HTN Voice: Population Health Management, shaping the care pathway through flow optimisation

By Orlando Agrippa, CEO of Draper & Dash Predictive Healthcare Analytics

Working on the ground with healthcare teams and executives, I’ve seen time and time again the serious impact that factors which are often overlooked in the realm of patient care can have. Beyond the issue of medical optimisation and clinical treatment, patients are often let down by the management of their journey and care pathway. Frequently, these are patients that are high dependency and high cost, and such oversight has devastating consequences on both patient experience and outcome, as well as on the healthcare provider itself. Something as simple as changing the setting of a patient’s care can be enough to significantly boost their wellbeing, not to mention reduce the strain on the healthcare organisation itself. However, this is oftentimes forgotten in the face of more “urgent” issues. With the pressure on healthcare teams within the NHS at an all-time high, it is clear to me that novel methodologies designed to monitor and manage the patient journey will be crucial to lifting some of this weight from their shoulders, improving the ease and efficiency with which they can plan each care pathway. And thus, it was from this very ethos that our newest solution was born – the Population Health Module.

Population Health Management (PHM) is a current rising star in the NHS, a sentiment echoed by Dr Marc Farr, Chief Analytical Officer at East Kent Hospitals NHSFT and founder of Beautiful Information, when I spoke recently to him about his thoughts on the current state of this area. For those of you who know of Marc and Beautiful Information’s work, you’ll know that this is a definite area of expertise – something that was certainly reflected in his comments on the matter. He notes that as PHM begins to “take grip in the NHS”, it will come with the necessity for intelligence to support it, and while Marc believes the recent move from STPs to ICSs could create a delay, it may in fact form a “necessary building block” for the establishment of new governance. With this, he believes that genuine changes to the commissioning of services and contracts will take place. Indeed, recent years have seen increasing resources and promising examples of PH intelligence being developed by Public Health England, Marc highlighting the Decision Support Unit in the West Midlands and the Kernel linked dataset in Kent as particular successes.

Speaking to the current challenges in leveraging population health within the NHS, Marc describes how the development, maintenance and sharing of local linked data crops up as a common issue. Data utilised beyond direct patient care, thus extending beyond the clear-cut information governance model under GDPR, is still referred to as ‘secondary use’, and Marc believes that a less pejorative and more suitable term would be “data for improvement”. Or “#datasaveslives”. The ultimate aim should be to develop creative plans which work to link an ever-evolving range of datasets together in a way that allows all parties to be comfortable in the knowledge that good governance exists and that relationships are strong. This is a methodology already set in motion in some instances, one example Marc raises being the current work to link police and health data in a quest to develop statistical models that support earlier intervention into Intimate Partner Violence (IPV). Crucially, Marc believes that one of the elements that needs to shift is the recognition of the analytics underpinning PHM, too often lost within a digital work stream dominated instead by the technical challenges of single organisation and regional clinical system procurements.

As we keep our fingers crossed for #datasaveslives to be the next big hit on trending, we have also as a company taken steps towards creating our own PH-based analytics systems, developing a unique and powerful module to allow Integrated Care Partnerships and Systems. Through this, improved support is provided to high dependency, high cost patients, monitoring these cohorts and their journeys throughout community, acute, and mental health services. In turn, ICSs and ICPs can ensure that these patients receive the best, most cost-effective care and avoid the avoidable, cutting down on non-elective care admissions. Indeed, the deployment of this solution at some of our acute partner organisations has already supported the delivery of a number of real-world improvements to a range of critical healthcare metrics.

Notably, length of stay (LoS) – a focus that underpins much of our work at D&D and has substantial impact on both patient care and hospital efficiency – has shown significant improvements in numerous areas. By supporting the development of a range of new pathways, our partners saw a 25% drop in LoS for hip and knee operations, as well as a 17% reduction in the average in-patient LoS for those admitted on a non-elective basis, within a year of implementation. Similarly, the average in-patient LoS for elective admissions fell by 23.5% within this first year, in addition to one trust achieving a significant improvement in relative efficiency, as indicated by a reduction in their Reference Cost Index (RCI).

How this solution actually does the job revolves around targeting several key points, one of which being support to the improvement of system-level service design and the subsequent enabling of better demand management, in addition to reducing admissions for services that would in fact be better delivered in community settings. It is also designed to facilitate early discharges where early discharges are indeed appropriate, as well as helping the transition of high dependency patients between care settings in a seamless manner. The effectiveness of system partners is monitored through implementation of this solution, providing a financial case for investment in specific service types. Through these key functions, users are afforded the ability to track and manage patients throughout their journey, optimising their pathway and ensuring patients are receiving the absolute best levels of care, in the most appropriate setting possible.

Marc’s insight into how this underlying analytical capability is often left forgotten, and how there still remains an unwillingness to utilise or share data that would otherwise be of huge benefit to both patient outcomes and organisational cost-efficiency, emphasises an issue that serves as a serious blow to the progression of future improvements in the area of PHM. With so much of each patient’s welfare dependant on this being handled properly and efficiently, the need for technological intervention is clear. In light of this, integration of our PH module has already delivered demonstrable improvements to patient flow and organisational efficacy with our acute partners, something I truly believe has the potential for transferability across the board. It is therefore with great excitement that we share with you our new solution, and welcome any interested in learning more about the Population Health Module or our experiences to reach out.


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