Patient Care and Healthcare Analytics

Patient Care and Healthcare Analytics

Just about everything can be improved though optimization. This is certainly the case when it comes to healthcare. Just think about how much hospitals and general healthcare have been improved over the past decades, not to mention centuries. Things today are practically unrecognizable from back then. 

Here’s how patient care can be made better through healthcare analytics. 

Improving Readmission Rates

Hospital readmission rates are one of the most pressing issues facing the healthcare world today. This problem has several layers to it, which makes it complex, but also more worthy of analysis. 

On its most basic level, hospital readmissions are bad news for patients. Spending time in the hospital is hard on a person, both mentally and physically. But having to go back shortly after being released is even worse. Healthcare analytics provide ways to better predict a patient’s likelihood of readmission by synthesizing a broad range of inputs. Limiting readmissions can reduce the suffering of patients affected by a wide array of sickness. 

Furthermore, there’s a strong incentive for hospitals to improve readmissions on the administrative side. The Hospital Readmissions Reduction Program, along with the Affordable Care Act, laid out standards to financially incentivize hospitals to reduce readmissions. There has been noticeable improvement across the board following these regulations. While this is still an issue, hospitals can continue leveraging healthcare analytics to keep bringing their readmissions rates down. 

Better Preventative Medicine

Treating issues as they arise is important, but it’s not the ideal scenario. When possible, it’s always better to avoid illness than not. This is one area where healthcare analytics has a lot of room to create value for organizations. 

Building on the idea of lowering readmission rates, healthcare analytics can further aid in ensuring patients are directed to optimal outcomes. Integrating real-time data with patient care is one way hospitals and other healthcare providers can radically improve the patient experience. For instance, live tracking and analysis of vital signs—even when not at the healthcare facility—can help detect issues before they require triage. 

Research firm Deloitte recognizes several areas in which predictive analytics can play an important role in preventative healthcare. They mention greater efficiency and accuracy of diagnosis as two important factors. Predictive analytics can also assist “increased insights to enhance cohort treatment.” Essentially, the more data that exists in terms of inputs versus patient outcomes, the more it becomes possible to improve care for everyone afflicted by related illnesses. 

When it comes to improving patient care, few things usurp the magnitude of preventing health issues. Healthcare analytics can help with this across the spectrum. 

More Informed Staffing and Scheduling

Moving back to more administrative examples, healthcare analytics can be hugely helpful for making better staffing and scheduling decisions. It’s no secret to many working within the healthcare world that these issues are taking a massive toll on workers, and thus their patients. 

One survey found almost 95 percent of nurse managers believe issues related to staffing and scheduling are bad for morale. While this statistic is certainly stunning in its starkness, it’s not totally unexpected. Staffing and scheduling are complex issues in the healthcare world—particularly at hospitals, where shifts run at odd times and absences can have profound ripple effects. 

Healthcare analytics can help managers do a better job with building and maintaining staffing and scheduling. Improving the workflows of nurses and other staff members will in turn lead to better outcomes for patients. 

Guaranteeing Data Remains Safe

There’s no overstating the importance of data security when it comes to healthcare analytics. Just imagine the feeling of going through an illness only to find your sensitive data has been compromised. For some, this second tragedy can be almost as bad, or worse, than the first. 

No matter the organization, data security needs to be a top priority. This becomes an even more crucial concern when it comes to healthcare. Much of the data collected from patients will be extremely private. This is why the healthcare industry has such stringent rules about sharing information. Make sure your organization chooses an analytics platform that puts security first. 

Providing optimal outcomes for patients is the ultimate purpose of healthcare. Consider how healthcare analytics can help move your enterprise closer to that underlying goal.

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