PwC An evidence-based overview of indicators for return-to-work John Walsh

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Transcript PwC An evidence-based overview of indicators for return-to-work John Walsh

An evidence-based overview of
indicators for return-to-work
John Walsh
PwC
The role of KPIs in the continuous
improvement cycle
Scheme Redesign
Return to Work
performance &
KPIs
CONTINUOUS
IMPROVEMENT
CYCLE
Interventions
Impacts & KPIs
(e.g. improved capacity to RTW)
KPIs are the evidence base to inform the continuous improvement cycle
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A role for efficient risk profiling in the
continuous improvement cycle?
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Example of what is possible – predictive modeling
of outcome for workers compensation
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What have we learned from this?
Statistical estimation is far more predictive than (even educated)
gut feel !!
Predictability improves as the claim develops (eg payment
history)
However much variance is still unexplained
“Known” predictors of claim outcome are often either:
– poor predictors, eg injury severity, bodily location
– or probably spurious, eg occupation, culture
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“Better” predictors are likely to be soft data, currently not
collected
Several key questions underpin the
development of a framework of predictive
indicators
Main Question:
What are the next steps to
develop and utilise these
indicators?
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What are the current issues and factors to
consider when determining RTW indicators?
How should RTW be defined and measured?
What are the modifiable impediments
influencing RTW?
How can we measure return to work and
associated modifiable factors?
The universe of possible influencing factors is
very large, but not all of them are modifiable
All Factors Affecting
Return to Work
NonModifiable
Factors
First RTW
Factors
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Modifiable
Factors
Factors that affect
both First and
Durable RTW
Durable RTW
Factors
The universe of factors influencing RTW
is very large
Injured Worker – Health,
Psychological & Social
Characteristics
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Physical impairment
Psychological impairment – pain,
fear, anxiety, stress
Pre/post injury income
Social factors
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Injury Characteristics
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Injury nature, location &
circumstances
Type of treatment
Completion of rehabilitation program
Injury history – chronic, acute
Employer Characteristics
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Size of employer (wages,
employees)
Job category (desk or labour)
Ergonomic risk of work
Financial rewards of job
Job tenure
Workplace environment
Preventative interventions
Return to Work Outcomes
Injured Worker – Attitudes &
Perceptions
Self Perceptions:
· Of injury and impairment
· Of functional ability
· Ability to recover
· Ability to RTW
· Pain
· Fear of re-injury
· Depression, anxiety and stress
Perceptions of Employer, Workplace &
System:
· Job satisfaction
· Supervisor’s first response to injury
· Support offered to employees
· Attitudes and support of co-workers
· Suitability of duties,
accommodations and modified work
· Satisfaction with insurer
· Satisfaction with care provider
Unmodifiable factors Modifiable factors
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First RTW, Durable RTW
Employment characteristics at RTW
Recurrent injury, work absence and
claim
Health & psychological
Outcomes
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Employee attitudes to RTW
Physical and psychological
functioning
Capacity to RTW
Social functioning outcomes
Job satisfaction
Employer support
Employer – Attitudes &
Perceptions
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Injured worker willingness to RTW
Availability of workplace
accommodations
Capabilities to supply suitable and/
or modified duties
Claim characteristics
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Previous claim history
Date of injury
Date of claim
Workers compensation benefits type
Demographic characteristics
Rehabilitation & Medical Care
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Treatment type
Timely treatment
Rehabilitation completion
Treatment location
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Age
Gender
Level of pre-employment education
Martial status
Language spoken at home
Union membership
Interrelationship between dimensions:
they are part of an intersecting ‘whole’
Modifiable dimensions and Durable RTW
Physical
Workplace Injury
·
Fitness to return to work
Injury nature, location & severity
·
Capacity to return
to work
20
%
·
·
Psychosocial
20
%
Health and
psychological
functioning
Durable
Durable
RTW
RTW
Psychological
%
Employer
attitudes to
RTW
20
%
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Willingness to
return to work
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Flow of information
between key
stakeholders
Extent of cooperation
Attitudes of stakeholders
towards RTW
20
%
·
Management
of the
relationships
between key
stakeholders
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Willingness to provide
suitable duties
Management support
and encouragement of
injured workers
General health functioning
Psychological health and
functioning
Job satisfaction
Pain
·
·
Worker perception of
employer attitudes to
injured worker and
suitable duties
Worker expectations of
recovery
Worker motivation to RTW
The life cycle of claim reflects both positive and
negative influences – sometimes we call these
interventions!
Positive RTW experience
Interventions/experiences
Injury &
Claim
4 weeks
3 months
6 months
Negative RTW experience
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Time
From the evidence, we should be measuring
very different dimensions to those currently
measured
Routine data currently collected:
•
Mostly include demographics, injury characteristics, workplace
characteristics and claim characteristics
Key Dimensions which should be measured if we are to
understand and influence the life cycle of a claim:
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•
First return to work
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Durable return to work
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Capacity to RTW
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Health and psychological functioning
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Willingness to RTW
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Perception of employer attitudes to RTW
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Relationships between key stakeholders
Using the evidence base if it existed: Scheme objectives inputs – impacts and outcomes could/ must be systematically
linked
WorkCover
RTW objective
RTW Inputs/
Interventions
RTW Impacts
(out of scope)
RTW
outcomes
Capacity to RTW
Example: Policy
Example:
Case management
A timely, safe and durable
return to work for injured
workers
Example:
Employer interventions
Example:
Insurer interventions
Health & psychological
functioning
First RTW
Willingness to RTW
Durable RTW
Employer attitudes to
RTW
Management of the
relationships between
key stakeholders
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Approach 1 – Extending and improving current
data collection systems
• Immediate improvements in existing routine/ administrative data
collections could be achieved, to test and demonstrate the gains in
terms of better predictive modelling (eg risk profiling, statistical case
estimation)
Eg Claims and Policy data bases
 Mandating new variables
 Recommendations to improving the quality of insurer data on key variables
Eg National Return to Work Monitor (e.g. Campbell Research &
Consulting)
 Modify existing and include additional variables
 Improve survey design and sampling
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Approach 2 – Collecting new data
Recognising that outcome in workers compensation reflects the
inter-relationships between key stakeholders suggests several
supplementary data collection strategies to understand their
impact:
Eg - Employer, insurer and provider surveys
Eg- multidimensional case studies using the injury event as
the point of sampling over the course of recovery from Return
to Work exploring over time:
 willingness to RTW
 capacity to RTW
 attitudes to RTW
 relationships between stakeholders
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 attitudes towards interventions
A complication ………. importance of work
health will be more than ever

Longer working life
 Any addition to retirement age would give a material one-off increase in
workers compensation costs (and liabilities?) depending on benefit
structure.
 Would possibly increase nature & condition and latent claims

Increased incidence of chronic disease in the workplace
 Complex and chronic disease prevalence (eg mental illness, diabetes,
arthritis, cardiac disease, respiratory disease) is increasing, and
increases with advancing age. The workplace (and workers
compensation) will need to deal with these
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Work health (cont)

Fitness for duty issues (could go two ways)
 With change in physical and mental capacity, exposure to disease (eg
stress, chemical exposure) and injury (eg musculo-skeletal strain) in
some jobs may functionally increase (ie people don’t cope as well,
exposure goes on for longer ‘working lifetime’)
 Alternatively, exposure may actually decrease if people start to move to
other work areas through earlier retraining etc (eg construction field job vs
desk job), particularly in the face of “smart” strategies to target markets
and skills shortages (eg ‘grey tellers’ for banks to better match the
population of customers

Retaining skilled workers
 The Finland experience several decades ago is interesting in this regard.
The aging bump and the early retirement of affluent societies hit there
some time ago, with a consequent looming huge skills gap
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The case study approach – holistic analysis
examining the injury event from all
perspectives
Employee
Insurer
Injury
Case
Manager
Employer
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Provider
Conclusions
Effect of claim streaming and risk profiling is limited – because of
the data available
A new approach is difficult – mainly because of the paradigm we
are working in
But…. The paradigm needs revisiting if we are to move forward
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