EDITORIAL
Imtiaz Khan, PhD1*, Mohamed Maher1,2, Anjum Khurshid, PhD3,4
1Cardiff Metropolitan University, Cardiff, Wales, UK; 2SoulinData, Cardiff, Wales, UK; 3Harvard Pilgrim Health Care, Boston, Massachusetts, USA; 4Harvard Medical School, Boston, Massachusetts, USA
Keywords: dementia, diabetes, digital health, hypertension, non-communicable chronic diseases
Citation: Blockchain in Healthcare Today 2024, 7: 338.
DOI: https://doi.org/10.30953/bhty.v7.338
Copyright: © 2024 The Authors. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, adapt, enhance this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0.
Submitted: July 17, 2024; Accepted: August 13, 2024; Published: August 31, 2024
*Corresponding Author: Imtiaz Khan, Email: ikhan@cardiffmet.ac.uk
Competing interests and funding: Imtiaz Khan and Anjum Khurshid are members of the BHTY Editorial Board. Mohamed Maher reports no conflict of interest.
This editorial received no specific funding from any public, commercial, or not-for-profit sectors.
Globally, non-communicable chronic diseases (NCDs) such as hypertension and diabetes account for 75% of direct mortality.1 Concurrently, mental health diseases like dementia have recently become the biggest killer disease in countries like the UK2, with no cure, treatment or even effective intervention.3 To address this pressing issue, Healthcare 4.0 introduces a patient-centric paradigm shift, transitioning from traditional reactive medicine to predictive diagnosis and personalized preventive interventions.4 This shift leverages on the large volume and variety of health data generated from the growing use of electronic health records (EHR), the internet of medical things (IoMT) and personal wearable devices like the smartwatch, along with the growing capability of predictive and generative algo-rithms to create value from this health data.
However, unlike Industry 4.0, which extensively benefited from the internet of things (IoT) and sensor-derived data, Healthcare 4.0 has yet to fully capitalize even on EHR datasets, let alone IoMT and wearables-derived data. EHR data are often siloed in centralized databases of various service providers, such as hospitals and clinics, whereas IoMT and wearable-derived data remain in the respective vendor’s cloud, with limited and or complex data access and in-teroperability procedures.5 This data inaccessibility and incompatibility undermine the predictive and analytical capa-bilities of machine learning algorithms and data analytics, limiting medical practitioners’ decision-making abilities as well as the 4P vision of Healthcare 4.0 —prediction, prevention, personalization, and participation.6
From the patient’s perspective, restricted access to their health data, negatively impacts their perception towards data ownership and stewardship. This limitation can make patients feel coerced into a passive role in deci-sion-making, knowledge, and value-creation processes, often leading to non-participation or even non-adherence to medications and physician instructions.7
To realize the 4P vision of healthcare 4.0 particularly participation of patients, decentralization and democratization of health data is fundamental. However, adverse incentives of healthcare business models that are driven by organi-zations with interest in complicated and nontransparent financing mechanisms, prevent such decentralization that empowers patients. We posit that the establishment of a blockchain-based health data marketplace where EHR, IoMT and wearable-derived data can be monetised by selling it to data consumers like medical professionals, researchers, regulators, third-party (e.g. AI service providers) and policymakers can solve this data centralization problem.8 Blockchain-like distributed ledger technology (DLT) introduces new opportunities to develop such a health data mar-ketplace. The immutable feature of blockchain enables the attribution of ownership of digital assets (health data in this case) in a highly secure environment, while the smart contract feature provides flexible data stewardship capabili-ties (i.e. patients can choose which health data attribute to sell to which type of consumer), thus promoting privacy and trust. The smart contract also facilitates efficient and equitable distribution of revenue among the stakeholders (patient, clinics, caregivers etc.), fostering a coopetition-like socioeconomic ecosystem.9 Finally, the capability of cross-organization (hospitals, clinics) and technology (IoMT, wearables) data interoperability, traceability and integrity by DLT-like technologies10 makes them the most suitable candidate on which to build such a marketplace.
In recent years, several blockchain-based Health Data Marketplace have emerged11 with different business models and service choices. Patientory12 as a pioneering example facilitates monetization of health data, opportunities to participate in clinical trials, AI and video based heath coaching services etc. Here blockchain-like technologies been used to ensure data privacy and security. The platform’s interoperability further enhances its value, facilitating seam-less data exchange among patients, healthcare providers, and researchers, thereby improving healthcare delivery ef-ficiency. However, despite these successes, Patientory faces challenges in achieving long-term user engagement and satisfaction. This is primarily due to the fact that monetization and generalized static servitization (video coaching service) are not enough for sustainable user engagement. Here, using the user’s data the marketplace needs to offer (directly or through third party) a suite of AI or data analytics-based services with personalized and predictive capa-bilities tailored to adapt with the change of personal lifestyle, health and social conditions. The marketplace also needs to offer a community environment (through metaverse like technologies) through which collective intelligence, community surveillance can be achieved through collaboration and competition.
Integrating wearable-derived patient-generated data with clinical records will allow healthcare providers to use artifi-cial intelligence and improved computing capabilities to analyze large amounts of data and to develop more accurate evidence-based diagnostic tools and treatment plans tailored to individual patients. Health regulators, in particular, stand to benefit significantly from this model. With access to a vast pool of real-world data, regulators can make more informed decisions to improve efficiency, coordination, and accountability that will improve public health. Last but not least, the marketplace model encourages a shift from a service-oriented healthcare system to a knowledge-driven one, where patients are no longer passive recipients of care but active participants in their health journey.
This editorial is based on the podcast discussion and the paper titled “From Sharing to Selling: Challenges and Op-portunities of Establishing Digital Health Data Marketplaces Using Blockchain Technologies.” For a more detailed understanding, readers are encouraged to refer to the original paper and listen to the full podcast.
This editorial is based on the podcast where the first and second authored were questioned by the third author. All authors contributed to drafting and writing the editorial.
None listed by author.
None listed by author.
The authors would like to thank Tory Cenaj for inviting us to write this editorial.
Copyright Ownership: This is an open-access article distributed in accordance with the Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) license, which permits others to distribute, adapt, enhance this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0.