In an effort to help healthcare organizations achieve more from their analytics – and better position them to take on new artificial intelligence and machine learning initiatives – InterSystems has launched a new service it's calling Clean Data as a Solution. WHY IT MATTERS InterSystems says Clean Data as a Solution helps its customers meet a key organizational imperative: ensuring their clinical, financial and operational data is able to be normalized, aggregated and interpreted more quickly and accurately. Clean datasets – no duplicate records, formatting errors, incorrect information or mismatched terminology – are critical to even the most basic analytics projects. The service – which the company says can help not just hospitals and health systems, but also payers, life sciences companies, contract research organizations and more – can help position health organizations as they move toward more AI and automation to help manage datasets from multiple sources. Clean Data as a Solution offers product and data normalization functionality to support specific use cases such as integration, patient matching, aggregation, normalization, terminology and enrichment, de-duplication into a unified care record, clinical viewing capabilities and more, according to InterSystems.
Pieces Technologies, the Dallas-based AI and predictive analytics startup that grew out of Parkland Health & Hospital System, is showcasing its continuing innovation on the patient safety and population health fronts at HIMSS18. Pieces' cloud-based clinical decision support tools let healthcare organizations put algorithms to work helping reduce lengths of stay, prevent readmissions, lower medication risks, avoid unnecessary hospitalizations and more. The company's applications use natural language processing, machine learning and artificial intelligence for predictive modeling that can help streamline clinician workflows and improve patient outcomes. On Monday, March 5, Pieces CEO Ruben Amarasingham, MD, CEO of Pieces Tech will kick off the week with a presentation at the HIMSS Machine Learning & AI for Healthcare conference, called "Why Clinical Augmentation is Necessary for Healthcare AI to Work." He'll explain how oversight from carbon-based life forms is a necessary key to ensuring the efficacy and success of artificial intelligence applications. At Pieces Technologies booth, meanwhile, the company will be showcasing its capabilities while highlighting what it calls the "new ROI" – return on insights.
At few times in recent memory has the resolve of hospitals and health systems across the U.S. – and the wherewithal of the information systems and digital data that keep them running – been put to the test quite like it was in 2020. An all-hands-on-deck push from heroic physicians and nurses to save the lives of as many COVID-19 inpatients as possible. A massive nationwide scale-up of telehealth and remote patient monitoring unlike anything yet seen. Ongoing interoperability challenges as testing sites, labs, providers, payers and public health agencies tried to manage fast-moving waves of new patient data. Major new federal rulemakings meant to enable more seamless data exchange in the future.
In another big move aimed at its healthcare clients, Amazon Web Services revealed this week that its Textract machine learning technology – which can help healthcare organizations more easily extract data from scanned documents – is now HIPAA eligible, joining a half-dozen other cloud-based AI tools. WHY IT MATTERS It's important to note that HIPAA-eligible is not the same as HIPAA-compliant – it just means that the technology is able to be customized and put to use in ways that are. Organizations can't simply install Textract and expect to be compliant. That said, with proper configurations, the tool can be deployed at healthcare and life science organizations whose tasks that require HIPAA compliance, said Textract Product Lead Kriti Bharti in an Oct. 10 blog post. "Critical healthcare information often lies within documents such as medical records and forms. Healthcare and life science organizations need to access data that is locked inside those documents in order to fulfil medical claims, streamline administrative processes, and process electronic health records," said Bharti.
One of the effects of the COVID-19 public health emergency is that it has added urgency and speed to technology transformations that were already occurring, such as cloud migration and deployments of artificial intelligence and machine learning. At few places is that shift more pronounced than at Rochester, Minnesota-based Mayo Clinic, which six months before the pandemic arrived in the United States had embarked on a decade-long strategic partnership with Google Cloud. "Our partnership will propel a multitude of AI projects currently spearheaded by our scientists and physicians, and will provide technology tools to unlock the value of data and deliver answers at a scale much greater than today," said Mayo CIO Cris Ross at the time. Shortly after the partnership was announced, toward the end of 2019, the health system hired longtime CIO Dr. John Halamka as president of Mayo Clinic Platform, tasking him with leading a cloud-hosted, AI-powered digital transformation across the enterprise. In the months since, like the rest of the world, Mayo Clinic has found itself tested and challenged by the pandemic and its ripple effect – but has also embraced the moment as an inflection point, a powerful moment to push forward with an array of new use cases to drive quality improvement, streamline efficiency, and boost the health of patients and populations in the years ahead.