How big data can revolutionize patient care

By analyzing health data from a wide range of sources, we’re helping health professionals in Germany diagnose and treat patients based on the latest research and evidence

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Every day, health practitioners face numerous challenges. Clinicians, doctors and other medical experts have to find answers to a broad range of questions in order to make the right diagnoses – all for the sake of helping patients and saving lives.

Time and efficiency are crucial, but in the majority of cases, time is scarce.

Over the past decade, the complexity and demand on diagnostics have increased substantially while the incidence of multi-morbidities is on the rise due to the aging population (see Figure 1). These factors have led to increasingly more sophisticated guidelines that practitioners have to follow when treating their patients. In such a fast-paced environment where saving time and improving efficiency are of the essence, quality is a lifesaving priority.

How can physicians stay on top of the continual upsurge of information on advances in medical science so they can make the best decisions for patients? Without doubt, these advances in science and technology have brought about remarkable improvements to the ability of healthcare professionals. However the challenge is to find solutions and systems to generate and manage this knowledge effectively so it can be applied to regular care.

 The number of morbidities and the proportion of people with multimorbidity increased substantially with age. By age 50, half of the population had at least one morbidity, and by age 65, most were multimorbid. However, in absolute terms, there were more people with multimorbidity younger than 65 years than 65 years and older. (Source: Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. "Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study," <em>The Lancet</em>, 2012)

Converting big data into actionable information

In our German Health Analytics group at Elsevier, we are convinced that healthcare big data will revolutionize patient care. It is already making a big difference in this country and will continue to significantly improve the care patients receive.

The amount of knowledge and data in healthcare is constantly increasing, and the process will likely extend into the future. We see big data as a pool of information where we can gain useful insights. We use innovative methods to analyze big data and convert it into outcome-focused information and knowledge, helping overstretched medical professionals recommend treatments based on the latest research and evidence.

For example, we have developed tailor-made analyses and methods based on routine data from Germany’s sickness funds (public health insurance), which physicians can implement at the point of care. By working closely with analysts, physicians, statisticians, IT specialists and health economists, we are increasing the evidence-based knowledge on optimal treatments in real-world settings. We do this by combining our comprehensive analytic skills; collaborating with our strategic partner spektrumK, the service provider for health insurers in Germany, which owns a database of information from 6 million anonymized patients; and drawing extensive knowledge from Elsevier’s scientific and medical publications and databases.

Using our analytic methods, statistical models known as artificial neural networks, and high-performance computing, we are able to evaluate these 6 million anonymized patient datasets along with data from 25 million medical publications. As a result, physicians can rely on insights from the most recent clinical trials and real-world health data they would never have been able to access or process their own.

Big data as a basis for medical forecasts

We’re also helping physicians anticipate problems before they occur. By using predictive modelling based on existing cases, therapies and medical records, we’re creating tools to forecast the development of diseases before they emerge and determine the best treatment options for particular patient groups.

For example, a pharmacovigilance system we are developing using healthcare datasets will detect systematic adverse drug effects far earlier than is possible in today’s clinics. Such drug interaction models could save thousands of lives.

We aim to help physicians apply and use this knowledge in their daily work to improve patient care and outcomes while managing costs.

The importance of an international exchange

Since patient care and health research are practiced globally, national and international exchange can add significant value to its improvement. Experts, policymakers, regulatory bodies, providers and physicians should learn from each other by sharing experiences and practice examples.

That is why we collaborated with spectrumK to present the Forum Health Care Research with Routine Datain Berlin for the second time.

On June 9, renowned experts presented best-practice examples from Denmark and the United States, discussing the importance of medical data for patient care in Germany with about 130 German participants from research, policy and self-government.

Real-life examples such as electronic medical records (EMRs), which are already a successful model in Denmark, prove that the right analysis and application of big data in healthcare facilitates improvement in patient care and outcomes. The implementation and daily use of the EMR — which can be accessed by all doctors with the consent of patients — show how patients already benefit from correct use of big data and how big data analysis and electronic interconnection can support patient safety.

This is only the beginning

In an environment that involves treating patients and saving lives, the need for medical improvements is unlikely to come to an end. Even though we are still at the early stages of analysing and using big data effectively in healthcare, we have seen significant gains. Big data will undoubtedly revolutionize patient care, leading continued improvements in care, health outcomes and, above all, the ability to save lives.

Elsevier Connect Contributor

Peter Walther, PhDDr. Peter Walther is Director of Business Development and Communication for Elsevier Health Analytics. As a health economist, he conducted research on Germany's sickness funds (public health insurance). He then gained many years of experience at national healthcare associations and in industry, working with physicians, pharmacists and sickness funds, including the National Association of Statutory Health Insurance Physicians (KBV) and the Association of the German Pharmaceutical Industry (BPI).

Most recently, Peter spent several years in the pharmaceutical industry, developing and negotiating healthcare models for the chronically ill with sickness funds.

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