From our fitness trackers to our EMR’s, the amount of healthcare data is staggering. Although healthcare analytics is about a decade behind, the opportunities to learn from other industries and to catch up is tremendous. Already, we have seen the likes of Google and Amazon eye the industry with their expertise in retail, software, and (of course) data. Healthcare analytics is a broad field with many avenues that can be explored.
One avenue in healthcare analytics is finding counterintuitive patterns that others have missed. This technique has been used by hedge funds to find correlations and inefficiencies in the market. Recent studies in palliative care have shown some promise. In the study “Improving Palliative Care with Deep Learning”, researchers found that the number of scans of the spine and urinary system were just as statistically important in predicting the probability of time of death as someone’s age. Although ripe with promise, this field has to meet organizational cultural challenges between groups that do not want to share data.
Healthcare analytics can also help in the field of medical imaging. In radiology, artificial intelligence has been superior in recognizing patterns in imaging data because of its ability to look through troves of data that could take years of experience for a radiologist. However, do not count out humans just yet. Although a machine may be very good at finding a disease through an algorithm, there will still be oversight by healthcare professionals. There may never be complete automation in the healthcare industry just like a human driver serving as a backup for a self-driving car.
These are just two things that healthcare analytics can touch on. Because of the amount of data produced, and the ability to learn from other fields, healthcare analytics has exponential opportunity for growth. As data analytics become easier and more efficient to use, the insights gained will be invaluable.