Leveraging the Hyperledger Fabric for Enhancing the Efficacy of Clinical Decision Support Systems


  • Ramya Gangula Department of Information Systems and Security, Kennesaw State University, Kennesaw, Georgia
  • Sri Varun Thalla Department of Information Systems and Security, Kennesaw State University, Kennesaw, Georgia
  • Ijeoma Ikedum Department of Information Systems and Security, Kennesaw State University, Kennesaw, Georgia
  • Chineze Okpala Department of Information Systems and Security, Kennesaw State University, Kennesaw, Georgia
  • Sweta Sneha Department of Information Systems and Security, Kennesaw State University, Kennesaw, Georgia




CDSS, Hyperledger Fabric, blockchain, interoperability, alert fatigue, patient outcome


Adopting and implementing the Clinical Decision Support System (CDSS) technology is a critical element in an effort to improve national quality initiatives and evidence-based practice at the point of care. CDSS is envisioned to be a potential solution to many current challenges in the healthcare sphere, which includes information overload, practice improvement, eliminating treatment errors, and reducing medical consultation costs. However, the CDSS did not manage to achieve these goals to the desired levels and provide context-appropriate alerts, although integrated with the electronic health records (EHRs) (1). Clinical decision support alerts can save lives, but frequent ones can cause increased cognitive burden to clinicians, worsen alert fatigue, and increase the duplication of tests. This ultimately increases health care costs without refining patient outcomes. Studies show that 49–96% of clinical alerts are ignored, raising questions about the effectiveness of CDSS (1). Blockchain, a decentralized, distributed digital ledger that contains a plethora of continuously updated, time-stamped, and highly encrypted virtual record, can be a key to addressing these challenges (2). The blockchain technology if integrated with the CDSS can serve as a potential solution to eliminating current drawbacks with CDSS (3). This article addresses the most significant and chronic problems facing the successful implementation of CDSS and how leveraging the Hyperledger Fabric can alleviate the clinical alert fatigue and reduce physician’s burnout using patient-specific information. The proposed architecture framework for this study is designed to equip the CDSS with overall patient information at the point of care. This then empowers the physicians with the blockchain-integrated CDSS, which holds the potential to reduce clinician’s cognitive burden, medical errors, and costs and ultimately enhance patient outcomes. The research study broadly discusses how the blockchain technology can be a potential solution, reasons for selecting the Hyperledger Fabric, and elaborates on how the Hyperledger Fabric can be leveraged to enhance the efficacy of CDSS.


Download data is not yet available.


Ancker JS, Edwards A, Nosal S, Hauser D, Mauer E, Rainu K, et al. Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system. BMC Med Inform Decis Mak 2017; 17(1): 1–9. doi: 10.1186/s12911-017-0430-8

Cyran M. https://blockchainhealthcaretoday.com; 2018. Available from: doi: 10.30953/bhty.v1.13 [cited 15 September 2019].

Mittal N, Thakur M. Using blockchain to address interoperability concerns in healthcare. Int Biopharm Ind 2018; 1(2): 58–61.

Berner ES, La Lande TJ. Overview of clinical decision support systems. In: Berner ES, La Lande TJ, eds. Clinical decision support systems. New York, NY: Springer; 2007, pp. 3–22.

Bresnick J. https://healthitanalytics.com; 2017. Available from: https://healthitanalytics.com/features/understanding-the-basics-of-clinical-decision-support-systems [cited 15 September 2019].

Brief E. Top 10 health technology hazards for 2020. ECRI Inst. 2019;9. Available from: https://elautoclave.files.wordpress.com/2019/10/ecri-top-10-technology-hazards-2020.pdf [cited 5 January 2021].

Centers for Disease Control and Prevention. Implementing clinical decision support systems. 2018. Available from: https://www.cdc.gov/dhdsp/pubs/guides/best-practices/clinical-decision-support.htm [cited 01 October 2019].

Kuperman GJ, Bobb A, Payne TH, Avery AJ, Gandhi TK, Burns G. Medication-related Clinical decision support in computerized provider order entry systems: a review. J Am Med Inform Assoc 2007; 14(1): 29–40. doi: 10.1197/jamia.M2170

Ash JS, Sittig DF, Campbell EM, Guappone KP, Dykstra RH. Some unintended consequences of clinical decision support systems. AMIA Annu Symp Proc 2007; 26(30): 26.

Alert Fatigue and Patient Risk: An Effective Drug Decision Support System Could Eliminate Both. www.managedhealthcareexecutive.com. 2016. Available from: https://www.elsevier.com/__data/assets/pdf_file/0019/272152/MHE1116-Elsevier-Alert-Fatigue-WP.pdf [cited 11 November 2019].

Hassan Fu, Ali A, Rahouti M, Latif S, Kanhere S, Singh J, et al. Blockchain and the future of the internet: a comprehensive review. 2020; 2: arXiv preprint arXiv:1904.00733.

Shahsavarani AM. Clinical Decision Support Systems (CDSSs): state of the art review of literature. Int J Med Rev. 2015; 2(4): 299–308.

Sousa J, Bessani A, Vukolic M. A Byzantine fault-tolerant ordering service for the Hyperledger Fabric Blockchain Platform. 2018, pp. 51–58. Available from: https://ieeexplore.ieee.org/document/8416470 [cited 5 December 2019].

Engelhardt M. Hitching healthcare to the chain: an introduction to Blockchain technology in the healthcare sector. Technol Innov Manag Rev 2017; 7(10): 22–34. doi: 10.22215/timreview/1111

Zheng Z, Xie S, Dai H, Chen X, Wang H. An overview of blockchain technology: Architecture, consensus, and future trends. In 2017 IEEE international congress on big data (BigData congress). Honolulu, HI: IEE, 25 June 2017; pp. 557–564.

The Linux Foundation. Hyperledger. Available from: https://www.hyperledger.org [cited 1 February 2020].

IBM. Hyperledger fabric: the flexible blockchain framework that’s changing the business world. Available from: https://www.ibm.com/blockchain/hyperledger [cited 1 February 2020].

Enyeart D. Membership Service Providers (MSP). 2018. Available from: https://github.com/hyperledger/fabric/blob/release-1.4/docs/source/msp.rst [cited 15 February 2020].

Androulaki E, Barger A, Bortnikov V, Cachin C, Christidis K, De Caro A, et al. Hyperledger fabric: a distributed operating system for permissioned blockchains. 2018. Available from: www.arxiv.org: https://arxiv.org/abs/1801.10228v2 [cited 23 March 2020].

O’Dowd A. Peers. 2018. Available from: https://github.com/hyperledger/fabric/blob/release-1.4/docs/source/peers/peers.md [cited 12 May 2020].

Center for Internet Security. Data breaches: in the healthcare sector. Available from: https://www.cisecurity.org/blog/data-breaches-in-the-healthcare-sector/ [cited 5 September 2020].

Snell E. Health IT security. 2018. Available from: https://healthitsecurity.com/news/58-of-healthcare-phi-data-breaches-caused-by-insiders. [cited 5 September 2020].

Polge J, Robert J, Le Traon Y. Permissioned blockchain frameworks in the industry: A comparison. ICT Express. 2020 Sep 12. Available from: https://www.sciencedirect.com/science/article/pii/S2405959520301909 [cited 10 January 2021].

Ma C, Kong X, Lan Q, Zhou Z. The privacy protection mechanism of Hyperledger Fabric and its application in supply chain finance. Cybersecurity 2019; 2(5): 1–9. doi: 10.1186/s42400-019-0022-2

Alewine J. Introduction. 2019. Available from: https://github.com/hyperledger/fabric/blob/release-1.4/docs/source/whatis.md [cited 2 January 2021].

Soundararajan V, McDaniel B, Shin J, Sneha S, Soundararajan V. Leveraging Blockchain to Improve Clinical Decision Support Systems. In Forum/Posters/CIAO! DC@ EEWC 2019 May 24.

Additional Files



How to Cite

Gangula, R., Thalla, S. V. ., Ikedum, I. ., Okpala, C. ., & Sneha, S. . (2021). Leveraging the Hyperledger Fabric for Enhancing the Efficacy of Clinical Decision Support Systems. Blockchain in Healthcare Today, 4. https://doi.org/10.30953/bhty.v4.154



Research Articles

Most read articles by the same author(s)