This article is part five of a six-part blog series with Dr. Brad Jones.
Medicaid expansion is something that has been hotly debated over the past several years. At the beginning of this year, the Governor of Georgia announced that he’s going to pursue a Medicaid waiver that could pave the way for a limited expansion here in the state of Georgia. This spring, the Georgia legislature approved a bill authorizing the Governor to begin that process.
Integrating Social Determinants of Health
When it comes to strategic planning for this expansion, there is going to be a critical need for data analytics and applied research findings. First, we have to understand from a geo-cultural perspective where the needs really are. Then, we can utilize relevant disparate data sets to identify, understand, and integrate important and meaningful social determinants of health such as poverty, education, broadband connectivity, etc. In addition, coordination with other pertinent metrics/programs such as risk management, Promoting Interoperability (formerly Meaningful Use), and the new Primary Care First legislation must be woven in to truly meet the healthcare needs of the most vulnerable Georgians and have the most effective financial and clinical outcomes.
Tailored Approaches through Data Analytics
Many southern states have opted out of Medicaid expansion through the Affordable Care Act (ACA). This recent announcement by the Georgia governor and subsequent authorization by the state legislature affords a great opportunity to pilot something in Georgia that could potentially be expanded and replicated not only across the South, but also other states with similar prevailing political ideologies. They might see the need for Medicaid expansion but may be uncomfortable with a full expansion due to their fiscal policies. They think, “I see and understand the need to expand, but how can we do this in a fiscally-responsible, cost-effective way that a majority of my constituents will understand and agree with?”
The reality is that it all goes back to cost-effectiveness. We can use strategically-applied data analytics and research findings to help public health entities like Medicaid administrations serve underprivileged and underrepresented populations in a cost-effective way while simultaneously improving the services they provide.
If state-level Medicaid administrators desire to do a tailored approach to Medicaid expansion, it is crucial that they utilize data analytics and applied research findings to form their evidence-based decisions. At Truitt Health, we are prepared and equipped to be a major part and help in that regard.
[Look for the final post in this six-part blog series next week!]