Too often, patient pathways of care become convoluted and inefficient, frustrating patients and carers in the process. Edge Health supported a health system to identify these inefficiencies and create better outcomes for the local population.
We worked in partnership with the acute care provider, local GPs and other stakeholders to develop algorithms which identified patients with specific characteristics and which then classified them based on risk. We were able to identify specific cohorts of patients who were receiving unnecessary or repeated interventions – not only wasting their time, but valuable NHS resources - and, working with staff, we modified the pathway. For instance, we were able to track and make recommendations for frail elderly patients who were being over-rehabilitated in hospital, but who on discharge were not receiving appropriate home care, resulting in them being re-admitted to hospital with broken hips (example below).
By using complex information to produce real-world solutions, we helped the health system to improve patient experience monitoring and reduce the number of clinics, whilst maintaining service provision. This in turn lead to significant financial savings which could be reinvested in patient care.
Pathway Miner is our analytical engine for helping identify unwarranted variation in hospitals or health systems. It uses linked patient level data to generate longitudinal data visualisations, which stimulate and engage local clinicians. In the background, advanced algorithms then search for cohorts of patients that have similar characteristics, which inform commissioning developments.