Supexor Studyathon: An introduction to analyzing real-world clinical data in hand and wrist disorders

In this one-day, hands-on ‘studyathon’ for clinicians working in the field of hand and wrist disorders, we will jointly perform an outcome study with big data on hand and wrist disorders. The concept of a studyathon is derived from a hackaton, where computer programmers work together is a short period of time on the same goal. In a studyathon, this goal is to perform a scientific study.

In introductory sessions, we will provide you with basic insight in research methods, data processing, and analytic tools. After this, in small groups, you will develop your own research question and answer this questions with the help of experienced data scientists, using our own Supexor dataset and/or a large dataset from The Netherlands. The end goal is an answer to the research question that was posed and draft a first version of a scientific manuscript in a team science approach.

The goals for the day thus are twofold:

1. perform a scientific study together while, at the same time
2. provide participants insights in the use of big data in the field of hand and wrist disorders.

In healthcare, there is an increasing presence of digital data, comprising patient outcomes collected in daily clinical care. These ‘big data’, like our Supexor data, can be extremely valuable for answering clinical questions on, for example, the expected outcome of specific treatments, the influence of patient- and disease characteristics on outcome, the effect of different treatments in similar patients, or the effect of a change in treatment policy.

While big data are widely accepted as potentially very valuable, using them for answering clinical questions can be challenging and requires a different approach than more experimental, small-scale, single-question clinical studies. Specific knowledge on the strengths and weaknesses of using real-world clinical data and on the specific research methodology is needed. In addition, analyzing large data sets with real-world clinical data requires modern tools and specific statistical analyses to provide valid answers to clinical questions.

Teaching goals

• To understand the concept of big data in health care and specifically big data on hand and wrist disorders;
• To understand the strengths and weaknesses of using real-world clinical data compared to experimental data, such as data from randomized controlled trials
• To understand the common problems in analyzing big data sets, such as missing data and selection bias, and the main tools to handle these;
• To understand the basic principles of comparative effectiveness and prediction modeling research with clinical data;
• To know how to translate a general clinical question into a specific, answerable research question;
• To understand the research steps needed to answer specific research questions using large real-world clinical data using programming languages such as R;
• To experience the potential that we have now that we are using Supexor in our clinics.

What is the target audience for this course?

This course is primarily aimed at clinicians working with Supexor in their clinics, who are interested in learning about how big data can be used to answer clinical questions. However, clinicians and researchers from outside our Supexor-partnership can also participate. Because of the small scale working group format, professionals with varying levels of expertise in research methods, statistical analysis, and data science can participate and expand their knowledge on this topic.

Preparation

Although not obligatory, we will provide participants with reading material and instructional videos on basic statistical concepts and analysis tools that will be used during the course. Participants will be asked to suggest clinical questions related to hand and wrist disorders to be answered when routinely collected outcome data are available.

Core Faculty

Ruud Selles¹, Harm Slijper¹, Lisa Hoogendam¹, Jaimy Koopman¹, Yara van Kooij², Maurizio Calcagni³ and Myrna Gunning³.
1. Erasmus MC. 2. Xpert Handtherapie 3. Universitätsspital Zürich

Location

Zurich

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