26 Feb How data can help providers
by Dan Kotok
“Sixty-three percent of hospitals routinely exchange patient data with the hospital they share the highest volume of patients with,” found a 2018 study from the Journal of the American Medical Informatics Association. For healthcare providers, data makes a huge difference in the work they do and the patient outcomes they secure.
Data helps providers improve patient care, reduce readmissions, improve staffing, find cures, and create precision medicine. With all these benefits, it might be time for hospitals to start sharing more. Let’s dive into each benefit of big data for healthcare providers:
Improve patient care
One of the benefits of big data is that it is easy to share, helping others synthesize and learn from it. This is especially helpful in the healthcare industry, where every bit of data healthcare providers have on a patient helps achieve better health outcomes.
But healthcare providers have only embraced this “sharing is caring” idea recently. Why is that? A lot of it has to do with incentives.
Many insurance companies used to offer “fee-for-service plans (which reward using expensive and sometimes unnecessary treatments and treating large amounts of patients quickly).” Under this model, healthcare providers didn’t have an incentive to share patient information with each other, so there wasn’t a reason to harness the power of data analytics in that way.
But now insurance companies are shifting to plans that prioritize patient outcomes. This means that providers do have a financial incentive. Sharing data about patients not only helps patients but also cuts costs for insurance companies.
Providers can use predictive data analytics to decrease readmissions for hospitalized patients. Unnecessary readmissions can slow down hospital staff and prevent the care provider from doing what they do best—provide—to more people. But data in healthcare is beginning to stop that.
For example, Parkland Hospital, a hospital in Dallas, Texas, uses advanced analytics to identify and effectively treat high-risk patients. As a result, Parkland has reduced 30-day readmissions, which means they have saved over $500,000 each year.
Chances are, you’ve experienced the pain of long wait times in the doctor’s office. Lucky for all of us, data can help here, too.
In 2016, hospitals in Paris used big data and machine learning systems to look at ten years of admissions data and predict admission rates down to the day and hour. This meant that they wouldn’t be over-staffed during slow times, and they would have enough staff to care for patients during busy times adequately.
This sort of analytics involves time series analysis techniques, which means looking at the data to find patterns that can be used to make predictions. Then machine learning comes into play, determining “which algorithms provide the best indicator of future trends, when they are fed data from the past.”
The Cancer Moonshot Task Force has a goal to make “a decade’s worth of progress in cancer prevention, diagnosis, and treatment in just 5 years.” They’re operating based on ten research recommendations, a few of which (unsurprisingly) involved using data. Here’s how:
- They’re using patients’ tumor profile data to learn more about what therapies work, what types of patients they work on, and in which types of cancer.
- They’re creating a system for sharing and analyzing cancer data.
- They’re analyzing patient data from the past to predict patient outcomes
The possibilities of this initiative are bright and hopeful. And on top of that, cancer is just one major area of health concerns that big data is helping to solve and find a cure for. Imagine what data can also do for the many other unsolved conditions.
Create precision medicine
When it comes to precision medicine, the motto is “one size doesn’t fit all.” Every individual is different, so it makes sense that generic treatments don’t always do the trick.
“In addition to being more effective, a targeted approach can spare patients from debilitating side effects of standard treatments,” said Lisa Esposito, a patient advice reporter.
Providers and researchers are using genomic data “to make decisions about specific treatment paths that may be more or less effective for the individual at hand.”
It’s little wonder that 63 percent of hospitals routinely exchange patient data with each other. It’s only surprising that the number isn’t higher. Data helps healthcare providers improve patient outcomes, reduce readmissions, improve staffing, find cancer cures, and create precision medicine—ultimately, it makes better care providers out of our healthcare.
In part four of this blog series, I take a look at the specific ways that big data can be beneficial to another key player in the healthcare space: pharmacies.
Dan is a Senior Account Executive here at Simplus. He has specialties in Salesforce.com, training user and system testing cycles, end user and support training, business process mapping, LSS project management, implementations, and change management.