A Canadian Simulation Model for Major Depressive Disorder: Study Protocol.

BACKGROUND: Major depressive disorder (MDD) is a common, often recurrent condition and a significant driver of healthcare costs. People with MDD often receive pharmacological therapy as the first-line treatment, but the majority of people require more than one medication trial to find one that relieves symptoms without causing intolerable side effects. There is an acute need for more effective interventions to improve patients' remission and quality of life and reduce the condition's economic burden on the healthcare system. Pharmacogenomic (PGx) testing could deliver these objectives, using genomic information to guide prescribing decisions. With an already complex and multifaceted care pathway for MDD, future evaluations of new treatment options require a flexible analytic infrastructure encompassing the entire care pathway. Individual-level simulation models are ideally suited for this purpose. We sought to develop an economic simulation model to assess the effectiveness and cost effectiveness of PGx testing for individuals with major depression. Additionally, the model serves as an analytic infrastructure, simulating the entire patient pathway for those with MDD. METHODS AND ANALYSIS: Key stakeholders, including patient partners, clinical experts, researchers, and modelers, designed and developed a discrete-time microsimulation model of the clinical pathways of adults with MDD in British Columbia (BC), including all publicly-funded treatment options and multiple treatment steps. The Simulation Model of Major Depression (SiMMDep) was coded with a modular approach to enhance flexibility. The model was populated using multiple original data analyses conducted with BC administrative data, a systematic review, and an expert panel. The model accommodates newly diagnosed and prevalent adult patients with MDD in BC, with and without PGx-guided treatment. SiMMDep comprises over 1500 parameters in eight modules: entry cohort, demographics, disease progression, treatment, adverse events, hospitalization, costs and quality-adjusted life-years (payoff), and mortality. The model predicts health outcomes and estimates costs from a health system perspective. In addition, the model can incorporate interactive decision nodes to address different implementation strategies for PGx testing (or other interventions) along the clinical pathway. We conducted various forms of model validation (face, internal, and cross-validity) to ensure the correct functioning and expected results of SiMMDep. CONCLUSION: SiMMDep is Canada's first medication-specific, discrete-time microsimulation model for the treatment of MDD. With patient partner collaboration guiding its development, it incorporates realistic care journeys. SiMMDep synthesizes existing information and incorporates provincially-specific data to predict the benefits and costs associated with PGx testing. These predictions estimate the effectiveness, cost-effectiveness, resource utilization, and health gains of PGx testing compared with the current standard of care. However, the flexible analytic infrastructure can be adapted to support other policy questions and facilitate the rapid synthesis of new data for a broader search for efficiency improvements in the clinical field of depression.

Cost-effectiveness of pharmacogenomic-guided treatment for major depression.

BACKGROUND: Pharmacogenomic testing to identify variations in genes that influence metabolism of antidepressant medications can enhance efficacy and reduce adverse effects of pharmacotherapy for major depressive disorder. We sought to establish the cost-effectiveness of implementing pharmacogenomic testing to guide prescription of antidepressants. METHODS: We developed a discrete-time microsimulation model of care pathways for major depressive disorder in British Columbia, Canada, to evaluate the effectiveness and cost-effectiveness of pharmacogenomic testing from the public payer's perspective over 20 years. The model included unique patient characteristics (e.g., metabolizer phenotypes) and used estimates derived from systematic reviews, analyses of administrative data (2015-2020) and expert judgment. We estimated incremental costs, life-years and quality-adjusted life-years (QALYs) for a representative cohort of patients with major depressive disorder in BC. RESULTS: Pharmacogenomic testing, if implemented in BC for adult patients with moderate-severe major depressive disorder, was predicted to save the health system $956 million ($4926 per patient) and bring health gains of 0.064 life-years and 0.381 QALYs per patient (12 436 life-years and 74 023 QALYs overall over 20 yr). These savings were mainly driven by slowing or avoiding the transition to refractory (treatment-resistant) depression. Pharmacogenomic-guided care was associated with 37% fewer patients with refractory depression over 20 years. Sensitivity analyses estimated that costs of pharmacogenomic testing would be offset within about 2 years of implementation. INTERPRETATION: Pharmacogenomic testing to guide antidepressant use was estimated to yield population health gains while substantially reducing health system costs. These findings suggest that pharmacogenomic testing offers health systems an opportunity for a major value-promoting investment.

Pharmacogenomic Testing for Major Depression: A Qualitative Study of the Perceptions of People with Lived Experience and Professional Stakeholders.

OBJECTIVES: With increasing evidence for the clinical utility of pharmacogenomic (PGx) testing for depression, there is a growing need to consider issues related to the clinical implementation of this testing. The perspectives of key stakeholders (both people with lived experience [PWLE] and providers) are critical, but not frequently explored. The purpose of this study was to understand how PWLE and healthcare providers/policy experts (P/HCPs) perceive PGx testing for depression, to inform the consideration of clinical implementation within the healthcare system in British Columbia (BC), Canada. METHODS: We recruited two cohorts of participants to complete individual 1-h, semi-structured interviews: (a) PWLE, recruited from patient and research engagement networks and organizations and (b) P/HCPs, recruited via targeted invitation. Interviews were audiotaped, transcribed verbatim, de-identified, and analysed using interpretive description. RESULTS: Seventeen interviews were completed with PWLE (7 with experience of PGx testing for depression; 10 without); 15 interviews were completed with P/HCPs (family physicians, psychiatrists, nurses, pharmacists, genetic counsellors, medical geneticists, lab technologists, program directors, and insurers). Visual models of PWLE's and P/HCP's perceptions of and attitudes towards PGx testing were developed separately, but both were heavily influenced by participants' prior professional and/or personal experiences with depression and/or PGx testing. Both groups expressed a need for evidence and numerous considerations for the implementation of PGx testing in BC, including the requirement for conclusive economic analyses, patient and provider education, technological and clinical support, local testing facilities, and measures to ensure equitable access to testing. CONCLUSIONS: While hopeful about the potential for therapeutic benefit from PGx testing, PWLE and P/HCPs see the need for robust evidence of utility, and BC-wide infrastructure and policies to ensure equitable and effective access to PGx testing. Further research into the accessibility, effectiveness, and cost-effectiveness of various implementation strategies is needed to inform PGx testing use in BC.

Collaborating with Patient Partners to Model Clinical Care Pathways in Major Depressive Disorder: The Benefits of Mixing Evidence and Lived Experience.

BACKGROUND: Partnering with patients can enrich the design and development of models of clinical care pathways, yet the practice is not commonplace. Guidelines or "best practices" for patient involvement in modeling are scarce. OBJECTIVES: In this paper, we outline the steps we took to form an effective partnership with patients to design a robust microsimulation Markov model of major depressive disorder care pathways in British Columbia, Canada, with the aim of encouraging other teams to partner with patients in healthcare modeling endeavors. METHODS: We describe three unique phases of our collaborative process: uncertainty, mapping, and structured collaboration. We then explore the unique contributions the patient partners made, not only to the model itself, but to our process. Key perspectives are shared from both the modeler and the patient partners in their own words. RESULTS: The patient partners made distinct contributions by challenging and verifying modeling assumptions, noting limitations of the model, and suggesting areas for future research. Both the patient partners and the modelers saw great value in the partnership and agreed that the model was strengthened by the diversity of the team. CONCLUSIONS: We present our learning and key recommendations for future modeling teams in the absence of tested frameworks. We encourage more widespread adoption of patient involvement in modeling and the development of guidelines for such work to increase the democracy of scientific decision making.