@article {516436,
	title = {Accurately predicting bipolar disorder mood outcomes: implications for the use of electronic databases},
	journal = {Med Care},
	volume = {50},
	number = {4},
	year = {2012},
	month = {2012 Apr},
	pages = {311-9},
	abstract = {BACKGROUND: Monitoring mental health treatment outcomes for populations requires an understanding as to which patient information is needed in electronic format and is feasible to obtain in routine care.

OBJECTIVE: To examine whether bipolar disorder outcomes can be accurately predicted and how much clinical detail is needed to do so. RESEARCH DESIGN, DATA SOURCES, AND PARTICIPANTS: Longitudinal study of bipolar disorder patients treated during 2000 to 2004 in the 19-site Systematic Treatment Enhancement Program for Bipolar Disorder observational study arm (N=3168). Clinical data were obtained at baseline and quarterly for over 1 year. We fit a "gold standard" longitudinal random-effects regression model using a detailed clinical information and estimated the area under the receiver operating characteristic curve (AUC) to predict accuracy using a validation sample. The model was then modified to include patient characteristics feasible in routinely collected electronic data (eg, administrative data). We compared the AUCs for the "limited-detail" and gold standard models, testing for differences between the AUCs using the validation sample.

MEASURE: Remission, defined as Montgomery-Asberg Depression Rating Scale score ,
	keywords = {Adolescent, Adult, Bipolar Disorder, Electronic Health Records, Female, Humans, Longitudinal Studies, Male, Middle Aged, Models, Psychological, Models, Statistical, Outcome Assessment (Health Care), Psychiatric Status Rating Scales, Remission Induction, Young Adult},
	issn = {1537-1948},
	doi = {10.1097/MLR.0b013e3182422aec},
	author = {Alisa B. Busch and Neelon, Brian and Zelevinsky, Katya and Yulei He and Normand, Sharon-Lise T.}
}
