Assessing Physicians' Use of Treatment Algorithms: Project IMPACTS Study Design and Rationale

Abstract

Effective treatments for major depressive disorder have been available for 35 years, yet inadequate pharmacotherapy continues to be widespread leading to suboptimal outcomes. Evidence-based medication algorithms have the potential to bring much-needed improvement in effectiveness of antidepressant treatment in "real-world" clinical settings. Project IMPACTS (Implementation of Algorithms using Computerized Treatment Systems) addresses the critical question of how best to facilitate integration of depression treatment algorithms into routine care. It tests an algorithm implemented through a computerized decision support system using a measurement-based care approach for depression against a paper-and-pencil version of the same algorithm and non-algorithm-based, specialist-delivered usual care. This paper reviews issues related to the Project IMPACTS study rationale, design, and procedures. Patient outcomes include symptom severity, social and work function, and quality of life. The economic impact of treatment is assessed in terms of health care utilization and cost. Data collected on physician behavior include degree of adherence to guidelines and physician attitudes about the perceived utility, ease of use, and self-reported effect of the use of algorithms on workload. Novel features of the design include a two-tiered study enrollment procedure, which initially enroll physicians as subjects, and then following recruitment of physicians, enrollment of subjects takes place based initially on an independent assessment by study staff to determine study eligibility. The study utilizes brief, easy-to-use symptom severity measures that facilitate physician decision making, and it employs a validated, phone-based, follow-up assessment protocol in order to minimize missing data, a problem common in public sector and longitudinal mental health studies. IMPACTS will assess the success of algorithm implementation and subsequent physician adherence using study-developed criteria and related statistical approaches. These new procedures and data points will also allow a more refined assessment of algorithm-driven treatment in the future.

Evaluation of anhedonia with the Snaith–Hamilton Pleasure Scale (SHAPS) in adult outpatients with major depressive disorder

“…The current study replicated our previous study (Nakonezny et al, 2010), which evaluated the psychometric properties of the original (English) version of the SHAPS , in the context of using a sample of adult outpatients who were (on average at study exit) less depressed than the sample of adult outpatients used in the Nakonezny et al (2010) study (sample obtained from Project IMPACTS; Trivedi et al, 2007).…”

“…The purpose of the current study was to replicate our previous study (Nakonezny et al, 2010), which evaluated the psychometric properties of the original (English) version of the SHAPS , in the context of using a sample of adult outpatients who were (on average at study exit) less depressed than the sample of adult outpatients used in the Nakonezny et al (2010) study (sample obtained from Project IMPACTS; Trivedi et al, 2007). As in our previous study (Nakonezny et al, 2010), we used classical test theory analysis to examine the internal consistency, scale dimensionality, and convergent and discriminant validity of the SHAPS.…”

A Computerized Decision Support System for Depression in Primary Care

“…We have extensive experience in training and monitoring adherence and fidelity to algorithm implementation through our ongoing R01 MH-164062-01A1 grant for examining the efficacy of the implementation of a computerized algorithm in tertiary care psychiatric outpatient clinics compared to a paper-and-pencil algorithm. 26 …”

Measurement-based care for refractory depression: A clinical decision support model for clinical research and practice

“…In terms of feasibility in real-world clinical settings, we are currently comparing the effectiveness and feasibility of a computerized depression algorithm compared to the paperand-pencil format and usual care in an ongoing, large, multisite NIMH-funded study (5R01MH064062-2 (Computerized Decision Support System for Depression) in public mental health tertiary care settings (Trivedi et al, 2007). This study will examine the effect of the CDSS-D on physician adherence to the algorithm, as well as on patient outcomes compared to the paper-and-pencil format and usual care.…”

“…Previous attempts to implement guidelines for MDD using a paper-and-pencil format in clinical settings (Trivedi et al, 2004b;Trivedi et al, 2006c;Trivedi et al, 2007) have revealed problems with fidelity in terms of dosing, adequate duration of treatment, and visit frequency. One possible solution to this problem is to couple guidelines with a measurement-based, computerized approach (Hunt et al, 1998;Trivedi et al, 2000;Trivedi et al, 2001;Trivedi et al, 2002;Trivedi et al, 2004a).…”