Can Data Analytics Modernize Healthcare Management?
Healthcare providers cite “highly fragmented data” as the biggest roadblock to figuring out their total cost of care—58 percent of healthcare leaders, according to one survey. This is especially pertinent as we move away from the fee-for-service model of years past to a value-based one.
The Implications of Value-Based Care
Value-based care depends entirely on patient outcomes because they dictate how healthcare providers receive compensation. As NEJM Catalyst writes, value-based care agreements reward providers for “helping patients improve their health, reduce the effects and incidence of chronic disease, and live healthier lives in an evidence-based way.”
The very way in which hospitals provide care is trending away from focusing on individual interactions to focusing on long-term results. Patients require care that extends beyond standalone appointments; value-based care is focused on facilitating relationships with patients meant to improve their long-term outcomes. This is an important development for patients’ quality of lives, as well as affecting how hospitals set benchmarks and goals.
So, a big part of modernizing modern healthcare management is moving toward this patient-focused, value-based care model. But the question remains: How? To start, business intelligence in healthcare can help unlock crucial insights for healthcare providers, which in turn shapes how they structure their organization and deliver patient care. After all, only an organization that has a strong grasp on its strengths and weaknesses can improve performance.
Using Data for Healthcare Applications
The challenge in using data analytics to modernize healthcare management is really two-fold, however. First of all, organizations need a way to pull insights from their vast amount of stored data. Second of all, business users must be able to determine if those insights are actionable. In other words, some insights may be technically true, but not necessarily relevant to decision-making processes. Insights are only as valuable as they are helpful to your operations.
There are a few types of analytics to consider here, each with its own advantages. For example, search-based analytics allow users to make specific queries of structured data. The eventual goal is to get an answer and build a data visualization model to represent these findings. Artificial intelligence-driven analytics, on the other hand, help users find insights they were not specifically seeking by employing advanced insight-detection algorithms. A comprehensive data plan includes both because both types of insights have the potential to be very useful.
Machine-learning algorithms can help here in terms of relevancy by optimizing results over time, which saves human data scientists and users time. The more feedback human users provide, the more the machine learns what’s worthwhile and what isn’t. Utilizing a data platform that’s constantly refining itself means that intel only gets more spot-on over time, which is an especially useful tool for busy users in the healthcare industry.
Cybersecurity in Healthcare
Whenever you’re revisiting your data strategy, it’s always a prudent time to reconsider your commitment to cybersecurity. It’s detrimental when any company experiences a data breach or hack, but it’s particularly worrisome for healthcare organizations.
One pressing aspect to consider is who has access to organizational data. While accessibility is a huge advantage of modern data analytics platforms, it’s also important to have high-level controls in place to safeguard sensitive data. The ability to set and monitor controls will help you remain confident that only the right business users have access to the data they need—and nothing more.
Can data analytics modernize healthcare management? Yes, but only when it enables organizations to find truly actionable insights and does so in a way that protects sensitive data. New artificial intelligence advancements in data are helping healthcare providers hone in on the intel they need to optimize performance over time.