In recent years, distributed ledger technologies commonly referred to as blockchain have generated considerable interest and excitement across many industries, including health care, supported by claims of their radically disruptive and transformative potential. Academic literature focusing on blockchain’s potential to solve health care problems has proliferated [1-7]. Although scholars have identified many possible applications of blockchain in health care [8], blockchain’s perceived value ultimately rests on its potential to create a highly secure, tamper-proof, auditable electronic ledger that can enable responsive, fine-grained, and privacy-respecting access to and sharing of health care data. Accordingly, blockchain is often portrayed as a technological solution that can overcome existing barriers to health information exchange [8], one of the most stubborn challenges that continues to plague contemporary health care [9]. Blockchain advocates claim that these technologies will generate higher quality, more trustworthy, and readily accessible data, which can drive improvements across health care [10]. These improvements would then lead to (1) better quality medical care, including improvements in clinical decision-making and more effective public health management and disease prevention [11]; (2) more efficient, cost-effective, and timely health care administration; and (3) improvements in medical and health care research, resulting from more accurate and secure clinical trial data management and storage [12]. In particular, many believe blockchain will enable fine-grained, patient-controlled access, sharing, and management of electronic health records (EHRs), thereby overcoming existing problems associated with the current siloed approach to the storage and management of patient data, which is often regarded as blockchain’s favorite use case for health care [13,14].

However, expecting blockchain technologies to provide an effective, efficient, patient-centered solution to the multiplicity of problems associated with health care data management and sharing is a tall order. This was one of the expected benefits of EHRs; however, despite their widespread take-up in health care settings, ethically sensitive, lawful, timely, and secure sharing and management of health care data remain a critical but seemingly intractable challenge [9,15,16]. Academic literature concerned with health care applications remains overwhelmingly centered on blockchain’s potential, focusing on identifying the possible range of benefits that could be delivered. However, no serious scholarly attempt has been made to assess the extent to which these technologies have in fact been applied to real-world health care contexts and with what consequences, with little attention paid to real-world implementation challenges [17]. In short, academic scholarship remains largely speculative (Multimedia Appendix 1 [1,3,7,18]).

The aim of this study is to critically investigate the health care sector’s engagement with blockchain technologies to date, analyzing those experiences from a theoretical, cross-disciplinary perspective to ground a more realistic appraisal of the potential benefits, difficulties, and implications of implementing blockchain in health care settings. This investigation was animated by the following research questions:

Taken together, these questions can be amalgamated into a single overarching research question: what does health care’s actual experience of blockchain technologies to date reveal about the technologies’ real revolutionary potential [20]?

This paper proceeds by outlining the study’s design, data sources, analytic approach, and theoretical foundations. It then sets out its findings by first providing a qualitative overview and explanation of the extent to which blockchain technologies have been taken up in the health care domain. Second, it offers a critical examination of a series of multidimensional challenges, organized thematically, that constitute (or are likely to constitute) very substantial hurdles that must be overcome if blockchain is to be widely taken up in health care settings. Finally, it discusses these challenges in light of the most promising opportunities for generating real value in health care settings and suggests that the use of blockchain to provide fine-grained patient control over medical records is unlikely to live up to its perceived promise.

The mixed methods study reported in this paper forms the major component of a Wellcome Trust–funded cross-disciplinary project aimed at understanding the challenges, risks, opportunities, and experiences of the health care sector in using blockchain technologies. It took the form of a theoretical investigation, building upon the initial research study by Motsi-Omoijiade and Kharlamov [21] that sought to identify and map evidence of real-world engagement with blockchain technologies in the health care sector, classifying them according to their context of application (as patient care support, administration, or research data management), level of maturity, and the primary geographic region from which the application appeared to originate. The integrated catalog of health care blockchain applications and use cases created in that study provided a snapshot of the state of health care blockchain take-up on November 30, 2019. It identified 128 applications, referring to real-world instances in which blockchain technology has been developed into a commercially viable health-related service created largely from a web-based review of English language websites, gray literature, and academic papers (Multimedia Appendix 2 [21-28]). This study builds on the results of that earlier mapping and classification exercise by drawing on 2 focus group investigations and a series of iterative, in-depth, theoretically oriented desk-based investigations.

The 2 focus group discussions were organized in which a mix of both academic researchers and blockchain-for-health care sector experts participated. The first workshop, hosted at the outset of the project, was designed to generate insights that could inform and guide the direction of the study’s inquiries and help understand the current state of health care sector engagement and experience with blockchain technologies for specific health care purposes. The second workshop occurred toward the end of the study. Its aim was to share the provisional study findings with participants to elicit their critical feedback and provoke discussion. The focus group participants were identified and invited with the aim of bringing wide-ranging, relevant expertise to the discussion, given the project’s aim of adopting a multidisciplinary perspective to address the project’s research questions. This approach to recruitment reflects a belief that technical, legal, ethical, management, clinical care, and health service industry knowledge and experience would be needed to successfully apply blockchain to real-world settings.

The participant invitation list was compiled from the principal investigator’s existing knowledge of academic experts with existing or related interests in blockchain from several disciplinary backgrounds, combined with a light touch review of recent academic and digital health care industry publications to identify key health care sector experts with direct and ongoing experience in seeking to apply blockchain technologies to health care. This initial list was supplemented by the use of snowball sampling techniques (asking each academic and industry invitee to nominate 1 or 2 colleagues) to identify others with relevant expertise. The specific composition of the workshops differed in light of their different objectives and participant availability: the initial workshop comprised more academics than industry experts, whereas the final workshop was attended predominantly by industry experts relative to academics (Multimedia Appendix 3).

The project’s theoretical, desk-based investigations primarily drew on 2 data sources. First, the investigations drew from a wide variety of academic literature from multiple disciplinary perspectives, including computer science, computer security, digital health, organizational management, operations research, medical law, data protection law, medicine, medical sociology, and innovation studies. Given that relatively little information about health-related blockchain projects is publicized via academic journals [29], and existing scholarly literature on blockchain in health care settings has not hitherto been concerned with real-world engagement and experience, relevant academic sources were identified by deductive critical reflection. This entailed developing and refining a series of thematically focused investigations aimed at acquiring a deeper, more fine-grained, cross-disciplinary understanding of the major issues and challenges that would invariably confront those endeavoring to apply blockchain to health care settings. These included matters of data security and integrity, health information technology (IT) implementation, user resistance, internal and external governance, interoperability, organizational management, and data privacy. Second, gray literature (including observations and reflections from those with direct experience of the health sector’s engagement with blockchain to date) provided a vitally important source of insight, given that the published scholarly literature represents only a small snapshot of global blockchain activity. This literature included reflections collected from various informal sources, such as guidance and opinion pieces published in various formats, including essay collections [30], blog posts, news articles, newsletters by industry bodies (particularly those published by the Healthcare Information Management and Systems Society [HIMSS]) and key industry experts from organizations offering blockchain for health care consultancy services such as Consensys Health and Hashed Health.

This study proceeded from the premise that blockchain’s reliance upon cryptographic techniques and networked, distributed computing facilities to provide a highly secure, shared but tamper-proof database means that its foundational value lies in its capacity to facilitate secure data sharing and collaboration, particularly between parties in circumstances where a lack of social trust would otherwise inhibit cooperation. So understood, the development, implementation, and scale up of blockchain technologies into health care contexts are likely to pose distinctive and novel challenges because of both its technological design and the health care contexts in which attempts are being made to implement it.

The analysis proceeded in 3 stages. First, it began by seeking to acquire a deeper, more qualitatively oriented understanding of the observed patterns of blockchain for health care engagement mapped from the Motsi-Omoijiade and Kharlamov [21] study. These first-stage inquiries drew heavily on insights and observations contained in industry publications [29], government reports, mainstream media, and initial focus group discussions. The resulting analysis produced a clearer, richer, and more nuanced understanding of (1) how blockchain technologies were intended to provide specific functional capacities across a variety of real-world health care contexts; (2) the range of applications, context-domains, and participants who were expected to engage with and those expected to benefit from these applications; (3) how blockchain was expected to address specific data-sharing problems encountered in health care settings; and (4) the wide-ranging and multidimensional difficulties or challenges that have been encountered in the course of these engagements to date or that can be expected to arise if those engagements continue to expand and deepen, particularly if they extend into clinical settings.

The second-stage analysis entailed a critical comparison of the benefits, difficulties, and drawbacks identified in stage 1 against the claims appearing in the academic literature about blockchain’s potential benefits and shortcomings (both generally and those specific to health care). This analysis sought to evaluate these claims, which were focused almost exclusively on the benefits of blockchain, with little mention or consideration of shortcomings, against early-stage experiences with blockchain implementation in real-world health care settings. The resulting mismatch between academic claims and actual experiences of the technology prompted further scrutinization and critical analysis of the implementation problems identified from the first-stage analysis, grouping them together thematically (rather than primarily in relation to specific functional applications or particular kinds of health care data). This grouping was based on recurring difficulties and challenges that have been encountered (or are likely to arise in relation to specific health care applications, particularly those that directly affect clinical practice) in seeking to design, configure, and implement blockchain technologies in health care settings. The encountered challenges were typically multidimensional in character, entailing dynamic interacting and often complex technical, social, regulatory, and organizational difficulties that would need to be addressed successfully before the technology is likely to produce significant value for health care.

The final stage of analysis sought to develop a more theoretically grounded account of the observations generated at the second stage analysis, drawing upon different fields of scholarship, including academic discussions focused on blockchain’s revolutionary potential; the nature, dimensions, and challenges of innovation more generally; and of health IT implementation in particular (including studies of EHR implementation). The aim was to produce an integrated, theoretically informed, cross-disciplinary understanding of the experience of the health care sector’s engagement with blockchain technologies to date, providing a firmer foundation for appraising its prospects by reference to the underlying nature and form of coordination that blockchain technologies currently enable.

The theoretical framework for this study draws primarily on 3 different but complementary perspectives that collectively contribute to addressing the project’s overarching research question. First, it draws upon the growing cross-disciplinary literature that has typically emphasized blockchain’s revolutionary potential to enable novel forms of social cooperation between strangers without the need for a trusted third-party intermediary. Blockchain’s potential to enable trustless cooperation is ultimately attributable to its underlying technological architecture and distributed operation to produce a shared database that is effectively tamper-proof, enabling the replacement of social trust with computational trust in specific contexts. This has prompted some scholars to describe blockchain as a truth machine [31]. More recently, however, a more skeptical strand of literature has started to emerge, drawing attention to a wide range of reasons why the technology may fail to live up to its promise [32]. As these inquiries progressed, it became necessary to look to a wider variety of literature to make sense of these real-world implementation challenges. This led to the investigation of a second body of academic scholarship located within the field of innovation studies, a different multidisciplinary strand of work that includes a wide range of industry studies that demonstrate that technologies do not arise in the fully developed form [33-35]. Instead, they find that a period of considerable confusion usually follows the emergence of a new technological invention, with little agreement about what its major subsystems should be or how it can best be put together as a product or service, resulting in significant experimentation [36,37].

Health care’s current and ongoing engagements with blockchain can be located within this early experimental phase, situated at the entrance to the so-called valley of death. This refers to a gap between the development of new scientific knowledge and the establishment of proof of concept but before full development and commercialization [38,39]. Industry estimates suggest that 4 in 5 new inventions are never commercialized because of their failure to overcome numerous barriers to innovation encountered during this crucial development phase [40,41]. Innovation studies scholars have identified multiple valleys of death, which they have explored from various angles. Some understand the valley primarily as a financing and funding problem that arises after the establishment of a proof of concept. At that moment, significant investment is required to scale up; however, there is considerable technical and commercial uncertainty about its likely success, which thus discourages further investment [34]. Occasionally, this leads to various policy prescriptions, such as government funding initiatives and translational centers comprising academic and commercial stakeholders, to help bridge the gap [42]. Others focus on the difficult transition of university research to a product or service brought to market by a commercial firm, particularly in the case of drug development [43].

For the purposes of examining the prospects of blockchain in health care, the most salient strand of this literature is concerned with identifying the barriers to innovation that create and contribute to the valley of death. Scholars have classified these barriers as either internal to the organization (including factors such as a restrictive mindset, lack of competence, insufficient resources, and an unsupportive organizational structure) or external and thus largely beyond the firm’s direct control (including factors such as a paucity of external finance; resistance or lack of support from specific actors, such as customer resistance or an unsupportive government; and various factors which result in a restrictive macroenvironment, such as an undeveloped network and ecosystem, technological volatility that narrows the window of opportunity during which an innovation can be introduced, inappropriate infrastructure, and a restrictive local culture) [44]. However, these largely generic, rather abstract, accounts of various obstacles that must be overcome for technological innovations to largely succeed treat the underlying technology as a black box rather than engaging with technological design and specific development challenges in seeking to configure and embed the technology into sector-specific social and organizational systems, processes, and practices [45,46].

Rather than treating blockchain in health care as a closed black-box, these theoretical investigations drew upon a third set of analytical lenses situated within academic investigations of health care IT system implementations, particularly studies undertaken from a social practice perspective [45,47-49]. These studies highlight the critical role of context, culture, and the values that are brought to bear by medical professionals in clinical environments, identifying clinical consultation as a complex social encounter that occurs within a heavily institutionalized environment [50]. In particular, scholars from these traditions emphasize the role of values in clinicians’ understanding of what constitutes and how they seek to practice excellent care. Moreover, they stress the nature of clinical knowledge as tacit, context bound, and ephemeral rather than codifiable, transferable, and enduring such that the implementation of health IT into clinical settings often departs substantially from those envisaged by system developers and designers [50]. Accordingly, insights of this kind cast significant doubt on the capacity to hard code norms into technological systems in ways that can be seamlessly integrated into clinical environments, especially when these norms concern the sharing of health data, which is typically and legally understood as highly sensitive and worthy of special protection.

The results of this study are presented in 3 parts, which correspond with the study’s analytical approach outlined in previous sections. First, it briefly describes the health care sector’s engagement with blockchain technologies to date in the United States, United Kingdom, and at the transnational level. Second, it critically reflects upon a series of 6 challenges that must be overcome and 3 normative trade-offs that must be satisfactorily resolved if blockchain technologies are to cross the valley of death, transitioning successfully from invention to innovation in health care settings. Third, it critically discusses key findings by referring to a selection of wider academic literature concerned with organizational cooperation and radical versus incremental technological innovation and reflects upon the promises of patient-controlled blockchain-enabled EHRs before offering some concluding reflections.

The Motsi-Omoijiade and Kharlamov study [21] revealed that, apart from the Estonian government’s eHealth initiative [22], active engagement with blockchain technology in health care began around 2016, primarily in the United States and, to a lesser extent, in Europe, with several recent initiatives occurring at the transnational level. As of November 30, 2019, their study had identified 128 health care blockchain applications (in which a blockchain application is defined as providing a specific functional health care purpose so that a single blockchain system might provide multiple applications) from an English-language website review, over half of which were geographically located in the United States (65 applications), with the United Kingdom as the next most popular site of activity (12 applications) [21]. However, less than half of these had a commercially available blockchain product or service, with most still at the experimental or development stage. Of these applications, a substantial minority (50/128, 39.1%) focused on applications to enable user-controlled access to some kind of personal health data, with a significant proportion concerned primarily with using blockchain to facilitate health care administration (34/128, 26.6%) and support for patient care or health management (primarily in facilitating remote care consultations between patient and clinician located elsewhere) or in the form of wellness applications to encourage healthy behaviors (31/128, 24.2%) and for medical research data management (13/128, 10.2%; Multimedia Appendix 2).

A closer examination of the technical and contextual dimensions of these applications and their primary sources of funding revealed that, first, the overwhelming majority of blockchain for health care initiatives had used permissioned or hybrid systems, in which the tasks of sharing and updating the ledger are restricted to those authorized to do so. Second, in both the United States and the United Kingdom, private sector investment and funding have been driving these initiatives, although various government programs support blockchain initiatives, including funding support [51,52]. Although some early initiatives sought to generate funding via an initial coin offering, including start-up firms claiming specialist blockchain expertise, these have failed to generate positive returns for investors (and a significant number of initial coin offerings generally were merely vehicles for fraud) [23,53]. More recently, investment funding has been provided by venture capitalists, evidencing their confidence in the technology’s potential value to the health care sector. The commercial and entrepreneurial expertise that they bring to the sector might help the fledgling industry navigate the fraught and uncertain early development phase [54,55]. Third, the current and ongoing focus of interest in blockchain for health care, at least in the US context, has been predominantly at the intraorganizational and business-to-business (B2B) level rather than being primarily concerned with clinical care provision. Much of this activity has primarily concerned blockchain systems for managing nonclinical data, as health care providers explore the capacity to harness blockchain technologies to enhance administrative and operational efficiency. Fourth, by comparison, the UK health sector’s experience and engagement with blockchain technology has been far more muted, with only a handful of initiatives, all at the pilot or early-stage implementation phase. These initiatives are primarily for patient care management, with very limited reliance on blockchain functionality. Finally, several promising transnational blockchain initiatives to facilitate medical and health research have been launched in recent years. The following discussion briefly outlines the US and UK experiences (as the 2 most active sites of blockchain engagement in health care) and more recent transnational blockchain initiatives.

In the United States, ongoing blockchain activity in health care is coalescing at the intraorganizational and B2B level. These applications are intended to facilitate data sharing between business units within the same umbrella health care organization or within recently established consortia of health care organizations seeking to cooperate in the sharing and management of specific forms of health care data stored via a blockchain-enabled ledger [55]. The primary drivers supporting blockchain development to date appear to have focused on its potential to reduce costs and enhance efficiency in health care administration and operations. These applications are broadly concerned with either health care operations management, primarily in the management of supply chains, or administrative data pooling.

Turning first to health care operations management, considerable blockchain activity has occurred either to streamline and automate internal operational processes or to improve the efficiency and verifiability of supply-chain management [29,56]. Examples of the former include the Coalesce Health Alliance consortium’s development of blockchain to improve the accuracy and efficiency of patient health care claims management across different entities within the Blue Cross Blue Shield ecosystem [57]. Similarly, the US Department of Health’s Office of National Security has built a blockchain providing organizational units with linked, real-time access to a standard set of spend data to improve the department’s procurement process, reportedly generating major efficiency gains [58]. In health care supply chain management, significant blockchain activity has occurred to address the potentially serious risks of a compromised health care supply chain [56]. The Food and Drug Administration has actively encouraged these applications by launching a pilot project (announced in February 2019) to encourage drug supply chain stakeholders to develop digital systems to comply with the Drug Supply Chain Security Act 2013, which mandates the creation of an electronic, interoperable system that can trace and identify distributed prescription drugs across the United States. It attracted 26 participants (including several pharmaceutical supply chain stakeholders [59,60]), generating a variety of projects. These include the MediLedger Project, which sought to build a blockchain network around a tamper-proof ledger of pharmaceutical supply-chain transactions to inform responses to product ID verification requests communicated via a permissioned messaging network [61]. The Pharmaceutical Utility Network has taken a different approach, pursuing a platform first strategy [61,62] rather than focusing on a specific use case. It is developing an open-source blockchain platform that integrates regulatory requirements (such as the Drug Supply Chain Security Act) to enable those involved in the pharmaceutical supply chain (including pharmaceutical manufacturers, distributors, dispensers, and software vendors) to use the platform’s services to demonstrate compliance with regulatory requirements, seeking to use blockchain as a form of RegTech. [63,64] Other supply-chain management blockchains in the health care sector focus on single use cases, often with some RegTech functionality, such as the Clinical Supply Blockchain Working Group’s platform [65], which is now seeking to apply its blockchain-based inventory and event-tracking system to a real clinical trial [66].

Blockchain applications are also being used to facilitate administrative data pooling at the intra- and interorganizational levels. Health care consortia in the United States began emerging in 2018, seeking to use blockchain either to create a single ledger shared between member organizations to serve as a single source of truth or to enable network members to create a shared pool of records to which access is controlled and recorded via the blockchain. For example, the Synaptic Health Alliance [67] aims to use a blockchain network to address costs, delays, and inefficiencies in provider directory data (comprising demographic information about physicians and other providers), which insurers are required by federal law to maintain and keep up to date. Each insurer has typically maintained its own directory; however, these often contain inaccurate data, resulting in delayed claims and payment processing. Synaptic’s blockchain pilot seeks to create a common source of truth for provider directory data created by pooling and comparing each member’s directory data to create a complete, accurate shared directory.

Similarly, the Professionals Credentials Exchange (ProCredEx) is a consortium of health care organizations seeking to enhance the efficiency of the physician credentialing process [57]. In the United States, when a new physician is hired or begins working for a new payer’s network, the employing health care organization must gather a wide variety of certificates and credentials, a process that takes up to 6 months (sometimes longer), with physicians often required to supply evidence of their professional credentials to a dozen different organizations or more, which must be repeated for all physicians every 2 years by each organization [29]. The ProCredEx blockchain network enables organizations to contribute their credentialing records (essentially, a digital asset) to a shared pool, effectively creating a members-only digital asset exchange so that members can access verified credentials and actively contribute credentials information that other members can acquire. The shared ledger tracks asset ownership, exchange, and use and forms a basis for asset reputation. Buyers of these information assets finance the platform, whereas curators of the assets receive payment for their contributions, as do partners who help facilitate the use of the blockchain network [68,69].

In comparison with its US counterpart, interest in blockchain in UK health care has been considerably more limited [70]. The UK blockchain use cases have been directed at patient care management largely outside the clinic, in which secure and auditable data sharing remains the central functionality provided by blockchain technologies. Unlike the United States, UK health care is delivered primarily via a publicly funded National Health Service (NHS), in which NHS hospital treatment and primary care are free at the point of use to UK residents. Decisions about the commissioning of services, including the use of new technologies, are taken primarily at the local level by entities known as clinical commissioning groups or exceptionally at the national level by NHS England, which is informed by guidance issued by the UK’s National Institute for Health and Care Excellence [71]. The NHS Long Term Plan states that the NHS will seek to “make better use of data and digital technology” [72] as part of the NHS digital transformation agenda; however, it makes no explicit reference to blockchain technologies. However, the NHS England’s Director of Digital Development has been reported as having a general interest in considering blockchain as one of a variety of technologies that the NHS will explore [73].

Nevertheless, NHS England has commissioned Dovetail Labs to develop a novel digital application to enable different members of a multidisciplinary team working with type 2 diabetes patients to share health information. The application operates via a distributed ledger that logs patient consent to share digital data along with user authentication, data access, and transfer records [74,75]. In addition, at least two local clinical commissioning groups have commissioned small-scale digital applications that are described as using blockchain technology. Hence, a partnership between Guardtime and Instant Access Medical and Healthcare Gateway has produced a comprehensive blockchain-supported personal care record platform (called MyPCR). The platform is intended to assist patients in managing chronic long-term health conditions by issuing digital alerts to help them adhere to their personalized treatment plan or personal care pathway via a smartphone app, granting patients complete access to their personal care pathway while generating an automated tamper-proof record of health data provenance and integrity that is compliant with data protection legislation [76]. Similarly, MedicalChain has launched a blockchain pilot enabling patients to create a free wallet to manage access to their digital health records, enable general practitioner video consultations, and enable them to pay for services using cryptocurrency (with users incentivized to pay for telemedicine services with Medicalchain’s MedTokens) [77,78].

At the transnational level, a rather different kind of blockchain application has emerged, which enables network members to run secure but privacy-preserving computational analyses on the data of other members to improve their algorithmic models for research purposes while the data never leaves the host organization [79]. For example, members of the Machine Learning Ledger Orchestration for Drug Discovery blockchain network, comprising 10 large pharmaceutical companies, 5 technical partners, and 2 universities, use blockchain and federated learning to train an algorithm to identify a rare mutation in cancer, enabling pharmaceutical companies to collaborate on therapeutic drug discovery. Each pharmaceutical company can, via the network, run the machine learning algorithms of their academic partners on each other’s data sets. The data remain at their local site so that proprietary information from one data set cannot be leaked to another. Nonsensitive algorithmic models are exchanged between the members, which are then collectively consolidated to improve the predictive performance of the algorithmic models by leveraging all the data across the federation. A permissioned blockchain tracks and logs all operations taking place on the federated data using a software framework (Substra) for enabling the execution of distributed machine learning tasks in a secure way. The value of collaboration is particularly evident in attempts to develop drug treatments for rare diseases: each individual organization will have too few patients with a given rare disease to undertake statistically significant analysis; however, by pooling access to their data to enable federated learning, collaboration without data sharing becomes possible. Similarly, the AI Centre for Value-Based Healthcare consortium has created a federated learning network with patient data from 4 hospitals and 3 universities, allowing research partners to train algorithms on the federated data set. Collaborations of this kind, which use blockchain networks to facilitate privacy-preserving, federated data access, offer considerable promise to advance medical research [29]. Health care blockchain industry expert Robert Miller [80] observes the following:

Although the above 6 challenges might be overcome in time, several further challenges rooted in inherent tensions between desirable qualities or functional requirements that arise when configuring blockchain applications may prove more intractable. Although technical blockchain experts have identified various design trade-offs when building blockchain systems for specific purposes [82], reflecting the micropolitical nature of software choices [98], the following 3 are particularly apposite to health care settings:

The above findings draw attention to the number and variety of formidable, multidimensional challenges that must be satisfactorily addressed if blockchain technologies are to traverse the valley of death. Nevertheless, this study also shows how early engagements with blockchain in health care have begun to demonstrate that these technologies can enable and facilitate novel, valuable forms of health care data sharing and cooperation in real-world health care settings under specific circumstances. The following discussion critically reflects upon these key findings by reference to 3 quite different strands of academic literature: first, it examines the character and tensions inherent in these incipient forms of blockchain-enabled cooperation; second, it draws on insights from innovation studies to consider the character of blockchain as radical or incremental health care technologies; and third, it evaluates the prospects of blockchain for health care’s favorite use case, that is, to enable patient sovereignty over EHRs while overcoming the currently siloed approach to patient data.

Recent health care blockchain initiatives have successfully demonstrated how technology can facilitate limited, purpose-specific forms of cooperation through the shared pooling of data to solve common problems. These incipient forms of cooperation involving data sharing, which consortia of health care organizations are actively seeking to develop, rely upon interactions that organizational studies scholars refer to as coopetition. Although the interaction between firms conventionally focuses on either of 2 contrasting and antagonistic logics—competition (traditionally defined as the conflicting and rivalrous relationship between firms) on the one hand and cooperation on the other [134]—the actual interaction between firms can involve cooperation in some activities while competing in others [135]. As these coopetitive relationships entail 2 diametrically opposing logics of interaction, they are inherently complex, generating tensions between and within organizations [136,137]. In particular, each organization faces conflicting incentives: a desire to cooperate through the pooling of resources to generate shared benefits on the one hand and the incentive to capture private benefits for themselves on the other [137,138]. Several theories have been offered, claiming to predict the effect of coopetition on firm performance [137,139], including transaction cost theories. Transaction cost theories highlight the difficulties of fostering trust between parties in a coopetitive relationship, as each participant has incentives to opportunistically behave while facing high levels of uncertainty [140]. This creates barriers to open collaboration, making it difficult to develop the necessary level of trust needed for common projects to succeed. On the other hand, several scholars have noted that the inherent tension between cooperation and competition arising within coopetitive relationships can, if managed efficiently, create shared value and generate beneficial outcomes for each party [137]. On this view, the key to successful coopetition is effective management of the coopetitive tensions within the relationship that nurtures and maintains an appropriate balance between competition and collaboration. Various insights from this literature help illuminate the challenges likely to arise within health care consortia comprising organizations that would otherwise regard themselves as competitors seeking to share health care data via a permissioned blockchain network. The configuration of access rules within a permissioned blockchain system offers a potentially novel mechanism through which social distrust might be replaced by computational trust, thereby enabling new forms of cooperation at the B2B level that might not otherwise occur, as the trust gap is too difficult to overcome.

That said, the need for strategies to successfully manage the tension between organizations within the network highlights the importance of a blockchain network’s internal governance arrangements, particularly in establishing and maintaining rules concerning changes to the network’s architecture, protocols, rules of admission, and incentive mechanisms. Details about the internal governance arrangements that underpin the various blockchain consortia that have emerged in recent years are not publicly available because of the confidential nature of the underlying partnership agreements. Nevertheless, one would expect that formulating and maintaining a set of governance arrangements that will prove durable and resilient over time is likely to be extremely difficult, as the interests of participants are not wholly aligned and hence, difficult to settle in advance. These internal governance arrangements must identify how critical decisions about, for example, the structure of economic incentives or rewards for participants to engage in the consensus protocol, how the network will be maintained, and how other changes to the network’s structure and operation will be made and by whom. Potentially conflicting interests may not be readily apparent at the time of the network’s inception but may subsequently arise as organizational needs, the larger industry context, and other external factors inevitably change over time. However, perhaps it is only when the rubber hits the road in the context of specific disagreement between network participants that the critical need for robust governance structures that command the respect and allegiance of the network’s members becomes apparent.

Finding an appropriate but flexible equilibrium between the need for social trust between network participants on the one hand and hardwiring computational trust into the technical architecture and operation of the blockchain system will be a very tough nut to crack. It remains an ongoing and continuing challenge for the foreseeable future, at least until blockchain in health care achieves a level of maturity in which a widely shared set of agreed norms concerning the core requirements of good blockchain governance can emerge. Furthermore, these networks are likely to encounter what has been referred to above as the computational trust paradox; by seeking to rely on computational trust to provide a basis for enabling cooperation between firms, this may reinforce and accentuate the need to nurture and maintain social trust between the parties in domains in which computational trust cannot be secured.

Early engagement with blockchain technologies in health care contexts has largely used permissioned blockchain systems (including so-called enterprise blockchains) rather than open, permissionless systems that many blockchain advocates believe will revolutionize social cooperation between strangers without the need for conventional trusted third-party intermediaries, such as banks and governments. Although the blockchain for health care promise has not typically emphasized the role of permissionless blockchains, a significant revolutionary narrative is evident in claims that blockchain technology will disrupt health care [17]. Within this narrative, blockchain is portrayed as enabling radical patient empowerment achieved via hard-coded access controls, securely facilitating the seamless exchange of patient records currently stored in disparate data silos while enabling patients to exert fine-grained control over who is granted access to those records, wherever located, and on what terms [141,142]. It is blockchain’s potential to overcome the many existing technical, legal, and bureaucratic obstacles that obstruct the free flow of health data while preventing patients from exerting control over access to their own health care records that is typically highlighted rather than emphasizing the role of permissionless blockchains in achieving this vision.

The health care sector’s focus on permissioned (rather than permissionless) blockchain systems to date will disappoint radical blockchain enthusiasts such as Bruce Schneier, a well-known computer security expert. Schneier claims that permissioned blockchains are “completely uninteresting” as they are no different from centralized databases in relying on conventional forms of trust to facilitate social cooperation [143]. However, his perspective fails to recognize that even open, permissionless blockchains ultimately and invariably rely on social trust to support their internal governance arrangements [112,113]. By enabling participants to rely on computational trust mechanisms to enforce the explicitly agreed terms of their cooperation, permissioned blockchains could facilitate novel forms of cooperation, leading to valuable and potentially transformational change.

The transformational potential of permissioned blockchain systems can be illuminated by reference to a distinction drawn by technology management researchers between inventions, which refers to an “idea, sketch, or model for a new or improved device, product, process or system” and innovations, which, in the economic sense, arise “only with the first commercial transaction involving the new product, system or device” [144]. Within this literature, a further distinction is commonly made between incremental and radical innovation. Incremental innovations introduce relatively minor changes to an existing product, exploiting the potential of the established design (although they may entail considerable skill and ingenuity) [145-148]. In contrast, radical innovations are based on different engineering and scientific principles, potentially opening up whole new markets and applications [146,147,149]. This distinction is considered to have important competitive consequences: incremental innovation tends to reinforce the capabilities of established organizations, whereas radical innovation forces them to ask a new set of questions, draw on new technical and commercial skills, and use new problem-solving approaches [36,146,148,150]. Hence, radical innovation often creates great difficulties for established firms [148,151-153]. As the late Clayton Christensen famously argued, radical innovation can disrupt the entire industry as incumbent firms lose out to smaller firms with fewer resources who use these radical innovations to deliver superior functional performance, eventually leading to their adoption by the incumbent’s established customers [154].

It is too early to assess whether permissionless blockchains will ultimately form the basic technological architecture underpinning a dominant design for particular kinds of health care applications. It is not possible to reliably predict whether they will come to be regarded as incremental or radical innovations or, indeed, whether they come to be understood as innovations at all or merely just an interesting invention with little real-world utility. However, the preceding insights suggest that we cannot assume that the use of permissioned rather than permissionless blockchains in health care necessarily implies that they cannot subsequently establish themselves as radical innovations. Bruce Schneier’s dismissal of permissioned blockchains overlooks the possibility that they may offer particular functional properties capable of meeting a very specific sectoral need. In functional terms, permissioned blockchains are something of a hybrid—analogous to centralized databases insofar as participation and access require authorization from a network controller but can mathematically provide the verified security and automated audit functionality of permissionless blockchains without the heavy computational expense. Accordingly, they might prove radical in their effects [155], creating shared value by facilitating new forms of coopetitive collaboration between health care organizations while generating significant efficiencies.

Mention has already been made of frequent references in both academic and industry literature to the potential of blockchain-enabled EHRs to revolutionize health care. According to this vision, blockchain operates as a form of middleware, facilitating the flow of data between independent IT systems, thereby integrating disparately located silos of patient health care records while enabling patients to exercise fine-grained but automated control over their EHRs via smart contracts that automate the execution of patient instructions or consents [14,109]. In so doing, blockchain is widely portrayed as solving the tension between the need to respect the privacy and confidentiality of individual health records and recognizing the tremendous knowledge potential unleashed by pooling and aggregating patient data. Blockchain for health care scholarship has largely taken these claims at face value. Although various blockchain-enabled EHR projects are currently being experimented with, the preponderance of activity appears to reflect the views of industry experts, who advise that blockchain applications focusing on patient care records are best avoided in the early stages of the sector’s engagement with the technology because of the demanding and complex legal and regulatory requirements that apply to personal health information. Nevertheless, many believe that these demands can eventually be overcome, so that patient-controlled, blockchain-enabled EHRs will eventually emerge [91,117]. Even if the difficult and complex challenges and tensions identified in the preceding section can be satisfactorily overcome, whether these systems will live up to their promise depends upon the validity of underlying assumptions about their benefits, particularly in clinical contexts.

Academic literature concerned with health IT implementation has hitherto been dominated by the technology acceptance model (TAM), which originates from the perspective of health information systems research that studies the systems that support health and medical work [156]. This approach, developed jointly by doctors with an interest in computers and computer scientists with an interest in medicine, adopts a positivist outlook that regards the relationship between technology and their expected benefit as linear and causal [81]. Similar assumptions appear to underpin 2 distinct, albeit related, elements of the vision of blockchain-enabled EHRs offered by their proponents. The first assumption is that blockchain will enable the seamless integration of patient records currently stored in distinct data silos, thereby effectively providing patients and clinicians with a single, up-to-date, and comprehensive repository of each patient’s medical records over his or her lifetime. The second assumption is that configuring blockchain-enabled EHR systems to enable patients to control access to their records will ensure respect for privacy without impeding the transfer and sharing of patient data for clinical and other legitimate purposes.

In relation to the first assumption, Berg et al [157] highlighted studies of EHR implementation that emphasize the personalized nature of health care work, thus setting “natural limits to the possibilities of IT to revolutionise this work.” These studies suggest that the considerable energy and resources thus far devoted to various components of the EHR failed to substantially improve the quality or efficiency of frontline clinical work. Moreover, they argue that EHRs are unlikely ever to produce dramatic gains in the quality of care because of the importance of the creative human work needed to bridge the gap between clinical design and technical reality [50]. In contrast, biomedical literature often rests on a TAM model, evoking a belief that IT systems will make clinical information instantly available, implicitly assuming that meaning can be transmitted unproblematically along with the data contained in the EHR. This assumption also appears to underpin the beautiful dream of blockchain-enabled EHR systems, suggesting that, if properly designed, blockchain will enable more accurate, secure, and timely data access that will drive quality improvements across health care, including clinical care. However, studies from more sociologically informed traditions roundly reject this assumption, providing evidence that clinical data must be interpreted in context and framed before they become meaningful, and this is not achieved simply by placing information on an electronic platform that is accessible by multiple users [50]. These studies rest on assumptions that differ from those underpinning the TAM model (including understandings of what counts as success for the purposes of evaluating health IT systems), drawing on a wider range of methodological approaches [158]. They highlight the critical role of context, culture, and the values brought to bear by medical professionals in clinical environments, identifying the clinical consultation as a complex social encounter that occurs within a heavily institutionalized environment [50]. In particular, scholars from these traditions emphasize the role of values in clinicians’ understanding of what constitutes and how they seek to practice excellent care and the nature of clinical knowledge as tacit, context-bound, and ephemeral rather than codifiable, transferable and enduring [50]. These studies find that in many failed EHR projects, technical designers typically missed these subtleties and produced artifacts that fitted poorly with the situated nature of knowledge and the microdetail of clinical work practices [81].

Conversely, the TAM model assumes that the failure of EHRs to generate their expected benefits can be largely explained by shortcomings in EHR system design and implementation, resulting in user resistance to the technology [50], which can be overcome by system design improvements and more sensitive implementation. One of the most significant lessons from studies of EHR adoption is that considerable clinician resistance to these systems has often resulted from the unintended but radical alteration and disruption of clinical workflows and patient interactions accompanying the introduction of EHRs, adversely affecting physician workload [81,122,159]. In addition, the data captured in these records have been described by a legal expert as often error prone, incomplete, unprotected, and dispersed across numerous organizations unknown to the patient [130]. However, if used as middleware to support the integration of EHRs across disparate data silos, blockchain technologies should not, in theory, affect clinical workflows or practices, as they operate as a backend technology. In other words, blockchain should not exacerbate workload burdens or introduce additional integration work of the kind that has typically accompanied EHR implementation. However, HIMSS [160] warns that:

This cautious view, offered by one of the health care IT sectors’ leading industry bodies, suggests that one cannot assume that implementation of blockchain as a backend technology will not add further system complexity simply by avoiding any change to the front end experience of users [98].

The second assumption underpinning the promise of blockchain-enabled EHR systems—that they will enable patient data sovereignty and empowerment by providing patients with fine-grained control over who may securely access their health care records and on what terms—resonates with broader societal shifts in favor of self-service economy models across many sectors [161]. Blockchain for health care advocates assumes that patient-controlled health care records will resolve dilemmas arising from the tension between ensuring compliance with privacy and confidentiality norms and duties and fostering the aggregation of patient care records for medical research and other legitimate purposes [162]. This assumption is likely to be both mistaken and naive for several reasons. First, although it is essential that patients are enabled to exercise their rights of informational self-determination in relation to health and care information that directly pertains to them [163], some patients will enthusiastically embrace the capacity to control access to their medical records [164], whereas others will not [165]. A significant proportion of patients (including children and those with mental illness or disability) cannot make informed decisions about access to and sharing of their clinical data; therefore, alternative consent models will be needed. Second, there will be circumstances in which patient consent cannot be secured; however, the ability to access that patient’s health records will be necessary, particularly in emergency situations. Third, in other circumstances, patient rights to data privacy and confidentiality may be legitimately overridden by compelling public interests, particularly when appropriate technical and organizational measures are taken to safeguard those interests so that patient consent is neither legally nor ethically needed to justify access to their records. For example, the public interest in data sharing and access can, particularly in times of public health care emergency, justifiably override individual rights to privacy and the need for patient consent to data sharing.

Taken together, the vision of patient data sovereignty underpinning blockchain-enabled health records exhibits a techno-solutionist mindset, reflecting a belief that technological fixes can be used to solve complex social problems [166]. Critiques of this kind draw attention to the complex and messy set of interacting norms, practices, and dynamics that arise in the real-world contexts for which simple technological solutions are unlikely to be found, which the disappointing experience of EHR implementation has vividly demonstrated. Despite this, the underlying information as property paradigm that informs these beliefs appears to hold considerable sway in contemporary debates about data governance, both within health care and beyond [167]. However, as the German Data Ethics Commission points out, supporting and promoting the practical capacity of patients to access their health care records and take an active role in decisions about access to those records does not necessitate a propertisation model of data governance, which underpins the views of those who favor the making of micropayments to data subjects in return for access to their personal data [163,168,169].

Apart from unfounded assumptions that technological access controls built into health IT systems can be expected to successfully mediate and resolve the complex interests in patient data, any such shift in favor of patient sovereignty over health care records may reflect an underlying reconfiguration of the ethical basis upon which patients receive care. Rather than characterizing patients as vulnerable individuals and beneficiaries of care provided by an expert clinician who is professionally obliged to act in their best interests, patients may increasingly be expected to self-manage their own medical records based on largely unexamined claims that this will empower them to exert greater control over their own care [85]. However, if these systems are configured in ways that force adherence to norms that are at odds with the basic cultural and moral norms of contemporary health care settings, this might provoke backlash. This might occur, for example, if systems are designed to shift responsibility for care to patients and away from clinicians and care providers in ways considered contrary to the professional duty and commitment of clinicians to act in the best interests of their patients [170]. Alternatively, if patients are unable to make meaningful decisions about the sharing of their data, they are likely to stick with defaults; however, these might fail to reflect legitimate patient expectations and existing informational privacy and confidentiality norms. These and other similar risks underline the importance of meaningful stakeholder engagement in the design and implementation of blockchain systems, as well as the importance of more critical engagement with the logic of empowerment that frequently accompanies their promised benefits [50].

Accordingly, the vision underpinning blockchain for health care’s favorite use case, which is capable of seamlessly integrating patient-controlled EHRs accessible by clinicians in real time wherever located, is based on problematic and unrealistic assumptions. Their promised benefits are therefore unlikely to be realized in practice. Even if blockchain technologies can operate as middleware, enabling organizations to access and retrieve patient health care records stored at different sites in real time, blockchain cannot ensure that the information stored in those records is an accurate representation of the underlying real-world events they purport to reflect. Conferring responsibility for making access decisions on patients themselves will not avoid conflicting and sometimes difficult trade-offs between respect for patient privacy and other rights and legitimate interests implicated in health care. In other words, the health care data silo problem is only one aspect of a much larger, more complex set of needs, rights, and interests associated with medical and health care information, which are likely to continue to defy hard-coded solutions.

However, one of the most valuable insights arising from technology-in-practice studies of EHRs for understanding the real value that blockchain-enabled EHRs might create arises from the recognition that there are two conflicting work processes in play with EHRs: immediate clinical care (primary use) on the one hand and tasks such as audit and research, which are one step removed from the clinical encounter (secondary use) on the other. These studies show that when EHRs are used as a formal tool (eg, with structured templates and a requirement for data to be coded), they often slow down and frustrate the clinical encounter but can greatly accelerate secondary uses of clinical data. Accordingly, Greenhalgh et al [50] argue that, rather than promising that the EHR will save time or make clinical care more efficient, a more honest message would be that creating accurate and complete clinical records requires the sacrifice of time and effort by frontline clinical and admin staff, which is (sometimes) justified by more benefits for efficient business processes (eg, billing) governance and research. In other words, the real value of blockchain-enabled health records might rest in their secondary use, enhancing health care administration and medical research rather than in substantially improving clinical care.

This study has both empirical and theoretical strengths. Its strengths are 3-fold. First, by focusing attention on the health care sector’s experience in attempting to use blockchain technologies for specific purposes, it fills an important gap in the existing literature by offering a more grounded, evidence-based but theoretically informed appraisal of blockchain’s prospects for transforming health care, unlike the burgeoning academic literature that has focused overwhelmingly on the technology’s potential to solve health care problems. Second, it identifies and critically examines a series of complex, multidimensional implementation challenges that must be satisfactorily confronted if blockchain technologies are to be widely taken up within health care contexts, illuminating the nature and dimension of these difficulties by referring to a range of theoretical perspectives. Third, the critique offered here contrasts sharply with the considerable hype that accompanied the emergence of blockchain technologies. It provides a more theoretically and empirically grounded appraisal of the oft-proclaimed radically transformative potential of blockchain technologies in a specific domain, notably within complex health care environments that are typically saturated with technologies, many of which are highly sophisticated and often safety-critical.

The limitations of the study rest in the lack of publicly available, authoritative data concerning blockchain uptake in health care. Hence, the snapshot provided by the study of current and ongoing industry engagement and experience with blockchain relies heavily on web-based investigations of gray literature, particularly industry publications, to investigate the focus and tenor of discussions about these technologies in health care and the trajectory of their development. This methodological approach was limited in several significant aspects, insofar as it relied on unconfirmed industry sources publicly available on English-language websites as a substantial source of evidence for understanding the current state of blockchain development and implementation in health care contexts. As the accuracy of claims made on public websites is practically impossible to verify and often fails to provide significant financial information about the level of investment or revenue generated (or expected to be generated), the findings on blockchain take-up in the health care sector are not comprehensive, particularly given the growing interest in developing blockchain applications in non–English-speaking countries (eg, China [171,172] and Japan [173]).

Although significant assurance about the reliability and robustness of the study’s provisional findings was obtained by eliciting feedback from industry experts through the second focus group workshop while cross-checking the validity of these provisional findings against the published insights of industry specialists [174-176], the findings concerning the state of industry experimentation and maturity offered here are neither authoritative nor comprehensive. Nevertheless, they provide worthwhile insights into the general state of the health care sector’s engagement with blockchain technologies to date, the particular domains and applications in which this engagement is occurring, and the current direction of travel. Accordingly, these findings offer a useful reference point for critical reflection in the context of future investigations of blockchain in health care and beyond.

This paper has demonstrated that the health care sector’s engagement with blockchain technology has grown steadily since 2016, with the most promising activity occurring at the intra- and interorganizational level to enable data sharing and cooperation in health care administration and medical research. Although various blockchain initiatives have appeared in response to the COVID-19 pandemic [177], in which the rapid spread of misinformation intensified the importance of ensuring trustworthy health care information management, industry experts suggest that they have not hitherto taken root [178]. Contrary to the focus of the academic literature, the health care sector’s engagement with blockchain has not focused primarily on enabling and integrating patient-controlled EHRs into clinical practice. It is in nonclinical contexts that early-stage health care engagement with blockchain is now producing evidence that blockchain-enabled cooperation can create both collective and individual value for network members that is greater than the sum of its parts, generating potentially significant efficiency gains [121]. Accordingly, blockchain in health care cannot currently be dismissed as a passing fad. Although scholars of innovation studies have identified various barriers to innovation that arise when technological inventions seek to cross the valley of death during the development phase of innovation, this literature has tended to treat technological inventions as a black box. In contrast, the analysis offered here highlights the importance of attending to the design and functionality of the technology itself and the particular health care contexts and fields of practice into which it might be applied in ways that may deepen and enrich innovation studies literature that has tended toward a high level of generality and abstraction.

This study identified 6 complex and multidimensional challenges and 3 normative tensions that must be resolved if blockchain technologies are to be made readily implementable in health care. Negotiating and overcoming these challenges and tensions will require considerable commitment, including time, investment, and willingness by health care organizations to take substantial risks, experiment, learn, and share knowledge across the sector. It suggests that the technology’s progress through the development process will be difficult and lengthy. Moreover, as the National Advisory Group on Health Information Technology advised in its 2016 report, “implementing health IT is one of the most complex adaptive changes in the history of healthcare, and perhaps of any industry” [179]. Another leading expert observes that “while policy makers are calling for technology to be implemented rapidly and at scale, the reality is that when dealing with the multiple complexities of health and care, it is extremely difficult to go beyond small-scale demonstration projects” [85].

Even if blockchain succeeds in crossing the valley of death, it does not necessarily follow that these technologies will live up to their promise. The underwhelming experience of health IT offers a sobering reminder, with Kellermann and Jones [180] noting that despite the increased use of health IT in the United States, with aggregate annual national expenditure on health care growing from US $2 trillion in 2005 to roughly US $2.8 trillion in 2013, the efficiency of patient care is only marginally better. In the United Kingdom, 10 years after the launch of the National Program for IT, which promised to revolutionize care in the English NHS [181,182], it was described by the UK Secretary of State for Health as a “huge disaster that became impossible to deliver” despite costing £3.66 billion (US $4.84 billion) [183,184]. These experiences highlight the serious gap between the grand visions of IT’s transformative potential in health care and the fraught nature of implementation, given the inherently complex, dynamic, and context-driven nature of health care. They throw into high relief the inherent difficulties associated with seeking to hard code norms into complex sociotechnical systems in ways that that can satisfactorily resolve and mediate a wide variety of often conflicting rights, interests, expectations, norms, and risks associated with information sharing in dynamic, complex but safety-critical health care settings.

Although the blockchain for health care promise is rooted in a belief that blockchain systems will facilitate secure data sharing while enabling more fine-grained management of health care data, thereby creating more and better data that will drive improvements across the sector, real-world engagements and experiences with the technology in health care settings to date suggests that blockchain’s core value proposition is more nuanced and narrowly framed. Blockchain’s value generally (both within health care and beyond) rests primarily on its capacity to provide an automated, mathematically verifiable, highly secure, and therefore, highly trustworthy record-keeping function. It is this functional capacity that supports the technology’s nascent potential as middleware, facilitating various kinds of health care data sharing and exchange, particularly between health care organizations where a lack of social trust rooted in institutional incentives for opportunistic behavior might be replaced with the computational trust that permissioned blockchain systems can provide. In so doing, blockchain systems may enable new forms of cooperation that generate shared value from the pooling of health care data, although whether these networks can develop governance strategies that can successfully and sustainably mediate the relevant interests of network participants remains to be seen.

However, the difficulties of ensuring that the ledger accurately, systematically, and comprehensively tracks and reflects the real-world phenomenon that it claims to record may mean that the envisaged benefits of blockchain’s automated track and trace function may not be fully realized. Computer scientists and mathematicians have long recognized the garbage in, garbage out problem: the quality of output is determined by the quality of the input. Blockchain technology cannot guarantee that data arriving at and recorded in the ledger is an accurate, complete, and comprehensive record of the underlying real-world events that it purports to track; however, blockchain advocates typically overlook this critical vulnerability. In other words, although blockchain systems can deliver valuable functionality in terms of automatically and securely recording the handling of data items (for example, when a digital record has been viewed by a particular user), they cannot guarantee the integrity of the underlying data.

Nevertheless, blockchain’s automated audit function might offer real and significant value because, by creating a highly secure and verifiable record, it offers a vehicle through which organizations can demonstrate compliance with data handling norms at scale, thus operating as a form of RegTech. In this way, blockchain as middleware can automatically and securely track and record the location and handling of data items. Therefore, it might have real potential to facilitate the integration of health data silos stored in a variety of locations across multiple organizations using different IT systems [185]. The value of this contribution could potentially be significant, reducing costs and improving efficiency, transparency, and security, and could be widely applied across any sector in which sensitive data generation, processing, and sharing occur in large volumes.

Blockchain is frequently portrayed as offering the potential to deliver radical and positive transformations to many sectors, including health care. This study has identified significant activity within the health care sector aimed at exploring how blockchain technologies might deliver real value. It has been found that the technology is still in its infancy and that the nature and scale of its value to health care remain unproven [29]. Experience of early health care sector engagement has shown that the relevant question is not how can blockchain be used in health care settings but under what conditions can blockchain be realistically expected to provide a viable, scalable and efficient solution to a concrete health care problem in real-world health care settings that would add significant value relative to alternative solutions? In other words, when considering whether to engage with blockchain technologies, organizations must ask themselves whether a blockchain is really necessary to solve the problem at hand or whether other alternative approaches are preferable.

This shift in mindset is reflected in the divergence between the rhetoric of blockchain-enabled health care data sharing, which focuses primarily on the capacity of blockchain technologies to enable the seamless yet secure sharing of patient records that will enhance clinical decision-making, and the reality of engagement with blockchain, which has largely avoided clinical contexts. Instead, the most innovative health care blockchain applications have occurred at the interorganizational level, enabling the sharing of administrative data between health care organizations to improve the efficiency of health care administration. The most recent initiatives are aimed at facilitating shared access to the secondary use of patient data for medical research through cooperative endeavors to train algorithmic models on data sets in a secure, privacy-preserving manner.

However, to succeed in this endeavor, there remain very significant challenges associated with achieving social trust and cooperation, including the need for the effective and legitimate governance of blockchain networks, that no amount of technological sophistication or hard-coded solutions can, on their own, satisfactorily resolve. It remains to be seen whether these and other tensions inherent in these incipient forms of blockchain-enabled coopetition between health care organizations will be satisfactorily overcome and whether blockchain applications in health care might be characterized as radical or incremental technologies. Accordingly, the possibility of blockchain technology precipitating a revolution in the delivery of health care of the kind envisaged by blockchain for health care advocates appears to have been exaggerated. Nevertheless, there are real prospects of using blockchain in ways that could lead to genuine health care improvements. However, progress toward this goal is likely to occur slowly, incrementally, and more by stealth rather than through radical and rapid disruption over a short period and—at least in the first instance—likely to be concentrated across a much narrower range of applications than the blockchain for health care promise suggests.