Critical Illness and Homelessness · 2019-09-27 · Critical Illness and Homelessness Jan O...

Critical Illness and Homelessness

Jan O Friedrich, MD DPhilAssociate Professor of Medicine, University of Toronto

Medical Director, MSICU

St. Michael’s Hospital, Toronto, Canada

Critical Care Canada Forum – 2 October 2017

Conflicts of Interest

• None to report

Introduction• Homelessness is a serious social and public

health issue• 1.5 million in USA and 150,000 in Canada

• Comprehensive survey in Toronto in one night identified

5,232 homeless individuals (19/10,000 population)

– marginalized population who frequently present to

hospital in advanced disease states with serious and

potentially life-threatening illness

• Higher rates of infectious diseases, mental illness,

substance abuse, chronic diseases, injuries

• Associated with earlier onset of chronic health problems

which frequently are under treated• Refs: 2012 Annual Homeless Assessment Report, US Dept Housing & Urban Development.

Homeless Shelters and Beds/Housing/Indicators of Well Being in Canada, Human Resources

and Skills Development Canada. 2013 Street Needs Assessment, City of Toronto.

Introduction• Homeless that are hospitalized are

– Younger than non-homeless patients

– More frequently admitted for medical or psychiatric

vs surgical conditions

– Hospitalized for longer as having no residence can

delay timely discharge which leads to higher costs

• However, the course of illness and use of health

care resources of homeless patients admitted to

ICU is largely unknown

Published Literature

• Systematic review to July 2012 screening

2653 citations for studies of critically-ill

homeless patients

– No studies in which more than 50% of

participants were homeless

– Only 5 studies addressed critical illness related

issues in which any participants were homeless

– Ref: Chant, Wang, Burns, dos Santos, Hwang, Friedrich, Smith. Inten

Care Med 2014; 40: 123-5

Published Literature

• Refs: 1) Shariatzadeh et al, Medicine 2005; 84:147. 2) Rioseco et al, Rev Med Chile

2004, 132:588. 3) Frencher et al, J Trauma Inj Infect Crit Care 2010; 69: S191.

4) Norris et al, Chest 2005; 127:2180. 5) Glassberg et al, Chest 2008; 134:719.

Topic Study

Type

No (%)

Home-

less

No (%)

Critical

Ill

Main Findings

Bacteremic

Pneumonia

Prospect.

Cohort

73

(57%)

5 (4%) Homeless have 27-fold increase in

bacterial pneumococcal pneumonia

Bacteremic

Pneumonia

Retrospect.

Cohort

3 (7%) N/R Homelessness not mortality predictor in

bacterial pneumococcal pneumonia

Trauma Retrospec.

Database

326,073

(21%)

310,784

(20%)

Higher age/gender adjusted injury risk for

certain mechanisms of injury

Treatment

Preferences

Survey 229

(100%)

0 (0%) Homeless want more aggressive care than

either physicians or COPD pts on oxygen

Research

Consent

Retrospec.

Database

67

(13%)

N/R Less likely to be enrolled acute lung injury

trial due to lack of SDM

Reasons that homelessness in critical

illness is understudied• Represent “vulnerable” patient cohort, and while Ethics and Review

Boards seek to prevent exploitation, this protection may exclude them

from participating in studies

• By virtue of critical illness, they typically require substitute decision

maker (SDM) but often are estranged from family

– Publically appointed SDM typically do not provide consent for research studies

• May be excluded from studies requiring follow up owing to concerns

regarding their ability to attend future appointments

• Stigma associated with homelessness may make it less attractive for

researchers or funding agencies

• Concentrated within urban centres necessitating use of specific study

designs or collaborative research structures– Ref: Chant, Wang, Burns, dos Santos, Hwang, Friedrich, Smith. Inten Care Med 2014; 40: 123-5

Two More Detailed Examinations of Homeless

Patients Admitted to ICU Recently Published

• Propensity-Matched Cohort Study (Paris, France)

– 421 homeless compared to 9,353 non-homeless

• Matched 1:4 age, sex, admission diagnosis and date

– Focused on lengths of stay and outcomes

• Case-Control Study (Toronto, Canada)

– 63 pairs: matched 1:1 age, sex, admission ICU and date

– Detailed clinical course, treatments and end of life

decision making

Ref: Bigé et al, CCM 2015; 43:1246. Smith ... Friedrich, PLoS ONE 2017; 12:e0179207

Propensity-Matched Cohort Study (Paris, France)

• Consecutive admissions July 2000-Dec 2012

• 18-bed MSICU, tertiary care university hospital,

Paris, France (674 hospital beds)

•

– 421 homeless v 9,353 non-homeless

– Male: 89% v 57% p<0.001

– Median Age: 49 v 62 p<0.001

– Readmission: 12% v 7% p<0.001

• Ref: Bigé N, Hejblum G, Baudel JL, Carron A, Chevalier S, Pichereau C, Maury E,

Guidet B. CCM 2015; 43:1246


• 421 homeless v 9,353 non-homeless

– HTN: 5% v 22%

– Diabetes: 6% v 12%

– Heart Disease: 10% v 20%

– Cancer: 5% v 16%

– CKD: 1% v 4%

– Obesity: 0% v 3%

– Mental Illness: 14% v 16%

– Substance Use: 7% v 2%

– Alcoholism: 50% v 8%

– Cirrhosis: 14% v 6%• Ref: Bigé et al, CCM 2015; 43:1246


• 421 homeless v 9,353 non-homeless

– SAPS II: 37 v 37 p=n.s.

– No. Organ Supports similar p=0.49

• Mech Vent 44% v 37% p=0.003

– Resp Failure 33% v 34% p=n.s.

– Sepsis 6% v 8% p=n.s.

– Coma 34% v 21% p<0.001

• Non-EtOH

acute intox. 25% v 42%

• EtOH 34% v 13%

• Seizure 43% v 26%• Ref: Bigé N, Hejblum G, Baudel JL, Carron A, Chevalier S, Pichereau C, Maury E, Guidet B.

CCM 2015; 43:1246


• Matched Homeless Non-Homeless p

• ICU Mortality 19% 18% 0.62

• Hosp Mortality 21% 21% 0.95

• Mean ICU LoS 6.5 d 5.6 d 0.035

• Mean Hosp LoS 19 d 15 d 0.002

• Survivor Disposition

– Home, street 68% 60% 0.006

– Other hospital/rehab 32% 40%

• Ref: Bigé et al, CCM 2015; 43:1246

Case-Control Study (Toronto, Canada)

• Any of 4 ICUs at St. Michael’s Hospital

– MSICU [medical-surgical] – 24 beds

– NTICU [neurosurgical-trauma] – 19 beds

– CVICU [cardiac/vascular surgery] – 15 beds

– CICU [cardiac] – 10 beds

• tertiary care university hospital – 462 hospital beds

• 63 randomly-selected homeless patients

• admitted 2009 – 2011

• Ref: Smith OM, Chant C, Burns KEA, Kaur M, Ashraf S, DosSantos CC, Hwang SW, Friedrich JO.

PLoS ONE 2017; 12(6):e0179207


• 63 homeless patients

• matched to 63 non-homeless patients by

– Admit Year: all

• 79% admitted within 60d of each other

– Age: all except 2 patients

• One was 1 year younger and the other was 1 year older

– Sex: all

– Admitting ICU: all except one patient

• MSICU v TNICU

• Ref: Smith OM, Chant C, Burns KEA, Kaur M, Ashraf S, DosSantos CC, Hwang SW, Friedrich JO.

PLoS ONE 2017; 12(6):e0179207

Case-Control Study (Toronto, Canada) • Homeless (n=63) Non-Homeless (n=63)

• Age (y) 48 ±12, 22-71 48 ±12, 22-71

• Male 90% 90% p-value

• Weight (kg) 77 82 0.08

• Comorbidities

– HTN 16% 40% 0.005

– Diabetes 8% 8% 1.00

– COPD 11% 5% 0.32

– Cancer 3% 10% 0.27

– Depression 17% 11% 0.45

– Schizophrenia 8% 2% 0.21

– Severe Liver Disease 1% 0% 1.00

• Ref: Smith ... Friedrich. PLoS ONE 2017; 12:e0179207


• Prescription Meds 48% 67% 0.047

– Anti-seizure 14% 3% 0.054

– Thyroid 0% 8% 0.058

• Substance Use

– Alcohol 70% 17% <0.001

– Illicit Drugs 46% 8% <0.001

– Smoking 40% 21% 0.03

• SDM at admission 38% 83% <0.001

• Ref: Smith ... Friedrich. PLoS ONE 2017; 12:e0179207


• Tox Screen Done 75% 38% <0.001

• Tox Screen +ve 72% 71% 1.00

• Toxin Detected

– Alcohol 41% 10% <0.001

– Benzodiazepines 27% 16% 0.19

– Opioid 10% 3% 0.27

– Cannaboid 10% 3% 0.27

– Cocaine 8% 2% 0.21

– Acetominophen 10% 0% 0.03• Ref: Smith ... Friedrich. PLoS ONE 2017; 12:e0179207


• Arrival via EMS 87% 65% 0.006

• Admitted to ICU from 0.004

– Emergency Room 76% 56%

– Operating Room 13% 22%

– Hospital Ward 8% 9%

– Referring Hospital 0% 13%

• APACHE II 18 ±8 16 ±9 0.11

• MV on admission 56% 43% 0.21

• Ref: Smith ... Friedrich JO. PLoS ONE 2017; 12:e0179207


Heart Rate Mean BPGlascow Coma Scale

0

2

4

6

8

10

12

14

ICU

Day 1

ICU

Day 3

ICU

Day 7

Homeless Non-Homeless

p=0.11

p<0.01

*

p=0.04

*

0

20

40

60

80

100

120

140

ICU

Day

1

ICU

Day

3

ICU

Day

7

ICU

Day

1

ICU

Day

3

ICU

Day

7

p=0.02

*

p=0.09

p=0.01

*

(No Differences: P/F Ratio, No. on Vasopressors, No. Transfused,

Creatinine, Platelets, Bilirubin)


• Specialist Consults 3.5 ±2.5 4.2 ±2.6 0.10

• Diagnostic Tests

– CT 54% 48% 0.59

– Echocardiogram 33% 32% 1.00

– Ultrasound 19% 14% 0.63

– MRI 13% 11% 1.00

• Invasive Procedures

– Bronchoscopy 14% 11% 0.79

– Angiography 6% 14% 0.24

– Lumbar Puncture 5% 3% 1.00

– Upper Endoscopy 2% 6% 0.36



• Dialysis 8% 10% 0.99

• Blood transfusion 22% 22% 1.00

• Parental Nutrition 2% 2% 1.00

• Medications

– Sedatives 95% 90% 0.49

– Thiamine 71% 21% <0.001

– Nicotine Replacement 38% 14% 0.004

– Corticosteroids 22% 27% 0.68



• Microbiology Testing 52% 41% 0.28

• Any Positive Culture 51% 37% 0.15

– Blood 14% 10% 0.54

– Respiratory 38% 21% <0.05

(S.pneumo, MRSA, MSSA, H.flu, E.coli)

– Urinary 10% 11% 1.00

• Antibiotics 59% 59% 1.00

– Days, median [IQR] 5 [3-9] 3 [2-6] 0.06



• Vasoactive 27% 19% 0.40

– Days, median [IQR] 3 [2-6] 2 [1-2] 0.06

• Ventilator Days 1 [0-5] 0.5 [0-2] 0.052

• ICU days 6 ±8 4 ±5 0.04

– Median [IQR] 3 [2-8] 2 [1-5] 0.07

• Hospital days 19 ±25 13 ±13 0.07

– Median [IQR] 11 [5-24] 8 [5-19] 0.17



• Hospital Mortality 18 (27%) 5 (8%) 0.005

• Process 1.00

– Withdrawal 11/18 (61%) 3/5 (60%)

– Non-resuscitated arrest 5/18 (28%) 1/5 (20%)

– No limitations 2/18 (11%) 1/5 (20%)

• End-of-Life Decision Making 0.15

– Family involved 9/18 (50%) 5/5 (100%)

– Family not involved 8/18 (44%)

– Known wishes 1/18 (6%)

• Survivor Disposition 0.20

– Home/shelter/jail 35/45 (78%) 38/58 (66%)

– Hospital/Long-Term Care 10/45 (22%) 20/58 (34%)


Summary – Paris & Toronto Detailed Studies• Pre-Admission

– Mean age ~50 years old

– 90% Male

– Lower prevalence many comorbidities (e.g. HTN)

• Possibly due to younger age, but since also present after

matching by age, likely also due to under diagnosis

– Higher alcohol and substance abuse history

• At Admission

– More emergent vs elective (operative) admissions

– Similar acuity of illness

– More mechanical ventilation

• Due to coma (EtOH, seizures) rather than respiratory failure

Ref: Bigé CCM 2015; 43:1246. Smith...Friedrich, PLoS ONE 2017; 12:e0179207

Summary – Paris & Toronto Detailed Studies

• During Admission

– Similar intensity investigations and treatments

• More thiamine and more nicotine replacement

– Lower GCS up to at least ICU Day 7-?substance use

• Direct effect on level of consciousness

• Sedatives required to treat withdrawal symptoms

– More respiratory cultures positive pathogenic

organisms

• Trend to more antibiotics

– Trends to longer duration of ventilation and

vasopressors


Summary – Paris & Toronto Detailed Studies

• At Discharge

– Longer ICU and hospital lengths of stay

– Lower proportion discharged to rehabilitation or other

hospitals

– Effect on mortality unclear

• Paris – similar mortality

• Toronto – higher mortality (small numbers)

– Higher mortality not due to higher withdrawal of life

support


Challenges/Limitations• Identifying patients as homeless within studies of ICU

patients is typically challenging

– Often identified as low socioeconomic status, poor,

disadvantaged, or experiencing social deprivation without

referencing housing status

• Accurately identifying patients as homeless within

hospital databases is similarly challenging

– Both the Paris and Toronto studies discussed these difficulties

• Homelessness is a dynamic state and patients may be

homeless at and for different time periods

– Binary classification based on index hospitalization may be too

simplistic

– E.g. chronically homeless patients likely have different

outcomes than the transiently homeless patients

Summary

• Homeless patients admitted to ICU are difficult to study

resulting in limited published data

• Acuity of illness at ICU admission, and intensity of

treatment were similar

– At least within the context of public health care systems

• Overall, outcomes appear to be somewhat worse than

matched controls

• Additional research in other health care settings to

validate the findings of these single-centre studies are

needed with an aim of trying to develop strategies that

improve outcomes in this vulnerable population

The End

• Thank you for your attention

• Questions?

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