Evidence-based medicine spurs data-driven, efficacious treatments
Big Data makes personal diagnostics and treatment possible, lowering costs, improving care
Healthcare CIOs must feel ill some days at the office. Their organizations are under tremendous pressure by boards of directors and governments to keep costs down, while the medical establishment and those same governments simultaneously foist more requirements to collect, store, and analyze ever-increasing, staggering volumes of data. It’s a headache that no amount of aspirin will fix.
An aging population in some geographies combined with an ever expanding array of available treatments is placing strain on government managed healthcare budgets. The usual response has been to raise more from the taxpayer. That no longer works as governments discover that under the existing model, the demand for healthcare is limitless. Add in fiscal crises and it is easy to understand why healthcare needs a fundamentally different approach. The scale of the problem should not be under estimated.
Shrinking budgets and exploding data
In Europe, where the euro crisis seems to have more lives than cat videos on the Internet, some nations are seeing sharply reduced tax revenues and are forced to make major cuts to healthcare spending. According to the OECD Health Data 2012 report, compared with the prior year, the Irish government slashed its healthcare budget by 7.6percent. In Greece, where the fiscal crisis is even worse, lawmakers hacked 13 percent from its healthcare expenditures and sent more than 35,000 nurses, doctors, and other healthcare workers to the unemployment lines.
It’s not just economically battered countries taking the knife to healthcare budgets. Relatively stable nations, such as Denmark and Norway, also trimmed government health spending. In the United States, the Obama Administration has proposed $401 billion in budget reductions over ten years to government-funded Medicare and Medicaid programs.
While applying cuts to healthcare, governments also are putting doctors, health administrators, medical researchers, and others in the field under the gun to gather and store more information, adding to the compliance burden of IT. For example, as part of a movement toward evidence-based medicine, the Affordable Healthcare Act in the U.S., commonly referred to as Obamacare, created the Patient-Centered Outcomes Research Institute, which will gather data on as many as 12 million patients over long periods to determine which treatments are the most efficacious for a given ailment.
IT can help, but there are hurdles
The technical hurdles for IT to collect and distribute these data are not trivial. It is thought that only around half the country’s medical practitioners currently use electronic health records. Data standardization is not uniform, making it difficult or impossible for a hospital or clinic to share the information without embarking on a significant IT project.
Healthcare CIOs are not only confronting regulated information collection, retention, and sharing requirements, they also face daunting data demands from inside their organization. The volumes of data generated are mind boggling. For example, every time a patient gets hooked to an EKG machine, it gathers 1,000 data points per second. A two-dimensional mammogram requires 120 Mbytes for each image, while a 3D MRI can hit 150 Mbytes and a 3D CT scan can top out at one gigabyte. All that information—both structured and unstructured data formats—must be stored and accessible for the life of the patient.
Looming on the horizon is full patient genomic data and the promise it offers for personalized medicine. Once considered a far-off medical opportunity for the future because of the expense involved, it’s happening now. What’s happening? Fortunately, the costs to determine an individual’s genome are dropping like a stone. The National Institute of Health in the U.S. says the cost of sequencing a person’s 3.2 billion base pairs and its near gigabyte of data has dropped from $100 million in 2001 to $9,000 today. The NIH estimates that price will tumble to $1,000 by 2015. That means middle class citizens will be able to afford having their personal genomes sequenced. It is thought that many will take advantage of this opportunity provided if people believe it will lead to improved treatments.
Little wonder, then, when writing a profile in The New Yorker of one of her teachers at Elmhurst Hospital in New York, Rivka Galchen observed,
…each year of medical progress, with its new diagnostic tests and revised insurance paperwork, brings more data to sift through and less time in which to do so.
Prescription: more data in your diet
Although it’s easy to sympathize with M.D.s like Galchen, who cringe at each new form to complete, each new checklist to run through, she should be complaining about the lack of data, not its abundance. In fact, it’s possible that this healthcare crisis is simply an information technology crisis that can be solved with even more data combined with better analytical tools.
In the US, healthcare gobbles up 17.6 percent of the nation’s GDP. According to a recent McKinsey and Co report, that spend is some $600 billion higher than would be expected given the US size and wealth. McKinsey suggests that a combination of data-driven, evidence-based medicine and modern tools that prod patients to lead healthier lives will go a long way to reducing that resource overutilization. That process is already underway with initiatives designed to match spend to outcomes at both the practitioner and pharmaceutical company levels. What solutions might bear fruit in this endeavor?
Dr. Eric Topol, an eminent cardiologist, has been profiled as an enthusiastic practitioner of mobile-health initiatives. He says that judicious application of smartphones and software can save patients, insurers, and governments enormous amounts of money. In one interview he showed an application available now that delivers the results of a standard echocardiogram for patients while potentially eliminating 70-80 percent of the prescriptions at approximately $800 per test. Millions of echocardiograms are conducted each year. The projected savings are enormous. He also performs ultrasound examinations with his smartphone without sending the patient to a technician, which adds to the cost and time-to-diagnosis.
Topal is convinced that the smartphone paired with the right software is not just the future of medicine, it’s the present. He told NBC News, “I’m prescribing more apps than I am medication.” And the market is growing at breakneck speed.
Mobile health care apps show promise
There are 97,000 m-health apps for smartphones available today with 42percent following the paid-app revenue model. Fifteen percent of m-health applications target medical professionals. And the market is predicted to reach $26 billion in 2017.
Medical applications for smartphones are being used to diagnose those afflicted with Parkinson痴 disease. Researchers at the Electro-Optical Systems Lab at Georgia Tech have developed an app called iTrem which uses GPS capabilities in most smartphones to monitor for tremors that are consistent with Parkinsons potentially eliminating the expensive clinical observation process. Asthmapolis sells a smartphone app that monitors location data for asthma patients at the time they use their inhalers. It combines that data with information from the Center for Disease Control in Atlanta to spot prevention opportunities which can help reduce trips to emergency wards. Numerous apps for diabetics, multiple sclerosis victims, and other disease abound to help people keep on their diseases under control.
The common thread in these simple, inexpensive smartphone tools is that massive amounts of data is collected on anonymized patients that can be analyzed to benefit others without having to embark on major research projects. Evidence-based medicine supports patient care at far less cost than traditional methods of analysis. Data-rich diagnostics also help get treatment to patients faster. However, the ready availability of such technologies and possible treatment is not evenly distributed. It’s not, I think, so much ironic as an apt homonym that patience is a trait all patients must have in today’s healthcare process.
Reasons for optimism
I’m optimistic that healthcare will continue to get better for individuals while keeping costs down. My optimism is based on four things.
There is a global shift among medical practitioners and educators to leave “cookbook style” diagnosis procedures, where symptoms are treated by a recipe approach, to evidence-based medicine, which applies data-centric methods.
There is major effort to collect as much medical data as possible, in any format, to analyze and accurately determine proper treatment for a wide range of diseases.
With smartphones in hand, patients are taking more responsibility by their watching health data. According to Pew Research, 70 percent of Americans currently track at least one health metric for themselves or a loved one. That number is only going to grow as more apps target more patient needs.
Most important, IT vendors have finally delivered an infrastructure that can handle the data volumes and variety necessary to analyze the information fast enough to become first-rate diagnostic partners for practitioners. These advanced systems will be the foundation for improved patient care through proven and precise treatment programs while concurrently cutting unnecessary costs.
Suggesting any timetable for these four conditions to become dominant in healthcare is speculative. However, the fact that they are all real and gaining momentum suggests it won’t be long before we witness their positive effects. We can already see how m-health initiatives are changing doctor-patient relationships and evidence-based medical teaching is underway at universities. Newly minted doctors will demand tools to practice data-driven diagnosis and treatment. IT can and should take a leadership role in developing and deploying systems capable of delivering an ROI that is not only obvious, but within our grasp.
What’s next?
For SAP’s part, we have compiled a “Global Health Care and Big Data” document identifying health care big data challenges and how we think SAP HANA can impact them on a use case basis. One inspiring story involves a student who designed a mobile app that won first place in the SAP University App Rumble competition. The app uses SAP HANA to help diabetes sufferers better manage their condition. Upcoming events should bring this issue into focus. SAP will be presenting on big data themes at TechCrunch Disrupt SF 2013 (Sept 7-11) and the Intel Developer Forum (Sept 10-12). We hope to see you there.
Having any kind of medical problem is always unnerving. It can be frightening when practitioners seem perplexed about the cause or when treatments are ineffective. The use of big data-driven, evidence based healthcare will help diminish those anxieties as practitioners learn more quickly about diagnosis and appropriate treatment.
