Leaders across a variety of industries realize the benefits of data analytics in their organization's decision-making support. Many realize that the greatest challenge is not the technology or even the personnel but a lack of leadership. Read this article to learn the key characteristics and attitudes a leader responsible for implementing DDDM must encompass and how these characteristics are used in a healthcare setting.
Advantages of Electronic Health Records and Big-Data in Healthcare
One significant advantage of EHR in the healthcare realm is the network capacity to share and disseminate patient data within hospital networks or accountable care organizations. In this way, duplication is avoided and an individual can receive more consistent and safer treatment regardless of location. Patients are also able to readily access their medical data in new ways, such as with apps or mobile fitness tracking devices (FitBit, etc). This further empowers patients to take ownership and accountability of their own healthcare. Healthcare analytics can improve predictive capabilities by understanding population behavior and thereby estimating average length of stay which is a strong indicator for medical complications or other hospital-acquired illnesses.
It is estimated that big-data and analytics can save the United States an estimated $300 billion per year. For example, the way we are able to analyze historical patterns of disease and track outbreaks can help us understand how to mitigate and halt these outbreaks faster. The rise of big-data will also support genomic analytics and allow us to begin to elucidate how the human genome can be used to make medical decisions. Groves et al. describes how big-data is allowing new value pathways: right living, right care, right provider, right value, and right innovation. Essentially, with changing capabilities towards analytics and big-data in the healthcare field, we can better align decisions to the expectations and benefit of the patient. Another advantage of adopting EHR is being able to disaggregate results to look at underrepresented groups or populations and determine areas of health disparities.