CMS Quality Conference 2024

It was an exciting few days attending the 2024 CMS Quality Conference – catching up with old friends and meeting new friends, attending informative presentations, and engaging in insightful discussions.  One clear message that transcended the sessions was that the pandemic brought about new technology and the need to be more flexible to “meet patients where they are”.  Even though the pandemic has subsided the “horse is out of the gate” so to speak and we will continue to advance in this direction over the coming years.

There were several few key themes that emerged:

Equity and Engagement

  • Equity is truly about ALL people.  The legislation is flexible and enables issues to be defined at a local level with the understanding the equity issues will vary between inner-city and rural areas and across different geographies.
  • There is growing support to provide payment for community services that address health related social needs.  One particular challenge in addressing equity issues in this area is the lack of community services available in some geographic areas.  Although equity gaps can be identified there may be a desert of social services that are essential address identified needs.
  • CMS has launched the Rewarding Excellence in Underserved Populations (REUP) program which is an upside-only monetary award for organizations that treat a high percentage of underserved populations.
  • Patient centered care is a focus across all agencies.  Policy makers have made a commitment to include the patient and caregiver voice in program development.  Additionally, patient experience measures are being expanded and programs are extending payment to include support such as caregiver training.

Outcomes and Alignment

  • CMMI was heavily focused on improving costs over the first 10 years and is shifting to focus on quality over the next 10 years.
  • There is a commitment to align measures both across CMS and with other agencies such as the Joint Commission, ONC, and AHRQ to reduce the reporting burden on providers.
  • One step in this direction was the creation of the Universal Measure Set which streamlined quality measures across the various CMS quality initiatives. CMS is developing population-specific “add on” measures that are applicable only to specific care settings.

Safety and Resiliency

  • The definition for harm needs to be expanded to include emotional and psychological, financial and socio-behavioral harm in addition to physical harm across both patients and the healthcare workforce. We have seen a concerning increase in healthcare worker safety events over the past few years.
  • A culture of safety is strongly correlated with high levels of workforce engagement and improved patient experience.
  • There has been an increased focus on maternal and infant safety across HHS.
  • The soon to be released 13th Statement of Work includes the provision of resources for workforce safety and for quality performance improvement activities.

Interoperability and Scientific Advancement

  • Interoperability continues to be a challenge, but we are making advancements to break down data silos and improve consistency across data sources. These steps are critical as we are striving to collect the right data at the right time to support informed care decisions across the continuum of care.
  • There has been a shift towards digital quality measures to reduce the burden of data collection.  These digital measures are also able to be integrated with other clinical data to evaluate the relationship of process measures with outcomes.
  • CMS is dedicated to advancing science, analytics and technology.  There is a focus on increasing the data and research that support evidence-based care.  Additionally, there is an interest in leveraging predictive tools to support more individualized, patient-centered care.
  • Real world data is a powerful resource to identify health gaps and to evaluate the impact of programs on closing those gaps.
  • AI will inevitably be a part of our future and it is our responsibility to help focus on the responsible use of AI in healthcare. Generative AI has current limitations in the form of reproducibility and explainability and can be prone to “hallucinations” that could be harmful in clinical practice.  We should work to advance the field forward while addressing these limitations and limiting risk.
  • Models are only as good as the data that are used to train them.  We need to work to mitigate bias in the data that is used to train AI tools.

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Joseph Beals, PhD, MBA, FAMIA

Joe is an accomplished healthcare executive with a track-record of bringing innovative technologies to market and helping client organizations develop and execute digital health strategies. A common thread throughout his career is a passion for translational data science – the “bench to bedside” operationalization of evidence-based insights and data driven technologies.

Joe has extensive experience in health informatics research, including predictive model development, clinical trial design, and process and outcomes improvement. He has published widely and received research awards from the American Medical Informatics Association, the Society of Critical Care Medicine, and the Journal of Biomedical Informatics. He worked closely with the FDA on one of the first real-world evidence supported regulatory clearances for AI/ML software used in predicting patient deterioration. Joe has led US and European federal grant projects, most recently as co-principal investigator on a contract from the US Department of Health and Human Services Biomedical Advanced Research and Development Authority to develop and deploy an Emergency Department triage tool.

In a prior role as CEO of PeraHealth, Joe expanded the company’s focus to encompass health care delivery challenges across the care continuum, including in sub-acute and home health environments and he oversaw the transformation of the company’s analytics service offerings in these areas. Following the acquisition of PeraHealth by Spacelabs Healthcare, Joe led Spacelab’s data science and analytics strategy, spear-heading the company’s digital health and analytics roadmap. Joe is a long-time proponent of the concept of augmented intelligence in healthcare – the operationalization of innovative AI/ML technologies which can both enhance the effectiveness and improve the experience of clinical care providers.

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Kathy W. Belk

Kathy is a clinical informaticist, data scientist and healthcare technologist with over 25 years of experience conducting healthcare research and performance improvement initiatives.

She has a passion to transform healthcare through data-driven care redesign and a diverse background enabling her to balance innovative strategy with rigorous scientific methodologies to create fit-for-purpose solutions.
She has extensive experience leading data-driven projects for pharmaceutical, biotech, medical device companies, health service providers as well as specialty societies and government agencies. Her work includes both traditional and innovative study designs across a wide range of topics and clinical areas and has resulted in more than 100 peer-reviewed publications and/or presentations in scientific journals and conferences.

Kathy has extensive data collection and linkage experience across many types of healthcare datasets including two used by the U.S. Food and Drug Administration, for which she was a subject matter expert. In a prior role with Premier, Inc., she served as data expert and lead scientist for an innovative pay-for-performance demonstration project with the Centers for Medicare & Medicaid Services. More recently she has led a range of data science, analytics and clinical technology initiatives for effective development and deployment of clinical decision support technology.