Healthcare Data & Risks of the Uninsured

Today, we live in a world of exploding data.  And yet in health care, we often find ourselves in the difficult position of questioning if we have the data to answer the question(s) at hand.

There is lack of individual claims data for the roughly 40 million previously uninsured. As they are about to flood into the US health insurance market due to the Affordable Care Act, payors and providers alike want to know what their health risks look like and what impact they will have on their business.

Traditional claims based risk assessment tools hardly predict the risks accurately without claims. Third party data have been suggested by many that could add some insight to understanding the risks of the currently uninsured. Is there any sampling data for this segment of population on their demographics, health-related behaviors, and medical or/ and Rx expenditures? I am working with other SAS CHAI team members to find answers to these questions and would like to share with you what we found.

Health Data Community (http://www.data.gov/health) is one of the data portals that we used. The search function is user friendly. One of the most relevant data for the uninsured comes from Medical Expenditure Panel Survey (MEPS). It has the survey statistics of the cost and utilization of health care and health insurance coverage aggregated at different age-sex levels (http://www.meps.ahrq.gov/mepsweb/data_stats/meps_query.jsp).

You may be thinking how the aggregated data could help in grappling with the challenge of profiling the risks of the uninsured. I think advanced analytics, simulation and modeling in particular, would help quantify timely and economically the uncertainty of healthcare risks of the uninsured by using the readily available survey summary statistics. Also this might be a first step in the absence of availability of detailed data.

Each market is different and has its unique characteristics. An adjustment should be taken into account local demographics and health determinants, and changes of healthcare seeking behaviors once the barriers of access to care are removed.

Local population statistics can be found in the US census data (http://www.census.gov). Health determinants and weights are reported in the county health rankings data (http://www.countyhealthrankings.org/). All of these data sources can ultimately be used to help understanding the risk profiles of the uninsured in the local market.

There must be many other data sources out there, or even other folks trying to address the same issues. I would appreciate any feedback you might have.

Top photo by http://www.flickr.com/photos/hirosheridan / CC-Attribution

tags: Cool Technology, government, health analytics, structured data

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