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Healthcare Facility Capacity Prediction

The Brief

BaptistCare, a leading not-for-profit Christian care organisation, is committed to delivering exceptional care with people at the centre. Serving over 24,000 individuals across more than 100 locations in NSW, ACT, and WA, BaptistCare focuses on building strong, caring communities. To enhance their healthcare services and better predict capacity and length of stay for elderly patients, BaptistCare sought to utilise advanced machine learning technologies.

They partnered with Experience Digital to develop a robust machine learning model capable of forecasting healthcare capacity and days of stay based on factors such as age, medical condition, and other health indicators. This collaboration aims to boost BaptistCare’s operational efficiency by improving forecasting and resource allocation, ensuring that each individual receives timely and personalised care, furthering their mission to transform lives and support their communities.

Our Approach

To meet BaptistCare’s need for precise healthcare capacity predictions and optimal length of stay forecasting, we adopted a comprehensive machine learning development approach. Our task was to design a predictive model that leverages critical patient data, including age, medical conditions, and other relevant health indicators, to improve accuracy in capacity planning and resource allocation across BaptistCare’s facilities.

We began by thoroughly analysing BaptistCare’s existing data, identifying key variables that significantly impact healthcare capacity and patient stay duration. With this information, our team developed a machine learning model capable of processing and analysing vast amounts of data to predict future trends and outcomes accurately.

Our approach involved several stages:

  1. Data Collection and Preparation: We gathered data from various sources within BaptistCare, covering patient demographics, medical histories, and other relevant factors.
  2. Feature Engineering: We transformed raw data into meaningful features to enhance the predictive power of the machine learning model.
  3. Model Development and Training: Using advanced machine learning algorithms, we built and trained the model to identify patterns and make accurate forecasts.
  4. Validation and Testing: The model was rigorously tested against historical data to ensure its accuracy and reliability.
  5. Deployment and Integration: Finally, we seamlessly integrated the model into BaptistCare’s existing systems, ensuring it could be effectively utilised by their staff.

The Outcome

Throughout the project, we worked closely with BaptistCare’s team to ensure the solution aligned with their specific needs and operational standards. The outcome is a robust, data-driven tool that enables BaptistCare to accurately predict healthcare capacity and patient stay durations, allowing them to continue providing exceptional and timely care to their communities.

About

BaptistCare is dedicated to providing care that truly places people at the centre. As a leading not-for-profit, Christian-based care organisation, their primary focus is on the well-being of the individuals they serve, ranging from older Australians and their families to those experiencing significant disadvantage. BaptistCare is committed to building strong, caring communities, supporting over 24,000 people across more than 100 locations in NSW, ACT, and WA.

With a devoted team of over 6,000 employees and 600 volunteers, BaptistCare transforms lives by helping individuals live well through a variety of services, including residential aged care, in-home care, retirement living, and community services and housing. For BaptistCare, “People First” is not just a philosophy; it’s their core identity and has been since 1944.

About Experience Digital

Enabling businesses to thrive in the Digital Era.

Experience Digital is a trusted national digital software, data, automation, and systems integration house that has vast experience in assisting clients to transition to a digital future.

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