This application seeks continued support for a team of statisticians, economists, and clinicians to collaborate on the development and application of longitudinal hierarchical discrete choice models for understanding diffusion of mental health technologies and for causal inference. By developing better statistical models for understanding the dynamics of treatment adoption, or innovation, and of treatment rejection, or exnovation, researchers will gain greater insight into longitudinal patterns of usual care treatments.
In Specific Aim 1 we will extend likelihood-based approaches to accommodate a flexible family of dynamic discrete choice diffusion models. This will permit the study of the effects of patient, provider, product, and market characteristics on technology adoption or rejection.
Specific Aim 2 will extend Aim 1 to include geographic variation in the diffusion of mental health treatment technologies. This will permit estimation of geographic specific diffusion effects.
In Specific Aim 3 we will extend Aim 1 to study the causal effect of patient, provider, product, or market characteristics on diffusion. This involves the use of estimators that unconfound covariate effects while accounting for within- and between-patient, provider, product, and market variation, thereby permitting unbiased inferences. We will apply these methods to cohorts of patients with depression, bipolar affective disorder, and schizophrenia using multiple sources of data. An Advisory Board comprised of leaders in statistics, economics, and psychiatry will convene annually to validate methods and ensure integration of techniques into mental health services research. The methodological advances from this research will enable researchers, policy makers, and methodologists to better characterize factors impacting technology innovation/exnovation and to expand the inferences for usual care.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH061434-05
Application #
7121646
Study Section
Special Emphasis Panel (ZMH1-DEA-Z (03))
Program Officer
Rupp, Agnes
Project Start
2001-02-01
Project End
2008-07-31
Budget Start
2006-08-01
Budget End
2007-07-31
Support Year
5
Fiscal Year
2006
Total Cost
$518,692
Indirect Cost
Name
Harvard University
Department
Administration
Type
Schools of Medicine
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
02115
Busch, Alisa B; Neelon, Brian; Zelevinsky, Katya et al. (2012) Accurately predicting bipolar disorder mood outcomes: implications for the use of electronic databases. Med Care 50:311-9
O'Malley, A James; Frank, R G; Normand, S-L T (2011) Estimating cost-offsets of new medications: use of new antipsychotics and mental health costs for schizophrenia. Stat Med 30:1971-88
Teixeira-Pinto, Armando; Normand, Sharon-Lise (2011) MISSING DATA IN REGRESSION MODELS FOR NON-COMMENSURATE MULTIPLE OUTCOMES. Revstat Stat J 9:37-55
Neelon, Brian; O'Malley, A James; Normand, Sharon-Lise T (2011) A bayesian two-part latent class model for longitudinal medical expenditure data: assessing the impact of mental health and substance abuse parity. Biometrics 67:280-9
Fullerton, Catherine A; Busch, Alisa B; Frank, Richard G (2010) The rise and fall of gabapentin for bipolar disorder: a case study on off-label pharmaceutical diffusion. Med Care 48:372-9
Neelon, Brian H; O'Malley, A James; Normand, Sharon-Lise T (2010) A Bayesian model for repeated measures zero-inflated count data with application to outpatient psychiatric service use. Stat Modelling 10:421-439
Teixeira-Pinto, Armando; Normand, Sharon-Lise T (2009) Correlated bivariate continuous and binary outcomes: issues and applications. Stat Med 28:1753-73
Busch, Alisa B; Frank, Richard G; Sachs, Gary et al. (2009) Bipolar-I patient characteristics associated with differences in antimanic medication prescribing. Psychopharmacol Bull 42:35-49
Huskamp, Haiden A; Busch, Alisa B; Domino, Marisa E et al. (2009) Antidepressant reformulations: who uses them, and what are the benefits? Health Aff (Millwood) 28:734-45
Busch, Alisa B; Huskamp, Haiden A; Neelon, Brian et al. (2009) Longitudinal racial/ethnic disparities in antimanic medication use in bipolar-I disorder. Med Care 47:1217-28

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