Search all AHRQ sites
Menu
SHARE:
AHRQ Research Studies
Sign up: 
AHRQ Research Studies Email updates
Research Studies is a monthly compilation of research articles funded by AHRQ or authored by AHRQ researchers and recently published in journals or newsletters.
Results
1 to 2 of 2 Research Studies Displayed
Yoon S, Taha B, Bakken S
Using a data mining approach to discover behavior correlates of chronic disease: a case study of depression.
The purposes of this methodological paper are: 1) to describe data mining methods for building a classification model for a chronic disease using a U.S. behavior risk factor data set, and 2) to illustrate application of the methods using a case study of depressive disorder. Its application of data mining strategies identified childhood experience living with mentally ill and sexual abuse, and limited usual activity as the strongest correlates of depression among hundreds of variables.
AHRQ-funded; HS019853; HS022961.
Citation:
Yoon S, Taha B, Bakken S .
Using a data mining approach to discover behavior correlates of chronic disease: a case study of depression.
Stud Health Technol Inform 2014;201:71-8..
Keywords:
Chronic Conditions, Behavioral Health, Depression, Health Information Technology (HIT), Electronic Health Records (EHRs)
Lawrence JM, Black MH, Zhang JL
Validation of pediatric diabetes case identification approaches for diagnosed cases by using information in the electronic health records of a large integrated managed health care organization.
The researchers explored the utility of different algorithms for diabetes case identification by using electronic health records. They found that case identification accuracy was highest in 75% of bootstrapped samples for those who had 1 or more outpatient diabetes diagnoses or 1 or more insulin prescriptions and in 25% of samples for those who had 2 or more outpatient diabetes diagnoses and 1 or more antidiabetic medications.
AHRQ-funded; HS019859.
Citation:
Lawrence JM, Black MH, Zhang JL .
Validation of pediatric diabetes case identification approaches for diagnosed cases by using information in the electronic health records of a large integrated managed health care organization.
Am J Epidemiol 2014 Jan;179(1):27-38. doi: 10.1093/aje/kwt230..
Keywords:
Children/Adolescents, Diabetes, Chronic Conditions, Electronic Health Records (EHRs), Health Information Technology (HIT), Diagnostic Safety and Quality
