Khan K1, Lowe R2, Jannenga H3, Walton A4
1The University of British Columbia, Vancouver, Canada, 2Physiopedia, London, United Kingdom, 3WebPT, Phoenix, United States, 4Connect Helath, Newcastle, United Kingdom
Learning objective 1: Describe what 'big data' and Artificial Intelligence is (and is not) and how best practice organisations are already using big data to advance clinical practice.
Learning objective 2: Discuss how big data will influence the future of the global physiotherapy profession and what your role in this will be.
Learning objective 3: Be in a better position to make decisions about utilising big data in your professional context.
Description: In a new world of personalised medicine, current research methods will not be able to keep pace with the information needs of patients, clinicians, managers, researchers, and health policy makers. Big data is already an engine for the knowledge generation that can address unmet information needs . Artificial intelligence is already here. Ignoring it today is like ignoring the internet in the 2000s. In healthcare collecting data is easy; for data to be useful it must be collected in appropriate form, analysed, interpreted skillfully, and acted upon.
The role of big data in medicine and physiotherapy is in building more detailed health profiles and effective predictive models around individual patients so that we can better diagnose and treat disease . It can help prove the value of our practices (and disprove those that are not effective) within the healthcare system. Cost, clinical and satisfaction data all provide objective information that can direct education, improve practice and outcomes, change perspectives and support pro-physiotherapy efforts. Collecting outcome measures is a widely accepted part of improving clinical practice and demonstrating value; two best practice examples will be explored during this symposium. There are also many other forms of big data , that are not yet being fully exploited and we will share examples including some from low income contexts. The concept of data sharing and gathering a global pool of clinical outcomes data using widely accepted standardised measures to evidence and raise the value of our global profession will be discussed. Artificial intelligence including machine learning is already being used in physiotherapy. We will highlight examples and give insight to short-term future opportunities.
While we are busy collecting and analysing data to support our place in the health care system, we must not allow these technologies including machine learning and artificial intelligence to dictate the future of the profession. Incorporating big data and next-generation analytics into physiotherapy research and practice will require not only new data sources but also new thinking, training, and tools . This symposium aims to stimulate conversations among clinicians, managers, researchers, and health policy makers to ultimately strengthen the global physiotherapy profession within an increasingly data rich healthcare system.
Implications / Conclusions: The gathering and effective use of huge quantities of data is a hot topic within the computing discipline and there are many efforts by big players such as IBM to apply these approaches within the healthcare system. The physiotherapy profession needs to recognise that it too must be proactive and leverage these developments to improve practice and also provide evidence of the important role of the profession within the healthcare system. This symposium aims to highlight the important issues at stake, some of the related activities already taking place and stimulate discussions on the path forward.
Key-words: 1. Big Data 2. Clinical Data 3. Artificial intelligence
Funding acknowledgements: N/A
Relevance to physical therapy globally: Big data has the potential to positively disrupt the global physiotherapy profession by improving clinical practice and quantifying value provided in healthcare systems. To take advantage of this potential and strengthen physiotherapy services globally, data collectors, data analysts and knowledge translation providers must collaborate internationally with the combined aim of proving the value of physiotherapy as key part of the healthcare system.
Target audience: Physiotherapists, managers, educators and researchers from around the world with an interest in using big data to advance the global physiotherapy profession.
Big data (FS-09)
Khan K1, Lowe R2, Jannenga H3, Walton A4