<p>Interested in exploring predictive analytics for your hospital or health service?</p> <p>We’re only just at the beginning of what’s really possible for predictive analytics. But there’s already plenty of opportunities for hospitals that are ready to transform their approach to data.</p> <section class="blogSectionHeading" id="1"> What is Predictive Analytics? </section> <p>Predictive analytics involves using machine learning or predictive modelling techniques to make predictions about what might happen next. Just like predictive text on your phone uses the context of the words you've just typed (along with past usage patterns) to suggest what you'd like to write next, predictive analytics does the same thing — but with numbers.</p> <p>It works by using machine learning, predictive modelling, and algorithms to learn from the data, find patterns in historical data, and map relationships between different bits of data, to predict future values (and outcomes).</p> <section class="blogSectionHeading" id="2"> How is Predictive Analytics Changing Hospitals and Healthcare? </section> <p>Despite limited data analytics capabilities and practices in most health systems, predictive analytics is already having a significant impact on healthcare and hospitals.&nbsp;</p> <p>The biggest difference is that hospitals are actually starting to use some of the huge volumes of data they collect as a tool for decision making. With predictive analytics, we can provide structure to that data so that we not only understand what it means, but can produce actionable insights that enable hospitals to make better decisions faster.</p> <p>In a hospital and healthcare setting where resources are tightly managed, being able to accurately predict demand ahead of time can make a real difference. It can allow staff to focus their resources precisely when and where they’re needed most, reducing risk and improving patient outcomes.</p> <p>But let’s get a bit more specific…</p> <section class="blogSectionHeading" id="3"> 6 Examples of Predictive Analytics in Healthcare </section> <p>We’ve used predictive analytics in a range of ways, allowing hospitals to access specific insights from their data, supporting risk reduction, service improvement, and efficiency. Here are just a few examples of what’s possible…</p> <section class="blogSectionHeading" id="4"> 1. Insights that Drive Waitlist Reduction </section> <p>Predictive analytics can help to address long-term waitlist problems by providing insights into areas like:</p> <ul> <li>Demand and capacity</li> <li>Waitlist composition</li> <li>Clinical urgency</li> <li>Case-mix complexities</li> </ul> <p>These insights can drive service improvement projects and waitlist reduction plans.&nbsp;</p> <section class="blogSectionHeading" id="5"> 2. ED Scenario Modelling </section> <p>As COVID-19 becomes endemic, many emergency departments are pursuing operational and structural changes to keep up with growing demand. Predictive analytics can be used to model scenarios that guide business cases associated with ED restructures to avoid costly traps and ensure the best outcomes</p> <section class="blogSectionHeading" id="6"> 3. Real-Time ED Prediction and Flow Optimisation </section> <p>Digital twins are continuously updated digital representations of physical systems. They can be used in combination with predictive analytics to identify risks, find opportunities, and suggest strategies in real time. By setting up digital twins of your emergency department, you can forecast your ED state over the coming hours to determine which patient movements would maximise flow.</p> <section class="blogSectionHeading" id="7"> 4. Predicting Risk of Hospitalisation </section> <p>The rehospitalisation of patients within weeks of a previous discharge is a well-established problem from the perspective of both hospital demand and patient safety.&nbsp;</p> <p>You can monitor the risk of rehospitalisation by:</p> <ul> <li>Using SystemView’s Risk of Hospitalisation (RoH) components to identify inpatient rehospitalisation risk at a patient level</li> <li>Integrating RoH into clinical models of care and using predictive analytics to quantitatively assess patient benefits</li> <li>Developing custom models that improve RoH accuracy for specific patient cohorts</li> </ul> <section class="blogSectionHeading" id="8"> 5. Procedure Operating Time Studies </section> <p>Theatre time varies widely across consultants, hospitals, and jurisdictions, making it challenging to define set procedure times and appropriately utilise theatres.&nbsp;</p> <p>SystemView’s core product provides booking suggestions to optimise theatre utilisation and chronological management via the Elective Schedule Monitor component. Our Predictive Analytics Team can extend on this application through a more detailed analysis of theatre use data that can help uncover more insights into session underrun/overrun risks and how to minimise them.</p> <section class="blogSectionHeading" id="9"> 6. Outpatient Appointment Non-Attendance Predictions </section> <p>For many areas, outpatient appointment non-attendance rates are approaching 10%. This is cause for concern due to the negative impacts on patient health and safety — plus, every missed appointment is a missed opportunity to provide healthcare and maximise the use of hospital resources.</p> <p>We can apply machine learning algorithms to commonly collected hospital data in order to predict when patients are more likely to miss their outpatient appointments. This can allow hospitals to use targeted strategies to reduce the likelihood of non-attendance, like verifying patient attendance prior to the appointment, or giving the patient options to cancel or rebook.</p> <section class="blogSectionHeading" id="10"> Leverage Predictive Analytics with SystemView </section> <p>SystemView is a hospital management system that allows hospital teams to monitor hospital demand, activity, and patient flow. It integrates data from various source systems into one place to enable charts, dashboards, and visualisations, real-time monitoring and alerts, trends and reports, and the actionable insights needed to manage patient flow.</p> <p>Although our core product is equipped with advanced data capabilities, many of our customers can benefit from additional support to make the most of their data and solve specific problems.</p> <p>That’s where our Predictive Analytics Team comes in.</p> <section class="blogSectionHeading" id="11"> Our Predictive Analytics Process </section> <p>Curious about how our predictive analytics service works?&nbsp;</p> <p>SystemView’s Predictive Analytics Team starts by meeting with your health service team to understand your requirements, before exploring possible solutions. Depending on what’s required, we’ll then draw upon a range of tools and techniques, including:</p> <ul> <li>SystemView’s core product – Our team is intimately familiar with the SystemView data warehouse, allowing us to move quickly and leverage the curated datasets to tackle pressing issues or explore opportunities</li> <li>Statistical and descriptive analytics tools – We may use these tools to pull apart data and help expose details normally hidden or lost in the noise</li> <li>Predictive analytics methods – We often use statistical models, machine learning, and simulations to explore the dynamics behind the data and make predictions about future outcomes (or answer ‘what if?’ questions)</li> <li>Scenario modelling – This approach may be used to test and develop new business cases</li> <li>Automated pipelines – We can generate custom dashboards, tables, and visualisations</li> <li>Digital twins – These visualisations can help to provide live forecasting and optimisation</li> <li>Prescriptive analytics – We can use AI systems informed by models and other evidence to answer the question ‘so what would we do?’ and transform the insights into decisions (almost like a self-driving hospital)</li> </ul> <p>Throughout the process, our team will be in touch regularly to unpack any evolving requirements and continuously demonstrate, test, and refine solutions. And if you need further support at any point down the line, we’re here to help.</p> <section class="blogSectionHeading" id="12"> Explore Custom Solutions With SystemView’s Predictive Analytics Team </section> <p>Interested in using advanced predictive analytics to solve a specific problem in your hospital or health service? SystemView’s Predictive Analytics Team works exclusively with SystemView customers to help unlock new insights that drive efficiencies, service improvement, and smarter decision making. We’re experienced in tackling a variety of challenges at all scales, from supporting clinical teams to national healthcare reforms. Our past solutions have included:</p> <ul> <li>Analysing demand and capacity at team, hospital, and national levels</li> <li>Managing waitlists for outpatients and elective surgery</li> <li>Supporting automated clinical systems using AI</li> <li>Allocating procedure operating times</li> <li>Managing inpatient occupancy and flow</li> <li>Improving emergency department flow</li> <li>Managing ambulance ramping and access block</li> <li>Reducing rehospitalisation rates</li> <li>Analysing costs and revenues</li> </ul> <p>Whether you’ve already got the core SystemView product and you’re ready to extend its capabilities, or you’re starting to explore options for a more advanced hospital analytics solution, we’d be happy to help.</p> <p><a href="https://www.healthcarelogic.com/web/guest/contact-us">Contact us</a> to find out more about our Predictive Analytics service or to request an initial consultation to discuss a specific challenge.</p> <style> .blogSectionHeading { font-weight: 600; font-size: 24px; } </style>