Short-term Mortality after Hospital Discharge A Closer Look at Cardiovascular & Cardiometabolic Diseases

Presented by Sarah Singh PhD candidate Epidemiology and Biostatistics Western University

Canadian Research Data Center Network National Policy Challenge 2019 Statistics Canada, Ottawa June 11th, 2019

Presentation Layout

▪ Background

▪ Research Questions

▪ Data & Methodology

▪ Results

▪ Policy Recommendations

▪ Limitations

▪ Conclusions

Background

Definitions and Context

▪ Cardiometabolic diseases (CMD) – A group of metabolic disorders including insulin resistance, impaired glucose tolerance, dyslipidemia, hypertension, and central adiposity, that increase the risk of CVD.

▪ Cardiovascular diseases (CVD) – Diseases of the heart and blood vessels

▪ People with CMD are 2X more likely to die from coronary heart disease and 3X more likely to have a heart attack or stroke than those who do not have the syndrome1

Heart attack or Stroke

High Blood

Pressure

Obesity

Diabetes

Burden of disease in Canada

▪ CMD and CVD together represent a leading cause of death and hospitalization in Canada

▪ High impact on Canadians2-4:

▪ 12 million Canadians experience obesity

▪ 2 million Canadians suffer from diabetes

▪ 2.5 million Canadians diagnosed with heart disease

▪ Most costly disease in Canada:

▪ >11% of total Canadian cost of illness5

▪ >$21.2 billion in direct and indirect costs5

▪ Disease burden ongoing for half a century and persists today due to increase in risk factors, widening health inequalities and aging population

Short-Term Mortality after Hospital Discharge

▪ Mortality linked to hospitalization commonly used as quality of care indicator by cardiac care organizations (Canadian Cardiovascular Society, American College of Cardiology/American Heart Association and European Society of Cardiology6-8)

▪ Informs quality improvement and cost control

▪ High rates → poor quality of care, poor hospital performance, lack of coordination of care, ineffective medical interventions, poor community health care

Short-Term Mortality after Hospital Discharge

▪ High-quality healthcare system for all Canadians (universality) is a top policy priority which can only be adequately addressed by examining the full range of deficiencies in quality of care across all levels of healthcare.

▪ Few studies exploring outcome; requires linked data sets (mortality and hospital data)

• Family physician

• Ambulatory care

• Hospital

• Specialist care

• Long term care

• Rehabilitation

Research Questions

Research Questions

1. Do short-term mortality rates after hospital discharge vary over time?

2. Do short-term mortality rates after hospital discharge vary by geographic regions?

3. How can policy impact short-term mortality rates after hospital discharge ?

Two-Phase Project

•Rationale & Interpretation: Indicator for health care quality and system performance in a geographic area

•Policy-Implications: Identify and learn from high-performing areas, identify underperforming areas for support and quality improvement initiatives

Phase I

Ecological

(Population-level) analysis

•Rationale & Interpretation: Indicator for poor outcomes or quality of care in an individual and the identification of individual-level factors for this risk

•Policy-Implications: Identification of high-risk patients may lead to the development or refinement of standards of care

Phase II

Individual-level analysis

Data & Methodology

Study Design ▪ Study Design Longitudinal ecological study

▪ Time period 2000-2012

▪ Ecological unit Census division (CD)

▪ Aim #1 Examine 12-year national trends in short-term mortality rates after hospital discharge

▪ Aim #2 Examine geographical variations in short-term mortality rates after hospital discharge across census divisions (CDs) in Canada

▪ Aim #3 a) Identify target CDs for policy action and,

b) Determine whether CD-level risk factors (possible policy interventions) are associated with short-term mortality rates

▪ Inclusion criteria Consistent census divisions with population > 40 and > 5 events per year

▪ Exclusion criteria Quebec data not included

Data sources

DAD

Discharge Abstract Database 2000-2015

Administrative, Clinical and Demographic data on hospital

discharges

CVSDD

Canadian Vital Statistics Death Database 2000-2012

Demographic and medical cause of of death data

CCHS

Canadian Community Health Survey 2000-2012

Self-reported social, health and demographic data on Canadians

Outcome variable

▪ 30-day cardiovascular mortality rate after hospital discharge

▪ 30-day

▪ Death that occurs within 30 days of being discharged from an acute care facility

▪ Cardiovascular mortality rate

▪ Mortality based on cause of death as ‘Major Cardiovascular Diseases’ including hypertensive heart disease, ischemic heart disease, atherosclerotic heart disease, cerebrovascular diseases (ICD-10 I00-I78, ICD-9 390-434,436-448) obtained from CVSDD

▪ Calculated as age standardized rate of mortality nationally and per CD

▪ After hospital discharge

▪ Hospitalization for cardiometabolic disorders including diabetes mellitus, hypertension, hypercholesterolemia, heart failure, angina, myocardial infarction, coronary artery disease, stroke (event-based)

▪ Based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and The Canadian Enhancement of The International Classification of Diseases, Tenth Revision (ICD-10-CA) obtained from DAD

CD-level risk factor variables

▪ Selection based on common risk factors known to influence CVD

▪ Data from CCHS (2000-2012)

▪ Calculated as the proportion of the population within a CD with characteristic

Traditional CVD Risk Factors

• Obesity

• Smoking

• Poor Diet

• No physical activity

Demographic Factors

• Elderly (over 65 years)

• Female

• White

Socioeconomic Factors

• Urban

• Living below poverty line

• Unemployed

• Uneducated

• Food insecure

Statistical analysis

▪ Age standardized rates (ASRs) calculated via direct standardization using five-year age groups, for each census division and each year. (Standard population is the 2011 Canadian population).

▪ Aim #1: Linear regression models used to test national trends

▪ Aim #2: Geographic variation examined as ASRs across CDs; represented as a) average ASR over time per CD (mean of ASRs across all years 2000 to 2012) and, b) absolute difference in ASRs (difference between ASR in 2012 and ASR in 2000)

▪ Aim #3: Ordinal logistic regression models were used to assess univariate and multivariate associations between short-term mortality rates and risk factors, adjusted for CD population density and province, continuous time variable included

▪ SAS version 9.4 (SAS Institute Inc, Canada) software used

Results

Population ▪ Approximately 293 CDs throughout Canada

▪ After exclusions for Quebec (98) and low counts in provinces (Yukon, NW Territories esp.), 130 CDs included in this study

Province CDs per province CDs included in study

NL 11 10

PE 3 2

NS 18 14

NB 15 15

ON 49 46

MB 23 1

SK 18 11

AL 19 13

BC 29 18

Total 185 130

Do short-term mortality rates vary over time?

▪ Relatively stable rates (no significant trend over time, p=0.62)

▪ Rates increase only slightly from 146.5 in 2000 to 150.4 in 2012, peaking at 202.4 in 2006

Title: National trends in short-term mortality rates over time

period (2000-2012)

Do short-term mortality rates vary by geographic regions?

Title: Map of Average Short-Term Mortality Rates across time period (2000-2012) in CDs across Canada

No data available

0-485.7

485.7-756.7

756.7-1222.7

1222.7-2121.5

BC

PE

NS

AL SK MB ON

NB

NL

How can policy impact short-term mortality rates? Identify target CDs for policy action

Title: Quadrant plot of average short-term mortality rates compared to differences in rates per CD, 2000-2012

Improved rates, low average

Q4

Worsened rates, high average

Q1

Improved rates, high average

Q3

Worsened rates, low average

Q2 Census

Division

(CD)

Note: horizontal

axis crosses

vertical axis at

national average

ASR across

Canada

How can policy impact short-term mortality rates? Identify target CDs for policy action

Title: Quadrant plot of average short-term mortality rates compared to differences in rates per CD, 2000-2012

(magnified)

Improved rates, low average

Q4

Worsened rates, high average

Q1

Improved rates, high average

Q3

Worsened rates, low average

Q2 Census

Division

(CD)

Note: horizontal

axis crosses

vertical axis at

national average

ASR across

Canada

How can policy impact short-term mortality rates? Identify target CDs for policy action

Title: Bar Graph of CD Quadrant Status by Province, 2000-2012

Q4= Improved rates,

low average

Q3= Improved rates, high

average

Q2= Worsened rates, low

average

Q1= Worsened rates, high

average

How can policy impact short-term mortality rates? Determine whether CD risk factors (possible policy interventions) are associated with short-term mortality rates

Traditional CVD Risk

Factors

• Obesity

• Smoking

• Poor Diet

• No physical activity

Demographic Factors

• Elderly (over 65 years)

• Female

• White

Socioeconomic Factors

• Urban

• Living below poverty line

• Unemployed

• Uneducated

• Food insecure

How can policy impact short-term mortality rates? Determine whether CD risk factors (possible policy interventions) are associated with short-term mortality rates

Traditional CVD

Risk Factors

• Obesity

• Smoking

• Poor Diet

• No physical activity

Demographic Factors

• Elderly (over 65 years)

• Female

• White

Socioeconomic Factors

• Urban

• Living below poverty line

• Unemployed

• Uneducated

• Food insecure

Quadrant status of CD

Not significantly associated

Policy Recommendations

Policy recommendations

▪ Policies to improve CVD outcomes should be focused on characteristics of healthcare system and tailored to the region

Issue Recommendation

1. Quality of care Mandatory reporting on a range of indicators by all health institutions

2. Hospital resources Reconsider the global budget funding schemes for hospitals

3. Coordination of care Measures to improve access to patient information at all health care levels (primary, secondary, tertiary care)

4. Medical procedures Physician funding scheme that does not incentivize/penalize certain procedures over others

5. Community care Optimization of health care services within the community (e.g. increased use of allied care in rehabilitation services)

Limitations

Limitations

▪ Data on individuals who have agreed to share/link their data which may not be representative of the entire population → selection bias

▪ Low counts not released; exclusion of CDs may be non-random → selection bias

▪ Data weights unavailable → may be addressed in the future

▪ No causation can be implied

▪ CDs may have changed boundaries over the years however, most stable unit after provinces

▪ Future analyses should account for the effects of comorbidity (Charlson Comorbidity Index), disease severity and, length of stay

▪ Cautionary note: Issue of ecological fallacy should be avoided in interpretation

Conclusions

Conclusions

▪ Trends in short-term mortality after discharge have not changed over time

▪ Geographic variations in short-term mortality after discharge exist across CDs (and within provinces)

▪ Policies at the national, provincial, and regional levels are needed to develop targeted interventions that:

▪ Reduce mortality rates over time

▪ Reduce unnecessary geographic variations

▪ Enhance the overall quality of care for cardiovascular health

▪ Improve cardiovascular disease outcomes in the population

References

1. Ohio State University Wexner Medical Center. (2019, February 4). Study links protein, clusterin, to cardiac and metabolic diseases. ScienceDaily. Retrieved June 6, 2019 from www.sciencedaily.com/releases/2019/02/190204085942.htm

2. Riediger, N. D., & Clara, I. (2011). Prevalence of metabolic syndrome in the Canadian adult population. Canadian Medical Association Journal, 183(15), E1127-E1134.

3. Leiter, L. A., Fitchett, D. H., Gilbert, R. E., Gupta, M., Mancini, G. J., McFarlane, P. A., ... & Camelon, K. (2011). Cardiometabolic risk in Canada: a detailed analysis and position paper by the cardiometabolic risk working group. Canadian Journal of Cardiology, 27(2), e1-e33.

4. Manuel, D. G., Leung, M., Nguyen, K., Tanuseputro, P., & Johansen, H. (2003). Burden of cardiovascular disease in Canada. Canadian Journal of Cardiology, 19(9), 997-1004.

5. Tarride, J. E., Lim, M., DesMeules, M., Luo, W., Burke, N., O’Reilly, D., ... & Goeree, R. (2009). A review of the cost of cardiovascular disease. Canadian Journal of Cardiology, 25(6), e195-e202.

6. Grace, S. L., Poirier, P., Norris, C. M., Oakes, G. H., Somanader, D. S., & Suskin, N. (2014). Pan-Canadian development of cardiac rehabilitation and secondary prevention quality indicators. Canadian Journal of Cardiology, 30(8), 945-948.

7. Thomas, R. J., Balady, G., Banka, G., Beckie, T. M., Chiu, J., Gokak, S., ... & Pack, Q. (2018). 2018 ACC/AHA clinical performance and quality measures for cardiac rehabilitation: a report of the American College of Cardiology/American Heart Association Task Force on performance measures. Journal of the American College of Cardiology, 71(16), 1814-1837.

8. Schiele, F., Gale, C. P., Bonnefoy, E., Capuano, F., Claeys, M. J., Danchin, N., ... & Quinn, T. (2017). Quality indicators for acute myocardial infarction: A position paper of the Acute Cardiovascular Care Association. European Heart Journal: Acute Cardiovascular Care, 6(1), 34-59.

Acknowlegements

▪ Dr. Stephanie Frisbee

Assistant Professor, Western University

▪ Dr. Piotr Wilk

Graduate Chair, Western University

▪ Dr. Saverio Stranges

Department Chair, Western University

▪ Western RDC

▪ Professor Wasem Alsabbagh

School of Pharmacy, University of Waterloo

Thank you Questions?