Mayo Clinic, fresh off being named the best hospital in the country by US News and World Report for the seventh straight year, is looking to create another long-term vessel of success after entering into a decade-long partnership with Mercy, sharing data to create better health outcomes.
The organizations both have a tremendous amount of data, but previously haven’t been able to glean the type of insights they’re looking for because of the complexity and unstructured nature of the information. Technology has helped bridge some of this gap, with new artificial intelligence and machine learning tools working in a cloud environment yielding patterns in the data that will illuminate the best treatment options for a patient.
To be clear, this isn’t the type of dataset that’s manageable in Microsoft Excel on your home computer. Mercy alone has half a billion deidentified patient encounters from its clinics as just a part of its dataset. Mercy’s extensive reach into local communities with diverse backgrounds combined with Mayo’s technology and complex care expertise makes the collaboration formidable in creating new patient treatment workflows. With the insights gained from this partnership, the organizations are trying to pull the treatment window forward, with better preventative and proactive methods to control or stop diseases earlier.
The hope is that the volume and variety of data, thanks to differing patient populations and geographies, will help resolve issues of bias or homogeneity in the results. This is crucial in ensuring that outcomes are as effective and equitable as possible. It’s a subject we’ve explained in our blogs, looked at real-world examples, and searched for solutions for. That doesn’t mean, however, that this technology is inherently bad and artificial intelligence algorithms can fight inequity as well. The data is all fully deidentified and each organization will maintain stewardship over their own information and outcomes.
The relationship is intended to be a long one, so researchers from the teams will be focusing on the development and validation of their algorithms, which should identify proven treatment paths that can be used not just at Mercy and Mayo, but across the healthcare industry. The organizations have plans to dive into more specific areas of care, including transplants and complex cancers, as the project moves forward.
It's a fascinating partnership not just for the potential of improving disease treatment and prevention but also because it features two early adopters of electronic health records, providing a better repository of historical data than could be found elsewhere. They’re also overcoming the challenge of pulling insights from unstructured data, which is a place where every single healthcare organization we talk with struggles.
We feel that the solution to dealing with unstructured data is to never get all of the discrete data you need out of the myriad of formats of faxes, scans, emails, and paper. You don’t need an army of data entry staff to get that done and you certainly don’t need someone else’s army. With our HealthyData automation software, you can keep your data in-house, with a handful of your experts, freeing the rest to pursue higher value tasks. If you’d like to see how it works, please reach out and we’ll set up a demo right away.
About the Author: Chris Mack
Chris is a Marketing Manager at Extract with experience in product development, data analysis, and both traditional and digital marketing. Chris received his bachelor’s degree in English from Bucknell University and has an MBA from the University of Notre Dame. A passionate marketer, Chris strives to make complex ideas more accessible to those around him in a compelling way.