Big Data: A Prescription for Improving the Quality of Healthcare

by Michele Nemschoff

Healthcare has come a long way since the days of the country doctor. Over the last hundred years, advances in the diagnosis, treatment and prevention of disease have dramatically improved the quality of patient care. Today, as healthcare becomes more and more digitized, Big Data is positioned to revolutionize the industry by personalizing healthcare in ways the country “Doc” could never have imagined. What follows is a look at some of the ways Big Data is dramatically improving the quality of healthcare.

Faster time to treatment

Of necessity, the country doctors of yesteryear practiced “cookbook medicine.” The treatments they gave their patients were predetermined, and based solely on symptoms. If you had a fever you got the same potion, powder or pill that every other patient with a fever got, regardless of any circumstances that might prove unique to your condition. For today’s physicians, fast and accurate diagnosis and treatment calls for informed real-time decisions. Big Data analytics tools factor in unique circumstances such as lifestyle choices and demographics along with the patient’s symptomatology to help doctors arrive at a more accurate diagnosis and treatment regimen in real time.

Fewer hospitalizations and re-admissions

While many hospitalizations are necessary, a large number of hospital admissions can be avoided through proactive patient care. Big Data analytics is helping to reduce hospitalizations by arming physicians with better technology and richer, more detailed information about each of their patients. Using these valuable resources, physicians are able to select the most patient-appropriate treatments to ensure the best outcomes.

New data tools are also helping physicians practice preventive care more effectively, by enabling them to keep patients up-to-date with regard to immunizations and lab work. In addition, sensor devices used by patients at home and on the go are delivering streams of constant data that can be monitored and analyzed in real-time to help patients stay healthier as they self-manage their conditions.

Once a patient is hospitalized, data analysis of electronic health records, demographic, geographic and genetic data, along with predictive analytics, can be used by physicians to select the best course of therapy to optimize outcomes and reduce the need for re-admission.

Faster time to market for safer, more effective new drugs

Unlike healthcare, the pharmaceutical industry, aka “Big Pharma”, was an early adopter of Big Data. Utilizing sophisticated Big Data platforms such as Hadoop, drug researchers are able to dig deeper into disease states to better understand underlying causes and gain insights, which can lead to new treatments.

In addition, the ability to analyze large volumes of patient data also helps drug research scientists to select more targeted drug candidates to participate in drug studies. Using Big Data, drug trials themselves can be carried out more efficiently and more effectively to help bring safer more effective pharmaceuticals to market sooner.

Going forward, the optimal benefit to hopefully be derived from Big Data with respect to drug therapy will be that it will be customized and personalized to ensure the best pharmaceutical fit for the patient.

Better Medication Therapy Management

Despite advances in medication therapy management best practices, CDC estimates show that adverse drug events continue to plague the healthcare system to the tune of 700,000 emergency room visits per year and extra medical costs of $3.5 billion annually. This is largely due to the fact that the healthcare system is overburdened and out of step with technology.

Today’s physicians are overwhelmed by mountains of information and patient data that must be evaluated quickly yet thoroughly in order to design and implement optimal drug therapies. In turn, clinical pharmacists, whose role it is to monitor and manage drug therapies, are burdened by rising numbers of patients taking multiple medications. Fortunately, Big Data analytics is positioned to change all that. Case in point—Surveyor Health. Incorporating a proprietary analytics technology known as “Knowledge Surveying” into an award-winning evidence-based risk management application called Med Risk Maps, Surveyor Health is enabling clinicians and clinical pharmacists to identify drug interactions, contraindications and additive toxicities at the point of patient care—in real time.

In addition, Med Risk Maps allows clinical care providers to simulate modified drug regimens in order to determine the regimen most likely to produce the best patient outcome. Erick Von Schweber co-founded Surveyor Health with his wife Linda, after Linda’s mother suffered a near-fatal illness brought on by the additive toxic effects of multiple medications. In a recent interview with this author, Erick Von Schweber summed up the role of Surveyor Health’s Med Risk Maps in improving healthcare as follows, “Relevant med risks at a glance—mitigated in moments.”

By optimizing a safer course of drug therapy, using Big Data in medication therapy management improves the quality of healthcare by reducing doctor and emergency room visits, hospitalizations, re-admissions, and most importantly, by reducing patient deaths.

image credit: MapR Technologies
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Michele Nemschoff is VP, Corporate Marketing at MapR Technologies. MapR delivers on the promise of Hadoop with a proven, enterprise-grade platform that supports a broad set of mission-critical and real-time production uses.  Prior to her role at MapR, Michele held senior marketing roles at PARC, Indigo and Plantronics.