Overview	People	Research	Course	Publications	Resources	Links
	Research Projects Mental Health Informatics Enabling Psychiatrists Access to Knowledge Resources (Funded By NIH/NLM. PI: Vimla L. Patel) The core aims of this NLM systems grant include presenting mental health professionals with access to guidelines and other resources in real time at point of care and adapting the Infobuttons information resource delivery system to the field of mental health with a particular focus in the specific area of pharmacology. Infobuttons work by creating links within the application that passes the clinician’s context to an application that matches the context to an information need, selects a resource for that need, formulates a query to that resource, passing the query to the resource, and displaying the results to the clinician. The query initiates an action on a web-based resource (for example, a request for a specific file, a posting to a common gateway interface (CGI) program). The result of the action is to open a browser window on the clinician’s desktop with the requested information. The Psychiatric Clinical Knowledge Enhancement System (PSYCKES) is a web-based patient medication history information and clinical decision support system designed by the Dr. Thomas White at the New York State Office of Mental Health (OMH) to improve compliance with psychiatric evidence based practices, improve quality of care, and reduce the cost of pharmacotherapy. PSYCKES provides numerous custom reports and timeline graphs for clinicians to review the patient’s medication history over variable lengths of time. We have developed a fully integrated PSYCKES-Infobuttons system towards achieving these specific aims. In the past year, we have greatly benefited from the fact that OMH has rolled out PSYCKES statewide to all of its institutions. Research Team: David Kaufman, Alla Keselman, Thomas White, Gerald Segal, Molly Finnerty, Amy Bennett Staub and Vimla Patel). Cognitive Aspects of Mental Disorder Diagnosis and Treatment in Primary Care (Funding Pending. PI: Vimla L. Patel, Columbia University) Depression and anxiety disorders are highly prevalent and often profoundly impairing. In low-income communities, primary care physicians (PCPs) are often the only source of care for these disorders, yet PCPs often under-diagnose and ineffectively manage them. Moreover, little is known about PCPs’ decision-making processes for mental disorders. This is a new and important focus for services research, driven by the overarching goal of finding more effective ways to deliver psychiatric care in PC. Although there has been considerable work on depression and anxiety disorders in PC, little of this work has directly examined the nature of PCPs’ decision making for these disorders. We propose to apply a cognitive framework to understand the nature of PCPs’ decision-making in diagnosing and treating major depression (MDD) and post-traumatic stress disorder (PTSD), to provide an in-depth characterization of PCPs’ knowledge of these disorders and reasoning strategies and relate these processes to quality of care to identify factors that promote or hinder accurate decisions. We will focus on cognition in the context of socio-cultural and environmental factors that affect service delivery to Hispanics. We will use simulated patients, and combine qualitative and quantitative data collection and analysis. The primary aims of this application are (1) to conduct an ethnographic investigation of the socio-cultural, organizational and environmental factors that affect management of MDD and PTSD in an urban outpatient PC practice; (2) to characterize how the process of doctor-patient interaction during the clinical interview affects PCPs’ diagnostic decisions about MDD and PTSD (compared to decision-making about a chronic medical disorder), focusing on the impact of cognitive (clinical expertise, decisions), socio-cultural, and environmental factors and identifying sources of inaccuracy; and (3) to analyze how PCPs’ diagnostic and management decisions for MDD and PTSD emerge and develop throughout the complete patient workup, focusing on how PCPs’ knowledge of MDD and PTSD affects their ability to integrate information from various stages of the workup. This research will provide a foundation for the development of education and training programs and guidelines for PCPs on how to effectively diagnose and manage MDD and PTSD, taking into account socio-cultural differences, in an effort to reduce disparities in the delivery of mental health care. Research Team: Vimla Patel,Trevor Cohen, Nicole Yoskowitz, Alla Keselman, Rafael Lantigua, Mark Olfson, Yuval Neria, Randall Marshall, and Larry Amsel Cognition and Computer Comprehension of Dangerous Discourse (Funded By NIH/NLM. PI: Vimla L. Patel) Psychiatric discharge summary content covers a broad conceptual territory: in addition to concepts derived from clinical psychiatry and general medicine, these documents contain concepts drawn from the world at large. These concepts are particularly relevant to the assessment of dangerousness of psychiatric patients, an essential component of clinical decision making in emergency psychiatry. Human beings have many means by which to endanger themselves and others. The task of manually defining each real-world concept required to meaningfully interpret dangerousness contained in these documents is daunting. Latent semantic analysis is an unsupervised corpus-based statistical method that automatically derives quantitative estimates of the similarity between words and documents from free text documents. This research aims to determine if the similarity measures derived by LSA are meaningful in relation to discourse on dangerousness, as well as the extent to which such knowledge structures can be used to categorize documents according to their dangerousness using simulated cognitive models of human categorization informed by studies of expert clinical comprehension. Research Team: Trevor Cohen, Brett Blatter and Vimla L. Patel