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The Impact of Star Physicians on Diffusion of a Medical Technology
Shinn, Laura Tungol
Shinn, Laura Tungol
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Thesis/Dissertation
Date
2011
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Economics
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http://dx.doi.org/10.34944/dspace/2359
Abstract
This dissertation studies the effect of star power among physicians on the diffusion of a medical technology. Studies of the diffusion of medical technologies document institutional and market level factors influencing diffusion rates and patterns. The role of the physician in the diffusion of medical technology in hospitals is not widely studied. This dissertation seeks to fill this gap. Certain "star" physicians and hospitals are recognized as highly attractive to patients. A star physician is defined as a physician who meets any of the following criteria: (i) completed residency training at top 30 ranked hospital, (ii) graduated from a top 30 medical school or (iii) is included in Castle & Connolly's Top Docs publications. A star hospital is defined as a member of the American Association of Medical Colleges' Council of Teaching Hospitals. Using quarterly data on all bariatric surgeries performed in the state of Pennsylvania from 1995 through 2007, I measure the effect of stars physicians and star hospitals on the diffusion of a surgical innovation in bariatric surgery called laparoscopic gastric bypass surgery. I use logistic and OLS regression to test for effects at both the hospital and physician level. At the hospital level, I find that having a star physician at a hospital raises the likelihood of that hospital diffusing laparoscopic gastric bypass from eleven percent to eighty-nine percent. I find that over the time period from first quarter 2000 to fourth quarter 2001, being a star hospital raises the likelihood of that hospital diffusing laparoscopic gastric bypass from thirteen percent to eighty-seven percent. At the physician level, the empirical results indicate that star physicians exert positive asymmetric influence on the adoption and utilization rates of non-stars at the same hospital. This dissertation supports earlier work in technology diffusion by finding a positive influence from key individuals. It adds to the literature on medical technology diffusion by testing a new data set for a chronic disease treatment.
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