Source:-healthitanalytics.com
Amazon Web Services and Deloitte are working to create an efficient and secure healthcare data ecosystem.
Amazon Web Services (AWS) is partnering with Deloitte to help customers securely find, subscribe to, and use third-party data in the cloud using AWS Data Exchange, a new service that can help address unique healthcare issues.
The partnership will build on the existing relationship between the two organizations and transform biomedical research, clinical trials, real-world data insights, population health, and reimbursement.
Most digital health data generated by patients, researchers, health systems, and payers is inaccessible to other organizations for multiple reasons, from security concerns to technology constraints and business model challenges. This means healthcare organizations aren’t fully leveraging the benefits of this data, slowing the pace of medical innovation and limiting the potential to improve care delivery.
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“The explosion of digital healthcare data and advances in artificial intelligence (AI) and machine learning (ML) hold the promise to answer some of healthcare’s most important questions — what’s working for whom, why and at what cost,” said Brett Davis, principal, Deloitte Consulting LLP, and general manager, ConvergeHEALTH by Deloitte.
“However, this data is locked in siloes across many organizations within the health ecosystem. The industry needs new business models that break down these silos to connect healthcare stakeholders, reduce inefficiencies and accelerate the translation of research to practice and improve patient outcomes. AWS Data Exchange provides the technology and infrastructure to support these new business models.”
AWS Data Exchange creates a secure, scalable data exchange infrastructure under terms and conditions that data owners can control. AWS Data Exchange also allows customers to benefit from third-party software, artificial intelligence algorithms, and professional services.
Deloitte’s ConvergeHEALTH Miner integration with AWS Data Exchange means users of Miner can easily find, access, and analyze aggregated and de-identified data from collaborators outside their organizations. This could transform the way organizations conduct research, clinical trials, population health management, and reimbursement.
The partnership will help life sciences and healthcare organizations use more data to perform better research and improve patient outcomes.
“AWS Data Exchange provides a secure and cloud-native channel to exchange data at scale, with cloud-based solutions like ConvergeHEALTH Miner supporting the analytical needs for data analysts, academic researchers and data scientists in the medical community,” said Stephen Orban, general manager, AWS Data Exchange, Amazon Web Services, Inc.
“We’re delighted to be working with Deloitte on AWS Data Exchange to help life sciences and healthcare organizations establish their strategies around the new data-driven collaborations and business models, while also helping data publishers with the engineering tasks needed to package, aggregate and anonymize their data for collaboration.”
This partnership adds to Amazon’s efforts to enhance healthcare using data. In November 2018, the company announced a new machine learning service that can extract meaningful information from unstructured EHR data and free-text clinical notes. Called Amazon Comprehend Medical, the service allows developers to comb through unstructured EHR data and pull out key clinical terms related to a patient’s diagnosis.
Deloitte has also highlighted the importance of data and analytics in the healthcare industry. In a 2019 survey, the organization emphasized the need for organizations to invest in innovative data technologies.
“Heading into the future, data analytics is one of the backbones for health systems seeking to use emerging technologies such as artificial intelligence (AI) and robotic process automation (RPA) to transform their care delivery or workforce,” the report stated.
“It is also important for strategies and initiatives that depend on data mining—such as understanding social determinants of health and the importance of customer experience and preferences.”