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Monitoring of Technology Adoption Using Web Content Mining of Location Information and Geographic Information Systems: A Case Study of Digital Breast Tomosynthesis

Monitoring of Technology Adoption Using Web Content Mining of Location Information and Geographic... Purpose: To our knowledge, integration of Web content mining of publicly available addresses with a geographic information system (GIS) has not been applied to the timely monitoring of medical technology adoption. Here, we explore the diffusion of a new breast imaging technology, digital breast tomosynthesis (DBT). Methods: We used natural language processing and machine learning to extract DBT facility location information using a set of potential sites for the New England region of the United States via a Google search application program interface. We assessed the accuracy of the algorithm using a validated set of publicly available addresses of locations that provide DBT from the DBT technology vendor, Hologic. We quantified precision, recall, and F1 score, aiming for an F1 score of >= 95% as the desirable performance. By reverse geocoding on the basis of the results of the Google Maps application program interface, we derived a spatial data set for use in an ArcGIS environment. Within the GIS, a host of spatiotemporal analyses and geovisualization techniques are possible. Results: We developed a semiautomated system that integrated DBT location information into a GIS that was feasible and of reasonable quality. Initial accuracy of the algorithm was poor using only a search term list for information retrieval (precision, 35%; recall, 44%; F1 score, 39%), but performance dramatically improved by leveraging natural language processing and simple machine learning techniques to isolate single, valid instances of DBT location information (precision, 92%; recall, 96%; F1 score, 94%). Reverse geocoding yielded reliable geographic coordinates for easy implementation into a GIS for mapping and planned monitoring. Conclusion: Our novel approach can be applicable to technologies beyond DBT, which may inform equitable access over time and space. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JCO Clinical Cancer Informatics Wolters Kluwer Health

Monitoring of Technology Adoption Using Web Content Mining of Location Information and Geographic Information Systems: A Case Study of Digital Breast Tomosynthesis

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References (23)

Publisher
Wolters Kluwer Health
Copyright
(C) 2018 by Lippincott Williams & Wilkins, Inc.
ISSN
2473-4276
DOI
10.1200/CCI.17.00150
Publisher site
See Article on Publisher Site

Abstract

Purpose: To our knowledge, integration of Web content mining of publicly available addresses with a geographic information system (GIS) has not been applied to the timely monitoring of medical technology adoption. Here, we explore the diffusion of a new breast imaging technology, digital breast tomosynthesis (DBT). Methods: We used natural language processing and machine learning to extract DBT facility location information using a set of potential sites for the New England region of the United States via a Google search application program interface. We assessed the accuracy of the algorithm using a validated set of publicly available addresses of locations that provide DBT from the DBT technology vendor, Hologic. We quantified precision, recall, and F1 score, aiming for an F1 score of >= 95% as the desirable performance. By reverse geocoding on the basis of the results of the Google Maps application program interface, we derived a spatial data set for use in an ArcGIS environment. Within the GIS, a host of spatiotemporal analyses and geovisualization techniques are possible. Results: We developed a semiautomated system that integrated DBT location information into a GIS that was feasible and of reasonable quality. Initial accuracy of the algorithm was poor using only a search term list for information retrieval (precision, 35%; recall, 44%; F1 score, 39%), but performance dramatically improved by leveraging natural language processing and simple machine learning techniques to isolate single, valid instances of DBT location information (precision, 92%; recall, 96%; F1 score, 94%). Reverse geocoding yielded reliable geographic coordinates for easy implementation into a GIS for mapping and planned monitoring. Conclusion: Our novel approach can be applicable to technologies beyond DBT, which may inform equitable access over time and space.

Journal

JCO Clinical Cancer InformaticsWolters Kluwer Health

Published: Jun 14, 2018

Keywords: Mammography, Access to care, Health services, Billing, Informatics, Health care facilities, Health services research

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