A system such as Healthcare@Home primarily caters to the following 3 categories of end users: clinical staff, patients and researchers / statisticians. A portal based interface has been developed and deployed to satisfy the needs of each category. A portal framework provides a secure and customisable interface.
The clinician portal faithfully mirrors the ICP. Various stages in the ICP have been captured by building and deploying a suite of portlets. Graphs provide for a timeline-based layered approach to a key problem in patient-centred health monitoring services: analysing trends to evaluate outcomes as a result of treatment interventions. It is a requirement that a variety of information can be presented in an uncluttered and intuitive manner. For the clinical end user, the multi-trends can be visualised in a concise ‘at-a-glance’ view of the patient’s status.
Detailed information is available by drill-down ‘behind’ each trend summary to reveal collated time-series data on whatever timescale is desired (day, week, month, year).
Detailed information can be obtained by intuitive interaction with the graph. A typical time series might exhibit ‘timeline flags’ denoting patient events/activities, targets within which the sensor readings should fall alongside the readings from sensor devices. The targets are set by clinicians based on the patient's medical condition and the stage of the treatment that they are in.
The patient portal interface has a simple design so that it can be accessed from various types of devices including: mobile phones, internet browsers and TV clients. The patient portal overlaps with classical Personal Health Record (PHR) functions that can be used in conjunction with Electronic Health Record (EHR) information. The overall objective is that patients gain better insight into their condition. The patient portal has an open design to permit visualisation of multiple trends and events in a uncluttered menu-driven manner.
The researcher / statistician portal is designed to supply anonymised read-only data to authorized statisticians, researchers and policymakers for service-based trends analysis. There is considerable value in the automated aggregation of service or clinical facility data (through federated interoperable mechanisms) especially for evaluating the impact of research or health policy interventions across the population and for planning future service provisions.