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Horizon Scanning Methods for Health Care Technology Innovation Identification: Rapid Scoping Review of Patent
Sonia Garcia Gonzalez-Moral1, Erin Pennock2, Olushola Ewedairo1
1NIHR Innovation Observatory, Population Health Sciences Institute, Newcastle University, The Catalyst Room 3.12, 3 Science Square Newcastle Helix, Newcastle upon Tyne, NE4 5TG, United Kingdom, 44 0191 2082262.
Patent analysis reveals healthcare technology trends, aiding strategic planning. Consistent methods are crucial for accurate insights into emerging innovations.
Area of Science:
- Health care innovation
- Technology management
- Intellectual property analysis
Background:
- Patents are early indicators of innovation, but their utility in healthcare horizon scanning is not well-defined.
- The healthcare sector features diverse technologies and substantial research investment, necessitating effective innovation tracking.
Purpose of the Study:
- To investigate the role and methods of patent analysis in advancing healthcare technology innovation.
- To identify intellectual property sources, evaluate retrieval and analysis techniques, and define objectives for using patent data to predict trends and inform strategies.
Main Methods:
- A rapid scoping review following Cochrane and PRISMA guidelines with a preregistered protocol.
- Searches of Embase, IEEE Xplore, and Web of Science for records from 2020 onwards.
- Inclusion of studies providing patent data, methods, and tools for healthcare technologies, screened by three independent reviewers.
Main Results:
- 124 studies were included from 1741 identified, with 54% original research and 43.5% reviews.
- Trend analysis (50%) and strategy recommendations (20%) were common research objectives.
- Cancer and respiratory conditions (including COVID-19) were key focus areas, with 33% of studies using automated approaches for analysis.
Conclusions:
- Patent data is valuable for identifying technological trends and informing policy and research.
- Inconsistent deduplication practices risk data inflation, highlighting the need for transparency.
- Data transformation and visualization are key for trend detection, with Python and R being common tools.
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