By analysing demographic shifts, epidemiological data, clinical data and other population and societal trends, demand modelling assists in predicting more accurately healthcare service requirements from a clinical and operational perspective.
In parallel, capacity modelling evaluates workforce availability, the physical capacity of facilities and the availability of specialist equipment to align resources with anticipated demand. These models can identify potential bottlenecks and inefficiencies within the system and can incorporate agreed interventions to resolve problems before they arise.
It is important to understand that there is no off-the-shelf solution for a highly complex undertaking like health service demand and capacity planning. The number of variables to be taken into consideration is constantly changing due to factors such as medical advances, changing population behaviours, human resource issues, and much else besides.
Additionally, there is no “one-time-fits-all” approach – modelling health system needs is an ongoing, live and iterative process. The rapid evolution of factors that can impact the system means that heath planning models function best where there is an ongoing ability to ingest new information to inform outputs. This approach ensures that the modelling stays current, relevant and, most importantly, delivers actionable outputs.
The unique model developed to replicate any given system and the demands placed on it must therefore be constantly updated to reflect both internal system changes and those affecting the external environment in which it operates.
Ultimately, demand and capacity models are only as good as those who fine-tune them with historical and emerging data as well as clinical and operational factors experienced on the ground.
The application of the best data and analytics, which are iteratively updated and improved, combined with the integration of clinical insights and operational expertise are an invaluable asset in enhancing healthcare delivery.
Collaboration and engagement with relevant stakeholders as models are developed and deployed are crucial to developing robust, adaptable, and sustainable models.
Amongst the key benefits of system specific capacity and demand models is the ability to plan ahead for different scenarios and design improvement initiatives in a confident and structured manner. Proposed new interventions and services to meet specific challenges and arising demands can be tested prior to implementation to assess potential impact and effectiveness. They are especially valuable in identifying any unintended consequences that may arise from proposed plans.
They enable health leaders and decision makers to compare the projected impact of proposed changes to service delivery – both in terms of different options available as well as relative to current system configuration. The modelling permits the impact of interventions to be benchmarked against key metrics including:
Advanced health analytics/ modelling, traditionally know as demand and capacity modelling, has the potential to become a real driver of change in the healthcare system, bringing the combined power of data and clinical and operational knowledge to the fore. This, in turn, can support service delivery to improve patient experience and quality outcomes, leading to a positive societal impact for all.
By harnessing clinical and operational insights and translating them into data-driven strategies, Ireland’s healthcare ecosystem can navigate complexities, enhance patient care quality, and achieve sustainable growth amidst evolving healthcare dynamics.
Summary
Ireland’s growing and ageing population will put increased pressure on an already strained health system in the coming years. While increased funding will be required, its application and investment needs to be informed by new ways of thinking and planning health services. The use of advanced data analytics to create accurate and dynamic capacity and demand models has the potential to enhance patient experience and outcomes. It can improve overall population health while delivering significant efficiency gains for the health service.