• Sign up for interRAI newlsetter
• Visit interRAI Canada website
• interRAICanada.uwaterloo.ca
Twitter: @interRAI_Hirdes
Where can you get more info?
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Thank you!
Questions? Comments?
Twitter: @interRAI_Hirdes