How Important is Analytics in Deciphering Healthcare Data?
Healthcare has always been a data-intensive industry due to stringent record-keeping and regulatory requirements. Healthcare data is quite rich and often contains human survival-related information. Analyzing healthcare data is of prime importance, considering the immense potential of saving human life and improving quality of life. Furthermore, the IoT revolution has redefined the face of modern […]
Healthcare has always been a data-intensive industry due to stringent record-keeping and regulatory requirements. Healthcare data is quite rich and often contains human survival-related information. Analyzing healthcare data is of prime importance, considering the immense potential of saving human life and improving quality of life. Furthermore, the IoT revolution has redefined the face of modern healthcare. IoT promises to deliver excellent progress in healthcare domain. In recent years, healthcare analytics has been the next big invention and the advancement that will take the healthcare industry to the next level. Furthermore, the use of healthcare analytics in process improvements cannot be overemphasized. Process improvement in healthcare can result in increased patient satisfaction, more efficient care, better population health, development of the skill of employees in all levels of a healthcare organization, reduced cost of care and an all-around increase in productivity. Here are some of the reasons why healthcare analytics is vital for understanding healthcare data better and gaining improved clinical outcomes:
Improve data mining
In the healthcare industry, data mining has been merely an academic exercise with only a few pragmatic and real-life success stories. However, with the proper use of healthcare analytics, this can be improved upon. Healthcare analytics helps in simplifying and fine-tuning the process of data mining. Data mining is essential in the healthcare industry as it enables the systematic use of the healthcare data and analytics to identify inefficiencies and best practices that improve care and reduce cost. So, it can be said that data mining and healthcare analytics work hand in hand.
Structuring healthcare data
Healthcare data tends to reside in multiple places. From different source systems, like EMRs or HR software, to different departments, like radiology or pharmacy. Healthcare data also occurs in different formats such as numeric, text, digital, paper, pictures, videos, and multimedia. With the help of healthcare analytics, the data can be grouped into a more structured format and used for understanding relationships between different variables and identifying patterns.
Developing more effective diagnostic and therapeutic techniques
As mentioned earlier, healthcare analytics can help companies bring together information from different sources. Healthcare data from clinical, financial, and operational sources can be used to determine the efficiency of processes, the state of patients, and the effectiveness of programs. This can be done effectively with the help of healthcare analytics. Healthcare analytics can also help in identifying the patients who are at the greatest risk of developing adverse health outcomes and developing more targeted wellness programs to optimize their health status.
Disease surveillance and preventative management
Healthcare analytics not only uses the data provided to by healthcare organizations, but also scours unstructured healthcare data from nontraditional sources, such as text messages, social media, and search engine to detect disease outbreaks and gauge their scope. This data can then be used for analyzing disease patterns and track disease outbreaks for improved health surveillance and prompt response to healthcare emergencies and develop better targeted preventative techniques and vaccines.
To know more about the why healthcare analytics is important to make the most out of healthcare data