Healthcare analytics is a subject that has been eagerly discussed for years. But now the anticipation around data-driven healthcare is becoming a reality. Organizations from across the healthcare spectrum are embracing and implementing analytics. And, in practice, the results are transformative.
To get a sense of how broad and deep this impact runs, consider how some organizations are actually utilizing advanced healthcare analytics right now.
To Streamline the Operating Room
Operating rooms are an amazing collection of technology, resources, and expertise. But, unfortunately, getting everything in the same place at the same time is notoriously hard to coordinate. And, as a result, operating room delays are common, forcing patients, their families, and staff to wait for hours on end.
The University of Chicago Medical Center is tackling this problem with the help of analytics. The hospital analyzes data in real time to spot potential bottlenecks and automatically notify the affected parties. After refining the system, UCM was able to reduce wait times by as much as 20 percent. Impressively, that is projected to save the hospital $600,000 annually.
To Care for Newborns
Newborns are highly vulnerable to infection in their first days of life. A small percentage of these newborns will develop an infection that could have lifelong heath consequences and even lead to death. These children are in dire need of antibiotics, but it’s unsafe to give these same drugs to healthy babies.
Kaiser Permanente set out to find a better way to identify the newborns in need of antibiotics. It analyzed the medical records of 600,000 infants to create a risk calculator. And, thanks to that tool, distribution of antibiotics has dropped by 50 percent.
To Reduce Length of Stay
A long stay in the hospital is hard on everyone. Patients are understandably uncomfortable and anxious, and their bills multiply the longer they are admitted. Hospitals, on the other hand, have to dedicate a lot of resources to one patient, which is expensive and restricting.
The challenge is to reduce the length of stay without compromising the patient’s care. The Cleveland Clinic tackled this problem using data from its knee and hip replacement division. It developed a model to predict which patients would be most likely to recover at home and which would require extra rehabilitation. The result of this initiative was a reduction in the average length of stay, as well as lower costs for both the patient and provider.
These examples are exciting, and they demonstrate that healthcare analytics is already generating impressive outcomes. But what really stands out is how creatively healthcare analytics is being practiced and how flexible it is. It has applications in every aspect of healthcare, and it can aid in every conceivable initiative.
Furthermore, it doesn’t take an army of data scientists to begin making the most of analytics. This is a tool that is widely accessible and almost universally applicable. Expect analytics to play a role in every healthcare improvement or advancement from now into the far future.
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