Editor's note: This article is part of a multi-page special report, 8 Ways to Fix the Affordable Care Act.
There’s no question the Affordable Care Act is in need of some legislative fixes, but underneath those policy bandages, technology is already transforming the way the industry treats patients and pays for care.
That undercurrent of innovation could use some nurturing as well, particularly as payers and providers look for ways to provide more efficient, value-based care.
The rise of telehealth is a perfect example. This year alone, lawmakers have submitted half a dozen bills to expand or reform telehealth payment in some way. Medicare and Medicaid coverage for telehealth services is still sorely lacking, and the nation’s top insurance companies have been pleading with the feds to remove the barriers to telehealth reimbursement.
States have made some progress when it comes to paying for telehealth and enacting parity laws, but those laws aren’t keeping pace with the relentless advancements of virtual care.
That’s not stopping providers from investing in telehealth technology, and most healthcare executives will admit that even though reimbursement is a struggle, the thought of being left behind is even more unsettling.
Admittedly, the CBO scores for telehealth bills are messy, but there’s little doubt that virtual care brings a slew of benefits by keeping patients at home and opening up access in rural parts of the country, where patients would otherwise spend hours traveling to the nearest medical center or forgo care altogether. Expanding payment models—a notably bipartisan issue—will provide support to local initiatives that are already well underway.
At the same time, data have become tools that both payers and providers can't live without. The problem: Most healthcare data are still unusable.
Quantity is not an issue—there’s a seemingly endless stream of healthcare data, and more on the way as patient-generated data gain a bigger foothold. The problems boil down to quality and usability.
Solving these two issues will be critical as the industry turns to data analytics to improve care, reduce costs and validate new payment models. Although there have been pockets of success thanks to burgeoning data-sharing partnerships between payers and providers, medical data are still difficult to untangle, and cleaning patient data is still incredibly burdensome.
Obtaining clean, usable data will serve as the backbone to deploying predictive analytics and machine learning that can predict illnesses, reduce unnecessary hospital visits, support population health initiatives, streamline care and reveal the best treatment options for patients with chronic illnesses.
Better data-sharing arrangements between payers, providers, researchers, government agencies and patients will speed the discovery of cutting-edge treatment options and advance precision medicine. But all of those efforts will be slow to mature without concerted (and coordinated) efforts to standardize data collection and dissemination across multiple platforms.