Wirelesshealthcare


Wireless Based Disease Management. (Google, Microsoft And IBM In The Healthcare Market)


Research into existing and emerging technologies that can be used to support remote disease management, modelling and monitoring services.

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Contents.

Profiles of IBM, Google, Microsoft, Voxiva, Tplus Medical and Cerner.
Also mentioned in this report, Oracle, 23andme, Siemens, Medstory and HealthLink.
The role of disease and epidemic monitoring within the new ehealth model.
Search engines as a platform for disease management.
Genomics and disease management.
Privacy and disease monitoring.
Opportunities and threats for healthcare providers and IT Vendors.
Relative merit of centralised and de-centralised deployment models.
Relative merit of opt-in and opt-out use models.

A diverse range of IT vendors will compete for a share of the disease monitoring and management market. Many will be pitching their middleware solutions against those of rivals, with both IBM's WebSphere and Oracle's Healthcare Transaction Base being offered as means of transporting data between wireless devices - used to collect vital signs from patients - and the intelligent applications that model and monitor epidemics and diseases. This middleware will also provide support and disease management to patients. However, Internet search companies such as Google, which already recognises that a large number of its users are searching for information to help them diagnose a particular condition, are also well placed to build a disease monitoring and management service.

IBM will use centralised supercomputer based applications, hosted by international disease control centres, as a means of gaining a pivotal role in the global healthcare market. Meanwhile Google is already forging links with companies developing wireless based disease monitoring and genetic testing services. These are not the only two IT vendors who recognise that disease monitoring and epidemiology, backed by advances in genetics, will become an increasingly important component within an integrated healthcare system.

However, IT vendors and healthcare providers should avoid becoming over-reliant on genetic profiling, as the current face-to-face consultation with a GP can often identify diseases that have a wide range of causes - including some that are psychosomatic. If GP consultations are automated and the number of patients turning to online services for a diagnosis increases, there will be a growing demand for intelligent technology that can identify psychosomatic diseases. This technology could be an extension of the intelligent software currently used, in beta form, to profile Internet search users.

Privacy will be an important consideration, with users either opting out of the large disease monitoring systems put in place by healthcare providers or being unwilling to opt into smaller-scale online systems. Nevertheless, if computer assisted disease management is marketed correctly, patients will be willing to trade a degree of privacy for a timely diagnosis - and support if they are found to have a disease.

This report examines a range of epidemic and disease monitoring and modelling technologies and identifies key trends in this market. It also considers the relative merits of the centralised 'top down' and distributed 'bottom up' deployment models and the opportunities each route to market creates for wireless device and medical software vendors.

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