California mandate to lower C-sections will impact population health – how can analytics help?

Following a surge of cesarean section (C-section) operations for expecting mothers, doctors in California must now reduce the number of C-sections performed to 23.9 percent for low-risk births. The state’s health insurance marketplace under the Affordable Care Act, Covered California, wants to curb this rate to improve patient safety and quality. Any hospital that doesn’t meet these metrics runs the risk of being removed from the state’s health insurance marketplace as an in-network provider. Currently, most hospitals in California deliver around 40 percent of their babies via C-section.

The medical rationale for reducing the rate of C-sections is strong. C-sections can expose a woman to unnecessary risks such as infection, hemorrhage or even death. Studies also show babies born by C-section have a higher risk of complications and spending more time in the neonatal intensive care unit. We talked to Bruce Carver, Associate Vice President of payer services at MedeAnalytics, about this new mandate and how data analytics can be leveraged to address it.

How could this approach impact hospitals in California?

There are some factors that would be beneficial for Covered California to keep in mind. Reaching the goal ultimately falls on the provider, who is giving patients that care. But hospitals should be examined on a case by case basis if they are not meeting the metric, because removing them from the insurance marketplace could have a huge impact on providers and members, especially in rural areas. 1.4 million people in California purchase their health insurance through 11 insurers on the state exchange. Additionally, there could be valid, uncontrollable reasons why a hospital might miss the metric. But, of the 243 maternity hospitals in the state, 40 percent have already met this target.

How can analytics play a role?

Analytics can ensure health plans are appropriately enforcing such utilization management requirements. For example, they can analyze if the problem exists with a certain market or provider. The real problem is not actually tracking these initiatives, but figuring out what action will illicit the desired outcome. Additionally, health plans are always at risk of losing member utilization through a third party contracting entity that could offer a lower price than the health plan itself. In this circumstance, the health plan does not have knowledge of such services or utilization.

How can Covered California achieve its goal?

To be successful, Covered California should allow data to drive the best decision to achieve the desired outcome, in this case, lowering the C-section rate to 23.9 percent. Over time, analytics can provide the retrospective insight to develop more predictive models that address cost and utilization issues before they have a significant impact on costs. Getting ahead of these issues early can often keep organizations from having to put out these mandates in the first place to correct the market.

MedeAnalytics can help your plan get control of its population health by using data analytics to communicate gaps in care to physicians and improve care coordination. Visit our Population Health page here to learn more, or contact us here.

MedeAnalytics

MedeAnalytics is a leader in healthcare analytics, providing innovative solutions that enable measurable impact for healthcare payers and providers. With the most advanced data orchestration in healthcare, payers and providers count on us to deliver actionable insights that improve financial, operational, and clinical outcomes. To date, we’ve helped uncover millions of dollars in savings annually.

Leave a Comment





Get our take on industry trends

How did we get here? Hospital analytics and the new normal

July 15, 2020

I have heard the word “unprecedented” so many times in 2020 that it has lost its significance; many of us have become desensitized to the extraordinary changes in the world this year.

Read on...

How to help employer groups plan in a time of uncertainty

June 15, 2020

Employers and their sponsored health plans are thinking about next year’s benefit designs with a significant challenge not seen before: the effect of the coronavirus pandemic. There are important considerations to take into account before making any decisions about new or existing coverage. Becky Niehus, a director of Product Consulting at MedeAnalytics, explores these new issues and what employers can do to ensure employees are “covered.”

Read on...

Healthcare’s return to “normal” after COVID-19: Is it possible?

June 9, 2020

As providers determine how to get patients to return to facilities for routine disease management and preventive screenings, opportunities are ripe for the application of analytics to triage at the right time to the right setting. Data related to COVID-19 will continue to flow rapidly, but there are possibly more questions than answers now about a return to “normal.”

Read on...

Avoid COVID-19 modeling pitfalls by eliminating bias, using good data

June 2, 2020

COVID-19 models are being used every day to predict the course and short- and long-term impacts of the pandemic. And we’ll be using these COVID-19 models for months to come.

Read on...