Getting Older! Choose your

Province wisely

Dr. Paul Hébert, M.D.

Dr. John Hirdes, Ph.D.

Acknowledgements

• Paul Hebert, MD FCAHS

• Jon Hirdes PhD FCAHS

• Anne Morinville PhD

• Andrew Costa, PhD

• George Heckman, MD

• Richard Cook, PhD

• Jonathan Chen, MMSc

• Veronica Jung, Bmath

• Stella Wiredu, RN PhD (c)

• Han Ting Wang MD MSc

• Collaborators • Funding• Canadian Frailty Network

• Ontario Ministry of Health and Long-term

Care

• Canadian Institute for Health Information

Imagine this person

• You assess an 82 year old man who lives at home. Spouse says he needs help with all his

ADL's.

• He has delegated major financial issues to his son. He manages daily bills, writes cheques,

but more difficulty with writing and fine motor grasp .

• He is SOB but says it might be related to his anxiety.

• Progressive weakness in legs over 4 years. He has an exercise regime but does not follow

it but no motivation .

• Determined to maintain independence; takes 2 hours to get dressed with assistance from

wife. He declines assistance with personal care . Wife supervises showers because she is

afraid of him falling.

• Recent diagnosis of Parkinson's, appears malnourished, high anxiety, depressed, currently

being seen by Geriatric Day hospital.

• He has multiple falls in the past few months.

Some months later

• At 3 am, you are asked to see this same 85 year old man from a nursing home

who fell from bed, has a low blood pressure and has difficulty breathing…No

additional information

• On initial inspection, blood pressure is 60/40, heart rate 130, and respiratory rate

35. He is semi-conscious, and screaming incoherently. Looks very thin and

emaciated

• He has bruises over his left eye, right flank and side of left leg. Leg is turned

outward

Outcome – dies in ICU after

2 weeks of careVasoactive drugs to support heart and

blood pressureIntravenous fluids to increase blood pressure

Mechanical ventilation to

support breathing

Continuous dialysis to support kidneys

Balloon pump to

support blood pressure

Blood

Frailty in the ICU

• Prospective study of 421 patients over the age

of 50 years from 6 Alberta hospitals

• Prevalence of Frailty was 32%

ICU and Frailty

• Hospital mortality 32% vs 16%;

• aOR=1.81 (95% CI of 1.09 to 3.01)

• Discharge newly dependent 71% vs 52%

• aOR=2.25 (95% CI of 1.03 to 4.89)

Some facts

• 60% of elderly Canadians die in hospital, not at

home

• In long term care, mortality 30 to 50% per year

• 40% to 50% of elder care in ER

• Severity of illness (Changes in Health, End-

Stage disease, and Signs and Symptoms scale

– CHESS scale) predicts mortality

Global vision

Implement program of research throughout the continuum of care to

develop a common and standardised approach in order to best

know how to:

– Evaluate at-risk/vulnerable/frail patients

– Elaborate care plans

– Target the right patients for interventions

– Measure/control care quality

– Allocate ressources efficiently

– Do research on the healthcare system (continuous

improvement of care and practices)

Home dependant

Home independant

Doctor’s office

Other hospitals

Nursing Home

Home dependant

Home independant

Dead

Long time hospital

Nursing home

Outcomes/ indicatorsOutcomes/ indicators

Outcomes/indicatorsOutcomes/ indicators

Measuring along the

continuum of care

ValuePatient-centered outcomes

Evaluation systems used in geriatric

medicine

Cognition

Mobility/falls

Mood

Self care

Continence

Nutrition

Pressure ulcer

MMSE/CAM

TUG / Berg

GDS

Barthel

?

MNA

Waterlow

FILLER

Observations

Cognition

Mood

Communication

Mobility

Self care

IADL

Continence

Falls

Pain

Social support

Formal services

Screeners

Derivative

scales

Risk

Stratification

Clinical

Protocols

Clinical domains(presence & risk)

First generationassessment

Second generation assessment

Third generation: same approach across sectors

Prof. Len Gray

All tools

have a

common

core

Common language: interRAI

assessments

CHESS: Changes in Health, End-Stage Disease and

Signs and Symptoms of medical problems

• Looks at: Changes (decision making, ADL status), health condition

(vomiting, peripheral edema, dyspnea), end-stage disease, weight loss,

fluids (decrease, input/output, insufficient), dehydration, food (decrease)

Range: 0–5

• 0 = No health instability

• 1 = Minimal health instability

• 2 = Low health instability

• 3 = Moderate health instability

• 4 = High health instability

• 5 = Very high health instability

Multistate Transition Markov Models

Home care

AT

ADMISSION

CHESS = 3-5Long-term care facility

CHESS

1,2

Hospital

DiedCHESS

3+

OtherHome

CHESS

0

Care

settingCHESS

1,2

Hospital

DiedCHESS

3+

OtherLong-term care

CHESS

0

Care

setting

Effect of: XControlling for:• Age• Sex• Marital status• Day of stay at ax• Facility size• Province• ADL Hierarchy• Cognitive

Performance• Physician visits• COPD• Pneumonia

• Diabetes• Arthritis• Renal failure• Urinary tract infection• Alz & Related

Dementia• Heart Failure• Cancer• Depression• Advanced directives

DNR• Advanced directives

DNH

Baseline characteristics of home care and long

term care residents (BC, AL, ON)

Home Care

Long-term Care

CHESS

Diagnoses at admission

Pe

rcen

tage o

f re

sid

en

ts

N=162,409

N=254,664

Higher CHESS scores at baseline in home care

Overall, diagnoses similar except for dementia and depression

Status 90 days post admission in Long term care in Ontario, Alberta & BC

from 2010-2015

Modeling changes and outcomes

from many states at once

What explains these differences?

Advanced Directives; Do they affect transfer rates?Adjusted odds ratios from nursing homes in Ontario, BC & Alberta (ref: Ontario)

Transitions at follow-up (T2)

Remained in Nursing Home

CHESS ScoreAdmitted to

HospitalDied

Discharged

Other Setting

Discharged

Home0 1-2 3+

Do Not Hospitalize (ref=Not Present)

CHESS Score

at baseline

(T1)

0 -- 1.04

(1.02-1.07)

1.10

(1.03-1.19)

0.67

(0.65-0.69)

1.48

(1.38-1.58)

ns ns

1-2 0.92

(0.90-0.95)

-- 1.07

(1.03-1.12)

0.63

(0.61-0.65)

1.46

(1.40-1.52)

ns ns

3+ 0.76

(0.68-0.85)

0.81

(0.76-0.87)

-- 0.47

(0.43-0.52)

1.48

(1.37-1.60)

ns ns

Do Not Resuscitate (ref=Not Present)

CHESS Score

at baseline

(T1)

0 -- 1.08

(1.05-1.11)

1.32

(1.21-1.45)

0.90

(0.87-0.92)

1.36

(1.25-1.49)

0.82

(0.72-0.94)

0.58

(0.51-0.65)

1-2 0.91

(0.88-0.94)

-- 1.19

(1.12-1.26)

0.82

(0.80-0.85)

1.38

(1.30-1.47)

0.85

(0.74-0.98)

0.55

(0.48-0.63)

3+ 0.75

(0.64-0.86)

0.85

(0.77-0.95)

-- 0.63

(0.57-0.71)

ns ns 0.53

(0.32-0.87)

Transitions at follow-up (T2)

Remained in Nursing Home

CHESS ScoreAdmitted to

HospitalDied

Discharged

Other Setting

Discharged

Home0 1-2 3+

Do Not Hospitalize (ref=Not Present)

CHESS Score

at baseline

(T1)

0 -- 1.04

(1.02-1.07)

1.10

(1.03-1.19)

0.67

(0.65-0.69)

1.48

(1.38-1.58)

ns ns

1-2 0.92

(0.90-0.95)

-- 1.07

(1.03-1.12)

0.63

(0.61-0.65)

1.46

(1.40-1.52)

ns ns

3+ 0.76

(0.68-0.85)

0.81

(0.76-0.87)

-- 0.47

(0.43-0.52)

1.48

(1.37-1.60)

ns ns

Do Not Resuscitate (ref=Not Present)

CHESS Score

at baseline

(T1)

0 -- 1.08

(1.05-1.11)

1.32

(1.21-1.45)

0.90

(0.87-0.92)

1.36

(1.25-1.49)

0.82

(0.72-0.94)

0.58

(0.51-0.65)

1-2 0.91

(0.88-0.94)

-- 1.19

(1.12-1.26)

0.82

(0.80-0.85)

1.38

(1.30-1.47)

0.85

(0.74-0.98)

0.55

(0.48-0.63)

3+ 0.75

(0.64-0.86)

0.85

(0.77-0.95)

-- 0.63

(0.57-0.71)

ns ns 0.53

(0.32-0.87)

Advanced Directives; Do they affect transfer rates?Adjusted odds ratios from nursing homes in Ontario, BC & Alberta (ref: Ontario)

Adjusted Odds Ratios by LHIN (ref=Toronto)

for 90-day Hospitalization from long term

care, CHESS=0

Adjusted Odds Ratios by LHIN (ref=Toronto)

for 90-day Hospitalization from long term

care, CHESS=1,2

Adjusted Odds Ratios by LHIN (ref=Toronto)

for 90-day Hospitalization from long term

care, CHESS=3+

Adjusted Odds Ratios by LHIN (ref=Toronto)

for 90-day Mortality from long term care,

CHESS=0

Adjusted Odds Ratios by LHIN (ref=Toronto)

for 90-day Mortality from long term care,

CHESS=1,2

Adjusted Odds Ratios by LHIN (ref=Toronto)

for 90-day Mortality from long term care,

CHESS=3+

Clinical conclusions

• Ontario transfers long term care residents to hospital 2

times more than other provinces

• Other provinces transfers 2 times more from home care

than Ontario

• Variations persist independent of disease or health

status

• Toronto care patterns explain much of Ontario effect

• Advance directives also important

Conclusions

• Now possible to link data across continuum of care

• Missing – primary care and hospital assessments of risk

across system

• interRAI assessments powerful when linked to other data

sources

• CIHI is a wonderful partner

• Analytic approach is very robust, but static and fixed in time

• Registry trial not yet possible – But let us dream of the day

Conclusions

• Are we transferring the right people from long

term care to hospital?

• Organization of care and available resources

have major effect on patient care

• Small changes in transfer rates will have major

impact on hospital resources.