268851 Population management: Using data analytics for improving prevention across an individual's life span

Monday, October 29, 2012

Nidish Mada, MS , Deloitte Consulting LLP, Arlington, VA
Sarah Marshall, MA , Quality Insights of Delaware, West Virginia Medical Institute, Wilmington, DE
Alan Fontes , State Health, DELOITTE CONSULTING, New York, NY
One of the provisions of the Patient Protection and Affordable Care Act (ACA) is the expansion of insurance coverage through Medicaid and State Health Insurance Exchanges. States must identify and address the needs and challenges that will be presented through the influx of these new populations. The challenge becomes more complex as States search for cost-effective ways to deliver and manage the delivery of healthcare. The solution is to use data analytics to successfully manage these new populations and support timely application of preventive services for them. This presentation will outline a proposed approach that combines the information architecture component of the MITA framework with advanced data analytics to bring together information from both within and across agencies to allow the States to identify and track key performance variables. This will enable stakeholders and decision makers to determine the impact of polices and trends to other major indicators and outcomes and result in significant increases in cost-optimization and performance management. For example, when reviewing the diseases that are placing the highest burden on the state, e.g., Diabetes, data analytics will enable investigation into each specific disease and determine the burden drivers. This drill down capability will allow States to determine if disease and/or case management programs need to focus on the individual disease, such as Diabetes alone, or whether it should focus on co-morbidities.Using data analytics, States will be able to shift their focus towards prevention and management of disease progression. By the end of this session, participants will be able to describe how states can use data analytics to successfully manage the new populations they will be serving under ACA, explain how data analytics can be used to promote prevention, wellness, and management of disease progression over the lifespan, and describe the proposed data analytics solution.

Learning Areas:
Administration, management, leadership
Chronic disease management and prevention
Planning of health education strategies, interventions, and programs
Public health administration or related administration

Learning Objectives:
• Describe how states can use data analytics to successfully manage the new populations they will be serving under ACA. • Explain how data analytics can be used to promote prevention, wellness, and management of disease progression over the lifespan. • Describe the proposed data analytics solution.

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: Nidish’ s background in state, local, and federal health provides him with the network and experience to understand and lead health reform work. Nidish has helped connect federal HIT initiatives to the state level, and provided assistance to state health agencies regarding their public health and HIE plans. Nidish has worked with experts to develop and utilize data analytics strategies to help solve health related issues faced by the state health care systems.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.