title: Canary in a coal mine: does the plastic surgery market predict the american economy?
abstract: BACKGROUND
  Economic tools have been used in the past to predict the trends in plastic surgery procedures. Since 1992, U.S. cosmetic surgery volumes have increased overall, but the exact relationship between economic downturns and procedural volumes remains elusive. If an economic predicting role can be established from plastic surgery indicators, this could prove to be a very powerful tool.
  
  
  METHODS
  A rolling 3-month revenue average of an eight-plastic surgeon practice and various economic indicators were plotted and compared. An investigation of the U.S. procedural volumes was performed from the American Society of Plastic Surgeons statistics between 1996 and 2008. The correlations of different economic variables with plastic surgery volumes were evaluated. Lastly, search term frequencies were examined from 2004 to July of 2009 to study potential patient interest in major plastic surgery procedures.
  
  
  RESULTS
  The self-payment revenue of the plastic surgery group consistently proved indicative of the market trends approximately 1 month in advance. The Standard and Poor's 500, Dow Jones Industrial Average, National Association of Securities Dealers Automated Quotations, and Standard and Poor's Retail Index demonstrated a very close relationship with the income of our plastic surgery group. The frequency of Internet search terms showed a constant level of interest in the patient population despite economic downturns.
  
  
  CONCLUSIONS
  The data demonstrate that examining plastic surgery revenue can be a useful tool to analyze and possibly predict trends, as it is driven by a market and shows a close correlation to many leading economic indicators. The persisting and increasing interest in plastic surgery suggests hope for a recovering and successful market in the near future.
authors.affiliation: Loma Linda, Calif. From the Loma Linda University Department of Plastic Surgery, Loma Linda University Medical Center.
authors.forename: Wendy W
authors.initials: WW
authors.lastname: Wong
authors.forename: Drew G
authors.initials: DG
authors.lastname: Davis
authors.forename: Andrew K
authors.initials: AK
authors.lastname: Son
authors.forename: Matthew C
authors.initials: MC
authors.lastname: Camp
authors.forename: Subhas C
authors.initials: SC
authors.lastname: Gupta
mesh_terms: D003365:Costs and Cost Analysis; D004467:Economics; D005260:Female; D005544:Forecasting; D005102:Health Expenditures; D006301:Health Services Needs and Demand / Q000191:economics*; D006801:Humans; D007182:Income; D016014:Linear Models; D008389:Marketing of Health Services / Q000191:economics*; D010818:Practice Patterns, Physicians' / Q000191:economics; D011237:Predictive Value of Tests; D013518:Surgery, Plastic / Q000191:economics* / Q000639:trends*; D014481:United States