You and I might look at a huge data set consisting of page after page of numbers and symbols and view it as largely meaningless. To the technicians and engineers at Rock West Solutions though, that same data set represents valuable information that they can share with their partners in the medical industry. Indeed, huge medical data sets are treasure trove for medical providers.
It is no secret that medical providers love data. In the era of cost-cutting, outcome-based medical care, and higher health care costs that are outpacing inflation year after year, medical providers rely on data to both improve patient care and reduce the cost of medicine. The key is figuring out how to break down continually growing medical data sets into smaller, well-defined chunks of information applicable to individual applications.
The main challenge of huge data sets is volume. Think of it this way: what would you do if you were tasked with finding a single person’s name printed somewhere in a stack of New York Times newspapers covering a full year of publication? Just the thought of pouring through all those newspapers in the hunt for single name would be enough to dissuade most of us from even trying. Likewise, gleaning useful information from incredibly large data sets is just as daunting.
It Is Worth the Work
It might not be worth it to you to dig through all those newspapers in search of a single name. But it is well worth the effort for the medical industry to find ways to extract valuable data from huge data sets. Using data effectively can be a game-changer for any medical provider. Here are just a few examples of what can be achieved when data is extracted and analyzed in the right way:
- Reduced Readmissions – Data can be combined with predictive analysis to help clinicians understand when a patient is likely to be readmitted for follow-up care. Likewise, the same data can help clinicians develop strategies and treatment models to prevent readmission.
- Cost Controls – Better diagnostics made possible through big data and signal processing can help control the costs of healthcare by eliminating unnecessary tests. Data can be used to formulate better treatment plans that are more effective, thus reducing costs even further.
- Improving Research – Ongoing research into diseases like cancer and Alzheimer’s is helped considerably by big data. Harvesting and analyzing patient data is helping researchers get a better handle on how the diseases they are studying progress. It is helping them understand genetic predisposition, environmental causation, and more.
- Saving Lives – Ultimately, extracting relevant data from huge data sets can save lives by giving medical providers a clearer picture of what they are dealing with. This is arguably the best defense for incorporating big data into medicine. If it saves lives, it belongs in medicine.
It is easy to look at big data in medical care as being overkill. But if you are a patient facing a potentially life-altering disease, big data might suddenly be important to you. It could be instrumental in offering care you can afford; care that might even save your life.
Data Makes Healthcare Better
Medical providers have had access to all kinds of data for some time now. But thanks to much larger data sets and advanced signal processing that is capable of harvesting actionable data, providers are discovering new ways to use data to cut costs and save lives. Both are reason enough to continue pursuing our knowledge of how data sets and signal processing can help make medical care better.