AI Article Synopsis

  • Blockchain technology and smart contracts have unexplored potential in radiology, offering solutions for secure data transfer and automated verification processes.
  • A survey was conducted among radiologists and trainees to gauge their knowledge and interest in blockchain technologies related to medical imaging.
  • The study aims to analyze current perspectives and possible future applications of blockchain in clinical radiology.

Article Abstract

Introduction: Although blockchain technology and smart contracts are garnering attention in various sectors, their applications and familiarity within the realm of radiology remain largely unexplored. Blockchain, a decentralized digital ledger technology, offers secure, transparent, and resilient data management by distributing the verification process across a network of independent entities. This decentralized technology presents a possible solution for a range of healthcare challenges, from secure data transfer to automated verification processes. To address such challenges in the context of medical imaging, blockchain could provide different approaches, including smart contracts, machine learning algorithms, and the secure dissemination of large files among key stakeholders such as patients, healthcare providers, and institutions. This manuscript aims to explore the current attitudes and perspectives of trainees and radiologists to the utilization of blockchain technology and smart contracts in clinical radiology. Additionally, the study provides an in-depth analysis of the potential applications for incorporating blockchain into radiology.

Methods: After obtaining The George Washington University Committee on Human Research Institutional Review Board (IRB) approval, we conducted a 10-question survey among radiologists and trainees at several institutions and private practices. Surveys were created via the Google Forms application and were emailed to potential participants. Participants were asked about their current academic level (medical student, resident/fellow, academic radiologist, private practice radiologist, others), their knowledge level about the field of imaging informatics and blockchain and smart contract technologies, their level of interest in learning more about blockchain and smart contracts, and their opinion about possible applications of blockchain and smart contract in the future of medical imaging.

Results: A total of 118 survey requests were distributed; 83 were returned, reflecting a 70.3% overall response rate. Of these, 19 were sent to private practices with a 15.8% response rate (3/19), and 99 to academic centers, yielding an 80.8% response rate (80/99). The survey respondents demonstrated a strong interest and need to further understand these technologies among radiologists and trainees. This study focuses on key components of this technology as it relates to healthcare and the practice of radiology, including data storage, patient care, secure communication, and automation, as well as strengths, weaknesses, opportunities, and threats (SWOT) analysis.

Discussion: To our knowledge, this is the first study to investigate and establish a baseline for the current perspectives on the application of blockchain technology and smart contracts in clinical radiology amongst trainees and radiologists across academic and private settings. Incorporating blockchain and smart contracts technologies into the field of radiology has the potential to achieve greater efficiency, security, and patient empowerment. However, the adoption of this technology comes with challenges, such as infrastructure, interoperability, scalability, and regulatory compliance. Collaboration between radiologists, hospital administration, policymakers, technology developers, and patient advocacy organizations will help guide and advance our understanding of the potential applications of blockchain and smart contracts in radiology and healthcare.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10640909PMC
http://dx.doi.org/10.7759/cureus.46941DOI Listing

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