Federal health tech leaders want to extract data for greater equity

 Federal health tech leaders want to extract data for greater equity


Designing technology infrastructure with target communities in mind increases the chances that groups will adopt it. That, in turn, raises greater equity in health care systems-a recurring message at last week’s Health Innovation Summit 22 from ACT-IAC.

The Biden administration has repeatedly called for equity considerations to be included in new policies or programs, and many federal leaders understand what that means for their particular agencies.

For the Center for Medicare and Medicaid Innovation at the Department of Health and Human Services, equity is “achieving the highest level of health for all people,” according to its Healthy People 2030 strategic refresh. One of the refreshing criteria for success is more robust data collection and intersectional analysis for populations defined by race, ethnicity, language, geography and disability, to identify gaps in care and create interventions to address it. To do that, CMMI said participants in all new models need to collect and report data to identify and monitor health effects and reduce variances, while existing ones models are encouraged to do the same.

All new models will also include patients from historically deprived populations and safety net providers, such as community health centers and disproportionate hospitals – facilities serving a more unequal number of low-income patients and receiving payments from the Centers for Medicaid and Medicare Services to cover the care of uninsured patients.

CMMI Deputy Director Arrah Tabe-Bedward said we spent a lot of time just trying to understand and start collecting data to understand what the Center can reach and how it can get more providers to participate.

“We think there are incredible opportunities that can be done with advanced models of primary care and [accountable care organization] models. That kind of structure, of course, requires that there be plenty of opportunity for information to be exchanged efficiently and effectively across providers and in care settings, in order to optimize the patient experience, ”he said. “And to get that right, as we drive toward the more ambitious goal we have set for ourselves for 2030, to ensure that all of our Medicare beneficiaries, and the majority of those on Medicaid, are in different harmonious relationships with care providers. ”

Tabe-Bedward said CMMI wants to make sure there is technology to support relationships and to ensure care is optimized.

Some communities lack experience in AI and machine learning, or actively lack confidence in the technology, thus hindering its implementation. Susan Gregurick, associate director for Data Science at the National Institutes of Health, said this problem was observed by the NIH’s Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Program.

“In this case, federated learning is the right approach. And I think that’s one of my messages without a hammer for all the many use cases … we really need to adopt and adapt. our technologies for communities and research programs that we really want to address, ”he said.

As a White House Presidential Innovation partner in Technology Transformation Services, Nina Walia is passionate about accessible data. For specific health care data, troves of PDFs and documents used by providers hide valuable information that is withheld, leading to much excessive data entry.

“If we start with the masses and the masses and everyone adopts the idea of ​​optical character recognition versus computer vision, we can start actually extracting this data in an automated process so that this data can be read by the machine. , “he said.





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