Scouting Report-Covera Health: Catching Medical Errors With Analytics
Earlier this month Covera Health raised $25 million in a Series C financing led by Insight Partners with participation from existing investors including Equity Group Investments. The company plans to use this funding to help expand its first product, Centers of Excellence Radiology, which is deployed by both employers and health insurance plans to guide patients toward the highest-quality radiology providers based on their requirements. As noted by MobiHealthnews, Covera Health “partners with providers to give them insight on reducing errors, and it works with payers to avoid unnecessary care and promote value-based payment.”
The error rate in diagnostic imaging is on average 3 to 5 % and there are as many as 40M diagnostic imaging errors annually.
Covera claims to be able to boost delivery of more accurate care, while “reducing downstream care costs by as much as 30%”
The company states that they cover over 1 million patient’s lives and the project will be able to scale its radiology platform to cover over 20 million patients by 2021.
At least 12 million Americans will receive a misdiagnosis every year. 40-80,000 people die from complications due to misdiagnosis annually.
Covera Health an AI-powered quality analytics platform was founded in 2017 in New York and has raised $57 million to date. According to the company’s website, their platform “generates robust measures of diagnostic accuracy across pathologies and patient types which are then used to validate accuracy relative to their peers.” This “allows them to pair patients with radiologists who excel at diagnosing their specific issue.” The company states that they cover over 1 million patient’s lives and the project will be able to scale its radiology platform to cover over 20 million patients by 2021. Covera believes its quality assessing platform allows employers and health plans to choose their preferred radiology providers according to their needs while allowing payers to choose value-based care and cutting costs by saving on unnecessary care. By reducing medical errors and preventing misdiagnosis the platform can improve health outcomes and quality of care. It has gained the trust and interest of stakeholders who are motivated to improve health outcomes and improve patient’s quality of care. Covera Health has a team of clinical and strategic advisors onboard.
Covera has designed an analytics platform that leverages advanced data science and artificial intelligence to help reduce and eliminate systematic medical errors, initially focusing on diagnostic imaging. This area is particularly ripe for research as the company notes, “though radiologists have an average operational error rate of only 3% to 5%, retrospective studies of more advanced imaging technologies such as MRIs and CT scans have found error rates of 30% or more for complex diagnoses.” In diagnostic radiology systematic error rates are due to a number of potential factors including increased workload, understaffing, distractions and interruptions, technical errors, and mental fatigue. Covera selects top radiologists for their Radiology Centers of Excellence program based on a detailed assessment of 10 years of medical records and radiology scans involving millions of data points. According to the company, this is made possible by “a unique data-sharing arrangement with radiology providers, (which grants direct access to records to a quality-review panel comprised of experienced, subspecialized radiologists), together with its proprietary artificial intelligence algorithms.” This process has allowed Covera to identify more than 1,000 top-performing imaging centers nationwide while simultaneously providing radiologists participating in the program with valuable insights that can help them improve their practices. Covera claims to be able to boost delivery of more accurate care, while “reducing downstream care costs by as much as 30% in a study of 80,000 employees in a blinded statewide trial”.
The Big Picture:
According to a 2018 article in RadioGraphics, there are approximately 40 million diagnostic errors involving imaging annually worldwide and approximately 75% of malpractice suits filed against radiologists relate to diagnostic errors. As noted above there are systematic circumstances that can lead to diagnostic errors (workloads, distractions, fatigue) as well as issues with interpretation of scans that can be attributed at least in part to sub-specialization differences. However, medical errors in diagnostics can also be attributed to systemic issues deriving from biases and underrepresentation within the sheer number of imaging data points which can lead to a faulty diagnosis. For example, according to a recent article in Healthline, women, and people of color are likely to face misdiagnosis 20-30% times more than their white or male counterparts. As a result, the burden of acquiring proper care is shifted to the patient instead of to the provider, where it should reside. AI-powered patient analytics platforms like Covera Health rely on machine learning algorithms to sort through patient-centered data and reduce the rate of misdiagnosis emanating from the imaging department. Catching and preventing misdiagnosis early can mean that patients may forego unnecessary procedures, resulting in lowering costs and improving care. As noted in Healthline, “whether it’s AI analyzing mass amounts of patient data to help doctors better understand where they might go wrong to changing the way medicine is taught, the medical community must be receptive to critiques and suggestions about how to ensure that the level of misdiagnoses are reduced over time as are actual rates of error.”
Health Data Analytics Platform Covera Health Lands $25M in Series C Funding, Covera Health Raises $25M in Series C Financing to Fuel Growth of Its Healthcare Quality Analytics Platform, Fundamentals of Diagnostic Error in Imaging