Travis Dalton, CEO of Claritev, and Jocelyn Jiang, Vice President of Product Development of Claritev’s Data & Decision Science offering, recently sat down with Richie Cotton of DataCamp’s DataFramed podcast to discuss how companies like Claritev are using data to solve some of the healthcare industry’s most intractable problems, including a lack of transparency around costs and quality, privacy and security concerns surrounding the use of healthcare data, and access to care in rural America.
Bringing transparency to the healthcare system
In the podcast, Jiang explains that the US healthcare system is not transparent when it comes to cost and quality, making it difficult for those who pay for healthcare services to make informed decisions. Even worse, prices can be drastically different from provider to provider for the same procedures. Claritev, with our Data and Decision Science offering, is trying to bring transparency, in the form of information about both cost and quality, to patients, payors and providers, according to Jiang.
Claritev’s Data and Decision Science solutions also allow organizations to predict high-risk patients using past claims data, Jiang explains. Unlike other companies that apply AI/machine learning to healthcare data to predict risks, Claritev uses interpretable decision trees* in our Data & Decision Science solutions. “With a decision tree, our clients can actually interpret results and form their benefits strategies accordingly,” Jiang says.
Ensuring data privacy and security
Not all healthcare data is usable due to concerns about privacy and security. However, there are ways to balance concerns about privacy and security with the need for accuracy.
“The very first step in our process is to separate personal health information from claim information. These are put in two separate repositories, linked by a common person ID,” Jiang says. “This protects information in the event of a breach.”
With personal health information removed from claims data, Claritev then uses the client’s deidentified claims, publicly available data, and tools such as various social determinants of health indices to analyze future patient risks. This allows Claritev to provide insights that enable our clients to make holistic benefits planning decisions while safeguarding personal health information.
Getting better data to healthcare providers
While Claritev has traditionally provided cost containment solutions to payors, our services and solutions can help providers as well with the unique issues they face.
“We want to serve the whole healthcare ecosystem,” Dalton says. “We strive to be a data and technology company that provides insights and solutions to impact cost, transparency and quality across healthcare.” As a step in this direction, Claritev is looking to work with rural providers to create better access to care in their communities, according to Dalton.
Listen to the podcast >*Claritev does not use generative AI in our Data & Decision Science solutions.
