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Summaries for Patients are a service provided by Annals to help patients better understand the complicated and often mystifying language of modern medicine.
SUMMARIES FOR PATIENTS
Choice of Statistical Analysis Can Change the Results of Studies of the Relationship between Hospital and Surgeon Volume and Outcomes of Cancer Surgery
21 October 2003 | Volume 139 Issue 8 | Page I-44
Summaries for Patients are presented for informational purposes only. These summaries are not a substitute for advice from your own medical provider. If you have questions about this material, or need medical advice about your own health or situation, please contact your physician. The summaries may be reproduced for not-for-profit educational purposes only. Any other uses must be approved by the American College of Physicians.
The summary below is from the full report titled "The Effect of Clustering of Outcomes on the Association of Procedure Volume and Surgical Outcomes." It is in the 21 October 2003 issue of Annals of Internal Medicine (volume 139, pages 658-665). The authors are K.S. Panageas, D. Schrag, E. Riedel, P.B. Bach, and C.B. Begg.
What is the problem and what is known about it so far?
An increasing number of studies suggest that patients who have surgery at hospitals or by surgeons performing a high number of the particular procedure they need (high-volume providers) do better than patients who have surgery at hospitals or by surgeons doing fewer procedures (low-volume providers). These types of studies are known as "volume–outcome studies" because they look for associations between the volume of surgeries performed and patient outcomes. Volume–outcome studies are complicated, and there is disagreement about whether high volume is truly related to better outcomes. It is difficult to sort out whether outcomes differ because of provider experience or because patients of high-volume providers are just healthier or otherwise better off than patients of low-volume providers. Also, factors that have little to do with experience may account for the better outcomes seen with high-volume providers. Such factors could explain why not all high-volume providers have good outcomes. Another complicating factor is a statistical issue called "clustering." Clustering refers to the fact that outcomes of one provider's patients will tend to be more like one another than like the outcomes of a different provider's patients. When this is the case, studies must include many more patients to be able to detect real differences in the care of high- and low-volume providers.
Why did the researchers do this particular study?
To see whether the results of volume–outcome studies change when statistical methods account for clustering.
Who was studied?
The researchers reanalyzed data from 3 of their own previous studies, including 24,166 colon cancer surgeries, 10,737 prostate cancer surgeries, and 2603 rectal cancer surgeries.
How was the study done?
The researches analyzed the data in the way most published volume–outcome studies have done and again using 2 different methods to adjust for clustering. They compared the results of each analysis.
What did the researchers find?
When the researchers used methods that accounted for clustering, high volume was not as strongly or as consistently associated with better outcomes.
What were the limitations of the study?
This study reanalyzed only data from 3 specific studies that all focused on cancer surgery. The results may not apply to other conditions.
What are the implications of the study?
While studies suggest that surgical patients fare best with providers (hospitals and surgeons) that perform a high volume of procedures, most have not accounted for the tendency of patients of one provider to have similar outcomes (clustering). When outcomes of individual patients are clustered, more patients are required to prove that providers' outcomes differ from one another. Planners considering regionalizing surgery and patients making decisions about where to go for surgery should remember that volume–outcome studies that have not accounted for clustering may exaggerate the statistical significance of differences in outcomes by provider.
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