Acute Care and Mental Health Recovery Summit: Breakthrough Learnings Through Collaboration
Ming Tang and Richard Corbridge shared key insights with attendees that will ensure clinical, delivery and interoperability success. They enlightened attendees on how executives should navigate healthcare’s uncertain future; and how data-driven technologies will support these endeavours. Richard Corbridge stated:
“The future of health, consumer care and pharmacy is fascinating. Predictive analytics tell us that there is a need to create a new model that uses data to drive a more personalised route for healthcare. We need to ensure that healthcare reflects an omnichannel experience; and we can create this through digital capacities.”
For all attendees and leaders in the health sector, this notion holds true. Predictive data optimisation will herald a new age of productivity and better patient outcomes in healthcare. As Ming Tang stated in her keynote speech, events like the Acute Care and Mental Health Recovery Summit provides a platform to discuss and explore data’s role in innovation.
“The role of data and analytics will transform the way we recover in the NHS. At the moment, we’ve dedicated future-forward thinking in terms of recovering our health ecosystem, with a focus on patients instead of just services. Neglecting opportunities to discuss the onward journey and the role digital tools will play throughout will preclude any forward momentum”
Addressing the Acute Care and Mental Health Challenge
The COVID-19 pandemic taught all of us the value of supporting a data-driven culture within individual Trusts and the entire health system. Without the support of integrated data analytics infrastructures, many attendees acknowledged how health facilities narrowly avoided breaking point in service provision.
In preparing for the future, RwHealth armed the health community with never-before-seen insights regarding recovery, vaccination success and other real-life challenges. Through predictive analytics and capabilities, the summit revealed key statistics that will determine the best approaches to tackling key issues.
One of the core topics discussed during the event was Acute Care’s Capacity and Demand issue – a challenge that was a top concern for 81% of the summit’s attendees. As COVID-19 struck, one of the most critical decisions our government and health care providers faced was how to best allocate limited medical resources, including intensive care unit (ICU) beds and ventilators.
According to Ming Tang, healthcare leaders can only avoid a true crisis if they stratified their continuity objectives based on predictive data and forecasting capabilities.
“As we try to level up recovery and health equalities, data will be invaluable in helping everyone access support and care. What we’re looking to do is pull together the healthcare fabric through data. What we want to do is maximise the use of technology to make sure that data is connected once, and used multiple times and efficiently.”
RwHealth’s Data Science Platform (DSP) was named as one of the tools to protect our health system against potential crisis events. Those who attended the event explored how the DSP could optimise decision-making support.
Preparing for Potential Surge Crises
Looking forward, the potential of a surge crisis may backtrack the progress that executives have made in safeguarding the NHS and public health.
In order to help health executives prepare for surge crises, RwHealth provided predictive analytics and modelling to highlight future industry challenges and solutions. To mitigate the effects of future crises, enhanced interoperability, cross-functional data initiatives and modelling technologies will be needed across the whole system. As Ming states:
“What we need to do is create an infrastructure that supports the plethora of digital applications, federated care and the individual patient journey. Our vision is to support the NHS Long Term plan and recovery road map, but making sure we do this through AI, Data and Machine Learning operations”
About RwHealth