## 5 Conclusions  
In this paper, we have proposed an off-the-chain consortium blockchain scheme for collaborative medical decision-making that includes the security of blockchain and privacy of personal data. We also have presented the proof of familiarity (PoF), a consensus gathering algorithm, designed to assimilate medical decisions of healthcare stakeholders (patient, doctor, insurance company, cured patient). Working mechanism and efficiency of the proposed PoF consensus algorithm is confirmed with an open source blockchain simulation platform (multichain 2.0). PoF ensures the integrity of a collective medical decision and privacy of stakeholders by storing previously stored decisions and identities by blockchain. While preserving the identity of stakeholders, PoF follows a two-layer security measure. Firstly, the identities of patients, doctors, cured patients, and insurance companies are locally stored, and secondly, the hash of those are stored in a block. Moreover, the qualitative performance of PoF is compared with the existing collaborative medical decision-making system, and theoretical comparison identifies PoF as an efficient use of blockchain in healthcare. PoF successfully reduced the risk of personal information (PII and PPII) leaking during collaboration of medical decisions. The following are the key outcomes we gathered from scheming and examining the PoF based collaborative medical decision-making system:  
* PoF based collaborative medical decision-making system provides middlemen with a less decentralized medical decision collaboration platform with no single point of failure.
* PoF based collaborative medical decision-making system uses modified blockchain architecture (off-the-chain) to secure clinical data privacy and security.
* PoF based collaborative medical decision-making system allows trusted participation of significant medical decision-giving entities to provide a better clinical decision.  
This study identified the reasons for the lack of medical collaboration and associated risks. Additionally, a PoF based collaborative scheme successfully mitigates ongoing issues of collaborative medical decision-making by using blockchain technology. Our future research directions include developing a fully-fledged real-time application, efficient use of previous decisions, and learning from the environment. In the future version of this study, we will consider the weighting factors among entities during collaborative decision-making. This shall then enable the system to be commercially used in a broader scope with more accuracy.  
Conceptualization, J.Y. and C.-S.K.; formal analysis, M.M.H.O.; methodology, N.-Y.L. and M.A.; project administration, J.Y. and C.S.-K.; supervision, N.Y.-L. and C.-S.K.; visualization, M.M.H.O.; writing--original draft, M.M.H.O.; writing--review and editing, M.A.  
**Funding:** This research was funded by Institute for Information and Communications Technology Promotion (IITP) grant funded by the Korean government (Ministry of Science and ICT) (No. 2018-0-00261, GDPR Compliant Personally Identifiable Information Management Technology for IoT Environment). The APC was funded by Institute for Information and Communications Technology Promotion (IITP) grant funded by the Koreangovernment (Ministry of Science and ICT) (No. 2018-0-00261, GDPR Compliant Personally Identifiable Information Management Technology for IoT Environment).  
The authors acknowledge computer and communication (CnC) lab members of Inje University for providing administrative and technical support. Finally, the authors thank anonymous reviewers for their valuable review.  
The authors declare no conflicts of interest.