Major Depressive Disorder
Longitudinal, multi-source, curated registries, offering rapid access to deep clinical data, insights and outcomes in MDD.
Research-Grade RWD in MDD
Unmet Need
Major Depressive Disorder can take a staggering toll on an individual physically, socially and financially, while care providers are overwhelmed with the sheer amount of patients.
5.9 million+*
MDD patients in the OM1™ Real-World Data Cloud with linked claims
575,000+*
MDD patients with deep clinical data, including clinical notes from mental health specialists
*Counts complete through Q2 2024
eBook
In this eBook, we present mental health research, models, and insights using our data and tools.
Webinar
Posters & Publications on Depression
- Poster (1st place winner): Alves P, Gerber J, Spencer A, Bandaria J, Leavy M, Weiss S, Curhan G, Marci C, Paulus J, Boussios C. Lessons Learned from the Development of Machine Learning Models to Estimate Validated Measures of Disease Activity and Symptom Severity Using Real-World Data for Four Chronic Conditions. ICPE, August 23-27, 2023.
- Poster: Semeniuta D, Marci CD, Bandaria J, Zabinski JW, Paulus JK, Boussios C. Identification of Treatment Resistant Major Depressive Disorder using a Machine Learning Algorithm. ICPE, August 2023.
- Poster: Gerber J, Marci CD, Leavy M, Alves P, Boussios C. Development of a Machine Learning Model for Estimating PHQ-9 Scores Using Clinical Notes from Real-World Data Sources. American Society of Clinical Psychopharmacology, May 2023.
- Poster: Nelson J, Hoffman V, Marci CD, Paulus JK. The Association Between Credit Risk Score and Major Depressive Disorder Burden Using a Machine Learning Estimation of the PHQ-9 in a Real-World Cohort. ICPE, August 23-27, 2023.
- Poster: Paulus J, Severtson G, Qian X, Kumparatana P, Hoffman V, Su Z, Marci CD. The Association Between Race, Social Determinants of Health, and Treatment for Major Depressive Disorder (MDD) in a Real-World Cohort. ICPE, August 24-28, 2022.
- Poster: Palmon N, Alves P, Momen S, Leavy M, Curhan G, Boussios C, Jones C, Gliklich R. Use of a Natural Language Processing-Based Approach to Extract Depression Symptom Severity and Suicide Ideation from Clinical Notes to Support Depression Research, ICPE 2021 Virtual Meeting, August 2021.
- Peer-Reviewed Journal: Gliklich RE, Leavy MB, Cosgrove L, Simon GE, Gaynes BN, Peterson LE, Olin B, Cole C, DePaulo JR Jr, Wang P, Crowe CM, Cusin C, Nix M, Berliner E, Trivedi MH. Harmonized Outcome Measures for Use in Depression Patient Registries and Clinical Practice. Annals of Internal Medicine. 2020;172(12): 803-809. DOI:10.7326/M19-3818
- Poster: Leavy, M, Clarke D, Gibson D, Hajjar S, Berliner E. Evaluating the Feasibility of Capturing a Core Set of Harmonized Depression Outcome Measures in Primary Care and Mental Health Patient Registries. SGIM Conference, June 2020.
- Poster: Mortimer K, Behling M, Swenson A, Li F, Brecht T, Strubel B, Cerf S, Lafontant A, Gliklich R. Depression and Patient Outcomes Among Rheumatoid Arthritis Patients in a Large US-Based Real World Cohort. ISPOR Annual Conference. New Orleans, LA. May 2019.
Award-Winning Research Team
Our team of award-winning researchers have authored hundreds of publications, including scientific posters, articles in peer-reviewed journals, white papers, and books.