Medicaid patients with complex needs drive the majority of state Medicaid spending: 4% of Medicaid beneficiaries account for 50% of state Medicaid spending and 15% of beneficiaries account for 75% of state Medicaid spending. A large portion of these high-cost Medicaid patients have both physical and behavioral health diagnoses. Examples include patients with chronic medical conditions like diabetes or heart disease who also have a behavioral health condition, such as bipolar disorder or depression.
Dual physical-behavioral diagnoses dramatically increase the need for and the benefits of care management and patient engagement. Unfortunately, most clinicians and other decision makers lack the information needed to manage this complex, high-cost population effectively. They are awash in data but lack timely, actionable information on patient’s conditions and needs. For example, absent the right tools, physicians are often unaware of all of a patient’s co-morbidities or treatment, particularly for behavioral health diagnoses.
Medicaid expansion makes use of advanced analytical tools critically important. Under the Affordable Care Act, Medicaid enrollment will increase by 24 million, according to new estimates by the Centers for Medicare and Medicaid Services (CMS). All these new enrollees are adults under 65, many of whom have untreated physical and behavioral health diagnoses. By 2020, Medicaid enrollment will reach nearly 100 million.
On May 1, we sponsored a webinar entitled “Managing Medicaid Patients with Physical and Behavioral Health Dual Diagnoses through Advanced Analytics”. Our main speaker was Kip Piper, a seasoned expert on Medicaid, Medicare, and health reform and a senior consultant with Sellers Dorsey. He provided a high-level briefing on how using a combination of analytical tools can be used to improve clinical and financial outcomes in state Medicaid programs, particularly for high-cost, high-risk Medicaid beneficiaries with dual medical and behavioral diagnoses.
If you are interested in listening to the post event audio, please email l.roman@elsevier.com.
