Research: SIM Models Enhance Health Data Accuracy

University of Delaware

First-of-its-kind research by Tarang Parekh, assistant professor of epidemiology, reviewed the State Innovation Models (SIM), a payment system introduced by the Centers for Medicare and Medicaid Services in 2013, which provides financial incentives to states to develop innovative payment models to improve healthcare systems.

In the study, recently published in the American Journal of Epidemiology, Parekh compared data from 2010 to 2015 from three SIM participating states, Arkansas, Massachusetts and Vermont, to Florida, Nebraska and New Mexico, which do not participate in SIM. He studied the effects of capturing social risk factors in adults hospitalized with atherosclerotic cardiovascular disease (ASCVD).

His research identified small but statistically significant improvements in capturing social determinants of health using Internal Classification of Diseases (ICD) codes, particularly among Medicare enrollees with ASCVD. This is important to improving health outcomes because while clinical care is important, more than 80% of the factors associated with being healthy are from social determinants of health like housing, education and the environment. To more effectively address these factors, improvements are needed in how they are quantified through systems like this that capture social risk factors more broadly.

"Currently, we try to address social determinants of health, but we are focused on very selective populations and regions, and different systems are asking about topics like food insecurity in different ways, so the severity of the social determinant is unclear," said Parekh. "A standardized collection method using ICD codes to capture social determinants of health will help us better understand the population we need to target. We'll also learn whether a specific condition is more heavily influenced by social determinants of health, allowing us to target those factors more effectively."

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