Dr. Data is IN…
The U.S. spends more on healthcare than any other nation: around $9,000 per person in 2012. Can data scientists help?
The technology that’s already increased retail revenues and made law enforcement more effective could enhance healthcare providers’ business, by improving patient outcomes and lowering costs.
What’s the future of big data in healthcare?
According to the McKinsey Global Institute, using data to better predict the healthcare needs of the U.S. population could save between $300 and $450 billion.
One of those at the forefront of the industry, with over 20 years’ experience of developing clinical analytics, is John McDaniel, practice leader for the U.S. Healthcare Provider Market at NetApp. He sees four key trends:
1. The Patient Data Warehouse
By 2015, the average hospital will have two-thirds of a petabyte (665 terabytes) of patient data, 80% of which will be unstructured data like CT scans and X-rays.
“It’s eye opening that the human body needs so much storage,” McDaniel told me. When it comes to streamlining healthcare, the important thing is to find a way to manage that data.
Already, Picture Archiving and Communication Systems (PACS) allow scans and X-rays to be shared seamlessly across departments. For example, when my husband broke his finger, the diagnostic X-ray taken at one hospital was automatically available at the specialist unit at the hospital where he went for treatment.
According to McDaniel, a lot of that patient data is currently moldering in silos, because healthcare professionals lack the means to share it effectively. As big-data techniques become commonplace, it’s becoming easier to navigate these masses of data, and so cut down on the number of repeated tests and treatments.
2. Predictive Medicine
Our grandchildren will view personalized medicine the way we view antibiotics. It’ll be impossible—terrifying even—to imagine a time when patients were treated with a “one size fits all” drug for cancer, diabetes or heart disease because we didn’t know the risks from our genes and lifestyle.
Big data is ushering in an era of personalized medicine. In the realm of cancer treatment, we already know who should receive what drug for certain types of breast tumor, based on genetic markers.
According to McDaniel, monitoring the genomic markers that predict expensive diseases will soon allow healthcare providers to provide earlier treatment to mitigate or even totally eradicate the risk of some cancers and other chronic or deadly diseases.
3. Wellness Maintenance
It doesn’t end there. Big data can unlock the patterns of risk factors—both genetic and behavioral—that lead to higher rates of some diseases in some people, and guide them to make the lifestyle and medication changes that will keep them well.
For example, McDaniel is working with a concierge practice to deliver a groundbreaking wellness-maintenance service. By keeping a close eye on markers for the “big ticket” illnesses like diabetes, congestive heart failure, and dementia, the practice can ensure that the patient is staying healthy through diet, activity and preventative medicine:
“If a patient with one of these illnesses carries on down an unchecked path then the cost will be between $1.5 and $3.5 million per patient.”
Accountable care organizations are leading the push towards more proactive, personalized health management—going so far as to help their customers to not get sick. According to the McKinsey Global Institute, better targeting of preventative healthcare messages to the right population at the right time could save $70-100 billion.
4. Just-In-Time Medicine
Obviously, treating patients at the wrong time and in the wrong place is costly. Scheduled care is much cheaper than unscheduled care. Today, the industry works hard to “maximize production,” but improved big-data analytics across the industry can help optimize it further.
Click the image to see how your body is a source of big data
Optimizing patient discharge timing could save up to $70 billion according to McKinsey. For example, hospitals have always struggled to find the right discharge time for patients. Too late, and the patient ties up valuable bed space; too early, and patient outcomes suffer (not to mention the costs of readmission via the emergency room).
McDaniel told me that big data can help here too. As well as clinical analytics, healthcare providers are increasingly looking towards analytics to manage patient throughput, triage cases, and make predictions at a population level. This allows providers to fine tune their resources so that they can provide what he calls “just in time medicine.”
As Dr. Ari Robicsek told Beckers Hospital Review recently: “We compute a patient’s risk of being readmitted. … A user can look at a panel of patients to see which patients are at risk—high, medium or low—of being readmitted in 30 days.”
Big data also promises to set benchmarks, ward to ward and state to state. The cost of everything from appendectomies to X-rays becomes transparent, improving competition and driving down costs. It’s estimated that there’s another $100 billion of savings possible here, too.
The Bottom Line
A hundred-billion here, a hundred-billion there: Pretty soon, you’re talking serious money.
With possible savings of 10% of the entire U.S. medical bill, insights from big data could be the prescription for better care, lower costs and higher productivity. Says John McDaniel:
“There’s no question. This is the future of healthcare.”
By Emma Byrne
Whats the future of BIG DATA in HEALTHCARE?
See on www.forbes.com