Datavant supports transparent research that utilizes real-world data in a privacy preserving manner. Below, we highlight research efforts that have used Datavant technology to link real-world data for the benefit of patients and the public good.
The authors sought to understand the degree of agreement of electronic data research networks as compared to data collected by standardized research approaches in a cohort study. The comparisons were made by linking data from MESA (Multi-Ethnic Study of Atherosclerosis), a community-based cohort, with EHR’s from six Chicago-area hospitals. Ultimately, nearly 70 percent had data in both systems and demonstrated mixed results. For some measurements, such as BMI, the correlations between the MESA and EHR data were quite high. For others, such as systolic blood pressure, the correlation coefficient was only 0.39.
By linking together medical encounter data from a number of different Chicago hospital systems, the authors identified 150,661 patients with diabetes (out of a total of two million patients). Using that information, the study estimated the geographic distribution of undiagnosed diabetic retinopathy and found that low-income and minority areas had a disproportionate rate of undiagnosed diabetic retinopathy. Based on that, a new screening mechanism that is not currently funded by Medicare or Medicaid was suggested.
The study attempted to understand the utilization of emergency departments for preventable conditions at the individual and neighborhood level by linking together emergency department admissions from four Chicago hospitals. By combining the data, the authors showed that individuals in medically underserved areas (MUAs) had a larger chance of emergency department use that could have been prevented.
Using the HealthLNK Data Repository, the authors sought to understand the relationship between hospital utilization and distance from the index hospital for patients with adverse events following an ambulatory endoscopy. Using mortality as the endpoint, the authors found that of the 86 patients (of the 22,898 in the study) who had early mortality, nearly half did not return to the index hospital. In total, there was a statistically significant relationship between a patient’s utilization of their index hospital and their proximity.