## 1 Introduction  
Shared decision-making (SDM) has been used as an optimum way of health care decision sharing among healthcare practitioners. Collaborative decision-making happens when individuals (two or more) underwrite diverse expertise and skill to the decision-making mechanism [1]. Studies [2; 3] have already inspired clinicians to use SDM while providing preventive health and medical verdicts. Collaborative medical decision-making exchanges sensitive electronic health records (EHRs) and personal health records (PHRs) among healthcare entities like insurance companies, cured patients, researchers, doctors, drug distributors, pharmacists, etc. Regrettably, the privacy of EHRs, sensitive information, and PHRs are frequently compromised during medical collaboration. Interoperability issues among healthcare stakeholders carry extra barriers to effective data sharing for collaborative decision-making in the medical sector. While designing new schemes to overcome these security issues, leveraging privacy-aware blockchain technology can be a substantial option. Accenture's [4] consumer survey reported that around 26% of consumer's electronic medical records (EMRs) in the USA were breached, where 31% of those lost social security number, contact information, EHRs, and PHRs. Guardian [5] reported the top 10 healthcare data breaching incidents and found 'Anthem Blue Cross,' a giant health insurance firm, as the number one data breaching company. The company disclosed 80 million data including sensitive medical data, social security numbers, addresses, etc. Several studies discussed the various cyber-physical risk factors in the healthcare domain [6; 7; 8]. Another study [9] discussed the risk of healthcare-related data leaking in a wireless body area network, cloud, and 5G. US-based identity theft resource center (ITRC) [10] announced businesses (55%) and healthcare industries (23.7%) as the top two identity breaching sectors from 2005 to 2017 (total 1579 breaches in the USA, 2017). False data injection attack in healthcare has been a widely discussed topic in clinical data security and the privacy domain [11]. A few reasons for clinical data breaching as reported by Snell [12] are unintended data disclosure (41%), hacking and malware (19%), internal incidents (15%), and physical damage (8%). It identified 380 dollars as a 'breaching cost for every health care record lost. Around 63% of patients visit an online platform for medical help and 62.4% of them trust their doctor for data sharing [13]. Lack of participants, sloppy stakeholder's identity securing mechanisms, corruption in decision picking mechanisms, lack of accountability, data manipulation, delayed communication, and corrupted mediums have been recognized as the major worries of collaborative medical decision-making [14; 15; 16; 17; 18; 19]. Despite aforesaid challenges, collaboration can always upgrade the existing healthcare amenity. The Health Insurance Portability and Accountability Act (HIPAA) [20] identified 'healthcare provider' (doctor and hospital) as the second largest identity leaking sector (Table 1). Presently, patients collaborate (Collaborations1-4) with entities one at a time (TimesA1-A5). This type of collaboration costs time, money, and the privacy of users (Figure 1). Existing collaborative healthcare decision-making has the following limitations [14; 15; 16; 17; 18; 19; 21; 22; 23]:  
* Multi-dimensional personal data privacy policies imposed by individual institutes. * Clinical data, medical decisions, and patient identities are being manipulated and distributed without proper acknowledgment and consent. * Scalability and management difficulties during collaborative decision gathering and storing. * Usage of centralized architecture with a single point of failure. * Incompatibility with institutional and regional regulations in SDM-based medical treatment. * Lack of association among health professionals. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \begin{tabular}{c} **Year** \\ \end{tabular}