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Finding Sources of Treatment Variation
By Brent A. Metfessel MD, MS, CMP™ (Hon)
If a medical provider or healthcare facility is found to have a significant variance from the norm on a measure, such as economic cost, drill-down analysis is important to find the reason behind the variance.
Episodes of care case-mix adjustment is naturally suited to this kind of analysis, but other population-based groupers such as DCGs also allow drill-down if the clinical categories that are precursors to the assignment of a risk score are used.
The Concept
The conceptual idea behind drill-down is to obtain greater and greater detail on an area of interest. Thus, if a provider is found to have a high overall cost variance or performance ratio, a user can select the provider and drill-down into emergency room usage, hospitalization frequency, types of illnesses seen, or procedures performed.
Case-mix is useful even for the more detailed reports since if, for example, ER use or the utilization of specified procedures is not adjusted for illness burden the “my patients are sicker” argument can easily hold.
However, if the procedures are related to illness classes, providers can be compared to their peers on procedure use for that illness class.
Example:
Dr. Jones is a family practitioner who had a high patient load from a single large health plan. These patients under his care had a total of 450 episodes over a two-year period. His case-mix adjusted performance ratio was 2.28 and cost variance was $157,400. Dr. Jones requested a drill-down analysis to determine why his practice patterns showed such a high variance from the norm.
One area that the health plan data analysts found had high variance were patients he saw with tendonitis of the lower extremity. He saw 30 episodes of care for this condition, having a total performance ratio for the illness class of 6.0 and a cost variance of $25,300.
On further drill-down, the analyst found that the major cost center included the frequency of MRI scans of the lower extremity for the tendonitis patients. His scan rate was 0.4, which means an average of 4 out of 10 episodes received scans, making a total of 12 scans in all. His peers of the same specialty showed 0.1 scans per episode of tendonitis of the lower extremity.
Dr. Jones showed a performance ratio of 3.0 and a cost variance of $10,800. On learning this information, Dr. Jones decided to alter his referral patterns so that his scan rate was brought closer to the norm.
Conclusion
What has been your experience, if any, with drill down analysis; helpful quality improvement adjunct or physician bane?
Related Information Sources:
Practice Management: http://www.springerpub.com/prod.aspx?prod_id=23759
Financial Planning: http://www.jbpub.com/catalog/0763745790
Risk Management: http://www.jbpub.com/catalog/9780763733421
Healthcare Organizations: www.HealthcareFinancials.com
Administrative Terms: www.HealthDictionarySeries.com
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The Sentinel Effect
The Sentinel Effect is the theory that productivity and outcomes can be improved through the process of observation and measurement. It is based on the now-controversial ‘Hawthorne study’ of the 1930’s. And, its implications in medical quality and healthcare improvements are enormous.
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