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Raphael Thys
Improving operational efficiency has emerged as a priority for healthcare facilities as they seek predictive ways to manage and allocate resources at a time of ever-increasing demand for their services.
Many of them are now turning to AI as a key enabler of a more progressive approach, helping them to plan their logistical responses based on the latest data – and maintain their focus on delivering end-to-end patient care of the highest quality.
Challenges for healthcare providers
A growing patient load creates significant operational challenges, not least for the management of the patient experience itself. For example, where appointment schedules are not properly optimised, the disruption to patient flow throughout a facility can have a significant impact on waiting times.
Providers need to be able to sustain a consistent flow of patients and visitors, and meet it with appropriate resources, including clinical staff, hospital beds and operating theatres, at every stage of the patient journey.
If these challenges are not dealt with adequately, the operational consequences can mount up: dissatisfied patients, and inefficient and expensive resource utilisation. Inconsistent patient flows create long queues at more congested points. Other service locations stand idle while still consuming power and human resources as they wait for patients to come through.
Leveraging AI to address these challenges
In response to this typical situation, data scientists from NCS' AI team have built a schedule optimisation tool – the Enterprise Schedule Optimisation Platform – that demonstrates how AI can plan more effectively than humans as the demand for healthcare services grows.
Healthcare administrators can only engage with a limited number of data points simultaneously. But AI can compute exponential permutations from a practically limitless source of data points, building predictive models that enable real-time operational response from the provider as well as helping them to plan future resource allocation.
This concept is now being developed at the Singapore National Eye Centre (SNEC), which has partnered with NCS to design, build and deploy a new Appointment Scheduling Optimiser (ASO). Easy to configure by trained business users, the ASO will transform the clinic’s operations, reducing patient waiting times and allocating resources more efficiently.
"Currently, appointment scheduling for all patient visits including those requiring initial consultations and the necessary same-day eye services and investigations is a time and labour-intensive process handled by appointment staff," says Jim Gu, SNEC's chief operating officer.
"To address the growing volume of appointment requests and limited visibility over demand at multiple service stations resulting in bottlenecks and long clinic waiting times, SNEC collaborated with NCS to leverage the ASO to resolve the various pain points."
The new approach disrupts the traditional mindset of taking patients' exact preferences for specific dates and appointment times, gathering instead more general preferences from patients who are due for appointments within a particular timeframe.
Using NCS' AI technology, advanced analytics and machine learning capabilities, the scheduler will consider these inputs as well as resource variables – clinician schedules and availability, types of service, facility availability – and objectively generate an optimal schedule. The ASO will also be responsive to real-time changes, re-optimising schedules to accommodate events such as patient no-shows or unavailable resources.
This level of versatility combined with the ASO's ability to maintain optimised scheduling in response to rapid shifts in service demand makes for a powerful AI-fuelled proposition.
Looking to the future
NCS' vision for healthcare digitalisation is based on the idea that AI is a key driver, which can bring a comprehensive range of benefits to every aspect of healthcare services. These benefits are already being realised on a number of fronts, from robotic nursing assistants and fall-prevention solutions to intelligent speech and sentiment recognition for call centres, and video analytics solutions for managing security and social distancing enforcement.
"AI is a key catalyst in ushering a new paradigm where healthcare providers can leverage it as a productivity multiplier to continue to deliver sustainable, quality healthcare services and further improve the patient experience in the face of rising costs and limited healthcare resources," says Daniel Ng, Enterprise Architect, Healthcare at NCS.
"AI in healthcare is most effective when it sets out with the intention to support, and not supplant, the patient-doctor relationship. Many of the algorithms we employ today are well known in the AI world. Only when it enhances our healthcare workers’ ability to focus their hearts and minds on patients – by abstracting the transactional or computationally complex tasks responsibly – can they then find their place as healthcare solutions," says Yong Xu Chang, Practice Lead for Applied Analytics at NCS.