According to the American Cancer Society, the cancer death rate dropped by 32% (or 3.5 million fewer cancer deaths) between 1991 and 2019 in the U.S. alone. The improvements in cancer care can be attributed to several factors, including a heightened awareness of key risk factors, better detection measures, and enhanced treatment options. While we can expect and even demand continued gains in those areas, the essential next frontier is focused on the role of data in developing treatments and managing care.
Given the complexities in which the oncology treatment community operates, delivering the highest quality of care depends on the physician’s judgment and analysis of emerging technology. Having the capacity to streamline the exchange of clinical data to help improve outcomes for patients and healthcare professionals has become a vital component of providing cutting-edge clinical care, especially in the rapidly evolving field of oncology.
By using tools that help transform data into digestible pieces, oncologists, hospitals, and research centers now have the ability to address the most complex electronic health record (EHR) interoperability challenges head on, leading to cohesive treatment plans based on a combination of real-world data, artificial intelligence (AI) and machine learning (ML). The connection between cloud-based computing software and cancer care may not be obvious, but they are dots that need to be connected, and the relationship between clinical care and software will only grow stronger in the coming years and even decades.
As healthcare systems and providers lean more heavily on cloud-based storage solutions to provide easier access to health records and more precise care for their patients, it’s important to remember that in healthcare, not all data is created equally. What’s more, the healthcare industry generates some of the largest datasets that often require a herculean effort to digest and convert into meaningful insights and advances in treatment.
The value of data in cancer care
Tumor registries are at the core of modern cancer treatment, access to which enhances and validates data while creating curated patient databases for increased usability and applicability. Furthermore, the ability to harness the massive information sprawl into relevant research questions and answers, all while meeting varying data management regulations and multiple layers of privacy and security restrictions, has been a boon to care teams, which are typically made up of specialists in different departments (or even health systems) with unique focuses.
From a broader perspective, digital data can inform patient-valued care, quality initiatives, and policy guidelines. In addition, the growing usage of assays that leverage smaller quantities of source material and produce higher volumes of data has led to the necessity for new and adaptable data storage solutions. Analyzing multifactorial data in a standardized, cost-effective, and secure manner is complex and requires technical solutions and back-end support, which can be a strain on smaller operations.
From data management to clinical practice
We knew that the technology we provide at Infor, as experts in cloud software, had the potential to play a critical role in how life-saving medicines could and should be used. Cancer treatment is less of a guessing game than ever, and precision treatment would not be possible without the advent of data collection and machine-learned analysis.
Infor and its Cloverleaf® technology have supported our partners and their certified teams of tumor registrars with access to patient records that are used to enhance and validate data, creating a curated patient database that’s far more robust in usability and applicability.
Real world application
In 2018, Infor partnered with Syapse, a company dedicated to extinguishing the fear and burden of serious disease by advancing real-world care, to collect, analyze and leverage massive amounts of data that could have a meaningful impact for patients and healthcare providers. The partnership has already proven to be a meaningful step in the mission to deliver more precise cancer care.
Most notably, data processing capabilities leapt from 18,000 to 3.2 million records per hour. The result of Syapse’s integration of Cloverleaf has established a fluid platform that hospitals, licensed customers, and industry peers can confidently trust. After switching to Cloverleaf, the 20-year data backload that would have taken two years to ingest was integrated in just five days. Although Syapse has continued to grow its customer base and, by associated, patient volume, it has not come close to reaching any constraints on scale.