Big Data Challenges With Connected Healthcare

Paul Clark

Wearable technology and 24-hour healthcare monitoring using the Internet of Things (IoT) is causing an explosion in biometric data. This information can be combined with genetic data, clinical medicine, and other details to better understand the relationships between external factors and human biology regarding patterns, causes, and effects of health and disease.

Analyzing this type of medical data to identify more effective treatments is forecast to save billions of dollars in healthcare costs and enable groundbreaking medical advancements. So with such promise, why is this data analysis not being used to its full potential? According to the SAP eBook, Connected Care: The Digital Pulse of Global Healthcare, the problem lies in the massive volume and disparate nature of health data.

Big Data challenges

In the Connected Care eBook, SAP partner Lenovo says the disjointed nature of many health systems leaves the potential of technology unfulfilled. Levono’s article, Drawing Connections Between Interoperability and the IoT, states that combining health data is a major challenge for the following reasons:

  • The massive amount of health data being generated by the IoT is overwhelming, so combining it with highly complex genomic data, electronic medical records (EMR), and other clinical data is an immense challenge.
  • Health data is held by diverse sources including healthcare providers, pharmaceutical companies, and life sciences organizations.
  • Different types of data come in a variety of formats including images, videos, paper files, digital text, numerical data, electronic records, and multimedia files. This diversity makes it difficult to combine all of the healthcare data available.

Medical data privacy and secrecy

While gathering data from disparate silos of medical information is a big challenge, it’s not the only one. A further challenge is secrecy, as key players in the healthcare industry are not used to sharing their data. And then there is the mounting challenge of data security.

The growing volume of personal health data being collected by the IoT begs the question: How secure is it? The Digitalist article, The Risks, Challenges, and Rewards of Ensuring Medical Data Privacy, explores how vulnerable healthcare data can be to theft, pointing out that criminals are often more interested in the social security numbers and other personal information that identifies the patients than the actual medical information.

Data privacy solutions

Intel’s Healthcare Innovation Barometer Infographic shows that many people are in fact willing to share their personal health data anonymously in order to lower the cost of healthcare. So the big question is: How can we protect health data while still making it available for critical health and research advancements? SAP’s Connected Care eBook recommends considering the following measures:

  • Creating a clear set of privacy guidelines and security rules that safeguard personally identifiable medical data
  • Leveraging data privacy best practices and knowledge from other industries
  • Establishing secure technology platforms that can handle massive amounts of data

How technology can help

Despite the obstacles, the potential benefits of combining medical data are putting the healthcare industry up to the Big Data challenge. Some of the following key technologies can help tackle this challenge head-on:

  • In-memory computing has the ability to combine and analyze large amounts of disparate data in various formats from multiple sources in real time.
  • Big Data solutions can quickly process huge data sets and conduct intelligent data mining to help identify links between patient information and treatment outcomes.
  • Predictive analytics software can make sense of data that was previously hard to obtain or non-existent behavioral, psychosocial, and biometric information.
  • Customized software applications can support the analysis of huge amounts of data.
  • Health platforms enable the processing and real-time analysis of medical Big Data from various sources in a single system.

While there are some Big Data challenges in healthcare, rather than being overwhelmed by the data, many healthcare, life sciences, and pharmaceutical organizations are looking for ways to capitalize on it. As a result, combining and analyzing biometric, genetic, and clinical data is already leading to groundbreaking medical advancements. For example, a comprehensive picture is being developed of individual and genetic characteristics worldwide; cancer clinics are using treatment response analysis to incorporate findings from previous chemotherapy results to help with current cases; and when researchers and healthcare providers can share their data in collaborative projects, pharmaceutical companies can bring advanced medicine to market faster. The potential rewards of connected healthcare can already be seen, and show astounding promise for the future.

For an in-depth look at how technology is changing the face of healthcare, download the SAP eBook, Connected Care: The Digital Pulse of Global Healthcare.

See how the digital era is affecting the business environment in the SAP eBook, The Digital Economy: Reinventing the Business World.

Discover the driving forces behind digital transformation in the SAP eBook, Digital Disruption: How Digital Technology is Transforming Our World.

About Paul Clark

Paul Clark is the Senior Director of Technology Partner Marketing at SAP. He is responsible for developing and executing partner marketing strategies, activities, and programs in joint go-to-market plans with global technology partners. The goal is to increase opportunities, pipeline, and revenue through demand generation via SAP's global and local partner ecosystems.