One of the most appealing aspects of using data for decision-making is numbers are unambiguous. Sure, some people can see data differently; but there’s simply no way to ignore the presence of hard fact without some serious mental contortions. Incorporating analytics to improve patient care in healthcare allows for a more object measure of performance.
Here are some things to consider when using healthcare data analytics to improve patient care.
Get More Objective Measure of Performance
Many aspects of a healthcare organization can be quantified, and thus, made more efficient through analysis. It’s important to remember making these gradual systemic and performance improvements aren’t just about saving money, which is great on the business side. Ultimately, healthcare data analytics is about radially improving patient outcomes.
Physicians can be monitored through a vast array of metrics aimed at tracking things from average length of visit to patient remission rates. Getting a clearer picture of individual performance in this way can help management give more tailored recommendations.
Understand Problems More Holistically
Healthcare companies are complex organizations. There are many places where things can go wrong — from costs to daily operations. One area that has been consistently troublesome for healthcare organizations — particularly hospitals — Is staffing and scheduling issues. One survey by Avantas found “70 percent of nurse managers are very concerned about the effects of scheduling and staffing problems on the patient experience and patient satisfaction. Further, more than half indicated they are very concerned about the effect on the quality of care.”
It’s clear nurse scheduling and staffing are issues for hospitals. But the depth of the problem won’t be clear until data is used to get to the bottom of it. Healthcare data analytics can be the solution for those who want to identify the true nature of challenges.
Use Data in the Moment with Ad Hoc Analytics
While much of the data analysis at a healthcare organization will be focused on longer termed problems, there are many insights to be had from in-the-moment issues as well. This is where ad hoc analysis and reporting can take healthcare data analytics to the next level. There are several intriguing cases where this kind of technology can be highly effective in a healthcare setting.
The great thing about ad hoc analysis is it doesn’t need to be about a grand concept or idea to be valid. It could be as simple as finding a pattern in the way certain personnel are consistently correlated to longer wait times. But it can also be used by researchers who want to save time by instantly searching vast data sets for answers — as opposed to waiting for results. Ad hoc analytics has the power to make a wide array of healthcare applications far more efficient.
Triage Before Issues Intensify
One thing no one wants to hear is they would have been okay if they’d only come in to see the doctor sooner. There are a few reasons why it’s recommended people visit a doctor for a checkup on a regular basis. These visits are more about establishing baselines than they are about diagnosing current issues. When you have a baseline, it becomes much easier to tell when something is out of the ordinary.
By collecting fundamental health data from patients, healthcare providers can get a more comprehensive picture of their wellness. Furthermore, they’ll be able to tell when something is wrong more quickly — making it far more likely they can triage the issue before it gets worse. Wearables are providing a huge trove of patient data. Getting that data into the hands of doctors has the potential to vastly improve diagnosis, treatment, and outcomes for patients.
Thanks to advances in analytics to improve patient care, patients are continually getting better treatment. Organizations that adopt a data-heavy approach to care will be able to leverage this into providing even better service for patients.