Real-world treatment modalities, health care resource utilization, and costs among commercially insured patients with newly diagnosed major depressive disorder in the United States.

BACKGROUND: In the United States, major depressive disorder (MDD) is one of the most prevalent mental health disorders. Treatment guidelines for MDD recommend pharmacologic and nonpharmacologic therapies tailored to the patient's disease severity, level of function, and comorbid health conditions. While previous studies examined real-world pharmacologic treatment patterns and costs among patients with MDD, few have examined the use of nonpharmacologic treatments and their association with health care resource utilization (HCRU) and cost. OBJECTIVE: To describe prevalence and associations between patient/provider characteristics and treatment modality and characterize HCRU and cost by treatment modality for patients with newly diagnosed MDD. METHODS: Commercially insured US patients, aged 18-62 years with newly diagnosed MDD between January 1, 2017, and September 30, 2019, were retrospectively identified from the Healthcare Integrated Research Database. Eligible patients were continuously enrolled in the health plan for 1 year before and 2 years after the first MDD diagnosis (index date). Those with co-occurring schizophrenia, bipolar disorder, postpartum depression, substance use disorder, and any prior MDD treatments were excluded. Treatment modalities assessed in the 2-year post-index period included antidepressant only (Rx-only), nonpharmacologic only (non-Rx-only), both antidepressant and nonpharmacologic (combination), and no treatment. HCRU and costs were assessed in the 2-year post-index period by treatment modality. Regression models identified associations between patient/provider characteristics and treatment modality, and the relationship between treatment modality and MDD severity changes. RESULTS: In total, 12,657 patients were included (mean age: 36 years; 60% female). During follow-up, 34% of patients received Rx-only, 25% received non-Rx-only, 28% received combination, and 13% received no treatment. MDD severity at diagnosis (26% mild, 54% moderate, 20% severe) was available for 51% of patients. Post-index inpatient hospitalizations were 11% for those with Rx-only, 10% for non-Rx-only, 16% for combination, and 29% for no treatment, whereas all-cause mean monthly total costs were $792, $633, $786, and $1,292, respectively. In multinomial logistic regression, age, sex, geographic region and urbanicity of patient residence, socioeconomic status, diagnosing provider specialty, and initial diagnosis location were significantly associated (P < 0.05) with treatment modality. In multivariable logistic regression, recipients of Rx-only (odds ratio = 2.03, P < 0.01) or combination (odds ratio = 3.26, P < 0.01) had higher odds of improving MDD severity than patients who received no treatment. CONCLUSIONS: In this real-world sample of commercially insured patients, we observed variations in outcomes by treatment modality and an association between treatment modality and disease severity. Further research is needed to explore the underlying causal relationships between treatment modality and patient outcomes. Study Registration: https://doi.org/10.17605/OSF.IO/YQ6B3 DISCLOSURES: Dr Grabner is an employee of Carelon Research, which received funding from the Innovation and Value Initiative for the conduct of the study on which this manuscript is based. Ms Pizzicato and Mr Yang were employees of Carelon Research at the time the study was conducted. Dr Grabner is a shareholder of Elevance Health. Drs Xie and Chapman are employees of the Innovation and Value Initiative.

Treatment goals for rheumatoid arthritis: patient engagement and goal collection.

Aim: We developed the Patient-Engaged Health Technology Assessment strategy for survey-based goal collection from patients to yield patient-important outcomes suitable for use in multi-criteria decision analysis. Methods: Rheumatoid arthritis patients were recruited from online patient networks for proof-of-concept testing of goal collection and prioritization using a survey. A Project Steering Committee and Expert Panel rated the feasibility of scaling to larger samples. Results: Survey respondents (n = 47) completed the goal collection exercise. Finding effective treatments was rated by respondents as the most important goal, and reducing stiffness was rated as the least important. Feedback from our steering committee and expert panel support the approach's feasibility for goal identification and ranking. Conclusion: Goals relevant for treatment evaluation can be identified and rated for importance by patients to permit wide input from patients with lived experience of disease.

Preferences for Treatments for Major Depressive Disorder: Formative Qualitative Research Using the Patient Experience.

OBJECTIVES: The goals of this formative research are to elicit attributes of treatment and desired outcomes that are important to individuals with major depressive disorder (MDD), to develop a stated preference instrument, and to pre-test the instrument. METHODS: A three-phase survey study design elicited the patient's journey with MDD to design and pre-test the discrete choice experiment (DCE) instrument. Participants were 20 adults aged ≥ 18 with MDD who did not also have bipolar disorder or post-partum depression. We engaged patient advocates and a multi-disciplinary stakeholder advisory group to select and refine attributes for inclusion in a DCE instrument. The DCE was incorporated into a survey that also collected depression treatment and management and sociodemographic characteristics. The DCE was pre-tested with ten adults with MDD. RESULTS: Six attributes were included in the DCE: mode of treatment (medicine only, psychotherapy only, all modalities including brain stimulation), time to treatment effect (6, 9, 12 weeks), days of hopefulness (2, 4, 6 days/week), effect on productivity (40%, 60%, 90% increase), relations with others (strained, improved, no impact), and out-of-pocket costs ($30, $60, $90/month). The DCE test led to the refinement of mode of treatment (medicine, medicine and psychotherapy, and all modalities); time to treatment effect (4, 6, 9 weeks); monthly out-of-pocket costs ($30, $90, $270). CONCLUSIONS: MDD treatment preferences revealed trade-offs among mode of treatment, time to treatment effect, functional outcomes, and cost. The findings demonstrate the potential for meaningfully incorporating the patient experience in preference measures.

Should We Pay for Scientific Knowledge Spillovers? The Underappreciated Value of "Failed" R&D Efforts.

Recent experience with COVID-19 has reminded us of the importance of scientific progress in enabling pharmaceutical innovation. Developing novel therapies is a highly risky but rewarding process: it not only produces innovative drugs, but also valuable scientific knowledge that benefits the community of innovators. This paper examines whether the existing reward system for pharmaceutical research and development (R&D) leads to socially optimal levels of scientific knowledge generation and sharing, with a particular focus on the value of failures in the pharmaceutical R&D efforts. We first outline a conceptual approach based on the idea that pharmaceutical R&D efforts produce both medicines and scientific knowledge, and illustrate this with some examples of how failures may generate information beneficial to concurrent and subsequent R&D efforts. We then summarize the relatively small literature on failures in pharmaceutical R&D and their impact on R&D decision making. Lastly, we discuss several market-based and nonmarket-based policy approaches that can address potential shortcomings in the current reward system which may lead to suboptimal R&D and knowledge sharing.

Putting Stakeholder Engagement at the Center of Health Economic Modeling for Health Technology Assessment in the United States.

While evidence generated from health economic (HE) models is being used more commonly in health technology assessment (HTA) in the US, it is not consistently adopted by different stakeholder groups or across therapeutic areas. We hypothesize that actively engaging with multiple stakeholder groups throughout the model development process may result in models more widely considered by decision makers. To test this hypothesis, the Innovation and Value Initiative has launched a modeling effort to build an open-source HE model focusing on the disease state 'major depressive disorder'. A 20-member advisory group has been formed with representatives from patients, employers, clinicians, innovators, payers, and researchers to guide the model development process. While this effort is still in the early stages, the ongoing stakeholder engagement effort has yielded valuable insights that inform the model design. We have also identified several challenges to implementing this new approach. Our early findings suggest that the stakeholder engagement approach to HE model development has the potential to improve HTA in the US.