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Partnerships |
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American
Psychological Association
National
Council for Community Behavioral Healthcare
Association
for Ambulatory Behavioral Healthcare |
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Advisors |
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| BHL
forms scientific advisory boards for specific functions. By clicking
below you can see an example of the group assembled by BHL to collaborate
on a NIMH grant to develop a National Practice Research Network (PRN).
The PRN will bridge the gap between our industry leading naturalistic
outcome database, clinicians, and academic researchers across the country.
20 leading scientists serve on the advisory board for the PRN.
Click to see the team. |
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BHL
is an industry leader in minimizing or eliminating data errors.
Case Mix Variables and Risk Adjustment
Many factors outside of therapy itself influence how well clients do
over the course of treatment. Case-mix variables include any condition
outside the control of the provider that might influence the outcome
of treatment. Case-mix variables, which include things such as comorbid
medical conditions, stressful life events, and employment status, ought
to be measured and then statistically controlled in outcome comparisons
Example:
A clinician profiled against his peers has one case in which a client's
child dies during the course of treatment. In another case, the clinician
has a client with a long history of failed treatments (many
hospitalizations
and previous therapists). In both cases, treatment is likely to be
difficult and the non-risk-adjusted outcome of the clinicians' entire
caseloads could look deceptively poor. The measurement of case-mix
variables would capture these salient points of treatment and appropriately
adjust
the clinicians' outcomes when compared to other providers' outcomes.
The failure
to measure appropriate case-mix variables leads to unfair comparisons of
providers. The unfair comparisons may not reflect
differences in effectiveness or skill, but rather significant variations
in the populations treated. Education level, medical status, income level,
and other variables tend to influence the outcome of therapy, and yet most
outcome measurement systems fail to take these variables into account.
No system can measure and control for all possible case-mix variables,
but a good system has to control for the conditions that account for the
most variation in outcome
We know that certain demographic differences can impact the outcome
of treatment. Employment status, co-morbid medical conditions, and stressful
events are among the most important variables that have been shown to
affect outcomes. BHL is committed to continually refining and improving
our risk adjustment system.
Sensitivity
to Change & Floor and Ceiling
Effects
There are other significant problems built into the use of short questionnaires--
sensitivity to change and floor and ceiling effects. Short questionnaires
are less sensitive to change. In striving to strike a balance between
brevity and sensitivity to change, the BHL system offers distinct tools
of varying lengths that have all demonstrated exemplary sensitivity to
change for that phase of treatment.
Furthermore,
most short outcome tools have serious floor and/or ceiling effects.
The use of instruments with floor and ceiling effects is comparable
to using a basal body thermometer that only measures up to 102 degrees
to study the temperature in the desert. On a hot summer day one might
conclude that the temperature never changes and stays at 102 degrees.
Concluding that a client is not improving, when in fact, they are indeed
making clinically significant changes not detectable by the measurement
tool, can lead to poor administrative, and clinical decisions. Many
state projects using brief questionnaires are disintegrating because
of this most serious limitation.
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