Efficacy Study of a Computer Decision Support System to Treat Depression (CDSS-D)

A Pilot Efficacy Trial of a Computer Decision Support System Compared to Usual Care for Depression Treatment in Primary Care

The purpose of this study was designed to test the feasibility and effectiveness of implementing a Computerized Decision Support System for depression (CDSS-D) during acute care in a primary care setting.

The research project was designed to test the feasibility and effectiveness of implementing a Computerized Decision Support System for depression (CDSS-D) during acute care in a primary care setting. The basic experimental design was a two-group, two-site study design. Three different clinics with a total of 4 primary care physicians agreed and provided informed consent and participated in the study. Half of the physicians used the CDSS-D to treat patients with MDD and the other half provided Usual Care (UC) treatment. The intervention, CDSS-D, incorporated a pre-existing depression treatment algorithm (Texas Medication Algorithm Project for Depression, Trivedi et al) with computer decision support programming, providing the treatment group physicians with a computerized algorithm.

Computer Decision Support System for Depression (CDSS-D) - This arm provided physicians with a computerized treatment algorithm and a decision support system to treat their patients suffering Major Depressive Disorder

Usual Care (UC) - This group of physicians treated their patients suffering from Major Depressive Disorder with their standard treatment as usual, and received no algorithm support with regard to treatment decisions

The CDSS for depression was based on an up-to-date model of the Texas Medication Algorithm Project that employs the principles of Measurement Based Care (MBC), while at the same time having a user interface for providers that is easy-to-use. MBC is the systematic use of measuring clinical outcomes at routine visits to guide treatment management. These outcomes may include symptoms, side effects, and medication adherence. Recent efforts from the large, multi-site effectiveness study, Sequenced Treatment Alternatives to Relieve Depression (STAR*D), show that a treatment plan guided by MBC is integral in implementing algorithm based care.

Usual Care was up to the discretion of the study physician and the patient treated. These physicians were provided with up-to-date treatment protocols for depression, but were not instructed to strictly adhere to a treatment algorithm. Therefore, they treated depressed patients as they "usually" would.

Mean change from baseline on the 16-item Quick Inventory of Depressive Symptomatology - Self Report (QIDS-SR-16)

Mean change from baseline on the 30-item Inventory of Depressive Symptomatology - Clinician's version (IDS-C-30)

Inclusion Criteria: Outpatients aged 18 and over Met Criteria for Non-Psychotic Major Depressive Disorder Had a baseline HRSD-17 score of at least 14 Exclusion Criteria: Patients with a current Axis I diagnosis of somatization disorder, anorexia nervosa, bulimia, or obsessive-compulsive disorder Patients with current alcohol or substance dependence Women with a positive pregnancy test or who are lactating Women of child-bearing potential who are not practicing a clinically accepted method of contraception Patients with general medical conditions that contraindicate antidepressant medications Patient whose clinical status requires inpatient or day hospital treatment

Kurian BT, Trivedi MH, Grannemann BD, Claassen CA, Daly EJ, Sunderajan P. A computerized decision support system for depression in primary care. Prim Care Companion J Clin Psychiatry. 2009;11(4):140-6. doi: 10.4088/PCC.08m00687.