BusinessHumans and technologySponsored

Building a data-driven health-care ecosystem

The application of AI to health-care data has promise to align the U.S. health-care system to quality care and positive health outcomes. But AI for health care hasn’t reached its full capacity.  One reason is the inconsistent quality and integrity of the data that AI depends on. The industry—hospitals, providers, insurers, and administrators—uses diverse systems. The resulting data can be difficult to share because of incompatibility, privacy regulations, and the unstructured nature of much of the data. The data can carry errors, omissions, and duplications, making it difficult to access, analyze, and use. Even the best data can cause data bias: the data used to train AI models can reinforce underrepresentation of historically marginalized populations. The growth of AI in all industries means data quality is increasingly vital.

While AI-driven innovation is still growing, the U.S. continues to spend more than twice as much as the average high-income country for its health care, while its health outcomes are falling: the latest data from the U.S. Center for Disease Control’s National Center for Health Statistics indicates U.S. life expectancy rates dropped for the second year in a row in 2021.

To spark innovation by identifying gaps and pain points in the employer-based health-care system, JPMorgan Chase launched Morgan Health in 2021. Morgan Health’s chief technology officer of corporate responsibility, Tiffany West Polk, says Morgan Health is driven to improve health outcomes, affordability, and equity, with data at its foundation. Gaining insights from large data streams means optimizing analytical platforms and ensuring data remains secure, while also HIPAA and Health Resources and Services Administration (HRSA) compliant, she says.

Currently, Polk says, the U.S. health-care system seems to be “quite stuck” in terms of keeping health-care quality and positive outcomes in line with rising costs.

  • “If you look across the broader U.S. environment in particular, employer sponsored insurance is a huge part of the health-care net for the United States, and employers make significant financial investment to provide health benefits to their employees. It’s one of the main things that people look at when they’re looking across an employer landscape and thinking about who they want to work for.”

Investing in new ways to provide health care

Nearly 160 million people in the U.S. have employer-sponsored health insurance as of 2022, according to health-care policy research non-profit KFF (formerly the Kaiser Family Foundation). JPMorgan Chase launched Morgan Health because of its focus on improving employer-sponsored health care, not least for its 165,000 employees.

Morgan Health has invested $130 million in capital during the past 18-plus months in five innovative health-care companies: advanced primary care provider Vera Whole Health; health-care data analytics specialist Embold Health; Kindbody, a fertility clinic network and global family-building benefits provider; LetsGetChecked, which creates home-monitoring clinical tools; and Centivo, which provides health care plans for self-insured employers.

All of these companies offer new approaches to conventional employer-sponsored health care to deliver a higher standard of care. Morgan Health’s collaboration with these enterprises will examine how these change patient outcomes, health-care equity, and affordability, and how to scale their successes.

“Many Americans today face real barriers to receiving high-quality, affordable, and equitable health care, even with employer-sponsored insurance,” Polk says. This calls for breaking the paradigm of delivery-incentivized health care, she says, which rewards providers for delivering services, but pays insufficient attention to outcomes.  

  • “We have a model today where our health-care providers are incentivized based on the number of patients they see or the number of services they perform. What that means is that they’re not incentivized based on improvements, patient’s health, and wellbeing. And so when you have a model that thinks volume versus value, those challenges then serve to compound the disparities that we have. And that then also means that those who have employer-sponsored insurance are also similarly challenged.”

For Morgan Health, AI and machine learning (ML) will be a key to problem-solving with health-care technology, Polk says. AI is ubiquitous across industries, and is the go-to when we think about innovation, she says, but the hype can mean we forget about the importance of data accessibility and quality.

Polk says solving this data challenge makes this an exciting and transformational time to be a chief technology officer and a technologist. The next stage of evolution in health care can’t proceed without better data, Polk says, and this is what the data and analytics team at Morgan Health are addressing.

  • “[AI] has become so ubiquitous in terms of how we think about everything. And we think that it is the thing that’s going to fix anything and everything in technology. And it has become so ubiquitous and so the go-to when you think about innovation, that I think that sometimes, there’s this way in which people kind of forget about what AI actually is underneath the covers.”

Garnering data-based insights

To address the strength of health-care data, the industry is moving increasingly toward standard electronic health-care records (EHRs) for patients. A 2023 Deloitte study says use of EHRs and health information exchanges (HIEs) is growing rapidly, with organizations building data lakes and using AI to combine and cleanse data. These measures provide a “strong digital backbone” for building connections between hospitals, primary care centers, and payment tools, the study says, and this should help reduce errors, unnecessary readmissions, and duplicate testing.

The U.S. Department of Health and Human Services (HHS) is also building a network for digital connection in the health-care industry, to allow data to flow among multiple providers and geographies. Its Office of the National Coordinator for Health Information Technology (ONC) announced in December 2023 that its national health data exchange—the Trusted Exchange Framework and Common Agreement (TEFCA)—is operational. The exchange connects Quality Health Care Information Networks, which it certifies and onboards, with standard policies and technical requirements.

Polk says Morgan Health is improving foundations to incentivize better outcomes for patients. Morgan Health’s work can create standards—grounded in data—that incentivize better performance, which can then be shared across the employer-sponsored insurance network, and among broader communities. Using AI features such as metadata tagging (algorithms that can group and label data that has a common purpose), she says, “is one way health-care companies can simplify tasks and open up more time for providing care.”

  • “If you do your data ingestion right, if you cleanse your data right, if you make sure that your metadata tagging is correct, and then you are very aware of the way in which your algorithms have been biased in the past, you can be aware of that so that you can make sure that your algorithms are inclusive moving forward.”

“I think the most important thing is incentivizing our health-care partners who provide for our employees to meaningfully improve health-care quality, equity, and affordability through incentivizing outcomes, not incentivizing volume, not incentivizing visits, but really incentivizing outcomes,” Polk says.

This article is for informational purposes only and it is not intended as legal, tax, financial, investment, accounting or regulatory advice. Opinions expressed herein are the personal views of the individual(s) and do not represent the views of JPMorgan Chase & Co. The accuracy of any statements, linked resources, reported findings or quotations are not the responsibility of JPMorgan Chase & Co.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

Source link