Medical Electronics Maps and Apps
As the Government focuses on the use of information and apps to enhance the UK’s healthcare service, Ben Toner considers whether the mobile networks will be able to cope with the predicted explosive growth
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n August the Government’s Health Secretary, Andrew Lansley, launched its ‘Maps and Apps’ initiative, inviting people to contribute to a conversation about innovation, information and apps for health and care. The Department of Health wants to find examples of the best, most popular existing health apps, and also ideas for apps that haven’t been developed yet.
It is looking for feedback from both end users and apps developers, including patients, doctors and nurses.
Of course, while initiatives like this will contribute to the predicted explosive growth of wireless device use in healthcare, it will also increase pressure on the mobile networks. The addition of medical applications to the already significant growth in mobile data will contribute to mobile network congestion and service quality. If wireless medical devices cannot perform equally or reliably then there could be an adverse affect on user experience and long term adoption. It is therefore important to consider the
wireless carriers’ quality of service guarantees and the cost of providing the service when creating mobile applications for the healthcare industry. For application developers this means that setting sustainable user expectations and cost management from the start are key factors in the creation of a commercially successful application.
Because we use connected applications in the home and office every day, we have become highly dependent on our mobile devices. Consequently as mobile device users, we have become accustomed to a certain level of convenience and reliability. However, what mobile devices users actually experience now masks the fact that public access connectivity today is actually a best-effort service. This is because the underlying technologies come under strain in a mobile environment, especially as we use more of them. In the USA The Food and Drug Administration recognises this and advises application developers to be aware of it. A good example is the launch of the Apple iPhone where some networks were driven to breaking point by an explosion of application use. For the device user, such oversubscription translates into dissatisfaction due to the delayed delivery of information that they have an expectation that it should be instantaneous. Consequently, an excessive
30 November 2011
use of battery power and service costs does not equally match their perception of quality of service or data value.
Commercial viability As the networks come under increasing strain, the likely response from wireless carriers will be to start offering innovative charging models. Concepts such as peak time charging, throughput limiting, and application-based charging are all being discussed, which is likely to impact the service quality and business model of any medical application.
Application developers will therefore have to be intelligent about how they use the network, the content of their application and the user experience perceptions they wish to set. The prudent approach is to create applications which allow the network usage to be configured at deployment time or while already deployed. An effective way to deliver this is through an intelligent connection manager that can assist in scheduling data transfers according to network usage and billing rules that can be configured at any time. If these rules were implemented on the device as a remote managed policy, then they could be changed according to the evolving need for patient data availability. This is a concept that lends itself well to healthcare applications as non-urgent data can be stored and delayed to provide benefit to cost control and battery life management, while conditioning users to the concept of ‘just in time’ data delivery. To understand the benefits derived from
segregating data, let us consider a diabetes patient who is fitted with a blood glucose monitor. When the concern level is low, the frequently collected data can be delivered in batches at a time of day when charge rates are relatively low. If the patient’s situation becomes critical, the data would be delivered immediately at a higher cost of delivery, but that is appropriate to the value of care response. As mobile medical devices are
increasingly deployed in the next few years, always-on connectivity is likely to become a must-have for users. Guaranteeing that a patient’s wireless medical device will work anywhere with that level of service quality will be a challenge given the varying performance across a mobile network and the forecast of service impacting congestion. This therefore highlights the importance of setting healthcare users’ expectations
Components in Electronics
appropriately in order to match the changing nature of mobile data services. Medical devices will also benefit from
more than one connectivity choice, such as cellular and Wi-Fi. This means that connectivity intelligence beyond the existing connection managers will also need to be developed to automatically control which service to use and when, as users will not want to do complex interactions with connectivity parameters themselves.
The design and operation of the multi- connected devices will be complex ‘behind the scenes’, but to both the patient and the care giver this must be both operationally transparent and financially equivalent to the relative value of the data being used. This will be true especially in geriatric care and for people with physical and cognitive challenges, where the user may not have the expected technical or physical ability to determine which type of connectivity should be used.
Making wireless a healthcare reality A wireless medical product delivered at the right purchase price and service cost will require appropriate design effort in the connection control and the delivery of data. To address this, intelligent network connection managers are needed to deliver the concept of delaying mobile data to when it is both cost effective and relevant to send. Such intelligent data management will provide a ready-made method of
managing cost, battery life and user experience, while effectively combating the issue of network congestion and overload. Such a data manager will offer application developers the comfort of offsetting some of the critical business decisions until deployment time. Providing a rules engine that allows the definition of when to send real-time and non-essential data types unlocks the ability to minimise the cost of the data service, utilising cheaper off peak rates and home WiFi connections. It also ushers the application designer down the path of focussing the user experience on the real-time data aspects and prevents setting up unattainable expectations for the delivery of non-essential data. Finally, an advantage of an updatable rules set after the device has been deployed unlocks the potential to incorporate a device user’s home WiFi into a system. This can be done from a remote station or device user’s home PC, removing the need to support the user interface for this on the device. By delivering a reliable service that
effectively meets healthcare demands within the confines of bandwidth, user experience and delivery of the business model, the long-term prognosis for wireless healthcare applications is good.
Roke Manor Research |
www.roke.co.uk Ben Toner is Business Sector Consultant at Roke Manor Research
www.cieonline.co.uk
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