New technologies have disrupted health care and imply exposure to complex scenarios. The Internet of Medical Things (IoMT) is increasingly receiving attention from practitioners and scholars to provide more alternatives for monitoring patients’ conditions; allowing access to private medical data; and obtaining secure and flawless tools to protect data from attacks that can access or steal essential information or, in some cases, produce a patient fatality [1-3]. In this new technological landscape, recent studies have highlighted that blockchain technology with smart contracts (SCs) provides the most reliable data security, cryptographic capacities, and decentralized storage and can lead to a low-cost ecosystem and sustainability in the medical setting [4,5].

The health care value chain is another research area where SCs have consistently shown effectiveness in avoiding counterfeiting and ensuring product security and safety. Implementing SCs on value chains can guarantee data provenance, eliminate unnecessary intermediaries, and provide an immutable history of transactions considering all the internal and external stakeholders. Although electronic health records (EHRs) are the most sensitive information in the SC environment, all the sensor devices are essential to provide a robust framework [6]. A health care value chain faces different challenges and aims to monitor diseases by considering real-time patient status updates. Furthermore, some visible barriers include data interoperability and communication among applications, medical devices or machines, and institutions. This increases complexity and continuously impacts costs and efficiency [7]. However, acquiring the logic of the value chain and adapting cutting-edge technologies to specific needs can save millions of lives and enhance quality of life for others.

There are different approaches to analyzing literature data. A classic methodology considers a small number of research studies to synthesize the different perspectives and angles of the topic and provide future avenues of research. In addition, there are various frameworks, such as systematic or structured reviews. Thus, a bibliometric framework considers an extensive quantity of literature by using statistical software. Multiple objectives are pursued, such as recognizing intellectual models and new trends. Our study aimed to provide a bibliometric analysis of SCs on the health care value chain and, thus, obtain a fundamental knowledge of the intellectual, social, and conceptual structure and other clustering techniques. This review’s analysis was primarily interdisciplinary, seeking to discover barriers and possible gaps in the SC domain.

Trust reduces complexity [8,9], manages uncertainty by compensation [8], and is an element of social capital [10]. Trust involves the truster and trustee as actors and expectations about actions in the future that could entail some risk for the trustee [11]. Trust applied to new technologies implies the transition from personal trust to system trust [8,11,12].

The literature refers to trust as a requirement of sustainable and human-centered technology [13]. Technologies, through trust, also look to fulfill social interests and be responsive. This affirmation is essential when technologies—including blockchain and SCs—are introduced in fields such as health care [11].

A blockchain is a distributed ledger [14] formed by chronologically ordered blocks [15,16]. It consists of multiple nodes connected peer to peer [15] and without a hierarchy among them [15]. Each block has an identification linked to the previous one via a reference or hash [14,15]. There is a genesis block, which is the first block of the chain, and any subsequent block also has the hash that allows for the identification of the previous one [15]. Blocks have a block header—that usually includes the hash of the last block, a time stamp, and a nonce [16]—and a payload or data with transactions [15,16]. The blockchain holds a consensus algorithm [14] that adds information to the chain [16]. Blocks are accepted or refused based on this algorithm [15]. In doing so, miners, who are a particular type of node, solve a challenge (ie, a mathematical puzzle) to verify the block and receive a reward [16] (ie, “gas”). Information cannot be modified once a block has been added to the chain. SCs are codes stored in a blockchain [17] containing transactions executed without intermediaries [14]. Thus, technologies such as blockchains and SCs promise transactions that do not require trust among parties—called trust-free, trustless [18], or trustless trust [11]—and distribute trust among the system—called distributed trust [11]. It is relevant to point out that their origins are independent despite the extensive joint use of blockchains and SCs. SCs were propounded as a transaction protocol [19], whereas blockchains uses cryptography to allow for the exchange between participants worldwide without the necessity of a central authority [20]. Blockchains and SCs look for trust development, where trust lies in the system design [18].

SCs strengthen the capabilities of a blockchain [21], aiming to (1) implement customizable business logic [22] through different functionalities [23] and (2) automatize the execution of preassigned transactions [3,24-26]. One of the most essential characteristics of SCs is that transactions are automatically executed [27]. For this, the interposition of a third party is not required [27]. This characteristic improves efficiency, accountability [28], and trust building [28,29]. SCs are transparently auditable [30] owing to their immutability. The decentralization of these systems also improves their resilience. Centralized systems represent a unique vertex of failure, a limitation that is overcome by SCs [31] deployed in blockchains [32]. Thus, SCs are especially relevant in health care as system trust generators [26,29].

This study fills a gap and responds to a request in the literature. Even though SCs are relevant in health care, a sufficient assessment is necessary. Some studies characterize SCs but do not refer to health care. It is the case of the proposal by Alzhrani et al [32], which presented a characterization of some SCs in real-world systems based on a blockchain’s taxonomy. Nevertheless, this study does not focus on health care, and only 11 SCs were selected to exemplify its taxonomy. Other studies have focused on the health care sector but had a limited scope [14,33] and have not provided an in-depth characterization of SCs. Vargas and da Silva [14] assessed 3 case studies or frameworks related to SCs in the IoMT. Sookhak et al [33] limited their study to entering patient data into EHRs.

Several theoretical studies or literature reviews regarding blockchains in health care have considered or mentioned SCs in the health care domain. Nevertheless, they need to focus on providing in-depth information about the role and features of SCs. The closest one is the review by Marbouh et al [1], who inquired about the advantages of blockchains in improving patient safety. The challenges and opportunities of this technology were the starting point of the aforementioned study, which referred to the uses of blockchains in health care. It introduced SCs and some uses of blockchains. Still, these contracts were not the study’s primary goal, and it did not offer a systematic survey of the literature based on propounded frameworks.

Furthermore, Villarreal et al [29] studied blockchains in health care management systems and classified the architectural mechanisms in the literature. This study acknowledged SCs’ relevance and problems in health care, but they were not systematized and referred to one specific telemedicine case. Similarly, in the study by Arbabi et al [34], the authors surveyed studies on blockchains in health care. They acknowledged the relevance of SCs but did not review their attributes in depth and suggested further assessment of the role of SCs.

Similarly, Khatri et al [35] systematically analyzed the broad topic of health care and blockchain integration and selected 50 publications for an in-depth analysis. In their study, the authors mentioned SCs; nevertheless, they did not propound specific functionalities or roles of SCs or link them with the authors’ proposal about blockchains. Finally, McBee and Wilcox [36] studied the application of blockchains in medical imaging. Nonetheless, the literature has barely mentioned SCs to specify the origin of the name “blockchain 2.0” and its relationship with artificial intelligence (AI) [37].

Finally, Arbabi et al [34] suggested further research on SCs in health care. The authors mentioned that the potential of SCs in health care requires an in-depth assessment. In addition, Hawlitschek et al [38] propounded the development of additional research on the design of trusted interfaces. Thus, our study aimed to fill a gap in the literature—detailed in Table 1—and be responsive to its suggestions [34,38], focusing on an extensive review of SC frameworks in health care as elements that enhance trust and shift the traditional concept of trust among people to system trust, providing a characterization of it.

Our study aimed to provide a holistic understanding of SCs in health care. We focused on developing a structured literature review of the state-of-the-art scientific landscape of new technological advances, tendencies, and bibliometric analysis to help provide a comprehensive understanding and up-to-date overview of the recent research and outline new perspectives and future research directions.

These contributions allow this research to fill a gap in understanding and respond to the suggestions by Arbabi et al [34] and Hawlitschek et al [38]. We adopted a systematic literature review approach because it allows for the replication of this study. A quantitative bibliometric analysis followed by an in-depth qualitative review of the studies enabled us to provide a detailed standpoint of the topic.

The search produced 374 results. The exclusion criteria were based on language (only English), type of source (review article, retraction, editorial material, and retracted publications were excluded), and availability (green submitted publications were excluded, and only open access publications were included). All these restrictions were established based on WoS filters. Finally, 163 publications were assessed. The selection encompassed the following criteria. Only those publications that (1) had the health care industry as their focus, (2) included a framework (framework, system, model, prototype, or similar), and (3) incorporated details about the roles of SCs and identified SCs were included in the study. In addition, the texts of the studies by Subramanian et al [64] and Elgendy et al [65] could not be accessed. A list of the 163 papers and their assessment results based on the aforementioned criteria can be reviewed in Multimedia Appendix 2. A final sample of 70 publications was selected to be reviewed. Figure 1, which was made using the template propounded by the PRISMA organization, details the selection process [66].

We assessed the selected studies to find the main trends. The biblioshiny app and the bibliometrix tool (K-Synth Srl) was used in this process [67]. First, the data were screened. A total of 7% (5/70) of the studies had incomplete information about the authors’ keywords. Some techniques such as multiple correspondence analysis [68] and network analysis [50] are sensible to missing data [69]. Keeping these studies could have biased the results.

Consequently, we decided to withdraw 7% (5/70) of the articles [70-74]. Thus, we included 65 articles in the bibliometric assessment. The aforementioned 7% (5/70) of the articles were withdrawn only for these purposes; they were read in depth for reporting in the literature review section. In addition, the terms “smart contract,” “smart legal contract,” “smart contracts,” and “smart legal contracts” were signaled as synonyms where required.

The studies were published in 34 journals, and one of the journals, IEEE Access, published 29% (19/65) of the studies. The countries with the most citations were the United States, the United Arab Emirates, South Korea, and Egypt with >100 citations per country. Table 2 summarizes the descriptive information.

The historical evolution of this topic encompasses 6 years, from 2018 to 2023. The oldest study in our group was the one by Dagher et al [75], published in 2018. Although this theme is relatively new, its historical evolution (Figure 2) reflects the relevance of COVID-19. The literature has propounded that this disease was one of the most important in recent years [76,77]. Until 2020, a total of 3 topics represented the field. After 2020, a new independent concept, security, emerged, and the term health care acquired relevance. In addition, the map of subjects organizes them into 4 groups given their significance and development (Figure 3). It shows that security, privacy, medical services, traceability, innovative health care, cybersecurity, and data sharing are the most developed and relevant topics, known as motor subjects. The IoMT constitutes a niche theme and developed topic. Cloud and edge computing are also niche themes. On the other hand, machine learning has a low level of development, which could be explained by its novelty and a medium level of relevance. This situation could reflect the first attempts to use SCs and machine learning together in the same framework.

We obtained the conceptual map and keyword cluster [67] through factor analysis, a data reduction technique. Multiple correspondence analysis was used. This technique depicts the words on a map based on a similarity measure [67]. The study yielded 3 factors in 2 dimensions (Figures 4 and 5), representing 74.44% of the variability or inertia (dimension 1: 51.28%; dimension 2: 23.18%). The factorial analysis tree supported the existence of 3 dimensions under the cutting line (Figure 5). The first factor represents the concern for the technical aspects of the topic. In this factor, Ethereum and InterPlanetary File System (IPFS) had the highest contributions (Ethereum: 3.083%; IPFS: 2.054%; together: 5.137%). The second factor concerns data privacy and security. Security, privacy, and data privacy represented the highest contributions to this factor (security: 8.191%; privacy: 4.498%; data privacy: 4.026%; together: 16.715%). Finally, the third factor is concerned with the processes themselves. Supply chain and supply chains had the highest contributions (supply chain: 5.135%; supply chains: 10.066%; together: 15.2%).

This study aimed to provide an extensive understanding of SCs in health care through a comprehensive review of their roles and characteristics based on the frameworks developed in the literature. In doing so, this study fills a gap in the literature [34]. SCs are code or short programs whose output is a transaction [15] that is produced automatically when certain previously established conditions are met. These programs reflect the business logic [15] and provide flexibility (requirements can be introduced) and efficiency (their execution does not need additional enforcement) to a blockchain. The extensive review of frameworks offered insights into the business logic that was prioritized.

A quantitative bibliometric assessment highlighted the topic’s novelty and importance, including subjects with high relevance and development. In addition, 3 factors were identified. These factors guided the in-depth review of each framework. Two roles of SCs were found—(1) process improvement, which encompassed 6 topics; and (2) patient data privacy enhancement, which encompassed 3 topics—and technical strategies and features that provide efficiency were found. These results provide more detailed information than previous inquiries, which have mentioned only this technology’s use for medical devices, prescription tracking, remote patient monitoring, counterfeit drugs, EHRs, and incident report systems [1]. In addition, several stakeholders were identified.

This study acknowledged the relevance of technical topics. Previous studies have provided taxonomies based on technological features that consider the blockchain type, ledger type, consensus, identification, authentication and authorization, and EHR storage and features [33]. This study provided a new perspective based on the features selected by the literature that provide efficiency to systems.

The studies on trust and health care had different scopes. Some authors focused on trust in the system [146,147]. Others considered trust among various actors in this system, such as physicians and patients [25]. Independently of the orientation, the main proposal was that trust is relevant for accomplishing health care goals. The quantitative and qualitative review findings characterized system trust in health care SCs, which considered systems [146,147] and actors [25], through what is trusted, who trusts, and how trust is supported.

Finally, this study revealed different levels of impact on the concerns of multiple health care stakeholders. Individuals’ rights—such as privacy [17,71], mobility [72,76,77,85], or health [88,89]—can be better protected. Physicians and researchers can use enhanced access to traceable and secure data when required [21,105]. SCs offer traceability, immutability, transparency, decentralization, automatization, and security to the different suppliers related to health care—such as hospitals, clinics, laboratories, research centers, and pharmacies—for their processes [16]. Governments can also obtain benefits from SCs. SCs facilitate private compliance with governmental regulations [90,91], preventing crime such as counterfeit drugs. In addition, SCs can facilitate the coordination of processes that require governmental intervention [22,31,81]. This study highlights new technologies, such as consensus and cryptographic methods, to address data security and privacy concerns. Second, this study details the different efforts to make potential solutions scalable and provide them to policyholders. Finally, this study shows the complexity of the health care systems, which is crucial for understanding the definition of multiple agreements among various involved stakeholders.

The strength of this review lies in its systematicity and comprehensiveness. This review evaluated studies that included SCs in health care in their frameworks. We applied several procedures to reduce the risk of selection bias. The criteria used in the selection process tried to avoid researchers’ subjectivity, provide transparency, and allow for the review’s replicability [148]. The PRISMA principles were followed, a peer review procedure was contemplated, 1 database was selected, and its coverage and overlap with 2 databases—a specialized and a multidisciplinary one—was assessed. Moreover, quantitative bibliometric techniques were guided by and complemented with an in-depth and detailed literature review.

Even so, the selection of articles had 2 significant limitations. First, the different academic databases needed to be unified or standardized. Indeed, we had to decide between possible bias caused by the differences between databases and data wrangling or selecting 1 database and assessing its coverage and overlap. Our decision was the latter, but we acknowledge that it entails a limitation. Second, our study included only open access documents because they were relevant to guarantee the review of this study and ensure our research’s transparency.