Key Statistical Measures (KSM)

Key Statistical Measures (KSM) :
A Financial and Statistical Portrait of Workers Compensation Boards in Canada
With :  Gylles Binet
 Guillaume Baril
 Ray Outair
Wednesday, October 6th, 2010
For a symposium in
such an old city,
a little bit of history
appears necessary
Where do KSMs come from…?
-10 000 BC
1759
1867
1990 2010
Before 1990
• All kinds of different Financial Statements
• Financing concepts : Unclear
• Difficulty to share information
• Employers doing business in many Canadian jurisdictions
1991 – The Revolution
• A new generation of WCB executives with a financial background
• Request for proposal in 1991 and report in 1992
• Goal: To develop a set of standards to report financial and statistical data
1992 to 1998 – The Gestation
• Consultant’s proposition for statistics and ratios : 34 indicators in 6 categories
• Categories : New Claims (6), Recurrent Claims (2), Active Claims (4), Status Change (6), Duration/Severity (5), Financial Statistics (11) • Animated discussions between CFOs and their technicians for a few years
1999 to 2004 – The Agitation
• January 1999 : First publication with 14 KSMs
• Creation of a dedicated Working Group – one member per jurisdiction
• Development of KSMs and IRs : we go from 14 to 34 measures
• 2003 : Introducing the AWCBC website as a mean for KSM and preface publication
2005 to 2010 – The Consolidation
• A single new KSM
• Refinement and cleaning up of definitions
• Education : Introducing « KSM 101 »
• Modernization of the KSM database management
Perspectives
Remarkable and unique accomplishment
Challenges :
–
–
–
–
Improving database management Make data extraction more user‐friendly
Educating the users
Maintain and adapt the database to evolving needs, keep it healthy (avoid anorexia and obesity), keep focusing on fundamentals
Pitfalls : Scattering, Anecdotic Key Statistical Measures 101
Introduction
• 40 financial and statistical measures
• 12 WCBs and total for Canada
• Different types of measures
• Examples
• Purpose
Objectives
• Improve understanding of the KSMs :
–Usefulness
–Pertinence
–Limits
• Learn to interpret the data adequately
Outline
•
•
•
•
•
•
Preface
Key Statistical Measures
Indicator Ratios
Definitions
Footnotes
Breakdown of Provisional Average Assessment Rates
Preface
• Outline main structural differences between Boards
• May provide useful information to explain gaps between different jurisdictions
Preface
• Contains : – Percentage of earnings used for calculation of wage‐loss benefits
– Waiting Periods
– Whether employers needs to pay for day of injury or period thereafter
– CPP offset
– Maximum Assessable Earnings
– Provisional Average Assessment Rates
Preface
2009
NB
NS
PE
Waiting Period
3 days
2 days
3 days
Impact : • Number/Frequency of Claims
• Average Duration of Claims
• Ratios like Cost per Claims
Key Statistical Measures (KSM)
• 40 KSMs published annually
• Presented in order of publication
• Certain measures should be analysed in parallel with other measures to be significant
Key Statistical Measures
MB
NB
ON
QC
KSM 24.2
Percentage of Lost‐Time Claims Receiving Wage‐loss 0.77 %
3.78 %
3.45 %
2.41 %
Benefits at the end of the 6th year after the accident year
KSM 21*
Injury Frequency (per 100 workers of assessable 4.08
1.36
1.45
2.32
employers)
PRODUCT*
KSM 24.2 0.051
0.031
Number of Claims on WageLoss Benefits after 6 Years
* Per 100
Number of Lost-time
Claims
workers
0.050
KSM
21
0.056
Number of Lost-Time
Claims
Number of Workers
Key Statistical Measures (KSM)
• Group 1 : Financial Data
• Group 2 : Claim Data
• Group 3 : Self‐Insured Employers
Group 1 – Financial Data
• Expressed in dollars
• Come from Financial Statement
• Definitions comply with accounting standards
Category
Source
1 : Basic Accounting Data
• Statement of Operations
• Balance Sheet
2 : Other Accounting and Financial Data
• Notes to the Financial Statement
• Annual Report
3 : Current Year Financial Data
• Not always in Annual Reports
• Many jurisdictions include them
Group 2 – Claim Data
• Characteristics of the claims
• Definitions are peculiar to AWCBC
Category
Characteristics
4 : Injury Frequency
Measure frequency of claims and scope of coverage
5 : Severity
Measure the severity of claims
6 : Operational Measures
Measure certain administrative delays
Group 3 – Self‐Insured Employers
• A variety of measures for self‐insured employers
• All are a parallel of another measure for assessable employers
Category
7 : Self‐Insured Employers
Characteristics
• Answer a specific need of information
• Many are not available Indicator Ratios (IR)
• 10 Indicator Ratios
A
B
• Connects 2 or more KSMs
• Helps to interpret the data
• Provides an additional perspective and makes data more comparable
Indicator Ratios (IR)
Example : Indicator Ratio #2 for 2008
AB
KSM 4.1
($ 000’s)
BC
NL
Current Year Benefit Costs Incurred for Assessable $705,616 $913,626
$87,723
$14,022
Employers
KSM 12
Assessable Payroll for Assessable Employers
$73,602
$71,777
$5,075
($ millions)
IR2
PE
$1,266
Current Year Benefit Costs Incurred per $100 of $0.96
$1.27
$1.73
$1.11
Assessable Payroll
KSM and IR Definitions
• Based on nationally accepted definitions • May be different than statistics published in Annual Reports
• Intent of Measure / Definition / Calculation
Footnotes
• Specific situations
• Useful to interpret data correctly
• Additional/complementary information
• Many footnotes indicate that the basis of comparison may be different
Breakdown of the Provisional Average Assessment Rate
• Importance of Average Rate
• Breakdown of Average Rate :
–Outlines the most important financial needs
–Allows for a fair comparison of the rate setting process in each jurisdiction
Breakdown of the Provisional Average Assessment Rate ‐ 2009
NS
ON
QC
SK
YT
Compensation Costs
1.72
1.01
1.41
1.24
1.72
Administration Costs
0.43
0.26
0.30
0.43
0.91
Occupational Health and Safety
0.09
0.09
0.15
Amortization of surplus and deficits
0.36
0.72
0.01
0.00
0.03
Others
0.05
0.19
0.23 ‐0.01
0.18
Total Average Assessment Rate
2.65
2.26
2.10
3.00
0.16
1.66
Roundup of KSM 101
• 40 KSMs and 10 ratios to describe a system, make comparisons and monitor trends
• KSMs should be analysed in parallel with others
• Preface / Definitions / Footnotes
• Breakdown of Average Assessment Rate
AWCBC Online Data Community AWCBC Online Data Community
What is the AWCBC Online Data Community (AOC)
 A BI toolset that users can leverage for reporting of jurisdictional and inter‐ jurisdictional data and analysis.
• A suite of tools that can be used to raise the level of the NWISP coding standard for the purpose of coding quality and consistency.
• A framework that supports robust data auditing, intelligent quality assurance mechanisms, intelligent notification services and sustainable code standard interdependencies. AWCBC Online Data Community
What is the objective:
• To develop successful policies and programs to reduce workplace injuries, diseases and fatalities.
• To reduce cost drivers.
• To identify priority and emerging issues.
• To improve coding consistency.
• To provide opportunity for evidence‐based discussions.
AWCBC Online Data Community
AWCBC Online Data Community
Demo
Data Extraction - AOC
AWCBC Online Data Community
The AWCBC Online Data Community will help you with:
• Data analysis. • Reducing workplace injuries, diseases and fatalities.
• Improving coding quality and consistency.
Questions?
Gylles Binet
Email: gylles.binet@csst.qc.ca
Phone: (418) 266‐4949 ext. 5997
Guillaume Baril
Email: guillaume.baril@csst.qc.ca
Phone: (418) 266‐4949 ext. 2942
Ray Outair
Email: nwisp@awcbc.org
Phone: (905) 542‐3633