Health systems face a unique challenge when navigating the CMS Quality Payment Program (QPP). All currently available options to comply with the QPP require the submission of some form of clinical quality measures. With multiple specialties and often multiple sources for tracking billing and clinical data, aggregating all available data in a coherent, efficient, and centralized way can seem nearly impossible for the average health system. This case study demonstrates how MIPSPRO assisted one of their health system clients by streamlining their quality reporting process.
The future is here!
This Wednesday, the CMS Innovation Center, in collaboration with the American Academy of Physicians and the Laura and John Arnold Foundation, announced the Artificial Intelligence (AI) Health Outcomes Challenge to predict unplanned hospital and skilled nursing facility admissions and adverse events.
When I was in graduate school, I quickly gravitated to projects and classes that focused on the relatively new field of database design and database technology. I loved the deep analysis of data and exploring the question of how to leverage technology to support storage and access to data in order to find answers. It was challenging, it was new, and it was a field that I knew would have a huge impact. My thesis was about data organization and optimization, and I was lucky to be able to experiment with all sorts of database challenges and software as I ultimately built my own contribution to the science.
At the Optum Forum conference this year, once again I was brought back to the data. As a recent partner with Optum, Healthmonix provides MACRA (MIPS and ACO) reporting for Optum clients in addition to our existing client base. At the conference, I heard the cries of how fundamental the data really is as we move forward in the value-based care market. As much as we need to work with providers and payers to change patterns of practice, a critical component is the data that supports the change and that measures the impact.
This is because data is what drives precision medicine and AI initiatives. It drives understanding, affirms what we already know, points out new patterns that we haven’t realized, and shows us where our perceptions are correct and where they are not.
In an environment of ever-increasing demands for information, healthcare providers must ask more, document more and learn more about their patients. With more information comes more insight; this is evident as some of the hottest topics for healthcare IT include Big Data, Artificial Intelligence and patient data analytics. But to get to the point where patient data can successfully be used to identify care gaps and provide predictive insights, the information must be documented correctly.
HIMSS is the seminal event in healthcare technology each year. This year it grew to 45,000 attendees and literally a mile of exhibit hall. We logged miles of walking in one day just to cover the exhibit floor, and still did not see it all. At this pivotal time in healthcare information technology, there were many important themes that were covered.
Nearly 90 percent of healthcare organizations suffer data breaches according to the Ponemon Institute.  The level of data breaches is predicted to continue to grow. What if there was a technology to better encrypt our health data, while also providing improved access to comprehensive health data for a patient? The quality of healthcare would rise, patient satisfaction would increase by leaps and bounds and costs would likely fall. Sound idylic?