Face to Face

Clinical trials and data analysis are even more important today in an era where controversial treatments are being espoused publicly based on certain biases. Crucial importance of peer review in doing controlled studies to eliminate bias is so important. We seem to have lost the significance of what peer reviewed, controlled studies really are and how they can bring answers based in data. Science is rapidly changing, becoming more complex. A single researcher or site doesn’t have enough patients to develop and validate medical innovations or it might take a lot longer to come up with the same results. What’s exciting today is that we have new technologies to allow us to delve deeper and faster into pooled medical databases. Today’s medical data explosion has made research more important than ever. We now have more searchable database access to help guide our treatments, and we are now using artificial intelligence (AI) to rapidly analyze this information. Research data gives us very important information about disease trends, risk factors, outcomes of treatments, public health interventions, patterns of care, healthcare costs, healthcare utilization and even disparities of healthcare and its delivery. Having a data ecosystem that collects patient’s demographics, patient’s symptoms, treatment and how they respond enables us to search all this information using AI to provide answers where we couldn’t get answers like this in the past. Our department is currently utilizing REDCap (Research Electronic Data Capture) in combination with Health Data Analytics Institute (HDAI) to take advantage of big data and computational technology. HDAI is analyzing large databases utilizing AI to produce predictive models for different patient treatments and in different patient demographics. So now we can search the data system for best outcomes from more patients and associate their results with hundreds of different variables. Nationally many academic centers are joining similar consortiums to share data. The time is here where we have the capability to quickly parse through millions of datapoints to analyze and offer the best care to our patients. Yes, data collection does slow down your clinic workflow, but the importance of continuous learning is why we ventured into academics in the first place. It was not simply to treat patients at a high volume. We must be persistent and ever curious. Evolution of our research and improved treatment is at the core of academic medicine. We want the best results for the longevity and quality of life for our patients. We want to always be pushing to the next level of better healthcare. Research will help us get there.