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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 2 of 2 Research Studies DisplayedNarindrarangkura P, Alafaireet PE, Khan U
Association rule mining of real-world data: uncovering links between race, glycemic control, lipid profiles, and suicide attempts in individuals with diabetes.
The objective of this study was to use the association rule mining (ARM) technique to identify a high-risk group of suicide attempts among patients with diabetes. Cerner Real-World Data™ was mined using this technique. The study results indicated that patients with diabetes who were never married and had average blood glucose levels below 150 mg/dl were more likely to attempt suicide, while patients aged 60 and older who had diabetes for less than five years were less likely to attempt suicide. The authors concluded that ARM showed the potential for knowledge discovery in large multi-center electronic health records data, and the results could be used by providers during outpatient clinic visits.
Citation: Narindrarangkura P, Alafaireet PE, Khan U .
Association rule mining of real-world data: uncovering links between race, glycemic control, lipid profiles, and suicide attempts in individuals with diabetes.
Inform Med Unlocked 2023; 42. doi: 10.1016/j.imu.2023.101345..
Keywords: Diabetes, Behavioral Health, Risk
Narindrarangkura P, Alafaireet PE, Khan U
Predicting suicide attempts among people with diabetes using a large multicenter electronic health records dataset.
This study’s goal was to determine the risk factors for suicidal behaviors of people with diabetes as they have a higher risk than the general population. The authors investigated risk factors and predicted suicide attempts in people with diabetes using the Least Absolute Shrinkage and Selection Operator (LASSO) regression. They used data from Cerner Real-World Data™ and included over 3 million diabetes patients in the study. They analyzed gender-, diabetes-type, and depression-specific LASSO regression models. The study included 7764 subjects diagnosed with suicide attempts with an average age of 45. They found risk factors for suicide attempts in diabetes patients, such as being an American Indian or Alaska Native, atypical agents, benzodiazepines, and antihistamines. Amyotrophy had a negative coefficient for suicide attempts with males with diabetes but had a positive coefficient for females. Using MAOI had a negative coefficient for suicide attempts in T1DM patients. Patients less than 20 years of age had a positive coefficient for suicide in depressed and non-depressed patients with diabetes.
AHRQ-funded; HS028032.
Citation: Narindrarangkura P, Alafaireet PE, Khan U .
Predicting suicide attempts among people with diabetes using a large multicenter electronic health records dataset.
Int J Psychiatry Med 2023 Jul; 58(4):302-24. doi: 10.1177/00912174231162477..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Behavioral Health, Diabetes, Chronic Conditions