The Current Quality of Big Data is Still Up for Debate
Big data may appear too big for many medical institutions. It is a fair suggestion. Many institutions that have implemented big data resourcing have found that they are storing and monitoring an excessive quantity of information. The data is powerful, but it is not being properly harnessed. The problem is not with the big data in healthcare mechanics. The problem is in the follow-through. Without proper action, all the data in the world simply results in an encumbered cloud of excess.
Learning What the Data Can Do
Why does healthcare need big data? Given the above argument, it doesn’t. As long as firms are sticking to inclusive systems and not actionable solutions, the data is extraneous. Fortunately, executive leaders have grasped the data’s potential. They need resources for sifting the information to the proper channels. For example, data from wearable medical devices could be incredibly powerful. It could drive costs down substantially be reducing patient return rates. But, big data is not quite at that point. More information is needed to make that a possibility, which leads to the next frustrating duality in big data.
The Need for More Information
The inherent problem with big data in healthcare is that the engineers and developers need consumer data to improve the system. Unfortunately, many institutions are waiting implementation in order to integrate the improved system. The back and forth desire for more data and an improved product is forcing big data healthcare companies to work at a slower than necessary pace. Engineers are doing what they can, and they are doing an impressive job. A solid amount of data is being sifted through healthcare institutions that have embraced big data management.
The barriers are extensive. There is a specific expertise needed to manage informatics vs analytics. Companies have answered that with extensive staff training and dashboard accessibility. System security is a growing concern. Engineers have also answered that with HIPAA compliance standards and reducing open-source design. Many of the high-profile issues have been addressed. Many medical bodies have tried to determine how satisfactorily the responses have been.
These problems are being answered but are the current answers good enough? When do medical bodies take the plunge, and when do they wait until it has become satisfactory enough? Engineers need test runs and time. Will medical companies afford them the time and patience necessary to make these systems superior in every way?
