by Mark Tochtenhagen
and Mark VerMeulen
August 1, 2007
Use benchmarking to improve your safety and loss control
programs
Do you cringe when your boss asks how your safety and loss
control efforts compare to the market? How truly effective is
your return-to-work program? Do you pay more or less than other
companies to treat injuries and supplement lost wages?
Sure, you have a mountain of historical loss information, but it
reflects just one perspective — your situation. And that alone
won’t give you the answers to these questions. Without solid
comparative data, you’ll never know just how your programs
measure up.
The American Heritage Dictionary defines “benchmarking” as
the ability to measure a rival’s product according to
specified standards in order to compare it with and improve
one’s own product. In this case, the product is your loss
prevention and control program.
Until recently, questions about the real effectiveness of safety
and loss control programs could only be answered by the actuary
— so secretive was “the data” that access was often kept
even from company executives. (We are, after all, speaking about
how those actuaries determine your risk; and hence, your
insurance premiums.)
Today there are many affordable products companies can license
to provide such analysis. When you integrate benchmarking tools
into your loss control information system, you’ll be able to:
1. Obtain real-time, on-demand answers to your questions;
2. Identify trends; and
3. Trigger proactive management before problem cases become
outliers.
How benchmarking works
The key to the solution requires that you start by thinking like
an actuary.
First, categorize your injury/illness data using ICD9 codes.
ICD9 codes are published by the World Health Organization and
are used in the medical and insurance communities to numerically
classify injuries and illnesses. These codes provide much
greater detail than the text descriptions used in your injury
reporting systems.
For example, ICD9 codes distinguish between open and closed
fractures, simple sprains versus disc herniations, etc. This
detail is very important when analyzing outcomes. You can
license the ICD9 data for a nominal fee and you don’t need to
be a clinician to make sense of the codes. But, chances are that
your third-party administrator (TPA) or carrier already uses
ICD9 codes, so simply request them with your monthly claim loss
run reports.
Second, correlate the ICD9 code with the outcome data. The
Official Disability Guidelines (ODG), published by the Work Loss
Data Institute, compiles claims data from over 3.5 million
cases. Using ODG, you’ll know the expected number of days lost
and medical/indemnity costs for each claim in your spreadsheet.
Drop in some formulas to compute averages and you’ll know just
how you measure up with respect to national norms.
Your first milestone
Realize that the only thing you’ve accomplished so far is
measuring the effectiveness of your program. Drawing actionable
conclusions from this stage of the analysis may be more a result
of luck than effective management. Even if you outsource all
claims administration, there are internal, external and data
factors that influence your outcome. For instance, your service
company cannot perform to expectations if there is significant
lag time in reporting or if the quality of care provided by
practioneers is sub par, or if your data contains outliers.
The real key to successful benchmarking is to use this data to
improve your program. You’ve laid the groundwork. Now to take
action, you’ll need to analyze a host of other variables
before determining root cause. This is where integrating
external ODG guidelines into your loss control information
system pays off.
Scrub the data
Whether you have 100 claims or 100,000, due diligence demands
that you examine outliers. Outliers can simply be bad data or
significant indicators. Let’s examine how to distinguish the
difference.
One of the biggest sources of outliers involves the ICD9 code
assigned to the claim. A single ICD9 may be adequate for the
majority of your claims, but many injuries involve multiple body
parts. When the guideline is properly integrated into your
information system, it should be able to process multiple ICD9
codes, picking the condition that drives the greatest duration
of disability and factors in the cost of all conditions.
The information system should also factor in surgeries that are
not ICD9-based. For example, a lumbar sprain/strain (ICD9 =
847.2) has an expected return to work outcome of 17 days. But if
that claim required lower back surgery, the return to work
increases to 142 days. Other factors such as diabetes or a heart
condition may warrant exclusion of the case altogether. Lastly,
consider age-adjusting the outcome. Younger workers ages 18 to
24 typically recover in half the time of workers ages 55 to 64.
Reclassification of injuries, exclusion of outliers and
age-adjustment alone could completely change your evaluation of
the data. When the guidelines are integrated into your
information system, these adjustments can be performed
automatically.
Identifying trends
Now that you’ve cleansed your data, you can begin to look for
trends. The number of comparisons you create depends on the data
in your system. A natural starting point is to compare the
outcomes among your facilities. This sheds light on geographic
differences and vendor performance. Next, compare department
performance within and among facilities. If there is no
significant difference among facilities, but like departments
show differing outcomes, you may have identified a problem.
In each case, pay attention to the guideline — if the outlier
department is at or near the norm, you could infer there is no
problem as the other department is outperforming the guideline.
Many users report being “shocked” when this analysis reveals
a wide variation in outcomes among plants or even hospitals that
are all part of the same organization.
If you are capturing provider information on the case level you
can easily benchmark provider outcomes. Identify the top ten
best and worst outcomes by ICD9, then filter by provider. Your
results will pinpoint those providers who excel, meet the
guideline, or perform poorly when treating specific injuries and
illnesses.
Trigger proactive management
The holy grail of a solid benchmarking program is to use the
outcome data to trigger proactive management. This is the best
way to improve your program. Share your data with plant managers
and supervisors, and demonstrate how your analysis grades
certain facilities, departments, and work processes.
Ask providers for an expected return-to-work date from the onset
of treatment. And if that falls outside the guideline, start
asking questions. Set up triggers to flag cases containing
problematic ICD9s so you can steer employees to those providers
with good track records.
Finally, never forget that the best way to improve your loss
control program is prevent injuries from occurring. If you’ve
uncovered trends relative to work processes or work experience,
share the results with loss prevention and implement the
appropriate training programs.
Driving results
The beauty with this type of benchmarking is that you are
dealing with averages — something everyone understands. There
are a tremendous number of dynamics that inhibit your efforts
such as union rules, management support, etc. However, no one
can dispute that your efforts are aligned with the best
interests of the company and its employees. Once you demonstrate
that a department, a work process, or provider consistently
delivers poor outcomes with respect to what is considered
normal, behaviors will change.
The key is to deliver your message with an emphasis on improving
the results rather than disciplining offenders. This is the
cornerstone to continuous improvement.
SIDEBAR:
Benchmarking rules of thumb
• No sample should contain fewer than 12 records. You cannot
draw adequate conclusions about what you consider a problem area
if you’re analyzing three injuries.
• Don’t over-rely on the published guidelines. They do not
factor in outcomes relative to your industry or cost
fluctuations in your geographic area.
• Look for consistent, repetitive patterns.
• Keep it simple, always comparing apples to apples.
- Mark
Tochtenhagen and Mark
VerMeulen
Mark Tochtenhagen and
Mark VerMeulen are co-founders and architects of PureSafety’s
Prognos™ software for incident, injury, illness and absence
management. Both authors can be reached at (614) 777-4636 or via
email at mark.tochtenhagen@puresafety.com
and mark.vermeulen@puresafety.com.