Closed Loop Intervention Impact Analysis Model
One of the major results of the project, delivered by Cardiff University, is the concept of a model for ‘closed loop intervention impact analysis’. This model, integrating across NSF, ICP and reference datasets, provides a standard framework within which to make clinical evaluations of the effect of particular intervention choices for preventing specified outcomes e.g., hospitial admission.
In the model, the flow of information assisted by information technologies can be summarised in 10 steps. The initial assessment clinic uses a portal to capture a range
of data items (approx. 57) from taking of history and physiological measurements using
a set of wireless instruments. In step 1, the results from a list of tests selected for the
patient are sent directly from instruments to the portal via a clinical data integration hub
(not shown). In step 2, data is assessed for ‘individualised risk’ to prioritise patients in
need of urgent referral and to compare their status with a ‘risk signature’ that might indicate
an immediate preventative or screening action to be taken. In step 3, a number of
optional specialised diagnostic tests may be triggered. Step 4 includes the collated data
populating an individualised patient ‘dashboard’ to help the clinician judge the status of
the condition against observed ranges - and help determine the best stepwise options for
the individual’s care and treatment. More detailed policy-based guidelines relevant to the
options at the ‘decision point’ are presented at step 5. Following discussion of options
with the patient, a specific intervention is selected and an appropriate personal outcome ‘target’ is set with active engagement of the patient. In step 6, the agreement on the target
sets up composite applications that communicate with the patient’s portal (step 7) for
comprehensive ‘at-home’ monitoring to manage the entire intervention ‘episode’. These
(prescriptive) actions write ‘procedural’ content into the detailed individualised care plan,
together with a schedule of appointments. At this point, different members of the care team
(through their view of the clinical portal) are alerted with additional professional support
of pertinence to the type of care/treatment intervention. An ‘end-to-end’ intervention analysis
application (step 8) systematically monitors progress against a single timeline to track
multiple (physiological) trends via the prescribed measurement modalities for evaluation
of interim outcomes (capturing any deviations from the plan) towards the agreed personal
target (step 9). Automating the recording of steps in the ICP in this way can capture new
evidence-based criteria i.e., whether patients revisit the clinic or ‘progress’ to the next part
of the care pathway according to the outcomes (i.e., the dotted line back to ’QUIRA’). This
end-to-end continuous care system has an advantage that patient status can be checked in
near-real time and should be flexible enough to overcome barriers to self management.
The improved data quality inherent in the device integration methodology provides a more
robust basis for clinical judgement.
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