The Economic Burden of Posttraumatic Stress Disorder in the United States From a Societal Perspective

Davis, Lori L.; Schein, Jeff; Cloutier, Martin; Gagnon-Sanschagrin, Patrick; Maitland, Jessica; Urganus, Annette; Guérin, Annie; Lefèbvre, Patrick; Houle, Christy R.

doi:10.4088/jcp.21m14116

Cited by 87 publications

(72 citation statements)

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“…The psychosocial impact of PTSD on patients is substantial, with increased risk of suicide attempts [3,4], disability and unemployment [5], and comorbid conditions such as depression and substance use disorder [6][7][8]. In addition, PTSD is associated with a substantial economic burden to society, with a recent study estimating the burden at $232.2 billion in the United States (US) [9].…”

Section: Introductionmentioning

confidence: 99%

“…Historically, PTSD has been predominantly studied among military individuals, likely due to the high prevalence of PTSD in this population [11,12]. However, this represents a minority (14%) of the overall PTSD population in the US, with 86% of the PTSD population comprising civilians [9]. In addition, recent issues like COVID-19 [13], civil unrest [14], and climate change [15] continue to occur around the globe, adding to the growing concern of increased exposure to natural and societal traumatic events among civilians.…”

Section: Introductionmentioning

confidence: 99%

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Identifying individuals with undiagnosed post-traumatic stress disorder in a large United States civilian population – a machine learning approach

et al. 2022

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Background The proportion of patients with post-traumatic stress disorder (PTSD) that remain undiagnosed may be substantial. Without an accurate diagnosis, these patients may lack PTSD-targeted treatments and experience adverse health outcomes. This study used a machine learning approach to identify and describe civilian patients likely to have undiagnosed PTSD in the US commercial population. Methods The IBM® MarketScan® Commercial Subset (10/01/2015–12/31/2018) was used. A random forest machine learning model was developed and trained to differentiate between patients with and without PTSD using non–trauma-based features. The model was applied to patients for whom PTSD status could not be confirmed to identify individuals likely and unlikely to have undiagnosed PTSD. Patient characteristics, symptoms and complications potentially related to PTSD, treatments received, healthcare costs, and healthcare resource utilization were described separately for patients with PTSD (Actual Positive PTSD cohort), patients likely to have PTSD (Likely PTSD cohort), and patients without PTSD (Without PTSD cohort). Results A total of 44,342 patients were classified in the Actual Positive PTSD cohort, 5683 in the Likely PTSD cohort, and 2,074,471 in the Without PTSD cohort. While several symptoms/comorbidities were similar between the Actual Positive and Likely PTSD cohorts, others, including depression and anxiety disorders, suicidal thoughts/actions, and substance use, were more common in the Likely PTSD cohort, suggesting that certain symptoms may be exacerbated among those without a formal diagnosis. Mean per-patient-per-6-month healthcare costs were similar between the Actual Positive and Likely PTSD cohorts ($11,156 and $11,723) and were higher than those of the Without PTSD cohort ($3616); however, cost drivers differed between cohorts, with the Likely PTSD cohort experiencing more inpatient admissions and less outpatient visits than the Actual Positive PTSD cohort. Conclusions These findings suggest that the lack of a PTSD diagnosis and targeted management of PTSD may result in a greater burden among undiagnosed patients and highlights the need for increased awareness of PTSD in clinical practice and among the civilian population.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identifying individuals with undiagnosed post-traumatic stress disorder in a large United States civilian population – a machine learning approach

et al. 2022

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“…With finite healthcare resources available, the ability to predict clinical outcomes to allocate resources toward individuals at the greatest risk of developing chronic post-TBI symptoms and disability could lead to both cost-savings and improvement in individual quality of life. This is particularly true for costly and impairing sequelae such as PTSD [ 34 ], for which proven treatments, including early psychosocial interventions, exist. In fact, implementing clinical intervention as soon as possible following a traumatic event leads to a decreased likelihood of developing PTSD [ 35 ].…”

Section: Discussionmentioning

confidence: 99%

Polygenic risk for mental disorders as predictors of posttraumatic stress disorder after mild traumatic brain injury

et al. 2023

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Many patients with mild traumatic brain injury (mTBI) are at risk for mental health problems such as posttraumatic stress disorder (PTSD). The objective of this study was to determine whether the polygenic risk for PTSD (or for related mental health disorders or traits including major depressive disorder [MDD] and neuroticism [NEU]) was associated with an increased likelihood of PTSD in the aftermath of mTBI. We used data from individuals of European ancestry with mTBI enrolled in TRACK-TBI (n = 714), a prospective longitudinal study of level 1 trauma center patients. One hundred and sixteen mTBI patients (16.3%) had probable PTSD (PCL-5 score ≥33) at 6 months post-injury. We used summary statistics from recent GWAS studies of PTSD, MDD, and NEU to generate polygenic risk scores (PRS) for individuals in our sample. A multivariable model that included age, sex, pre-injury history of mental disorder, and cause of injury explained 7% of the variance in the PTSD outcome; the addition of the PTSD-PRS (and five ancestral principal components) significantly increased the variance explained to 11%. The adjusted odds of PTSD in the uppermost PTSD-PRS quintile was nearly four times higher (aOR = 3.71, 95% CI 1.80–7.65) than in the lowest PTSD-PRS quintile. There was no evidence of a statistically significant interaction between PTSD-PRS and prior history of mental disorder, indicating that PTSD-PRS had similar predictive utility among those with and without pre-injury psychiatric illness. When added to the model, neither MDD-PRS nor NEU-PRS were significantly associated with the PTSD outcome. These findings show that the risk for PTSD in the context of mTBI is, in part, genetically influenced. They also raise the possibility that an individual’s PRS could be clinically actionable if used—possibly with other non-genetic predictors—to signal the need for enhanced follow-up and early intervention; this precision medicine approach needs to be prospectively studied.

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“…The economic implications of the metal health burden are huge. In the U.S., the societal economic burden of PTSD in 2018 was $232 billion ( 38 ), and of major depression was $210.5 billion in 2010 ( 39 ). Yet little investigation has been conducted on the economics of the new therapies.…”

Section: Introductionmentioning

confidence: 99%

The economics of psychedelic-assisted therapies: A research agenda

2022

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After a long hiatus, psychiatry is undergoing a resurgence of interest in psychedelic drugs as therapy for a wide range of mental health disorders Accumulating clinical evidence suggests substantial potential for psychedelics used in a therapeutic context, as treatment for, among other disorders, depression, post-traumatic stress disorder (PTSD), and addictions to tobacco, opioids and alcohol. As soon as 2024, powerful new therapeutic modalities could become available for individuals with mental health problems refractory to traditional therapies. Yet research has lagged on economic considerations, such as costs and cost-effectiveness, the economic effects of widespread implementation, pricing, and economic appraisal's methodological considerations relevant to psychedelic therapies. These issues are critical if psychedelic therapies are to become widely accessible. We describe six types of economic analyses and their rationale for decisions and planning including the needs of health care payers. We also outline desirable features of this research, including scientific rigor, long horizons, equity, and a global view.

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The Economic Burden of Posttraumatic Stress Disorder in the United States From a Societal Perspective

Cited by 87 publications

References 0 publications

Identifying individuals with undiagnosed post-traumatic stress disorder in a large United States civilian population – a machine learning approach

Identifying individuals with undiagnosed post-traumatic stress disorder in a large United States civilian population – a machine learning approach

Polygenic risk for mental disorders as predictors of posttraumatic stress disorder after mild traumatic brain injury

The economics of psychedelic-assisted therapies: A research agenda

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