4.7 Article

Quantifying Innovation in Surgery

Journal

ANNALS OF SURGERY
Volume 260, Issue 2, Pages 205-211

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/SLA.0000000000000662

Keywords

diffusion of innovation; innovation; surgery; technology

Categories

Funding

  1. National Institute for Health Research [NF-SI-0510-10186, CL-2008-21-502] Funding Source: researchfish

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Objectives: The objectives of this study were to assess the applicability of patents and publications as metrics of surgical technology and innovation; evaluate the historical relationship between patents and publications; develop a methodology that can be used to determine the rate of innovation growth in any given health care technology. Background: The study of health care innovation represents an emerging academic field, yet it is limited by a lack of valid scientific methods for quantitative analysis. This article explores and cross-validates 2 innovation metrics using surgical technology as an exemplar. Methods: Electronic patenting databases and the MEDLINE database were searched between 1980 and 2010 for surgeon OR surgical OR surgery. Resulting patent codes were grouped into technology clusters. Growth curves were plotted for these technology clusters to establish the rate and characteristics of growth. Results: The initial search retrieved 52,046 patents and 1,801,075 publications. The top performing technology cluster of the last 30 years was minimally invasive surgery. Robotic surgery, surgical staplers, and image guidance were the most emergent technology clusters. When examining the growth curves for these clusters they were found to follow an S-shaped pattern of growth, with the emergent technologies lying on the exponential phases of their respective growth curves. In addition, publication and patent counts were closely correlated in areas of technology expansion. Conclusions: This article demonstrates the utility of publically available patent and publication data to quantify innovations within surgical technology and proposes a novel methodology for assessing and forecasting areas of technological innovation.

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