Towards roadmap to implement blockchain in healthcare systems based on a maturity model

Abstract

Healthcare systems face various issues related to complex networks of intermediaries and a lack of transaction traceability. The most critical issues are the fragmentation of healthcare data, obstacles in providing efficient research and services, lack of clinical trial reporting, high cost and mismanagement of the drug supply chain, patient data security, and fake drugs. Blockchain technology has the potential to address these criticalities as it has in build traceability mechanisms and promises new business models by enabling incentive structures. This potential of blockchain gathers a high interest in the health industry. However, the implementation of blockchain in healthcare faces various issues as well. Currently, there are no practice-oriented maturity models to improve such an implementation. In this paper, we present a roadmap to develop a maturity model for blockchain in healthcare (MMBH) based on critical barriers (CBs), critical success factors (CSFs), and the best practices for blockchain implementation in healthcare systems. As a first step to develop the MMBH, in this paper, we present the initial results of a systematic literature review (SLR) to identify critical success factors for implementing blockchain in healthcare systems. We also applied fuzzy technique order preference by similarity to ideal solution (TOPSIS) to prioritize the identified CSFs.

Blockchain-Based Dynamic Consent and its Applications for Patient-Centric Research and Health Information Sharing: Protocol for an Integrative Review

“…This integrative review is expected to identify optimal approaches to implementing and evaluating the effectiveness of blockchain-based dynamic consent technologies. While blockchain products are being developed for health research environments, few implementation models exist [ 52 ]. Additionally, few articles describe their products’ limitations or weaknesses, contributing to narrow and unrealistic perspectives [ 53 ].…”

A new taxonomy of global software development best practices using prioritization based on a fuzzy system

“…Our future work includes implementing a GSD project management maturity model and developing the model's maturity levels 52 . We aspire to conduct a case study with GSD organizations to gain insights from practitioners on the structure, ease of use, and understanding of a GSD project management maturity model.…”

“…Our future work includes implementing a GSD project management maturity model and developing the model's maturity levels. 52 We aspire to conduct a case study with GSD organizations to gain insights from practitioners on the structure, ease of use, and understanding of a GSD project management maturity model. Improvements could be made by employing methods related to the PRISMA methodology, 53 identifying bigdata sources, current research trends using bibliometric techniques, 54 and exploring other fuzzy theories.…”

Big Data Maturity Assessment Models: A Systematic Literature Review

“…According to [36], there are obvious differences in the comprehensive performance of the available BDMMs. After reviewing the previous studies related to maturity models, the results indicated that the models of [45] and [47] provide end-users with all descriptive, prescriptive, and comparative functionalities, while the models of [38,48,50,62] serve a descriptive or prescriptive purpose of use. The models of [49,52] were the only ones acting as descriptive models, not providing any recommendations or improvement activities.…”