Defining Network Quality of Service Metrics for Medical Applications

Networked digital diagnostic, monitoring and patient treatment tools permeate medical practice. A plethora of telemedicine, national and other eHealth records, injury assessment, patient-specific devices, hospital theatre equipment tools have resulted in a multi-billion dollar industry worldwide.  Research suggests the application of these tools  to healthcare can improve clinical workflows and patient care outcomes. There are no commonly agreed metrics for Quality of Service (QoS) for medical applications, despite the fact that QoS metrics have been exceptionally well studied in digital IP and ATM networks, and are widely used for consumer services such as voice, multimedia and data services.  While many medical applications are well aligned with the technology used in consumer applications, and can take advantage of established metrics, many are not, thus presenting risks of service impairments to patients and providers.

We are especially interested in exploring what medical applications are compatible or incompatible with existing QoS metrics in wireless and cabled networks, encompassing the full gamut of network connectivity employed to run medical applications. We envisage the identification of robust QoS metrics for medical applications known to perform poorly with established QoS metrics. We would also like to explore the geographical distribution of available services in Australia, and where possible, establish available QoS performance, to map what medical applications are feasible for remote use across the geography.

Methodology is necessarily mixed. There will be a significant survey component involving medical practicioners and providers, and also network / telecoms providers, to collect the required datasets of applications, services, and geographically available QoS data. The technical component will require assessment and possibly measurement of QoS needs for applications that are known to perform poorly in existing networks. These may include packet loss, jitter, error rates and bandwidth variations. #digitalhealth