Towards a Blockchain based Fall Prediction Model for Aged Care

Abstract

Falls are one of the major health concerns for the elderly people. These falls often result in severe injuries which lead into huge medical expenses. Over the recent years, many ICT based fall detection and fall prevention solutions emerged to address the risk factors associated with falls. However, despite of these research studies, predicting the likelihood of falls still remains as a huge challenge in both medical and IT research domains. Data related to these risk factors being scattered among different healthcare providers can be attributed as a main reason for this challenge. This is further amplified by healthcare providers being reluctant to disseminate the data beyond their entities due to the security and privacy concerns. However, in recent years, blockchain has been proven as a promising technology to address the security and privacy challenges in healthcare data exchange as it provides a shared, immutable, and transparent audit trail for accessing data. Therefore, in this paper, we are going to propose a conceptual blockchain based fall prediction model leveraging smart contracts and FHIR (Fast Healthcare Interoperability Resources) standard to identify the elderly people who are at a higher risk of falling.