Besides managing individuals and the different structures involved, healthcare organizations also need to manage their data. Data is the way of the future and big data is the answer to many questions and problems facing the healthcare industry. The rise of the importance and use of data has led to the increased demand for data analysts. The increased quantity and uses of data have led to a higher requirement of Skills for Data Analysts. There are more expectations from data analysts and they as expected to continue to acquire new skill sets to stay ahead of the curve.The healthcare organizations that want to remain competitive in their data usage and analytics framework, work towards acquiring more Skills for Data Analysts as opposed to being stagnant.
Currently, many healthcare systems struggle with their data management. There are too many systems, some of which are not compatible with one another, and there is simply too much data for these systems to effectively handle and the analysts are not equipped with the right skillset to fix these ever emerging and new problems. Big data is growing and the more data is acquired the more ways it can be applied. Data Management in Healthcare is all about the strategy, organization, and efficiency of data analysts. The main goal of all of that is to reduce waste and make the healthcare experience better for everyone involved with it. With those kinds of issues in mind, data management in healthcare has become a topic that is increasingly important and significant to patients and their healthcare providers.
When looking at data management in healthcare, providers and analysts should certainly consider EMR systems and all they can provide, but they should also understand the limitations of those systems. The pros and cons of EMR must both be addressed. Clinical and organizational outcomes can be greatly improved with proper data management, and EMR systems can be a big part of that, but evidence has also been presented that shows drawbacks to the use of EMR in healthcare, such as the costs of acquiring and maintaining the system. An already burdened healthcare provider and their staff may actually lose ground when switching to an EMR system, because of the length of time it takes to learn that new system. Catching up once the system has been learned can also take considerable time, putting healthcare data management further behind. Some patients and their medical providers also have serious concerns about privacy, so they may be reluctant to manage their data (or allow it to be managed) in that way. Overall, however, healthcare providers should consider that EMR systems and data management as a whole can be highly beneficial to moving healthcare forward and reducing any mistakes that can come from disorganized and scattered patient data.
The Importance of Data Management
When data is too complex, trying to analyze that data also becomes complex. Before long, there are too many areas of input and too many ways data is outgoing, to keep everything straight in the middle. The confusion arises, and that can lead to medical and recording errors that can be very dangerous to the patient. It can also lead to billing problems with insurance companies, causing hospitals and other healthcare providers to struggle to get paid when they really need to, and/or to overcharge or charge for procedures that were not actually performed.
With all of those concerns taking place, it is clear that the management of healthcare data is a vital part of making sure providers and patients have a good experience. For a number of years, healthcare data was kept in paper records, which were stored at the office of their primary doctor or at the hospital where they were a patient. These records could be copied and sent to other providers through the mail or by fax, but that was cumbersome. It also led to delays, which sometimes reduced the effectiveness of treatment that was needed quickly. It was time to make changes.
How is Data Management Handled?
Now, the majority of data management in healthcare revolves around Electronic Medical Records (EMR). The systems that handle these records are expensive, but they can organize huge numbers of patient records, make them easily accessible to other medical professionals, and improve the way patients are cared for by their doctors and other providers. That is great news for patients and healthcare providers alike because it’s a significant step toward making sure there is adequate data management in healthcare. Unfortunately, EMR is not a perfect solution. The harvesting of such a vast amount of data in order to improve healthcare experiences isn’t easy and can be costly and time-consuming.
There is the potential for a very large payoff, but only if EMR can be used to its fullest potential. The infrastructure that is used for information is still complex, and getting all the raw data to analyze begins with trying to determine where that data should be collected from. Even with EMR systems, the level of data that some people have in their medical records, multiplied by the number of patients, can still mean millions or even billions of pieces of information that have to be sorted through in order to take what is needed for proper analysis.