Short-term Mortality after Hospital Discharge...Short-Term Mortality after Hospital Discharge...
Transcript of Short-term Mortality after Hospital Discharge...Short-Term Mortality after Hospital Discharge...
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?