PR Newswire | October 06, 2023
LexisNexis® Risk Solutions, a leading provider of data and analytics, released new insights on the latest national and regional provider density trends for primary and specialty care. The analysis explores how often prescriber data changes, the metropolitan areas seeing the biggest change in the number of primary care providers (PCPs) and the metropolitan areas with the highest and lowest number of heart disease patients per cardiologist.
Outflows of providers and coverage ratios can impact a community's ability to deliver accessible and efficient care, and with a looming shortfall of PCPs, it's important to understand where the existing PCPs are located. The analysis reveals the five metropolitan areas with the highest percent increase and decrease of PCPs between June 2022 and June 2023. According to the data, the Vallejo-Fairfield, CA area topped the list with a nearly 40% increase in PCPs. Conversely, the Fayetteville, NC area saw the highest decrease – losing nearly 12% of its PCPs.
As chronic diseases continue to increase, the density of specialty providers becomes paramount. The provider density analysis examines the number of patients with heart disease per cardiologist in metropolitan statistical areas (MSAs) spanning large, medium, small, and micropolitan areas. The data shows as MSAs get smaller, the number of patients per cardiologist increases substantially, with many rural communities having thousands of heart disease patients per cardiologist. Among major metropolitan areas, Boston has the best ratio with 196 heart disease patients per cardiologist, and Las Vegas has the worst ratio with 824 heart disease patients per cardiologist.
Additionally, the analysis found significant degradation of prescriber data in a short period of time. Over a quarter of prescribers (26%) had at least one change in their contact or license information within a 90-day period. This finding is based on the primary location of more than 2 million prescribers and illustrates the potential for data inaccuracies, creating an additional challenge for patients navigating the healthcare ecosystem.
"Data is an essential element to fueling healthcare's success, but the continuously changing nature of provider data, when left unchecked, poses a threat to care coordination, patient experience, and health outcomes," said Jonathan Shannon, associate vice president of healthcare strategy, LexisNexis Risk Solutions. "Our recent analysis emphasizes the criticality of ensuring provider information is clean and accurate in real-time. With consistently updated provider data, healthcare organizations can develop meaningful strategies to improve provider availability, equitable access, and patient experience, particularly for vulnerable populations."
iTWire | September 27, 2023
Teradata today announced new enhancements to its leading AI/ML (artificial intelligence/machine learning) model management software in ClearScape Analytics (e.g., ModelOps) to meet the growing demand from organisations across the globe for advanced analytics and AI.
These new features – including “no code” capabilities, as well as robust new governance and AI “explainability” controls – enable businesses to accelerate, scale, and optimise AI/ML deployments to quickly generate business value from their AI investments.
Deploying AI models into production is notoriously challenging. A recent O'Reilly's survey on AI adoption in the enterprise found that only 26% of respondents currently have models deployed in production, with many companies stating they have yet to see a return on their AI investments.
This is compounded by the recent excitement around generative AI and the pressure many executives are under to implement it within their organisation, according to a recent survey by IDC, sponsored by Teradata.
ModelOps in ClearScape Analytics makes it easier than ever to operationalise AI investments by addressing many of the key challenges that arise when moving from model development to deployment in production: end-to-end model lifecycle management, automated deployment, governance for trusted AI, and model monitoring.
The governed ModelOps capability is designed to supply the framework to manage, deploy, monitor, and maintain analytic outcomes. It includes capabilities like auditing datasets, code tracking, model approval workflows, monitoring model performance, and alerting when models are not performing well.
We stand on the precipice of a new AI-driven era, which promises to usher in frontiers of creativity, productivity, and innovation. Teradata is uniquely positioned to help businesses take advantage of advanced analytics, AI, and especially generative AI, to solve the most complex challenges and create massive enterprise business value.
Teradata chief product officer Hillary Ashton
“We offer the most complete cloud analytics and data platform for AI. And with our enhanced ModelOps capabilities, we are enabling organisations to cost effectively operationalise and scale trusted AI through robust governance and automated lifecycle management, while encouraging rapid AI innovation via our open and connected ecosystem. Teradata is also the most cost-effective, with proven performance and flexibility to innovate faster, enrich customer experiences, and deliver value.”
New capabilities and enhancements to ModelOps include:
- Bring Your Own Model (BYOM), now with no code capabilities, allows users to deploy their own machine learning models without writing any code, simplifying the deployment journey with automated validation, deployment and monitoring
- Mitigation of regulatory risks with advanced model governance capabilities and robust explainability controls to ensure trusted AI
- Automatic monitoring of model performance and data drift with zero configuration alerts
Teradata customers are already using ModelOps to accelerate time-to-value for their AI investments
A major US healthcare institution uses ModelOps to speed up the deployment process and scale its AI/ML personalisation journey. The institution accelerated its deployment with a 3x increase in productivity to successfully deploy thirty AI/ML models that predict which of its patients are most likely to need an office visit to implement “Personalisation at Scale.”
A major European financial institution leveraged ModelOps to reduce AI model deployment time from five months to one week. The models are deployed at scale and integrated with operational data to deliver business value.
Big Data Management
WebWire | September 29, 2023
SAS, a leader in AI and analytics, is helping to revolutionize the use of clinical trial data so new medicines can be delivered to patients faster than before. After a thorough evaluation, SAS has been chosen by global biopharmaceutical company AstraZeneca to help increase efficiency and drive automation in the delivery of statistical analyses for clinical and post-approval submissions to regulatory authorities, via SAS’s cloud-based software and technologies.
SAS will support the redesign of clinical and patient data flow by delivering industry-leading analytics and AI, manage changing trial designs in a fast-evolving regulatory environment, enable data re-use, and help accelerate reporting and submission timelines. It will also deliver increased capacity, automation, interoperability, and flexibility to bring in and analyze diverse and novel patient data sources – such as those coming from wearables, sensors and precision medicine – as part of the submissions process.
This will be achieved by supporting the analysis and reporting phases with SAS® Life Science Analytics Framework and SAS® Viya®, a scalable and powerful cloud-based industry platform enabling swift decision-making regardless of data volumes or complexity using modern cloud technologies. This has the potential to provide significant productivity gains by driving faster time to market and reduced IT costs. The SAS and AstraZeneca partnership will enable teams across the organization to collaborate and increase clinical research innovation.
Christopher J Miller, VP Biometrics at AstraZeneca, said, This partnership with SAS supports the transformation of how we use clinical data to support our patient-centric approach and focus on getting medicines to patients faster than ever before. It will also allow us to introduce new ways of working and embrace new technologies and trial models to accelerate our portfolio.
Bryan Harris, SAS Executive Vice President and Chief Technology Officer, said, “I’m delighted that SAS is building on the strong relationship it has had with AstraZeneca over many years by being part of this transformation program. The work they do positively impacts the lives of millions of people around the world.
“This is exciting because we have solidified a great foundation between our companies, but we also recognize we are just scratching the surface. We pay attention to technology and the advancements in AI, and we thrive on thinking through how our technology blended with AstraZeneca’s expertise and insight can create new medical solutions for their customers.”
SAS is a global leader in AI and analytics software, including industry-specific solutions. SAS helps organizations transform data into trusted decisions faster by providing knowledge in the moments that matter. SAS gives you THE POWER TO KNOW®.