1 (page number not for citation purpose) Blockchain in Healthcare Today ISSN 2573-8240 ORIGINAL RESEARCH Predictors of Commercial Success in Blockchain Healthcare Insurance: A Mixed-Methods Analysis Raaga Likhitha Musunuri, BDS, MS   ; Kimberly S. Brooks, MD, MS   ; Swapna Ashish Patel, BPharm, MS   ; Trupti Jayesh Majgunkar, MS   ; Krisha Patel, BS, MS   ; and Erin O’Neill, MS   Masters Students in Health Informatics, Bouvé College of Health Sciences and Khoury College of Computer Sciences, Northeastern University, Boston, Massachusetts, USA Corresponding Author: Raaga Likhitha Musunuri, Email: dr.raagalikhitha@gmail.com DOI: https://doi.org/10.30953/bhty.v8.401 Keywords: blockchain, commercial success, General Data Protection Regulation, healthcare insurance, Health Insurance Portability and Accountability Act of 1996, market capitalization, regulatory factors Abstract Background: Blockchain healthcare insurance offers substantial potential for improving data transparency, efficiency, and security. However, many blockchain healthcare projects struggle to scale up and achieve com- mercial success. Despite technical feasibility studies, limited research exists on the commercial success of these projects. This study explores the technical, regulatory, and strategic factors that contribute to market success in blockchain healthcare insurance initiatives. Methods: Using exploratory mixed methods, we combined quantitative market data analysis from CoinGecko Application Programming Interface (API) with manual metadata curation from publicly available data. We conducted descriptive statistics, Pearson correlation, and multiple regression analysis to evaluate relationships between key variables and market success. Results: The Health Insurance Portability and Accountability Act of 1996 (HIPAA) compliance emerged as a significant predictor of higher market cap (β = +12.6, p = 0.006), while insurance partnerships negatively impacted success due to early-stage complexity (β = –15.3, p = 0.009). The model explains 95.7% of market cap variance (adjusted R² = 0.957). Findings: These findings demonstrate how crucial technical preparedness and regulatory alignment are to the successful commercialization of blockchain-based health insurance. The importance of organizational scale is highlighted by a moderate association (r = 0.83) between team size and market success. The importance of strategic alliances and regulatory compliance is further shown by the theme analysis of white papers. Investors should concentrate on projects with well-defined regulatory policies, while entrepreneurs should give HIPAA compliance top priority early on. It is recommended that policymakers create more precise regulatory frame- works for blockchain in the medical field. For more thorough insights, future studies should increase the sample size. Plain Language Summary Blockchain technologies have the potential to transform healthcare insurance by improving data security, trans- parency, and efficiency. However, many blockchain healthcare projects struggle to progress beyond the pilot stage. Our study explored factors influencing the market success of blockchain healthcare insurance projects, revealing that compliance with the Health Insurance Portability and Accountability Act of 1996 (HIPAA) and regulatory standards are key predictors of success. Additionally, having too many early-stage partnerships can hinder progress, while strategic partnerships are more beneficial. Larger project teams lead to better market performance. Entrepreneurs should prioritize regulatory compliance, and policymakers should establish clearer blockchain frameworks. These factors are crucial for both technical functionality and commercial viability. Submitted: April 28, 2025; Accepted: July 8, 2025; Published: August 1, 2025 https://orcid.org/0009-0008-6823-8054 https://orcid.org/0009-0000-2675-4060 https://orcid.org/0009-0009-8905-8404 https://orcid.org/0009-0009-2195-7091 https://orcid.org/0009-0007-7815-9678 https://orcid.org/0009-0000-3404-3007 mailto:dr.raagalikhitha@gmail.com https://doi.org/10.30953/bhty.v8.401 Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.4012 (page number not for citation purpose) Raaga Likhitha Musunuri et al. As the 21st century began, the healthcare sector faced enormous pressure to offer high-quality services while keeping costs in check. Blockchain has evolved into a promising approach for implementing a distributed and secure healthcare data management and sharing service. From a conceptual standpoint, block- chain can be viewed as a distributed collaborative system upheld by various entities in an environment where trust cannot be assumed. Blockchain enables secure data processing among multiple parties without the need for trusted third par- ties. Secure data processing among multiple parties can occur, and since the launch of Bitcoin in 2008, blockchain has garnered intense focus from academia and industry. Financial projections based on research and from markets indicate substantial growth in this sector, with the global blockchain market expected to expand from approxi- mately $17.21 billion (€15.45 billion) in 2023 to $29.35 billion (€26.35 billion) in 2024, reflecting a compound annual growth rate of 70.6%. This revolutionary approach to data security and verifi- cation is transforming sectors where privacy and integrity are paramount. Due to its outstanding characteristics, such as data traceability, tamper-proof data storage, and service availability, blockchain-based healthcare data management has been the subject of extensive research. With the addition of access control mechanisms, block- chain-based solutions enable flexible data sharing, pro- mote accountability, and guarantee data authentication. As an example, Patientory (PTOY) leverages blockchain technology for storage and transfer of healthcare data, which guarantees secure and efficient data exchange.1 Health insurance represents a critical domain where blockchain’s transformative potential is particularly sig- nificant. The current healthcare insurance framework faces substantial challenges such as claim fraud, data security, interoperability, and trust challenges. The finan- cial impact of these fraudulent activities is staggering, with estimates suggesting that healthcare fraud diverts approximately 10% of global healthcare spending, threat- ening economic stability worldwide. Despite extensive research, the healthcare insurance industry still lacks real-time, comprehensive solutions for analyzing complex data from diverse sources. Blockchain technology combined with ensemble learning offers a promising solution through its decentralized, tamper-re- sistant ledger, enhanced security, and smart contract capabilities. By distributing patient data across networks, blockchain reduces centralized system risks while ensur- ing data immutability creates verifiable, unalterable med- ical records.2 However, there is a critical research gap between techni- cal feasibility and commercial success in real-world imple- mentations. Studies reveal that commercially successful blockchain healthcare projects represent merely 0.24% of tracked blockchain initiatives, as highlighted by Fang3 with most enterprise efforts remaining confined to explor- atory groups and not progressing beyond pilots or limited trials into mainstream adoption, as emphasized by Krish- nasamy and Gopalakrishnan.4 This research addresses the critical commercialization gap in blockchain healthcare insurance by investigating which factors meaningfully dif- ferentiate market-successful implementations from failed initiatives. Our research moves beyond theoretical feasi- bility to examine concrete determinants of commercial viability. To fill the research gap in understanding what makes blockchain healthcare insurance projects successful, the important factors were grouped into three main catego- ries: technical, regulatory, and strategic. We developed a conceptual framework (Figure 1) to address this identi- fied research gap in commercialization success factors for blockchain healthcare insurance projects, emphasizing real-world implementations rather than merely theoreti- cal possibilities. Our framework synthesizes insights from previous blockchain healthcare adoption studies3,4 while explicitly focusing on market success rather than imple- mentation feasibility. Technical factors include the underlying blockchain platform (e.g., Ethereum vs. custom solutions), specific use case orientation (e.g., insurance claims processing vs. patient record management), and system architecture design. Regulatory factors center on compliance read- iness, particularly adherence to the General Data Pro- tection Regulation (GDPR) and the HIPAA, which may serve as critical signals of institutional trustworthiness and market credibility. Strategic factors encompass orga- nizational characteristics such as the number and quality of partnerships, team size, and geographic focus. These connected factors together affect how the mar- ket views a project, how ready institutions are to adopt it, and how it stands against competitors, which ultimately impacts the project’s success in the market, measured here as log-transformed market capitalization. Based on earlier research that highlights the importance of trust in regulations for adopting blockchain, we suggest that reg- ulatory factors, especially HIPAA compliance, might have the biggest impact on a project’s success in the market, possibly accounting for major differences in how well it commercializes. Literature Review Contemporary healthcare insurance systems face mount- ing challenges from fragmented data architectures that impede effective information exchange and create vulner- abilities to widespread fraud. This fragmentation mani- fests as siloed patient information across providers and insurers, generating significant interoperability issues as https://doi.org/10.30953/bhty.v8.401 Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.401 3 (page number not for citation purpose) Success in blockchain healthcare insurance disparate systems employ incompatible data formats and standards. The financial impact of these systematic weaknesses is staggering. Medical identity theft alone costs the health- care industry over $30 billion (€27 billion) annually, while healthcare fraud schemes worldwide result in approximate losses of $260 billion (€233 billion) to medical insurance funds. These figures highlight the urgent need for inno- vative approaches to manage healthcare insurance data that address interoperability and security concerns. The scope and variety of healthcare insurance fraud further highlight this pressing challenge. In 2016, a significant federal investigation resulted in charges against more than 300 healthcare professionals involved in fraudulent billing schemes totaling approximately $900 million (€807 billion).5 Beyond financial fraud, practices such as inappropriate opioid prescribing, often incentivized by deceptive phar- maceutical marketing campaigns that minimize addic- tion risks, compromise patient safety. These fraudulent activities collectively threaten the financial sustainability of healthcare insurance systems and patient well-being, creating momentum for technological solutions that can enhance transparency, security, and trust across the healthcare insurance ecosystem while preserving appro- priate privacy protections. The evolution of healthcare reimbursement models introduced new complexities in fraud detection. Tradi- tional item-based payment systems have gradually shifted toward diagnosis-based models such as Diagnosis- Related Groups (DRGs), where insurers pay fixed amounts based on diagnostic categories rather than individual services rendered. While this approach helps control excessive medical treatment and rising costs by standardizing payments, it also creates new avenues for fraud through diagnostic code manipulation. Healthcare providers may intentionally upgrade low-cost disease codes to high- er-paying alternatives to maximize reimbursement. The sheer volume of patient cases, with some Chinese prov- inces processing 15 million inpatients annually, makes manual auditing impractical, necessitating advanced technological solutions that can efficiently identify suspi- cious patterns while maintaining data integrity across the healthcare insurance ecosystem.6 Blockchain serves as a distributed solution to the growing complexity of healthcare data, offering real- time analysis, traceability, and counterfeit resistance.20 The immutable ledger and cryptographic protections of this system are ideal for the insurance sector, where data integrity and audibility are essential.1 By identifying unusual claim trends automatically, blockchain-enabled fraud detection systems enable proactive interven- tions, thereby preserving data privacy. Nevertheless, the adoption of blockchain in health insurance is inconsis- tent due to regulatory misalignment and technological innovation.2 Only 0.24% of blockchain ventures in the healthcare sector achieved commercial viability, primar- ily due to regulatory uncertainties and limited ecosystem integration.3 Healthcare data are subject to privacy regulations like HIPAA, and projects that prioritize regulatory alignment and confidentiality are more likely to gain institutional trust and be successful.7 Integrating decentralized identi- fication systems with compliant blockchain frameworks elevates patient autonomy, privacy, and trustworthiness, which are key factors concerning the uptake of health- care. However, the fragmented regulatory environment and absence of interoperability standards pose significant Fig. 1. Conceptual framework of determinants of success in blockchain health insurance. HIPAA: Health Insurance Portability and Accountability Act of 1996; EDPR: ElcomSoft Distributed Password Recovery (software). https://doi.org/10.30953/bhty.v5.xxx Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.4014 (page number not for citation purpose) Raaga Likhitha Musunuri et al. challenges to institutional adoption and scalability in healthcare blockchain endeavors.8 According to studies on blockchain healthcare insur- ance initiatives, team size and strategy alignment are crit- ical factors. The lack of resources or an extremely limited focus tends to make teams unable to secure and sustain ongoing development and scaling.8 Conversely, larger, multidisciplinary teams are generally better attuned to address technical, legal, and regulatory issues associated with products.2 Collaborations among providers, regu- lators, insurers, and other stakeholders are essential for the success of programs. Excessive early-stage insurance partnerships can complicate operations and postpone financial returns.9 The results of literature studies indicate that strategic quality is more significant than quantity in these programs. Blockchain offers a workable answer to the problems that healthcare insurance systems face, including fraud, data fragmentation, and compliance, but only if technical implementation, regulatory alignment, and organizational maturity all line up. Methods and Findings Study Design and Rationale This study uses a combination of methods (e.g., looking at numbers from the market and gather- ing information by hand) to understand what makes blockchain healthcare insurance projects successful (Figure 2). The market data help us see how successful the market is (e.g., market cap), while manually pull- ing information from white papers adds important details about things like rules and partnerships, which are key to understanding how blockchain healthcare insurance projects work. Prior research focused on the technical feasibility of the blockchain in healthcare, while the market success factors remain understudied and unclear. Our study aims to do an exploratory analysis of the regulatory, technical, and strategic implications that enable market success and adaptability, such as the role of HIPAA compliance and partnerships with insurance companies. Fig. 2. Mixed methods methodology. HIPAA: Health Insurance Portability and Accountability Act of 1996. https://doi.org/10.30953/bhty.v8.401 Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.401 5 (page number not for citation purpose) Success in blockchain healthcare insurance Data Sources and Collection The primary data sources include market data from the CoinGecko API (https://www.coingecko.com/en/ap) and publicly available white papers and project documentation (snapshot collected on April 20, 2025). The data retrieval used the standardized /coins/markets and /coins/id end- points, extracting project-level information including mar- ket capitalization (US dollars), current trading volume, circulating supply, launch year (genesis date), and plat- form type. Retrieved data were saved in Comma-Separated Values (CSV) format and processed in Python (pandas v2.2.1). In addition to market data, metadata was manually extracted from the white papers and public documentation of the selected blockchain healthcare insurance projects. These documents provided valuable insights into various factors influencing the market success of these projects, including technical architecture, regulatory compliance, and strategic focus. The metadata collected focused on sev- eral key variables: HIPAA compliance, GDPR compliance, partnerships, platform type, use case, and team size. Sampling Strategy A purposive sampling method was used to select 10 block- chain healthcare insurance projects. The selection was based on the availability of white papers, market presence, and relevance to the healthcare insurance sector. Projects were included if they had publicly available white papers and market data, such as market cap and trading volume. Additionally, the projects selected were operational or had a visible market presence, indicating they were beyond the proof-of-concept phase. Defining a Successful Project The sample captured a cross-section of geographically diverse, thematically varied, and technically distinct projects in the blockchain healthcare ecosystem, despite its small size, which limits generalizability. But it was appropriate for an exploratory analysis in a niche and evolving sector. The HIPAA compliance was assessed as a critical factor in deter- mining whether the project adheres to United States health information privacy standards.10 Compliance with GDPR was considered for projects operating in European markets, ensuring they meet the data protection and privacy regula- tions.11 The nature of partnerships with insurance compa- nies, healthcare providers, and other relevant organizations was examined, as these partnerships can enhance the proj- ect’s credibility and integration into the healthcare system. While HIPAA compliance was evaluated for projects targeting the US market and GDPR for those operating in Europe, other relevant data protection laws such as the California Consumer Privacy Act (CPRA) were not systematically included in this analysis; future research should expand the regulatory scope to capture additional regional frameworks. The type of blockchain platform used by the projects was also documented, as it influences scalability, security, and interoperability. The use case of each project was also recorded to determine whether it focuses on insur- ance claims processing, medical record management, or another aspect of healthcare insurance. Finally, team size was noted as it could correlate with the project’s ability to scale and deliver successful outcomes. Data Processing and Statistical Analysis Key variables were “cleansed” (identify and resolve poten- tial data inconsistencies or errors) and standardized. The dependent variable, market capitalization, was log-trans- formed (log1p) to normalize skewness, as raw market caps varied widely across projects. The study used several statistical methods for data analysis and was conducted using Python (pandas, statsmodels, and seaborn libraries). Descriptive statistics were calculated to summarize the key characteristics of the selected projects, including market cap, team size, and compliance rates. Pearson correlation coefficients were computed to explore the relationships between different variables, such as team size and market cap or HIPAA compliance and market success. Multiple regression analysis was also conducted using log-trans- formed market cap as the dependent variable. This method allowed for the evaluation of how different independent variables contributed to market cap while controlling for the influence of other variables. The log transformation of market cap was necessary to normalize the data, as market caps can vary significantly across projects. Analyses were performed using Python libraries: stats- models (v0.14.0) for regression modeling and SciPy (v1.14.1) for correlation analysis. Visualization of key find- ings was performed using matplotlib (v3.10.0) and Seaborn (v0.13.2). The use of mixed methods in this study is crucial to understanding the factors influencing market success. Quantitative data, such as market caps, alone would miss the critical business, technical, and regulatory context that is essential for understanding why certain projects succeed or fail. Manual metadata extraction from white papers and documentation provided important contextual informa- tion regarding the organizational, strategic, and regulatory dimensions of the projects, which could not be captured by market data alone. Market data collected from CoinGecko was validated against secondary sources (e.g., CoinMarket- Cap) to ensure accuracy within a 5% threshold. Thematic Analysis Methodology This study also used a thematic analysis to qualitatively assess the white papers and public documents of selected (n = 10) blockchain healthcare insurance projects, which helped us understand the organizational, strategic, and regulatory factors that may not be captured through quan- titative market data alone. To achieve this, we collected https://doi.org/10.30953/bhty.v5.xxx https://www.coingecko.com/en/ap Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.4016 (page number not for citation purpose) Raaga Likhitha Musunuri et al. the data from the white papers and public project doc- umentation, which primarily had insights about various factors such as technical architecture, partnerships, regu- latory compliance, and strategic focus that added insights on market success. After this, we systematically coded these white papers using a deductive approach, which was derived from our research questions and literature review. This included categories such as regulatory compliance (e.g., HIPAA, GDPR), partnerships (with healthcare providers, insurers, etc.), platform type (Ethereum, custom, etc.), tokenomics (utility, rewards systems), and data privacy and artificial intelligence (AI) focus. This also involved identifying references to these themes within the white papers and assigning corresponding codes. For example, a reference to HIPAA compliance in a white paper was coded under the regulatory compliance theme, and other such things. Two independent researchers conducted the coding pro- cess, ensuring the reliability and consistency of the results. Any discrepancies were discussed and resolved through consensus. This process aimed to minimize coding bias and improve the accuracy of the analysis. After the initial coding, themes were further refined and categorized into broader patterns of strategic focus. For example, partner- ships were further divided into strategic partnerships with healthcare providers, insurance partnerships, and other partnerships (e.g., technology partners and investors). Two independent researchers reviewed manual metadata coding to ensure consistency. Discrepancies were resolved through consensus discussion. Reliability metrics (e.g., inter-rater agreement) are reported in Appendix A. This process minimized errors and ensured the data’s accuracy. However, future research should apply structured coding frameworks to standardize the extraction and analysis of metadata, which would further improve the reproducibil- ity of the study and reduce potential biases introduced by manual data collection. The themes were analyzed to identify the most influential factors impacting market suc- cess. These insights were then triangulated with quantita- tive data (e.g., regression results, correlations) to provide a more comprehensive understanding of the factors con- tributing to market success. Methodological Challenges The primary methodological challenges that arose were handling multicollinearity and bias minimiza- tion. Moderate multicollinearity was detected (e.g., HIPAA compliance variance inflation factors [VIF] ≈ 9) which was addressed through careful interpreta- tion of coefficients and acknowledging limitations in extrapolation beyond exploratory findings. Manual metadata extraction was standardized through pre- defined coding categories. Sampling bias was mini- mized by adhering to explicit project selection criteria. In addition, keeping the market data volatility in mind, all the CoinGecko data was collected within the same 1-week window (April 2025) to control cryptocurrency market fluctuations. Ethical Considerations All data utilized were publicly available through open- access sources. No human subjects or patient-level data were involved. Institutional Review Board (IRB) approval was not required. Results Descriptive Statistics and Project Characteristics Table 1 presents the descriptive statistics for the 10 blockchain healthcare insurance projects included in this study. The table includes various factors such as market cap, team size, HIPAA compliance, GDPR compliance, and insurance partnerships, which helped in understanding the interdependencies that affect the performance of these projects in the market. The projects exhibit considerable variation in market capitalization, with a mean of $3.76  mil- lion (standard deviation [SD] = 3.04) and a range from $0.3 to $8.2 million. Team sizes averaged 43.5 members (SD = 24.27), ranging from small teams of 10 to larger organizations with 80 members. Half of the analyzed projects demonstrated HIPAA compliance, while a larger proportion (80%) were GDPR-compli- ant. The projects maintained an average of 1.5 insur- ance partnerships (SD  = 1.08), ranging from 0 to 3 partnerships. Table 1. Descriptive statistics of 10 projects. Variable Count Mean SD Min 25% 50% 75% Max Market cap (in millions USD) 10 3.76 3.04 0.3 0.83 3.9 6.13 8.2 Team size 10 43.5 24.27 10 22.5 45 60 80 HIPAA compliance 10 0.5 0.53 0 0 0.5 1 1 GDPR compliance 10 0.8 0.42 0 1 1 1 1 Insurance partnerships 10 1.5 1.08 0 1 1.5 2 3 GDPR: General Data Protection Regulation; HIPAA: Health Insurance Portability and Accountability Act of 1996; Max: maximum; Min: minimum; SD: standard deviation; USD: United States dollars. https://doi.org/10.30953/bhty.v8.401 Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.401 7 (page number not for citation purpose) Success in blockchain healthcare insurance Market Capitalization Distribution As seen in Figure 3, the market capitalization distribution is heavily skewed, with MediBloc (MED), a blockchain healthcare platform for secure medical data management, dominating the chart. This supports the finding of reg- ulatory compliance being a significant success factor, as MED was one of the projects with the highest compli- ance and market cap, with close to $74.5 million (€66.73 million), substantially outperforming other projects in the sample. Interestingly, as we can see from Figure 3, there is no active market value, despite technical prow- ess and promise in projects like Humanscape (HUM), a patient-centered blockchain healthcare ecosystem, Doc. com (MTC), a blockchain-based telemedicine platform, Lympo (LYM), a blockchain-based health and wellness platform with incentivized fitness activities, AI Doctor (AIDOC), a blockchain-based healthcare platform using AI for medical diagnostics, and Remote Patient Moni- toring (RPM) applications. This points to the significant challenges faced by many blockchain healthcare initiatives in achieving substantial market traction. This skewed dis- tribution emphasizes the finding that successful projects possess distinctive characteristics that separate them from less successful counterparts in this emerging sector. The correlation matrix visually represented in Figure 4 reveals important relationships between key variables in our study. As observed in the figure, there is a strong pos- itive correlation between HIPAA compliance and market capitalization (r = 0.81), which indicates that regulatory compliance is one of the primary factors that drive a blockchain health insurance project’s success. Team size also showed a remarkable correlation with market capi- talization (r = 0.83), suggesting that organizational scale contributes to project success, as they might provide a bet- ter competitive edge. Insurance partnerships displayed a moderately strong correlation with market capitalization (r = 0.71), highlighting the importance of strategic alli- ances in achieving market success. Interestingly, GDPR compliance showed a weak correlation with market capitalization (r = 0.05), sug- gesting that while European data protection regulations may be important for global operations, they appear to have less direct impact on market success compared to US healthcare regulations in this sample. However, GDPR compliance showed moderate correlations with team size (r = 0.51) and insurance partnerships (r = 0.49), which may indicate indirect effects on market performance through organizational maturity and part- nership development. HIPAA Compliance and Market Success As observed in Figure 5, HIPAA compliance played a major influence on market success with these projects. HIPAA-compliant projects showed a higher market capi- talization compared to non-compliant counterparts. This also strongly supports our regression findings, which identified HIPAA compliance as a significant positive predictor of market success (β = 12.6, p = 0.006). The dis- tinct statistical significance that this relation has shown is that regulatory compliance is critical for blockchain Fig. 3. Market capitalization. AIDOC: AI Doctor; LYM: Lympo; MED: MediBloc; MTC: Doc.com; MTN: Medicalchain; HUM: Humanscape; PTOY: Patientory; RBM: Robomed Network; SOLVE: Solve.Care; USD: US dollars. https://doi.org/10.30953/bhty.v5.xxx http://Doc.com http://Doc.com http://Doc.com Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.4018 (page number not for citation purpose) Raaga Likhitha Musunuri et al. healthcare projects. The compliant projects had nearly 12.6 times higher market capitalization than those that do not. This reiterates that regulatory trust and insti- tutionality are important in the healthcare blockchain sector. Insurance Partnerships and Market Performance In addition, when we look at insurance partnerships and market capitalization, there are further interesting relationships that emerge (Figure 6). The scatterplot shows an overall moderate positive correlation with Fig. 4. Correlation heatmap. HIPAA: Health Insurance Portability and Accountability Act of 1996. Fig. 5. HIPAA Compliance versus Log Market Cap Boxplot. HIPAA: Health Insurance Portability and Accountability Act of 1996; USD: US dollars. https://doi.org/10.30953/bhty.v8.401 Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.401 9 (page number not for citation purpose) Success in blockchain healthcare insurance r = 0.61; it also shows reduced returns, which resulted out of operational complexity from too many part- nerships, and there are few other projects with higher returns despite lower partnership numbers. This could mean that while partnerships enhance and improve a project’s market outcomes, strategic alignment and quality are more important than numbers. This is also substantiated by our findings from regression analysis which showed a negative correlation between insurance partnerships and market success, when we controlled for other variables (β = –15.3, p = 0.009). In addition to this, it could be plausible that projects that had Fig. 7. Compliance and partnerships quadrant bubble chart. AIDOC: AI Doctor; DCN: Dentacoin (blockchain platform focused on dental healthcare); HIPAA: Health Insurance Portability and Accountability Act of 1996; HUM: Humanscape; LYM: Lympo; MED: MediBloc; MTC: Doc.com; MTN: Medicalchain; PTOY: Patientory; RBM: Robomed Network; SOLVE: Solve.Care. Fig. 6. Partnerships versus market cap scatter plot. USD: US dollars. https://doi.org/10.30953/bhty.v5.xxx http://Doc.com Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.40110 (page number not for citation purpose) Raaga Likhitha Musunuri et al. numerous early-stage partnerships might have faced operational complexity without immediate financial returns, which often ends up delaying the project’s abil- ity to scale and further impact its market growth. Confluence of Compliance and Partnerships Figure 7 shows the combined effect of HIPAA com- pliance and strategic partnerships that affect market success. As observed in projects such as MED and Medicalchain (MTN), a blockchain platform for secure electronic health record management, which are HIPAA-compliant with multiple partnerships at the top-right quadrant, they show a simple, straightfor- ward correlation of market success. On the other hand, other projects, such as Robomed Network (RBM), a blockchain platform connecting healthcare providers and patients using smart contracts, AIDOC, and Doc. com (MTC), either lack compliance or rely solely on partnerships or are located in the lower quadrants with weaker market caps. The positioning of projects like MED and Solve.Care (SOLVE), a blockchain platform for healthcare administration and payments, in the right quadrant confirms their superior market perfor- mance backed by both regulatory compliance and stra- tegic partnership development. This reiterates the idea that market success is not just determined by the num- ber of partnerships but by a combination of regulatory readiness and strategic alliances. Projects that focus on both compliance and meaningful partnerships appear to be more successful in capturing market value. Temporal Analysis of Project Launch Year and Market Success The next part of our analysis relates to the project launch year and market success relations, where we identified that the earlier launched projects (2015– 2016) achieved a higher market capitalization than later entrants (2017 and beyond). The early market entry provided a first-mover advantage to these projects. In the project PTOY, a blockchain healthcare platform for patient-controlled health data management, which was launched in 2017, strategic execution and regula- tory compliance were likely more significant factors in its market performance than simply being an early entrant, which implies that this is not a deterministic relationship. The trend line in Figure 8, with a correla- tion of r = 0.24, suggests a mild relationship between earlier launch years and market success. However, it highlights that the quality of execution remains cru- cial for long-term success. This finding indicates that while being an early mover provides certain advantages in the blockchain healthcare space, project longevity alone does not guarantee commercial success without proper regulatory alignment and strategic execution. Fig. 8. Project timeline: launch year vs. current market status. MED: MediBloc; DCN: Dentacoin; MTN: Medicalchain; PTOY: Patientory; SOLVE: Solve.Care. https://doi.org/10.30953/bhty.v8.401 http://Doc.com http://Doc.com Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.401 11 (page number not for citation purpose) Success in blockchain healthcare insurance Thematic Analysis of White Papers Our thematic analysis of blockchain healthcare insurance project white papers revealed several key themes that influ- ence market success. Table 2 summarizes these themes and the supporting evidence from our data analysis. The quantitative findings were reiterated by the the- matic analysis we conducted, during which we identified more nuanced insights about regulatory compliance, part- nership strategy, platform choice, use case, tokenomics, and AI/data privacy. During the analysis, we found that HIPAA compliance is a defining theme among leading projects. HIPAA-compliant projects are strongly associ- ated with higher market capitalization, as shown by both correlation (r = 0.79) and regression analysis (β = 12.63, p = 0.006). This suggests that regulatory alignment is not only a technical or legal checkbox but a key market signal for trust and adoption in blockchain healthcare. A cou- ple of projects, such as Solve Care and MED, highlighted HIPAA compliance as a key driver of their success, ensur- ing that their platforms gained trust and institutional adoption. The number of partnerships is positively correlated with market capitalization (r = 0.75), highlighting that ecosystem integration and external collaborations are central to project visibility and value. Projects with more partnerships tend to have greater resources, reach, and legitimacy, which translates into higher market cap. MED, for example, formed a key partnership with South Korean healthcare providers, boosting its market credibility. However, partnerships specifically with insurance com- panies showed a negative association with market cap in regression (β = –15.11, p = 0.009). This unexpected find- ing may reflect the challenges and slow pace of insurance sector adoption or that insurance-focused partnerships alone do not guarantee broader market traction. Team size is another strong theme that we identified, which was reinforced from quantitative insights, where we saw larger teams are associated with higher market capitalization (correlation r = 0.83). This suggests that organizational capacity – reflected in human resources – enables better execution, product development, and market engagement. Our thematic analysis also revealed that most of the projects use Ethereum or custom blockchain platforms, which employ dual or multichain architectures, but this was not a significant predictor in our regression anal- ysis, which implies that for this sample, technical stack alone is not a differentiator for market success. Another significant finding from this analysis is that projects like MED migrated from Qtum/Ethereum to their custom “Panacea” blockchain to improve scalability and interop- erability. This revealed that the interoperability with exist- ing healthcare systems, such as electronic health records (EHR) integration, was a stronger predictor of success than just the choice of platform. Another key factor identified was data privacy and AI diagnostics, as in the case of PTOY and tokenomics in the case of Dentacoin. This had less impact on market suc- cess, which implies that data ownership and privacy in the healthcare space are more valued than rewards. Finally, from our thematic analysis, we identified that projects spanned across different use cases (insurance, personal health records, dental, wellness, diagnostics, claims) and geographic focuses (Global, US, Asia, Europe). Dummy variable analysis and regression suggest that global focus may have a borderline positive effect (β = 8.84, p = 0.057), but use case category and platform are not statistically significant predictors. The correlation heatmap reveals that HIPAA compliance, team size, and partnerships are themselves interrelated, reflecting that successful projects tend to align across multiple strategic and organizational dimensions. Regression Analysis and Multicollinearity Our multiple regression analysis, using log-transformed market capitalization as the dependent variable and var- ious independent variables such as HIPAA compliance, team size, and insurance partnerships, yielded significant insights into the determinants of market success in block- chain healthcare projects. We used log transformation of the market cap variable to normalize distribution, as raw market caps have high variability across projects. HIPAA compliance emerged as a strong positive predictor (β = 12.6, p = 0.006), indicating that HIPAA-compliant projects exhibited substantially higher market capitaliza- tion compared to non-compliant projects. The complete regression analysis results are presented in Appendix A. Contrary to expectations, insurance partnerships showed a negative effect on market capitalization when controlling for other factors (β = –15.3, p = 0.009). This Table 2. Summary table of key themes. Theme Evidence from data/analysis. Regulatory compliance HIPAA compliance is the strongest positive predictor of market cap. Strategic partnerships More partnerships = higher market cap; insur- ance partnerships ≠ success. Team scale Larger teams correlate with higher market cap. Technical/platform choices No significant effect on market cap. Use case/geographic focus Diverse, but not significant predictors. Adoption challenges Many projects struggle to achieve scale; insur- ance focus is not enough. Interconnectedness Key success factors are correlated (compli- ance, partnerships, team). HIPAA: Health Insurance Portability and Accountability Act of 1996. https://doi.org/10.30953/bhty.v5.xxx Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.40112 (page number not for citation purpose) Raaga Likhitha Musunuri et al. finding suggests that while partnerships are import- ant, they must be strategically managed to avoid oper- ational complexity that could hinder growth. Team size demonstrated a positive relationship with market success (β  =  0.83, p = 0.031), supporting the notion that orga- nizational scale contributes to project success. Platform type (Ethereum vs. Custom) did not demonstrate statis- tical significance in our regression model (β = 0.17, p = 0.248), supporting our thematic analysis finding that the choice of blockchain platform alone may not be a deter- mining factor for market success. The high adjusted R² value (0.957) indicates that our model explains a substan- tial proportion of the variance in market capitalization, suggesting that the included variables are strong predic- tors of market success in blockchain healthcare insurance projects. As noted in our methodology, we detected moderate multicollinearity in our regression analysis, particularly between HIPAA compliance and insurance partnerships variables (VIF ≈ 9). While this does not invalidate our findings, it does suggest caution in interpreting the inde- pendent effects of these variables and highlights the need for larger samples in future research. The multicollinearity detected between compliance and partnership variables aligns with our qualitative obser- vation that successful projects tend to address regula- tory and strategic dimensions simultaneously, making it challenging to completely isolate their individual effects. Future studies should employ larger samples and explore techniques such as regularization to address multicol- linearity more effectively. The detailed statistical output of our regression analy- sis can be found in Supplementary Appendix A. Discussion The findings from this study provide a practical frame- work for stakeholders operating at the intersection of blockchain and healthcare (Table 3). A stakeholder-ori- ented decision matrix is proposed to help align strategic priorities with regulatory requirements and prevailing market conditions. As commercial success in this domain is closely linked to strategic positioning, trust-building, and operational readiness, the matrix offers a structured approach to informed decision-making. Project Launch Year This study explored whether the launch year of a block- chain healthcare project influenced its market success and long-term sustainability. Early movers, particularly those initiated between 2015 and 2017, tended to capture greater market value compared to projects launched in later years. This trend suggests early movers benefit from high market visibility and early investment potential. However, long-term survival appears to depend more on a project’s ability to adapt to evolving compliance require- ments and interoperability standards that exist in the healthcare space. Several early projects, like RBM, despite initial traction, eventually lost momentum due to a lack of alignment with regulatory expectations.12 As Fang3 emphasizes, commercial viability in blockchain health- care is not solely determined by timing in the market but by organizational maturity and adequate integration with the healthcare ecosystem. Team Size Organizational scale, reflected in larger team size, showed a moderately strong positive correlation with market success (r = 0.83), suggesting that startups with greater organizational maturity are more likely to possess the resources needed to navigate regulatory complexity and translate their solutions into real-world healthcare applications. Prior use cases show that many projects fail to prog- ress beyond the conceptual phase, often due to limited resources.3 Additionally, under-resourced teams may lack the necessary diversity and expertise to navigate legal, regulatory, interoperability, and technical chal- lenges associated with large-scale adoption. Effective strategic leadership is crucial to advancing these proj- ects through the final stages required for substantial market uptake. Future research could focus on iden- tifying specific thresholds in team composition and organizational structure that confer significant market success. Table 3. Stakeholder priorities and recommended actions based on study findings. Stakeholder Priority Strategic action Entrepreneurs Compliance Interoperability Align with HIPAA and EHR standards early Investors Regulatory readiness Team quality Prioritize regulatory maturity and organizational depth Healthcare Organizations Risk mitigation Conduct readiness assessments before partnering. HIPAA: Health Insurance Portability and Accountability Act of 1996; EHR: electronic health records. https://doi.org/10.30953/bhty.v8.401 Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.401 13 (page number not for citation purpose) Success in blockchain healthcare insurance Platform Type Platform type did not show a significant correlation with market capitalization in this study. Ethereum, as a public blockchain, may confer reputational trust and familiar- ity with developers; however, its general-purpose design may not always align with the specific privacy, scalabil- ity, and interoperability needs of healthcare applica- tions.13 While Ethereum-based projects exhibited minor positive trends, this suggests that platform choice may be a secondary factor compared to governance models, reg- ulatory strategies, and integration with existing health systems. Projects That Failed to Achieve Market Success It is important to acknowledge those projects that failed to reach commercial viability or maintain sustainable capitalization. Notably, RBM, a patient-centered plat- form combining AI and blockchain to connect patients and providers,13 gained early visibility and funding success but later struggled due to interoperability limitations and inadequate compliance with institutional standards. Sev- eral studies have cited the inability of RBM to navigate and integrate with dominant standards like FHIR (Fast Healthcare Interoperability Resources) as a key factor limiting its scalability in the health insurance domain.14,15 This case emphasizes that market capitalization is not only influenced by technical innovation or platform type but also by integration with healthcare data standards and adherence to evolving privacy regulations. Project examples that failed to achieve sufficient market success were excluded from this analysis, revealing a key limitation in the form of survivorship bias. Since only suc- cessful projects were included in the dataset, the analysis may underrepresent those factors like partnership quality, organizational structure, and so on that contributed to project failure in those cases. Future research should con- sider a wide variety of projects, including delisted proj- ects, to better understand the full spectrum of success and failure in blockchain-based health insurance ventures. Contextual Interpretation of Regulatory Findings The observed stronger association between HIPAA com- pliance and market success in this study is specific to the sample’s geographic and operational focus. This does not imply that HIPAA is inherently more important than GDPR or other data protection frameworks globally. Rather, it highlights that alignment with the dominant regulatory standards in a project’s target market is a key determinant of commercial viability. Jurisdictional Relevance of Regulatory Compliance Regulatory compliance was assessed regarding the pri- mary jurisdictional frameworks relevant to each project’s operational geography – namely, HIPAA for US-focused projects and GDPR for those operating in the European Union. While our findings indicate that HIPAA compli- ance was a strong predictor of market success in this sam- ple, this reflects the predominance of US-centric projects and should not be interpreted as a universal hierarchy of regulatory importance. We did not systematically analyze compliance with other regional data protection laws, such as the CPRA, which may also play a significant role in US markets. Future studies should expand the regula- tory scope to include such frameworks for a more com- prehensive analysis. HIPAA compliance had a stronger predictive value for market success (β = 12.6) compared to GDPR, which showed no statistical significance. This suggests that for blockchain healthcare projects targeting the U.S. market, The HIPAA compliance serves as a more crucial institutional trust signal than GDPR does for EU markets. Entrepreneur Insights Entrepreneurs in blockchain should prioritize early align- ment with regulatory frameworks like HIPAA, which gov- erns healthcare data privacy in the US, and the GDPR, which applies to personal data in the European Union. Early compliance builds trust and signals institutional credibility to potential partners and investors. The regres- sion and outlier analyses show that early onboarding to these frameworks is a strong, positive predictor of success- ful market signaling and partner acquisition. In addition, interoperability with existing systems plays an important role in ensuring market uptake and widespread adoption. This approach not only reduces costs and implementation time, but also positions startups as collaborative contrib- utors to the current ecosystem, rather than as isolated disruptors.4 Investor Insights Investors should prioritize the strategic quality of part- nerships over their sheer quantity. This study identified a negative correlation between the number of insur- ance partnerships and market capitalization (Regres- sion β  =  –15.3, p = 0.009), indicating that an excessive or unfocused partnership strategy may lead to oper- ational inefficiencies. Such complexities can hinder a project’s scalability, particularly in the healthcare sector, where technological adoption tends to be slow and risk averse. However, this relationship might be confounded by project maturity or strategic focus. Less mature proj- ects may overextend by forming numerous partnerships in the absence of a well-defined integration roadmap or regulatory foundation. As a result, the negative effect of excessive partnerships may reflect the challenges faced by unfocused projects in executing complex integrations. It is possible that fewer, more strategically aligned part- nerships focusing on integration and compliance are https://doi.org/10.30953/bhty.v5.xxx Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.40114 (page number not for citation purpose) Raaga Likhitha Musunuri et al. better predictors of long-term success. Therefore, inves- tors should focus on strategic partnership alignment and robust organizational infrastructure when evaluating blockchain ventures.3 Policy Recommendations Policy reform is an important factor in facilitating the broader adoption of blockchain technologies within the healthcare sector. Clear, comprehensive regulatory frame- works can help streamline implementation and enhance trust among key stakeholders, including patients, provid- ers, and institutional partners, by reducing ambiguity and demonstrating governance.16 Policymakers should prioritize the creation of standard- ized compliance frameworks specifically tailored to health- care’s complex privacy and interoperability demands. Yeung (2021) 8 and Krishnasamy and Gopalakrishna (2023)4 emphasize that inconsistent or fragmented regu- latory environments continue to pose significant obstacles to both the adoption and investment viability of block- chain-based healthcare solutions. In contrast, regulatory clarity has been shown to improve investor confidence and facilitate sustainable scaling. Compliance with local and international data protection standards (HIPAA, GDPR) will also be essential to ensure interoperability across borders, trustworthiness, and legal certainty.17 Reg- ulatory frameworks encompassing these standards should also be established. Governance mechanisms such as decentralized identity systems should be developed in tandem with legal reforms to enhance patient agency and transparency.7 Historical use cases also indicate that projects aligned with stan- dardized policy frameworks tend to demonstrate stronger market performance and more durable institutional inte- gration than those that sought to circumvent regulatory norms.3 Furthermore, it is important that these policies be made in conjunction with all stakeholders in mind, that is industry leaders, healthcare providers, and patients, to enable successful adoption, considering appropriate eth- ical considerations in addition to technical relevance to ensure market sustainability.18,19 Limitations The study has several limitations that should be consid- ered when interpreting the results. Firstly, the sample size is small. Only 10 projects were included; hence, the find- ings might not apply to the wider range of blockchain healthcare projects. Additionally, the manual extraction of project metadata could also introduce some biases, as it is not always easy to capture all the relevant details consistently. It is important to note that this study exclusively analyzed projects with ongoing market presence and available capitalization data, thereby excluding projects that failed to reach or sustain commercial viability. This introduces a survivorship bias, as the analysis may underrepresent factors contributing to project failure. We recognize that including failed or delisted projects in future research will be essential to fully understand the determinants of both success and failure in blockchain healthcare insurance. Furthermore, the study’s reliance on a market snap- shot further limits its accuracy, as market capitalization fluctuates over time, making the data potentially unrep- resentative of long-term trends. Lastly, some multicol- linearity was observed in the regression analysis, with VIF indicating some overlap among predictor variables. This is somewhat common in exploratory studies, but it’s still something to keep in mind when interpreting the findings. Conclusion and Future Recommendations Our mixed-methods analysis demonstrated that regula- tory compliance, particularly HIPAA compliance, is the strongest predictor of market success in this emerging sector. Strategic partnerships contribute to success when properly aligned with project objectives, though excessive early partnerships may introduce operational complexi- ties. Team size and early market entry provide additional advantages but appear less influential than regulatory compliance and strategic partnerships in determining market outcomes. The finding that HIPAA-compliant projects demonstrated significantly higher market cap- italization (β = 12.6, p = 0.006) underscores the critical importance of regulatory alignment in the healthcare blockchain sector. Projects that prioritize compliance with healthcare privacy regulations are better positioned to gain market trust and achieve commercial success in this highly regulated industry. The results reinforce the importance of balancing reg- ulatory readiness with strategic execution, ensuring scal- ability through organizational maturity, and effectively navigating the technical landscape of blockchain. Future research should systematically examine the influence of additional data protection laws, such as the California Consumer Privacy Act and other state or national regula- tions, to capture the full spectrum of compliance require- ments impacting blockchain healthcare insurance projects in diverse markets. Call to Action Our call to action is threefold, focusing on entrepreneurs, policymakers, investors, and venture capital to ensure the presence of blockchain in the healthcare insurance space more tactfully. For entrepreneurs and innovators, the focus primarily is on prioritizing regulatory compli- ance at the project initiation stages to ensure compliance of these projects with the U.S. market and is particularly HIPAA-compliant. https://doi.org/10.30953/bhty.v8.401 Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.401 15 (page number not for citation purpose) Success in blockchain healthcare insurance In addition, entrepreneurs should focus on developing strategic partnerships with established healthcare institu- tions rather than pursuing numerous partnerships with- out clear integration plans, which enable them to achieve a product-market fit and scaling feasibility. For this to happen, the entrepreneurs should ensure that their token utility models are in alignment with healthcare workflows and provide tangible benefits to the stakeholders, which enables a functional and strategic partnership. The start- ups and entrepreneurs should ensure that their focus is on technical integration and interoperability capabilities too, which help in integrating with the existing health infra- structure to improve adoption rates. The investors and venture capital should ensure that the evaluation of blockchain healthcare projects for potential investment is based on their regulatory readiness and compliance frameworks. These organizations should thoroughly investigate strategic alignment of partnerships rather than merely counting the number of partnerships and ensure that their focus is on the regulatory and strate- gic execution rather than just the selection of the platform (Ethereum and custom solutions) by the startup. The policymakers and regulators, on the other hand, should focus on developing standard and clear regulatory frameworks, specifically addressing blockchain applica- tions in healthcare insurance. This includes a strategic alignment between regulations such as HIPAA and pri- vacy protections to accommodate blockchain innovations. There is a sincere need for the creation of regulatory sand- boxes to facilitate compliant innovation. Finally, there is a need for establishing guidelines for tokenization models in healthcare to enhance market confidence. Policy frame- works should address regulatory compliance and provide incentives for blockchain adoption through clear guide- lines on tokenomics and patient data ownership. Future Research This study represents an initial exploration of the factors influencing market success in blockchain healthcare insur- ance projects. While our findings provide valuable insights for entrepreneurs, investors, and policymakers, contin- ued research is necessary to fully understand this rapidly evolving field and to develop comprehensive frameworks for evaluating and predicting project success. We realize the need for expansion of the dataset to include a larger sample of blockchain health insurance projects. There is a need to investigate the failed proj- ects, which will help us identify common pitfalls and risk factors. The need to develop a sophisticated metric to evaluate partnership quality beyond simple counting is of prime importance in the short term. Furthermore, there is a need to conduct longitudinal studies that track blockchain healthcare projects over time to assess the market trajectory based on regulatory compliance and partnership influence and explore the impact of different tokenomics models on long-term sustainability. This will further be influenced by the technical architecture deci- sions and market outcomes. Finally, there is a need to understand and focus on reg- ulatory convergence patterns that are present across global markets and their impact on blockchain healthcare adop- tion rates, especially in insurance. It is also imperative that as blockchain is growing, other emerging markets such as AI and IoT coexist, and it is very important to understand their market outcomes when they are integrated with blockchain. Funding This editorial received no external funding. Disclosure of Financial and Non-Financial Relationships and Activities The authors declare no financial or non-financial relation- ships or activities that could appear to have influenced the submitted work. Contributors Raaga Likhitha Musunuri, Kimberly S. Brooks, Swapna Ashish Patel, Trupti Jayesh Majgunkar, Krisha Patel, and Erin O’Neill all contributed to conceptualization, meth- odology, investigation, data curation, formal analysis, visualization, software, writing original draft, and writing review & editing. All authors contributed equally to this work. All authors have read and agreed to the published version of the manuscript. Data Availability Statement (DAS), Data Sharing, Reproducibility, and Data Repositories The data supporting the findings of this study are included within the article and its supplementary materials. The market data was collected from CoinGecko API (https:// www.coingecko.com/en/api) during April 2025, with spe- cific snapshot dates noted in the methodology section. Metadata from white papers was manually extracted fol- lowing the coding framework described in the methods and summarized in Appendix A. The complete dataset of market capitalization values, compliance metrics, and partnership data used for statis- tical analyses is available from the corresponding author upon reasonable request. Python code used for statistical analysis and visualization (using pandas v2.2.1, statsmod- els v0.14.0, SciPy v1.14.1, Matplotlib v3.10.0, and Sea- born v0.13.2) is available upon request. AI assistance was utilized for code optimization and debugging during the analysis phase. Acknowledgments The authors would like to acknowledge Northeastern University for providing resources and support for this https://doi.org/10.30953/bhty.v5.xxx https://www.coingecko.com/en/api https://www.coingecko.com/en/api Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.40116 (page number not for citation purpose) Raaga Likhitha Musunuri et al. research. We also thank the blockchain healthcare proj- ects whose public data made this study possible. 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Available from: https:// www.ncbi.nlm.nih.gov/pmc/articles/PMC9212252/ Copyright Ownership: This is an open access article distributed in accordance with the Creative Commons Attribution Non Com- mercial (CC BY-NC 4.0) license, which permits others to distribute, adapt, enhance this work non-commercially, and license their deriva- tive works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons. org/licenses/by-nc/4.0. The authors of this article own the copyright. https://doi.org/10.30953/bhty.v8.401 https://www.sciencedirect.com/science/article/pii/S2667102624000627?via%3Dihub https://www.sciencedirect.com/science/article/pii/S2667102624000627?via%3Dihub https://doi.org/10.1016/j.compeleceng.2024.109898 https://doi.org/10.30953/bhty.v4.166 https://doi.org/10.30953/bhty.v6.280 https://doi.org/10.30953/bhty.v6.280 https://www.sciencedirect.com/science/article/pii/S2096720924000551 https://www.sciencedirect.com/science/article/pii/S2096720924000551 https://doi.org/10.1016/j.future.2021.12.006 https://www.jmir.org/2024/1/e46556/ https://www.jmir.org/2024/1/e46556/ https://doi.org/10.2196/24109 https://doi.org/10.2196/24109 https://blockchainhealthcaretoday.com/index.php/journal/article/view/298 https://blockchainhealthcaretoday.com/index.php/journal/article/view/298 https://doi.org/10.1080/20479700.2016.1270875 https://www.thinkmind.org/articles/etelemed_2020_3_250_40097.pdf https://www.thinkmind.org/articles/etelemed_2020_3_250_40097.pdf https://pmc.ncbi.nlm.nih.gov/articles/PMC11082361/ https://pmc.ncbi.nlm.nih.gov/articles/PMC11082361/ https://www.dre.vanderbilt.edu/~schmidt/PDF/FHIRChain-jnca.pdf https://www.dre.vanderbilt.edu/~schmidt/PDF/FHIRChain-jnca.pdf https://doi.org/10.2196/17475 https://doi.org/10.3390/digital2010005 https://doi.org/10.56294/dm2023166 https://doi.org/10.2196/58445 https://doi.org/10.3390/su13095269 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9212252/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9212252/ http://creativecommons.org/licenses/by-nc/4.0 http://creativecommons.org/licenses/by-nc/4.0 Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.401 17 (page number not for citation purpose) Success in blockchain healthcare insurance Appendix A Regression analysis Addendum: Acronyms Blockchain Project Names and Tokens • AIDOC: AI doctor (blockchain-based healthcare platform using artificial intelligence for medical diagnostics) • DCN: Dentacoin (blockchain platform focused on dental healthcare) • HUM: Humanscape (patient-centered blockchain healthcare ecosystem) • LYM: Lympo (blockchain-based health and wellness platform with incentivized fitness activities) • MED: MediBloc (blockchain healthcare platform for secure medical data management) • MTC: Doc.com (blockchain-based telemedicine platform) • MTN: Medicalchain (blockchain platform for secure electronic health record management) • PTOY: Patientory (blockchain healthcare platform for patient-controlled health data management) • RBM: Robomed Network (blockchain platform connecting healthcare providers and patients using smart contracts) • SOLVE: Solve.Care (blockchain platform for healthcare administration and payments) • UHC: Universal Health Coin (blockchain-based healthcare payment solution) Technical Terms • CSV: Comma-Separated Values (data file format) • DAS: Data Availability Statement • DRGs: Diagnosis-Related Groups (patient classification system for healthcare payments) • EDPR: ElcomSoft Distributed Password Recovery (software) • EHR: Electronic Health Record • FHIR: Fast Healthcare Interoperability Resources (standard for healthcare data exchange) • HIPAA: Health Insurance Portability and Accountability Act of 1996 • MTM: Medication Therapy Management (healthcare service to optimize medication use) • RPM: Remote Patient Monitoring https://doi.org/10.30953/bhty.v5.xxx http://Doc.com Citation: Blockchain in Healthcare Today 2025, 8: 401 - https://doi.org/10.30953/bhty.v8.40118 (page number not for citation purpose) Raaga Likhitha Musunuri et al. • VIF: Variance Inflation Factor (statistical measure used in regression analysis) Regulatory Terms • GDPR: General Data Protection Regulation (European Union data privacy regulation) • IRB: Institutional Review Board Analysis Tools • AI: Artificial Intelligence https://doi.org/10.30953/bhty.v8.401