Does industry funding mean more publications for subspecialty academic plastic surgeons?

[BACKGROUND] Conflict of interest among physicians in the context of private industry funding led to the introduction of the Physician Payments Sunshine Act in 2010. This study examined whether private industry funding correlated with scholarly productivity in the respective subspecialties of plastic surgery and the wider academic plastic surgery community.

[MATERIALS AND METHODS] Full-time plastic surgeons and their academic attributes were identified via institutional websites. Fellowship-trained individuals were segregated into subspecialties of microsurgery, craniofacial surgery, hand surgery, esthetic surgery, and burn surgery. The Center for Medicare and Medicaid Services Open Payment database was used to extract industry funding information. Each individual's bibliometric data were then collected through Scopus to determine the correlation between selected surgeon characteristics, academic productivity, and industry funding.

[RESULTS] Nine hundred and thirty-five academic plastic surgeons were identified, with 532 having defined subspecialty training. Academic bibliometrics among subspecialty surgeons were comparable among the five groups with esthetic and craniofacial surgeons displaying a preponderance of attaining more industry funding (P = 0.043) and career publications respectively, with the latter not attaining statistical significance (P = 0.12). Overall, research-specific funding (P = 0.014) and higher funding amounts (P < 0.0001) correlated with higher Hirsch indices in tandem with higher academic rank. A funding level of $2000 appeared to be the approximate cutoff above which scholastic productivity became apparent.

[CONCLUSIONS] Our study demonstrated in detail the association between industry funding and academic bibliometrics in academic plastic surgery of every subspecialty. Even at modest amounts, industry support, especially when research designated, positively influenced research and therefore, academic output.