1 (page number not for citation purpose) EDITORIAL Creating a Health Data Marketplace for the Digital Health Era Imtiaz Khan, PhD1* , Mohamed Maher1,2 , Anjum Khurshid, PhD3,4 1Cardiff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 *Corresponding Author: Imtiaz Khan, Email: ikhan@cardiffmet.ac.uk Doi: https://doi.org/10.30953/bhty.v7.338 Keywords: dementia, diabetes, digital health, hypertension, non-communicable chronic diseases Submitted: July 17, 2024; Accepted: August 13, 2024; Published: August 31, 2024 Globally, non-communicable chronic diseases (NCDs) such as hypertension and diabetes ac- count 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-cen- tric paradigm shift, transitioning from traditional reactive medicine to predictive diagnosis and personalized preven- tive 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 smart- watch, along with the growing capability of predictive and generative algorithms to create value from this health data. However, unlike Industry 4.0, which extensively bene- fited 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 vari- ous 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 interoperability procedures.5 This data inaccessibility and incompatibility undermine the predictive and analyt- ical capabilities of machine learning algorithms and data analytics, limiting medical practitioners’ decision-making abilities as well as the 4P vision of Healthcare 4.0 —predic- tion, 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 decision-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 democ- ratization of health data is fundamental. However, ad- verse incentives of healthcare business models that are driven by organizations 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 market- place. 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 steward- ship capabilities (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 interop- erability, traceability and integrity by DLT-like technol- ogies10 makes them the most suitable candidate on which to build such a marketplace. Blockchain in Healthcare Today ISSN 2573-8240 https://orcid.org/0000-0001-7624-1319 https://orcid.org/0000-0003-2130-7717 https://orcid.org/0000-0002-8946-0622 mailto:ikhan@cardiffmet.ac.uk https://doi.org/10.30953/bhty.v7.338 Citation: Blockchain in Healthcare Today 2024, 7: 338 - https://doi.org/10.30953/bhty.v7.3382 (page number not for citation purpose) Imtiaz Khan et al. In recent years, several blockchain-based Health Data Marketplace have emerged11 with different business models and service choices. Patientory12 as a pioneer- ing example facilitates monetization of health data, op- portunities to participate in clinical trials, AI and video based heath coaching services etc. Here blockchain-like technologies been used to ensure data privacy and se- curity. The platform’s interoperability further enhances its value, facilitating seamless data exchange among pa- tients, healthcare providers, and researchers, thereby im- proving healthcare delivery efficiency. However, despite these successes, Patientory faces challenges in achiev- ing long-term user engagement and satisfaction. This is primarily due to the fact that monetization and gen- eralized 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 analyt- ics-based services with personalized and predictive ca- pabilities 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 artificial 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 pub- lic health. Last but not least, the marketplace model en- courages 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. Disclaimer This editorial is based on the podcast discussion and the paper titled “From Sharing to Selling: Challenges and Opportunities of Establishing Digital Health Data Mar- ketplaces Using Blockchain Technologies.” For a more detailed understanding, readers are encouraged to refer to the original paper and listen to the full podcast. Financial and Non-Financial Relationships and Activities This editorial received no specific funding from any pub- lic, commercial, or not-for-profit sectors. Conflicts of Interest Imtiaz Khan and Anjum Khurshid are members of the BHTY Editorial Board. Mohamed Maher reports no conflict of interest. Contributors 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. Data Availability Statement (DAS), Data Sharing, Reproducibility, and Data Repositories None listed by author. Application of Ai-Generated Text or Related Technology None listed by author. Acknowledgements The authors would like to thank Tory Cenaj for inviting us to write this editorial. References 1. Zimmermann M. Diet, nutrition, and the prevention of chronic diseases: by the World Health Organization, 1991, 203 pages, softcover. WHO, Geneva. Am J Clin Nutr. 1994;60:644–5. https://doi.org/10.1093/ajcn/60.4.644a 2. Alzheimer’s Research UK. Dementia leading cause of death in 2022. [cited 2024 July 07]. Available from: https://www. alzheimersresearchuk.org/news/dementia-is-the-uks-biggest- killer-we-need-political-action-to-save-lives/#:~:text=Our%20 new%20ana lys i s%20shows%20that , can%20save%20 people%20from%20dementia 3. van der Flier WM, de Vugt ME, Smets EMA, Blom M, Teunis- sen CE. Towards a future where Alzheimer’s disease pathology is stopped before the onset of dementia. Nat Aging. 2023;3:494– 505. https://doi.org/10.1038/s43587-023-00404-2 4. Dash S, Shakyawar SK, Sharma M, Kaushik S. Big data in healthcare: management, analysis and future prospects. J Big Data. 2019;6:1–25. https://doi.org/10.1186/s40537-019-0217-0 5. Wiederrecht G, Darwish S. The healthcare data explosion. [cited 2024 July 07]. Available from: https://www.rbccm.com/en/gib/ healthcare/episode/the_healthcare_data_explosion 6. Li J, Carayon P. Health care 4.0: a vision for smart and connected health care. IISE Transac Healthc Syst Eng. 2021;11:171–80. https://doi.org/10.1080/24725579.2021.1884627 7. Davis RE, Jacklin R, Sevdalis N, Vincent CA. Patient involve- ment in patient safety: what factors influence patient participa- tion and engagement? Health Expect. 2007;10:259–67. https:// doi.org/10.1111/j.1369-7625.2007.00450.x 8. Maher M, Khan I, Prikshat V. Monetisation of digital health data through a gdpr-compliant and blockchain-enabled digital health data marketplace: a proposal to enhance patient’s engage- ment with health data repositories. Int J Inf Manag Data Insights. 2023;3:100159. https://doi.org/10.1016/j.jjimei.2023.100159 9. Narayan R, Tidstrom A. Tokenizing coopetition in a block- chain for a transition to circular economy. J Cleaner Prod. 2020;263:121437. https://doi.org/10.1016/j.jclepro.2020.121437 https://doi.org/10.30953/bhty.v7.338 https://doi.org/10.1093/ajcn/60.4.644a https://www.alzheimersresearchuk.org/news/dementia-is-the-uks-biggest-killer-we-need-political-action-to-save-lives/#:~:text=Our%20new%20analysis%20shows%20that,can%20save%20people%20from%20dementia https://www.alzheimersresearchuk.org/news/dementia-is-the-uks-biggest-killer-we-need-political-action-to-save-lives/#:~:text=Our%20new%20analysis%20shows%20that,can%20save%20people%20from%20dementia https://www.alzheimersresearchuk.org/news/dementia-is-the-uks-biggest-killer-we-need-political-action-to-save-lives/#:~:text=Our%20new%20analysis%20shows%20that,can%20save%20people%20from%20dementia https://doi.org/10.1038/s43587-023-00404-2 https://doi.org/10.1186/s40537-019-0217-0 https://www.rbccm.com/en/gib/healthcare/episode/the_healthcare_data_explosion https://www.rbccm.com/en/gib/healthcare/episode/the_healthcare_data_explosion https://doi.org/10.1080/24725579.2021.1884627 https://doi.org/10.1111/j.1369-7625.2007.00450.x https://doi.org/10.1111/j.1369-7625.2007.00450.x https://doi.org/10.1016/j.jjimei.2023.100159 https://doi.org/10.1016/j.jclepro.2020.121437 Citation: Blockchain in Healthcare Today 2024, 7: 338 - https://doi.org/10.30953/bhty.v7.338 3 (page number not for citation purpose) Creating a Health Data Marketplace for the Digital Health Era 10. Shahaab A, Khan I, Maude R, Hewage C, Wang Y. Public service operational efficiency and blockchain—a case study of Companies House, UK. Gov Info Quart. 2023;40(1):101759. https://doi.org/10.1016/j.giq.2022.101759 11. Built In. Blockchain in healthcare: 18 examples to know [In- ternet]. [cited 2024 Aug 7]. Available from: https://builtin.com/ blockchain/blockchain-healthcare-applications-companies 12. Patientory Inc. CASE STUDY: forging the path to consumer directed health through blockchain technology [Internet]. 2019 May 20 [cited 2024 Aug 7]. Available from:  https:// patientory.com/blog/2019/05/20/case-study-forging-the- path-to-consumer-directed-health-through-blockchain- technology Copyright Ownership: This is an open-access article distributed in ac- cordance with the Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) license, which permits others to distribute, adapt, en- hance 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. https://doi.org/10.30953/bhty.v7.338 https://doi.org/10.1016/j.giq.2022.101759 https://builtin.com/blockchain/blockchain-healthcare-applications-companies https://builtin.com/blockchain/blockchain-healthcare-applications-companies https://patientory.com/blog/2019/05/20/case-study-forging-the-path-to-consumer-directed-health-through-blockchain-technology https://patientory.com/blog/2019/05/20/case-study-forging-the-path-to-consumer-directed-health-through-blockchain-technology https://patientory.com/blog/2019/05/20/case-study-forging-the-path-to-consumer-directed-health-through-blockchain-technology https://patientory.com/blog/2019/05/20/case-study-forging-the-path-to-consumer-directed-health-through-blockchain-technology http://creativecommons. org/licenses/by-nc/4.0 http://creativecommons. org/licenses/by-nc/4.0