Multi-Agent-Based Simulation of a Complex Ecosystem of Mental Health Care.

This paper discusses the creation of an Agent-Based Simulation that modeled the introduction of care coordination capabilities into a complex system of care for patients with Serious and Persistent Mental Illness. The model describes the engagement between patients and the medical, social and criminal justice services they interact with in a complex ecosystem of care. We outline the challenges involved in developing the model, including process mapping and the collection and synthesis of data to support parametric estimates, and describe the controls built into the model to support analysis of potential changes to the system. We also describe the approach taken to calibrate the model to an observable level of system performance. Preliminary results from application of the simulation are provided to demonstrate how it can provide insights into potential improvements deriving from introduction of care coordination technology.

Impact of the H1N1 influenza pandemic in two rural emergency departments.

INTRODUCTION: The World Health Organization declared an influenza H1N1 global pandemic in June 2009, which resulted in a great deal of research. However, no studies have been published on incidence, characteristics and impact in rural emergency departments (EDs). METHODS: Data were gathered from two rural EDs located in Southwestern Ontario. A retrospective chart review was performed on all visits to the hospitals' EDs with ICD-10 codes relating to influenza-like illnesses (ILI). The chart review periods were 1 September 2009 to 1 January 2010 for the H1N1 study group and 1 September 2008 to 1 January 2009 for the control group. RESULTS: There were 546 cases of ILI during the H1N1 pandemic period out of 8339 total ED visits (6.5%). This was a 4.1 fold increase from the previous year when 132 cases of ILI were identified out of 8125 ED visits (1.6%). Half the cases of ILI that presented during the H1N1 pandemic occurred in patients aged 1 to 20 years, a proportion significantly larger during the pandemic compared with the control period. Time-to-physician assessment did increase significantly during the pandemic (41 min vs 52 min) without resulting in an increased mean length of stay in the ED (122 min vs 120 min). Using the Canadian Triage and Acuity Scale, a patient severity rating that dictates time to medical care, no differences in severity of ILI cases were observed. Nor were there no differences observed in discharge rates, admission rates, transfers to other facilities, unscheduled ED visits with 72 hours, or mortality during the two periods. CONCLUSIONS: There was a significant increase in the incidence of ILI at the two rural EDs during the H1N1 pandemic compared with the previous year without a corresponding increase in severity of illness.

Heterogeneity of non-conscious fear perception in posttraumatic stress disorder as a function of physiological arousal: an fMRI study.

While posttraumatic stress disorder (PTSD) is often characterised by an excessive fear response and hyperarousal, research has generally neglected other clinical characteristics including hypoarousal. Findings indicate that concurrent autonomic activity is associated with increased non-conscious processing of fear, highlighting that autonomic responsivity may be an important determinant in the degree of activation within the brainstem-amygdala-MPFC (medial prefrontal cortex) network.

The neural networks of inhibitory control in posttraumatic stress disorder.

OBJECTIVE: Posttraumatic stress disorder (PTSD) involves deficits in information processing that may reflect hypervigilence and deficient inhibitory control. To date, however, no PTSD neuroimaging study has directly examined PTSD-related changes in executive inhibition. Our objective was to investigate the hypothesis that executive inhibitory control networks are compromised in PTSD. METHODS: Functional magnetic resonance imaging (fMRI) was used during a Go/No-Go inhibition task completed by a sample of patients with PTSD (n = 23), a matched sample of healthy (i.e. without trauma exposure) control participants (n = 23) and a sample of control participants with trauma exposure who did not meet criteria for PTSD (n = 17). RESULTS: Participants with PTSD showed more inhibition-related errors than did individuals without trauma exposure. During inhibition, control participants activated a right-lateralized cortical inhibitory network, whereas patients with PTSD activated only the left lateral frontal cortex. PTSD was associated with a reduction in right cortical activation and increased activation of striatal and somatosensory regions. CONCLUSION: The increased inhibitory error and reduced right frontal cortical activation are consistent with compromised inhibitory control in PTSD, while the increased activation of brain regions associated with sensory processing and a greater demand on inhibitory control may reflect enhanced stimulus processing in PTSD, which may undermine cortical control mechanisms.

Developing an integrated brain, behavior and biological response profile in posttraumatic stress disorder (PTSD).

The present study sought to determine a profile of integrated behavioral, brain and autonomic alterations in PTSD. Previous findings suggest that PTSD is associated with changes across electrophysiological (EEG and ERP), autonomic and cognitive/behavioral measures. In particular, PTSD has been associated with reduced cognitive performance, altered cortical arousal (measured by EEG), diminished late ERP component to oddball task targets (reduced P3 amplitude) and increased autonomic arousal relative to healthy controls. The present study examined measures of cognitive function, auditory oddball ERP components, autonomic function (heart rate and skin conductance) and EEG during resting conditions in 44 individuals with PTSD and 44 non-trauma-exposed controls, and predicted that an integrated profile of changes across a number of these measures would show a high level of sensitivity and specificity in discriminating PTSD from controls. Nine variables showing strongly significant (p < 0.002) between-group differences were entered into a discriminant function analysis. Four of these measures successfully discriminated the PTSD and non-PTSD groups: change in tonic arousal, duration of attention switching, working memory reaction time and errors of commission during visuospatial maze learning. Tonic arousal change contributed the most variance in predicting group membership. These results extend previous findings and provide an integrated biomarker profile that characterizes both PTSD and non-PTSD groups with a high degree of sensitivity and specificity. This outcome provides a platform for future studies to test how this profile of disturbances in autonomic and information processing may be unique to PTSD or may occur generically across clinical and/or other anxiety disorders.

Use of technology for care coordination initiatives for patients with mental health issues: a systematic literature review.

This systematic literature review investigates the use of technology for the coordination and management of mental health care with an emphasis on outcomes. Searches of MEDLINE/PubMed, Scopus, and EMBASE were conducted between January 1, 2003, and January 4, 2018, to identify articles that assessed patient outcomes associated with care coordination, evaluated technology to improve care, or discussed management of mental health care using technology. A total of 21 articles were included in a qualitative review based on the recommendations set forth by the PRISMA statement. Among the various health technologies, electronic health records were most commonly used for care coordination, with primary care being the most frequent setting. Care coordination was shown to provide easier patient access to health care providers and to improve communication between caregiver and patient, especially in cases where geographic location or distance is a challenge. Barriers to coordinated care included, but were not limited to, insufficient funding for health information technology, deficient reimbursement plans, limited access to technologies, cultural barriers, and underperforming electronic health record templates. In conclusion, many studies showed the benefit of coordinated and collaborative care through the use of technology; however, further research and development efforts are needed to continue technological innovation for advanced patient care.

Integrating objective gene-brain-behavior markers of psychiatric disorders.

There is little consensus about which objective markers should be used to assess major psychiatric disorders, and predict/evaluate treatment response for these disorders. Clinical practice relies instead on subjective signs and symptoms, such that there is a "translational gap" between research findings and clinical practice. This gap arises from: a) a lack of integrative theoretical models which provide a basis for understanding links between gene-brain-behavior mechanisms and clinical entities; b) the reliance on studying one measure at a time so that linkages between markers are their specificity are not established; and c) the lack of a definitive understanding of what constitutes normative function. Here, we draw on a standardized methodology for acquiring multiple sources of genomic, brain and behavioral data in the same subjects, to propose candidate markers of selected psychiatric disorders: depression, post-traumatic stress disorder, schizophrenia, attention-deficit/hyperactivity disorder and dementia disorders. This methodology has been used to establish a standardized international database which provides a comprehensive framework and the basis for testing hypotheses derived from an integrative theoretical model of the brain. Using this normative base, we present preliminary findings for a number of disorders in relation to the proposed markers. Establishing these objective markers will be the first step towards determining their sensitivity, specificity and treatment prediction in individual patients.

Predicting Future High-Cost Schizophrenia Patients Using High-Dimensional Administrative Data.

BACKGROUND: The burden of serious and persistent mental illness such as schizophrenia is substantial and requires health-care organizations to have adequate risk adjustment models to effectively allocate their resources to managing patients who are at the greatest risk. Currently available models underestimate health-care costs for those with mental or behavioral health conditions. OBJECTIVES: The study aimed to develop and evaluate predictive models for identification of future high-cost schizophrenia patients using advanced supervised machine learning methods. METHODS: This was a retrospective study using a payer administrative database. The study cohort consisted of 97,862 patients diagnosed with schizophrenia (ICD9 code 295.*) from January 2009 to June 2014. Training (n = 34,510) and study evaluation (n = 30,077) cohorts were derived based on 12-month observation and prediction windows (PWs). The target was average total cost/patient/month in the PW. Three models (baseline, intermediate, final) were developed to assess the value of different variable categories for cost prediction (demographics, coverage, cost, health-care utilization, antipsychotic medication usage, and clinical conditions). Scalable orthogonal regression, significant attribute selection in high dimensions method, and random forests regression were used to develop the models. The trained models were assessed in the evaluation cohort using the regression R2, patient classification accuracy (PCA), and cost accuracy (CA). The model performance was compared to the Centers for Medicare & Medicaid Services Hierarchical Condition Categories (CMS-HCC) model. RESULTS: At top 10% cost cutoff, the final model achieved 0.23 R2, 43% PCA, and 63% CA; in contrast, the CMS-HCC model achieved 0.09 R2, 27% PCA with 45% CA. The final model and the CMS-HCC model identified 33 and 22%, respectively, of total cost at the top 10% cost cutoff. CONCLUSION: Using advanced feature selection leveraging detailed health care, medication utilization features, and supervised machine learning methods improved the ability to predict and identify future high-cost patients with schizophrenia when compared with the CMS-HCC model.

Integrated multisystem analysis in a mental health and criminal justice ecosystem.

BACKGROUND: Patients with a serious mental illness often receive care that is fragmented due to reduced availability of or access to resources, and inadequate, discontinuous, and uncoordinated care across health, social services, and criminal justice organizations. This article describes the creation of a multisystem analysis that derives insights from an integrated dataset including patient access to case management services, medical services, and interactions with the criminal justice system. METHODS: Data were combined from electronic systems within a US mental health ecosystem that included mental health and substance abuse services, as well as data from the criminal justice system. Cox models were applied to test the associations between delivery of services and re-incarceration. Additionally, machine learning was used to train and validate a predictive model to examine effects of non-modifiable risk factors (age, past arrests, mental health diagnosis) and modifiable risk factors (outpatient, medical and case management services, and use of a jail diversion program) on re-arrest outcome. RESULTS: An association was found between past arrests and admission to crisis stabilization services in this population (N = 10,307). Delivery of case management or medical services provided after release from jail was associated with a reduced risk for re-arrest. Predictive models linked non-modifiable and modifiable risk factors and outcomes and predicted the probability of re-arrests with fair accuracy (area under the receiver operating characteristic curve of 0.67). CONCLUSIONS: By modeling the complex interactions between risk factors, service delivery, and outcomes, systems of care might be better enabled to meet patient needs and improve outcomes.

Sex differences in cell proliferation, cell death and defensive behavior following acute predator odor stress in adult rats.

Males show suppressed cell proliferation in the hippocampus in response to acute stress but no studies to date have examined cell proliferation in response to acute stress in females. In the current study, we examined the effects of acute exposure to a predator odor stressor [trimethyl thiazoline (TMT); the main component of fox feces] or a control odor on cell proliferation and cell death in the dentate gyrus and on behavior in adult male and female [intact, ovariectomized (OVX) or OVX+estradiol benzoate (EB)] rats. Further, we examined whether TMT-induced changes in behavior were related to cellular changes. During TMT exposure, rats were injected with the cell synthesis marker bromodeoxyuridine and perfused 24 h later. Acute TMT exposure suppressed both cell proliferation and death in males but not in any group of females. Interestingly, in the OVX females we observed an increase in cell death that was eliminated by EB treatment. Consistent with prior studies, estradiol treatment increased cell proliferation regardless of odor condition. Regardless of sex or hormone treatment, TMT increased defensive behavior, suggesting that the behavioral response to TMT is dissociated from this cellular response. This is the first demonstration of a sex difference in cell proliferation and death in the adult dentate gyrus in response to stress.

Reduced amygdala and ventral striatal activity to happy faces in PTSD is associated with emotional numbing.

There has been a growing recognition of the importance of reward processing in PTSD, yet little is known of the underlying neural networks. This study tested the predictions that (1) individuals with PTSD would display reduced responses to happy facial expressions in ventral striatal reward networks, and (2) that this reduction would be associated with emotional numbing symptoms. 23 treatment-seeking patients with Posttraumatic Stress Disorder were recruited from the treatment clinic at the Centre for Traumatic Stress Studies, Westmead Hospital, and 20 trauma-exposed controls were recruited from a community sample. We examined functional magnetic resonance imaging responses during the presentation of happy and neutral facial expressions in a passive viewing task. PTSD participants rated happy facial expression as less intense than trauma-exposed controls. Relative to controls, PTSD participants revealed lower activation to happy (-neutral) faces in ventral striatum and and a trend for reduced activation in left amygdala. A significant negative correlation was found between emotional numbing symptoms in PTSD and right ventral striatal regions after controlling for depression, anxiety and PTSD severity. This study provides initial evidence that individuals with PTSD have lower reactivity to happy facial expressions, and that lower activation in ventral striatal-limbic reward networks may be associated with symptoms of emotional numbing.

Integrated multisystem analysis in a mental health and criminal justice ecosystem.

Patients with a serious mental illness often receive care that is fragmented due to reduced availability of or access to resources, and inadequate, discontinuous, and uncoordinated care across health, social services, and criminal justice organizations. These gaps in care may lead to increased mental health disease burden and relapse, as well as repeated incarcerations. Further, the complex health, social service, and criminal justice ecosystem within which the patient may be embedded makes it difficult to examine the role of modifiable risk factors and delivered services on patient outcomes, particularly given that agencies often maintain isolated sets of relevant data. Here we describe an approach to creating a multisystem analysis that derives insights from an integrated data set including patient access to case management services, medical services, and interactions with the criminal justice system. We combined data from electronic systems within a US mental health ecosystem that included mental health and substance abuse services, as well as data from the criminal justice system. We applied Cox models to test the associations between delivery of services and re-incarceration. Using this approach, we found an association between arrests and crisis stabilization services in this population. We also found that delivery of case management or medical services provided after release from jail was associated with a reduced risk for re-arrest. Additionally, we used machine learning to train and validate a predictive model linking non-modifiable and modifiable risk factors and outcomes. A predictive model, constructed using elastic net regularized logistic regression, and considering age, past arrests, mental health diagnosis, as well as use of a jail diversion program, outpatient, medical and case management services predicted the probability of re-arrests with fair accuracy (AUC=.67). By modeling the complex interactions between risk factors, service delivery and outcomes, we may better enable systems of care to meet patient needs and improve outcomes.

Inhibitory neural activity predicts response to cognitive-behavioral therapy for posttraumatic stress disorder.

OBJECTIVE: Despite cognitive-behavioral therapy (CBT) being an effective treatment for posttraumatic stress disorder (PTSD), many patients do not respond to CBT. Understanding the neural bases of treatment response may inform treatment refinement, thereby improving treatment response rates. Adequate working memory function is proposed to enable engagement in CBT. METHOD: This study employed a Go/No-Go task to examine inhibitory function and its functional brain correlates as predictors of response to CBT in PTSD. Participants were recruited between October 2003 and May 2005. Thirteen treatment-seeking patients who met DSM-IV criteria for PTSD completed the Go/No-Go task while undergoing functional magnetic resonance imaging (fMRI), after which they entered 8 once-weekly sessions of CBT. PTSD severity was measured before treatment and again at 6 months following treatment completion using the Clinician-Administered PTSD Scale (primary outcome measure). RESULTS: After controlling for initial PTSD severity and ongoing depressive symptoms, greater activity in left dorsal striatal (Z = 3.19, P = .001) and frontal (Z = 3.03, P = .001) networks during inhibitory control was associated with lower PTSD symptom severity after treatment, suggesting better treatment response. CONCLUSIONS: These results suggest that neural circuitry underpinning inhibitory control plays a role in the outcome of CBT for patients with PTSD. TRIAL REGISTRATION: anzctr.org Identifier: ACTRN12610000017022.

Neural responses to masked fear faces: sex differences and trauma exposure in posttraumatic stress disorder.

Although women have a greater propensity than men to develop posttraumatic stress disorder (PTSD) following trauma, sex differences in neural activations to threat have received little investigation. This study tested the prediction that trauma would heighten activity in automatic fear-processing networks to a greater extent in women than in men. Functional magnetic resonance imaging (fMRI) data were recorded in 23 participants with PTSD (13 women, 10 men), 21 trauma-exposed controls (9 women, 12 men), and 42 non-trauma-exposed controls (22 women, 20 men) while they viewed masked facial expressions of fear. Exposure to trauma was associated with enhanced brainstem activity to fear in women, regardless of the presence of PTSD, but in men, it was associated only with the development of PTSD. Men with PTSD displayed greater hippocampal activity to fear than did women. Both men and women with PTSD showed enhanced amygdala activity to fear relative to controls. The authors conclude that greater brainstem activation to threat stimuli may contribute to the greater prevalence of PTSD in women, and greater hippocampal activation in men may subserve an enhanced capacity for contextualizing fear-related stimuli.

Alterations in theta activity associated with novelty and routinization processing in ADHD.

OBJECTIVE: Novelty and routinization-related information processing disturbances were examined in adolescent males with ADHD using an oddball paradigm and electrophysiological measurement of theta (4-7Hz) activity. METHODS: Fifty-four unmedicated adolescent males (12-18years) with Attention Deficit Hyperactivity Disorder (ADHD) and matched controls performed an auditory oddball task. Theta activity was sub-averaged, and Fourier Integrals with simultaneous measurement of electrodermal activity (EDA) was used to index response to stimulus novelty and routinization. RESULTS: ADHD participants showed an overall increase in theta activity to both novel and routine stimuli relative to controls. While controls showed increased theta activity in response to novel compared to routine targets across the brain, ADHD participants did not show this novelty-related increase in theta activity in the right anterior/frontal brain. CONCLUSIONS: The findings of this study are consistent with disturbances in theta activity and the brain substrates of novelty relative to routinization-related processing in ADHD. SIGNIFICANCE: These findings show that there are distinct alterations in theta activity related to stimulus novelty and routinization during an auditory oddball task in ADHD, and they highlight the value of using an event-related approach to elucidate the neural substrates of stimulus processing in ADHD.

Preliminary evidence of the short allele of the serotonin transporter gene predicting poor response to cognitive behavior therapy in posttraumatic stress disorder.

OBJECTIVE: This study was intended to assess the extent to which the low-expression alleles of the serotonin transporter gene promoter predict poor response to cognitive behavior therapy in patients with posttraumatic stress disorder (PTSD). METHOD: Forty-five patients with PTSD underwent an 8-week exposure-based cognitive behavior therapy program and provided mouth swabs or saliva samples to extract genomic DNA and classify individuals according to four allelic forms (S(A), S(G), L(A), L(G)) of the 5-HTT-linked polymorphic region (5-HTTLPR). We determined whether the 5-HTTLPR genotype predicted change in PTSD severity following treatment (n = 45) and 6 months later (n = 42). RESULTS: After controlling for pretreatment PTSD severity and number of treatment sessions, the 5-HTTLPR low-expression genotype group (S or L(G) allele carriers) displayed more severe PTSD 6 months following treatment relative to other patients. CONCLUSIONS: This study suggests a genetic contribution to treatment outcome following cognitive behavior therapy and implicates the serotonergic system in response to exposure-based treatments in PTSD.

Duration of posttraumatic stress disorder predicts hippocampal grey matter loss.

To examine the impact of environmental stress on grey matter volume in posttraumatic stress disorder (PTSD), we investigated the relationship between duration of PTSD and grey matter volume of hippocampus and anterior cingulate cortex. Twenty-one participants with PTSD and 17 trauma-exposed controls, matched for age and sex and with no history of substance dependence, underwent a T1-weighted structural MRI scan and voxel-based morphometry was employed. After controlling for age, depression and whole-brain volume, analysis of covariance revealed significant reductions in hippocampus and rostral anterior cingulate cortex in PTSD, and there was a significant negative correlation between right hippocampal volume and PTSD duration. This pattern suggests that prolonged PTSD may have cumulative adverse effects on hippocampal volume, highlighting the potential role of genetic-environmental interactions.