This Intervention and Practice Research Infrastructure Support Program (IP-RISP) application seeks funding to support conceptual, methodological, and organizational development to foster depression intervention research among primary care patients with chronic medical illness. The proposed development activities shaped by past and ongoing work will allow investigators to advance knowledge of depression among medically ill patients by using new concepts, measurement and statistical tools and by creating information systems integrated at the patient level. IP RISP funding would allow us to continue development of important goals that we have pursued since 1995 and represent unique strengths of this application. We have made important progress in the following four areas that are relevant to this application: 1) Integration of mental health research activities into the clinical management and strategic planning activities of HPHC; 2) design of innovative interventions to deliver mental health services to primary care populations at high risk of depression; 3) development of applications of new statistical theory for outcomes assessment and quality measurement; 4) access to a large clinical population in a network model of care enabling us to conduct research in real-world settings. The goal of infrastructure building will be accomplished through the following specific activities. 1. We will develop an information technology enabled disease management system for depression (ITEMSD) occurring in medically ill patients in primary care settings that will include a system for reporting and alerting disease managers about potential gaps in care; a disease manager guideline and documentation system that suggests actions to be pursued; a system for the disease manager to communicate patient assessments, alerts and actions taken to other staff and providers. Consumer preferences will be incorporated into the design of ITEMS-D through use of standard qualitative methods. 2. The team will train disease managers in the principles of Social Learning Theory (SLT) that serves as the theoretical foundation of ITEMS-D, particularly its self-efficacy construct. 3. The research team will work with the HPHC Chief Information Officer and the technology vendor, Perot Systems to design the ITEMS-D database so that it will be easily integrated into all of HPHC's patient-level information systems facilitating rapid access to patient data. 4. Infrastructure development will be used to leverage ITEMS-D to conduct pilot studies related to infrastructure development and the development of RO1, R21 and other grant applications. The experience and talents of the research team working in partnership with HPHC's clinical leadership will allow us to continue building capacity to develop depression intervention research in medically ill populations. We expect that development of ITEMS-D would address the needs of health care delivery systems and serve as the platform for launching future interventions beginning with medically ill populations but extending to other high-risk groups at high risk for depression and other common mental disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Resource-Related Research Projects (R24)
Project #
1R24MH067822-01A2
Application #
6827097
Study Section
Special Emphasis Panel (ZMH1-CRB-M (02))
Program Officer
Chambers, David A
Project Start
2004-09-01
Project End
2009-05-31
Budget Start
2004-09-01
Budget End
2005-05-31
Support Year
1
Fiscal Year
2004
Total Cost
$505,285
Indirect Cost
Name
Harvard Pilgrim Health Care, Inc.
Department
Type
DUNS #
071721088
City
Boston
State
MA
Country
United States
Zip Code
02215
Tisminetzky, Mayra; Bray, Bethany C; Miozzo, Ruben et al. (2012) Classes of depression, anxiety, and functioning in acute coronary syndrome patients. Am J Health Behav 36:20-30
Tisminetzky, Mayra; Bray, Bethany C; Miozzo, Ruben et al. (2011) Identifying symptom profiles of depression and anxiety in patients with an acute coronary syndrome using latent class and latent transition analysis. Int J Psychiatry Med 42:195-210