Idea Description
Supplementary Information
Innovation 'Elevator Pitch':
SAPIO aims to digitally transform the referral to treatment pathway in IAPT services, from an initial standardised digital assessment through to machine learning based insights using the historic IAPT dataset around treatment options and engagement.
Overview of Innovation:
SAPIO will provide a series of software modules, or features, within IAPT electronic patient record systems that will:
  • Streamline and digitise each stage of the patient journey from the point of referral, through assessment and appointment booking, to the start of treatment.
  • Leverage historical IAPT patient data at key decision points in the pathway for insights about how individual patients will respond to treatment. This could support therapists by signposting treatment options that have been effective for similar patients in the past.
  • Establish patterns of patient engagement through the use of predictive modelling, so that therapists might preempt patients at risk of dropping out and take action.
  • Use greater standardisation through the assessment stage, along with IAPT’s excellent data collection around diagnosis, treatment and outcomes, to improve the opportunity for even more reliable treatment insights into the future.
Modules within SAPIO include:
  • Standardised and digitised assessment that can be completed remotely by the patient as a first step.
  • Digitsed triage based on assessment.
  • Direct appointment booking by the patients.
  • Treatment insights.
  • Engagement insights.
  • Patient and clinician behavioural preference profiling and matching.
SAPIO is being developed by Mayden, the creators of the iaptus patient management system used by most IAPT services in the NHS in England. It is funded by the Small Business Research Initiative (SBRI). Phase 1, also funded by SBRI, tested feasibility and found clinical demand for a standardised and digitised assessment, as well as interest in treatment and engagement insights based on analysis of the historic IAPT dataset. The algorithm was able to predict whether or not a patient will recover from a given treatment type with precision greater than 90% and accuracy of 68.90% (+/- 0.83%). This has the potential to increase recovery rates by 12.5% (from 50% to 62.5%), and, for patients who did recover, to improve outcomes by a further 5%.

A prototype standard digital assessment was used by more than 800 patients a month in one IAPT service during Phase 1, and is already being adopted by other services.
Stage of Development:
Evaluation stage - Representative model or prototype system developed and can be effectively evaluated
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This scheme illustrates the requirement for more 'standard work' and process management systems in the NHS. It's the only way digital application can succeed.

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