Our Resources

Here you can find some of our resources that we developed as part of our work over the years and that are freely available to the public. We will continue to add more over time. 
Please note that some of the resources listed below include published academic articles. These items include links to external websites where the resource can be accessed. 

Want to use these resources in your work? Feel free to reach out to discuss how we can help!

IMPACT: A Framework for Outcomes

This framework helps you develop meaningful outcomes that link directly to your practice and services

Five Key learnings for Evidence-Supported Decisions and Service Optimisation

This resource provides some critical points that will help your organisation to transition towards an evidence-based and data supported culture. 

Decision-based models of the implementation of interventions in systems of healthcare

with W.W. Tan and A. Shlonsky

In this article we discuss an extension of hybrid type designs for implementation outcomes evaluation that integrates advancements in implementation sciences with causal inference models and structural causal models. This approach is grounded in the natural decision processes in organisations. (The link below will take you to the open-access article on the publisher’s website)

Talk to us

Have any questions? We are always happy to talk about new projects, innovative ideas and how we can help you.

Kailas Thonnithodi

Research and Project Assistant

Data Science | Research | Machine Learning | Artificial Intelligence | Data Engineering

Kailas has a strong foundation in machine learning, deep learning, and data analytics. He is currently completing a Master’s in Artificial Intelligence at Monash University, following a Bachelor of Artificial Intelligence from Deakin University. 

Kailas has experience working with data to develop predictive models and generate insights, with a focus on translating complex information into practical outcomes. At Stats With Purpose, he is keen to apply his skills in data, analytics, and AI to support evidence-based decision-making and contribute to meaningful social impact.