Leveraging Oncology Data

With an alarming 35 percent of treatment plans deviating from evidence-based guidelines, it is no surprise that obtaining actionable insights from data still proves to be a challenge across the healthcare ecosystem.

While electronic medical records and other technologies help organizations input, access and organize data, providers are still struggling to collect, communicate and make sense of it.

In essence, the full potential of Big Data remains untapped in healthcare. While we have no shortage of information on hand, providers must now determine how to best leverage that data for maximum benefit.

To overcome the obstacles to using data effectively, many healthcare organizations are building registries – organized systems that allow providers to collect information in a standard, uniform way to track and measure as well manage a particular disease.

The Role of the Registry

As registry technology has evolved, we have seen dramatic changes in the way care is delivered across the healthcare ecosystem. In the hospital setting, registries have been used for many years to manage patient follow up and in support of cancer research. There are national, regional and local registries focused on chronic disease management and to track quality of care. Although registries are not new, interest in disease registries use is increasing as greater emphasis is placed on health outcomes, prevention and wellness, as well as quality measurement and reporting for pay for performance and other value-driven healthcare initiatives.

For treatment and research of a disease like cancer, registries provide an opportunity to organize large amounts of complex, patient data. Evidence of this can be seen in Elekta’s Leksell Gamma Knife® Registry, a specialized registry comprised of stereotactic radiosurgery data from thousands of Gamma Knife® radiosurgery treatments conducted each year. Developed collaboratively between our teams at Elekta and renowned Gamma Knife centers and radiosurgery practitioners, the Registry provides clinicians with a powerful tool to identify global treatment patterns and connections between treatment parameters and outcomes. With an integrated view of longitudinal data, the goal of the Registry is to empower clinicians with the insights to better select patients, personalize treatment paradigms, and improve the quality of care.

And possibilities continue. According to Douglas Kondziolka, MD, Professor of Neurosurgery and Radiation Oncology at New York University School of Medicine, “New science using Big Data tools will allow us to probe data, ask new questions, and provide new discovery. Some examples already utilized in other fields of research include data mining, machine learning, geocoding, and new forms of graphic presentation.”1

The challenge? In healthcare, we have gone straight from paper to automation. While federal policies have encouraged data standardization and data collection is improving, there remains some important ground to cover. As a best practice, providers should put a data governance structure in place to ensure consistent data collection. The more standardized that data collection becomes, the better the registries will be at automation, which will improve the quality of the registry and its outcomes.

SEE ALSO: Physician-Forward Approach to Meaningful Use

Proven Value for Physicians

Data registries that have proven themselves to be the most valuable tend to embed registry data into the clinical workflow, which can help improve the accuracy and validity of the data captured. Data warehouse and analytics solutions allow for near real-time integration and are rapidly changing the role of registries. Instead of only supporting quality measurements retrospectively, the data can be accessed in near real-time by physicians for improvement in clinical decision making, and aiding in increasing quality and efficiency within practices.

In addition to embedding analytics for real-time analysis, we also see many organizations leveraging visual analytics. Through visual analytics, clinicians can quickly recognize and investigate patterns to assure or improve quality, rather than constructing a quality study or process that would involve construction of queries or random manual review of cases on data that is “locked” up in an EMR or a registry. Analytics that allow visualization of both population and individual patients help identify rare diseases, and can help clinicians easily review details around the treatments and outcomes for those populations.

A Look Ahead

Registry adoption from quality-driven organizations shows a step in the right direction, with providers setting a higher standard for the use of evidence-based data. We are seeing many organizations work together to aggregate registry data, leading to quicker accumulation of cases around rare diseases. This collaborative process helps produce even more statistically significant results. Additional interest in layering predictive, prescriptive and visual analytics into registries shows that providers are anxious to derive even more actionable insights. While immense progress has been made, better data collection is still critical to the advancement of today’s registries. As data-driven healthcare organizations emerge and establish data governance, we will see increased quality and efficiency, and most importantly, improved patient care.

1. Kondziolka D, Cooper BT, Lunsford LD, Silverman J (2015) Development, Implementation, and use of a local and global clinical registry for neurosurgery. Big Data 3:2, 7, DOI:10.1089/big.2014.0069.

Anna Theriault is the Director of Healthcare Data and Analytics at Elekta. Heidi Gianella is Manager of Elekta Data Solutions, Product Management.

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