Blockchain-Enabled Multisensor Clinical Laboratory Information System


  • Daeun Lok Johns Hopkins University
  • Kyle Bartrem Johns Hopkins University
  • Geraldine Chi Johns Hopkins University


Blockchain, Sensor, IoT, Information System, EHR, Clinical


The purpose of this paper is to design an information system for clinics to implement multiple sensors for laboratory testing and telemedicine use.  IoT is adopted in major hospitals but many smaller healthcare organizations have not benefited from the recent innovation due to lack of access to technology [1].  The paper presents the 'sensor lab' information system architecture for small clinics that includes sensors, a secure blockchain cloud to link the sensors and transmit data, and an electronic health record (EHR) analytics tool to evaluate patients’ health conditions.  Additionally, costs and benefits for smart clinics are shown to prove the business value of smart clinics.  The goal of a smart clinic is to improve outpatient visit efficiency and patient data security, provide telemedicine care management, and reduce clinic expenses.

Author Biography

Daeun Lok, Johns Hopkins University

Carey Business School MS Information Systems


Are Virtual Care Clinics the Wave of the Future? (2016, Aug.).

Retrieved from https://www.usnews. com/news/articles/2016-08-17/are-virtual-care-clinics-the-wave-of-the-future

Clinical Program (2017, May). Bio Sensors International. Retrieved from

Zweig, M.H. (1988, April ). Evaluation of the Clinical Accuracy of Laboratory Tests. Retrieved April 30, 2017, from

Clinical Lab (2017, May). Retrieved from https://www.

The Benefits of Blockchains Across Industries (2016, April). Retrieved from

Mega Data Breaches Could Drive the Blockchain Revolution. (2017, May). Retrieved from

Introduction to Smart Contracts. (2017, May). Retrieved from

Yuan, B., Lin, W., & McDonnell, C. (n.d.). Blockchains and Electronic Health Records. Retrieved April 30, 2017, from

Bulkin, A. (2016, May 03). Explaining Blockchain-how proof of work enables trustless consensus. Retrieved April 30, 2017, from -enables-trustless-consensus-2abed27f0845-work-enables-trustless-consensus-2abed27f0845

Barton, personal communication, April 28, 2017)

Kott, personal communication, April 17, 2017

Chronic Disease Overview (2017, May). Retrieved from

Privacy of Individually Identifiable Health Information, 65 FR 82802 (2000).

Wang, Y., Chen, R., Ghosh, J., Denny, J. C., Kho, A., Chen, Y., . . . Sun, J. (2015). Rubik. Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD 15. doi:10.1145/2783258.2783395

Gruenheid, A. (2016). Data Integration with Dynamic Data Sources (Doctoral dissertation, ETH Zurich).

Szlosek, D. A., & Ferretti, J. M. (2016). Using Machine Learning and Natural Language Processing Algorithms to Automate the Evaluation of Clinical Decision Support in Electronic Medical Record Systems. EGEMs (Generating Evidence & Methods to improve patient outcomes), 4(3). doi:10.13063/2327-9214.1222

Bureau, U. C. (2014, November 25). Ambulatory Health Care Services Receipts and Employment on the Rise. Retrieved May 02, 2017, from

Bernstein AB, Hing E, Moss AJ, Allen KF, Siller AB, Tiggle RB. Health care in America:

Trends in utilization. Hyattsville, Maryland: National Center for Health Statistics. 2003.

US Census Bureau. (2014, November 25). Ambulatory Health Care Services Receipts and Employment on the Rise. Retrieved May 02, 2017, from

Health Clinics Nationwide Compared to Planned Parenthood Centers (2017, May). Retrieved from

Suszek, A. (2017, May). Malpractice Claims for Delayed Diagnosis. Retrieved from

Dietsche, E. (2016, January 14). 60 things to know about the hospital industry | 2016. Retrieved May 02, 2017, from

Murray, D. (2004, March). S Corp, C Corp, LLC, LLP-which is best? Retrieved March 5, 2004, from

Lok, personal communication, April 17, 2017




How to Cite

Lok, D., Bartrem, K., & Chi, G. (2018). Blockchain-Enabled Multisensor Clinical Laboratory Information System. Asian Journal of Business and Management, 5(6). Retrieved from