Survival Data Analysis for Improving Patient Outcomes

By Bethany Phipps, The University of Adelaide

My Research Project was on the Survival Data Analysis for Improving Patient Outcomes. For a patient to undergo elective joint replacement surgery (JRS) clinicians must decide that coexisting chronic conditions are stable and impose minimal surgical risks. However the increased risk of patient outcomes after JRS due to comorbidity and multi-morbidity is not always addressed (multi-morbidity is the presence of additional diseases or disorders co-occurring with a primary disease or disorder). We now know that patients presenting with JRS are likely to have multi-morbidities. So the management of patient care for patients with multi-morbidities needs to be improved.

The aim of the study is to develop a statistical model, to predict post-operative patient pain and function using individual (pre-operative) patient multi-morbidity data. The ultimate purpose of the statistical analysis is to provide clinicians with a diagnostic tool for assessing the potential benefits of knee and hip replacement surgery for patients with multi-morbidities.

Through doing this research I was able to learn about the nature of receiving data from medical services. Not only is the paper work lengthy but so is the clean up. I realised not only how hard it is to collate and model the data in a way that produces meaningful results but also how important this is. With minimal understanding of the data and of the methods of analysis that you are using the results can easily prove misleading. Often I would find myself with an unintuitive result that was more a reflection of the limitations of my data set than any form of breakthrough. On the other hand understanding the data set and survival analysis allowed me to make well-supported conclusions even if they are built on gapped data. What I really learnt here is the importance of people. The importance of human minds to understand where our results is just as crucial as the results itself.


Bethany Phipps was one of the recipients of a 2016/17 AMSI Vacation Research Scholarship.


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