Mark Figgitt Dec 23, 2021 11:20:57 AM 9 min read

Better healthcare through hospital scenario modelling and predictive analytics

How AI and machine learning are the perfect partnership to patient care

From admission to discharge, there is a lot that needs to happen for a patient to receive optimal care and the desired outcome. Efficient staff rostering, resource allocation, and visibility over patient progress all need to align - there are a lot of moving parts. At the enterprise level in healthcare organisations, the challenges are significant; having eyes on everything, ensuring patient and workforce wellbeing while balancing budgetary considerations.

In order to meet these challenges, you need to have a clear idea of:

  • How many patients you can expect to admit?
  • What type of care they need (as they'll be allocated to specialities)?
  • How long they'll be in the hospital?
  • How many patients are already in the facility, and where they are on their journey?

By gaining a clear understanding of these key challenges in your hospital operations you'll be able to effectively allocate staff and physical resources.

And when your organisation is dealing with something as impactful as Covid-19, you need to know specifics such as the number of ventilators available.

Obviously, your most expensive resources are your staff and beds, but if your facility has a neo-natal unit, for example, you need to know how many incubators you have; you can't just turn patients away or put them out the door. They need to be catered for.

Getting staff scheduling right is critical. If it hasn't been done properly, and you need more staff for a particular time period, your costs are going to rise as a result of bringing in agency nurses or requesting staff to do the overtime - not to mention the extra stress being placed on those staff.

Meeting these challenges is measured by the 'quadruple aim'. Basically, this is about enhancing the patient experience, improving quality, reducing costs, and improving the work-life balance of healthcare staff.

No one person can be across all of this, although not for want of trying; typically administrators use historical knowledge to get everything to align, and that's not possible - especially when a global pandemic wipes out the notion of 'business as usual'.

Artificial Intelligence (AI) and Machine Learning (ML) - the perfect partner for patient care

What AI, and especially ML, do is look for patterns and provide suggestions. They take the available data and predict what kind of patient numbers a hospital is likely to expect. They can do this with a high level of certainty including what specialities will be needed, so you can plan what resources you'll need and how many staff you'll need rostered on at any given time. In other words, your planning becomes proactive rather than reactive - always a much more successful way of operating.

You can also build in scenario modelling - if you know what to expect in different situations, you can plan for it. AI and ML are able to examine different scenarios, giving you the information you need to make better decisions around resources, patient care and staff scheduling.

AI and ML also provide predictive analytics - it's like looking into the future. The idea is to spot systemic issues with any area, so they can be resolved before they become a problem. And it means you can match resources to demand.

When you bring a software solution on board that leverages AI and ML, it's not changing anything - it's providing options for clinical staff so they can make better, informed decisions in a shorter timeframe.

Patient flow, staff scheduling software - what to look for

Not all hospital capacity management software solutions are created equal. When you decide to evaluate the available options, there are some key considerations to keep in mind:

  • The ability to integrate with your current systems - it must be able to take data from multiple sources; a standalone solution won't do this. And the whole point is to utilise your data so that AI and ML can analyse it. It should act as a communication tool that provides the information needed to make effective decisions.

  • Ease of use - the last thing you want is a complex system that's difficult to get to grips with. The idea is to make life easier for your clinical staff, not harder. They're healthcare specialists, not tech wizards, so the solution you're considering should be simple to understand and to use. Anything that requires input from a nurse will take them away from their core function - patient care - so the technology they're using needs to minimise that time away and deliver value.

  • Implementation partner - these solutions are not set-and-forget. You need a partner on board who will not only help deploy the new system, but have a good understanding of your organisation, your staff, and your requirements. Your partner should consult with you about change management, because this is a change process. You don't want someone who'll simply throw the switch and leave; on-going support is crucial, because the solution should be configured to your specific needs on an on-going basis.

Bringing a capacity management solution on board is a journey. You and your software partner will work together continually to make improvements, because you can't realise 100% of the benefits the solution offers on day one. These grow as you work through the implementation and changes.

Our Capacity Management solution

We've leveraged AI and ML capabilities to develop capacity management solutions that provide accurate forecasting of patient demand to help facilities maximise capacity, improve staffing resource alignment, and deliver exceptionally safe care. It's a suite of products that work together, and in conjunction with existing hospital systems, to deliver optimal outcomes.

These products are continually enhanced based on client feedback - we're always looking for ways to improve. The solution is configurable, so it can be tailored for individual requirements.

Now more than ever, healthcare organisations need to innovate, to leverage the kind of technology that's been specifically designed to improve and streamline hospital management in order to provide optimal patient care, ensure the wellbeing of clinical staff, and reduce costs wherever possible.

Are you ready to be stronger together? Book a demo of our capacity management solutions today.

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Mark Figgitt

Mark Figgitt is the Executive Director for HealthStream Capacity Management in Australia and New Zealand. In addition to his Executive and General Management role, he is also responsible for the global product management and development of Capacity Planner™, and Capacity & Resource Advisor™.

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