Patients with co-occurring behavioral and medical conditions represent such a population

Whilst the aim of our study was to examine the relationship between baseline features and subsequent outcome , it is important to note that there are limitations with this approach. First, we did not account psychosocial stressors and other confounding factors/events that may have occurred in the time between baseline and follow-up. Indeed, it is possible that stressor cortisol concordance at follow-up does in fact distinguish between CHR subgroups, but that our measure at baseline was too distal to outcome. Second, CHR individuals are at elevated risk for a wide range of psychiatric disorders, particularly depression and anxiety , and so worsening of prodromal symptoms/transition to psychosis is only one of several potential outcome measures, all of which will inevitably involve more false negatives the shorter the follow-up period. Indeed, a recent study suggested that well-established risk factors are better at predicting poor functioning in CHR populations than transition to psychosis . The extent to which stressor-cortisol concordance at baseline is associated with other non-psychotic disorders and functioning at follow-up is therefore warranted.We assessed HPA axis function using basal salivary cortisol collected in the laboratory, as it is more reliable and, unlike home sampling methods, unlikely to be influenced by confounding factors such as exercise . However,grow cannabis in containers meta-analytic evidence indicates that the effect of chronic stress on cortisol varies across cortisol measures; whilst diurnal cortisol, afternoon/evening cortisol, and the CARi are elevated following chronic stress, basal morning levels are lower and the diurnal rhythm appears to be flatter . Employing alternative cortisol measures might therefore reveal different patterns of stressor-cortisol concordance across CHR individuals and controls.

Indeed, using a home sampling procedure, Cullen and colleagues reported a negative correlation between the CARi and negative life event distress in at-risk children with a family history of schizophrenia but a positive correlation in typically-developing children , whilst a study of adults found that diurnal cortisol was associated negatively with stressful life event exposure in first-episode psychosis patients, most of whom were receiving antipsychotic medication, but positively in controls . Thus, employing multiple measures of cortisol may be more informative than basal cortisol alone and enable the identification of dissociated relationships in at-risk individuals/psychosis patients and healthy controls. Cortisol output is not, however, the only method of assessing HPA axis function. In addition to endocrine measurement neuroimaging can be used to determine pituitary and hippo campal volume and density, distribution and/or affinity of glucocorticoid/mineralocorticoid receptors. The latter is particularly important as these receptors mediate the effects of glucocorticoids on cellular targets. As a related point, future studies are warranted to investigate glucocorticoid sensitisation , in CHR youth, as this may have implications not only for the HPA axis, but also the immune system , and dopamine levels . Thus, studies employing multiple methodological approaches, including genetic profiling, neuroimaging, and endocrine measurement, may be needed to adequately investigate the extent to which individuals at-risk for psychosis are characterised by increased HPA axis sensitivity. Our findings have other implications for future research examining HPA axis responsivity in at-risk individuals. First, we observed that the lapse-of-time between completion of stress measures and cortisol collection moderated stressor-cortisol concordance . Whilst we anticipated this pattern for daily stressors occurring within the past 24 hours, the findings for life events and childhood trauma were not predicted as these events did not occur on the day of measurement. It is plausible that reporting these events in the research environment is itself a stressful experience for some participants, and that it elicits a cortisol elevation and thus a relationship between stressor exposure and cortisol.

These findings highlight the importance of adjusting for the interaction between stressors and timelapse between assessments when examining stressor-cortisol concordance. Second, participant sex was identified as a potential confounder. The updated neural diathesis-stress model noted sex differences to be an important area for future research , whilst it was beyond the scope of the current study to explore whether sex modified the degree of stressor-cortisol concordance, future studies should investigate this possibility. Finally, whilst we defined CHR outcome status on the basis of attenuated positive symptoms and transition to psychosis, as noted above, there has been recent acknowledgement of the need to examine a broader range of outcomes, including, levels of social and role functioning, non-psychotic disorders, and negative symptoms . Future studies might therefore examine whether stressor-cortisol concordance is associated with these outcomes at follow-up.The nation’s health care system faces a mandate to improve quality in multiple dimensions, including those identified by the Institute of Medicine: safety, timeliness, effectiveness, efficiency, equitability and patient centeredness. Expenditures and gaps in health care delivery in general are not evenly distributed throughout the population; only 5% of the population account for half of all health care spending, and quality varies considerably across conditions and settings. An effective response to the quality mandate will require a focus on subgroups of patients who have severe or multiple health conditions associated with significantly higher costs and poorer outcomes.In the National Comorbidity Survey Replication, more than 68% of adults with a behavioral disorder report having at least one general medical disorder, and 29% of those with a medical disorder had a comorbid mental health condition. Research has documented the high rates of psychiatric comorbidity among specific medical conditions, such as HIV, diabetes, asthma and chronic medical illnesses. Conversely, studies have reported high rates of medical comorbidity among patients with psychiatric illness.

The co-occurrence of behavioral and medical conditions leads to elevated symptom burden, functional impairment, decreased length and quality of life, and increased costs. For patients with comorbid behavioral and medical conditions, problems with quality of care occur when they are treated in a primary care and/or specialty mental health setting. Even more concerning, premature mortality is elevated two- to four‐ fold. In response to these findings, care delivery models have been developed for patients with comorbid medical and psychiatric conditions. The most effective have been collaborative care approaches that use a multidisciplinary team to screen and track mental health conditions in primary care. These models build on the Chronic Care Model. Yet, even as these models are promoted, the gaps in our knowledge about cooccurrence may have important implications for how these collaborative models are structured. Research to date on the prevalence of co-occurring medical and psychiatric conditions has focused on national surveys, specific illnesses, disease-focused clinics or claims data for health insurance populations, such as Medicaid or Medicare. To our knowledge, no prior study has focused on a large patient population with a predominately employment-based insurance that receives treatment in an integrated health care system. Examining cooccurrence in this setting addresses several important gaps in the existing literature. First, employed patients in an integrated health care system represent an important and distinct sub-population of patients receiving care in the delivery model promoted by health care reform. Second, this kind of system generates encounter-based rather than claims-based data. The data are generated from all clinical departments within a comprehensive system of care. To address these gaps, pot for cannabis we examine the prevalence of behavioral health conditions in a large integrated health system that primarily serves patients with employment-based insurance. We compare the burden of medical co-morbidity and chronic diseases among those health plan members with a behavioral health condition to matched members without. This provides the opportunity to examine the robustness of the behavioral and medical disease nexus in this sub-population compared to the other sub-populations more commonly studied.Institutional review board approval was obtained from the Kaiser Research Foundation Institute for this retrospective database-only study. Initially, all KPNC patients aged 18+ with any behavioral health diagnoses in 2010 were identified. Automated clinical databases were used to identify all outpatient visits , hospitalizations and emergency department visits at KPNC facilities between January 1, 2010, and December 31, 2010, where a patient had a BHD. The BHDs used for this study included both mental health and substance use disorders: depressive disorders, bipolar spectrum disorders, anxiety disorders, attention deficit hyperactivity disorders , autism spectrum disorders, personality disorders, substance use disorders, dementia, schizophrenia spectrum disorders and other psychoses [see Appendix A for International Classification of Diseases, Ninth Revision codes relevant to this paper]. These categories were selected based on collaborations with NIMH’s Mental Health Research Network and KPNC’s Regional Mental Health leadership.

The first mention for each BHD during the study period was included, so patients in the sample could have multiple BHDs over the 1-year study period . The prevalence rates of BHDs were examined among all adult KPNC patients. Patients insured by Medicare or Medicaid were excluded from the study.Compared to the matched controls, each of the most prevalent BHDs [depression , anxiety , substance use , bipolar spectrum disorder and ADHD ] had significantly more patients with any medical comorbidities based on the ICD-9 categories. This was true across all ICD-9 categories examined, with the exception being Diseases of the Circulatory system and Neoplasms for the ADHD comparison, which did not differ . We had similar findings with respect to the burden of chronic conditions. With the exception of ADHD and bipolar disorder, each specific BHD had a significantly higher prevalence of each chronic condition compared to the matched controls. Those with ADHD diagnoses did not significantly differ in the chronic conditions related to the circulatory system , Parkinson’s disease or osteoporosis. However, there were significant differences between those with ADHD and their matched controls for the other chronic conditions. Patients with bipolar disorder did not significantly differ from their matched controls in prevalence of end-stage renal disease or osteoporosis. We also examined the Charlson Comorbidity Index and found that patients in the SubBHD sample had a significantly higher average Charlson Comorbidity index compared to their controls across all conditions examined .BHDs are highly prevalent in this health system. Fifteen percent of members with a health plan visit in 2010 had at least one BHD. By far, the most common were depression and anxiety. Moreover, among patients with BHD, psychiatric comorbidity is common; of those patients with a BHD, 28% had multiple BHDs. Among the five most prevalent BHDs, the proportion of patients with at least one psychiatric comorbidity ranged from 42% to 60%. Finally, those patients with a BHD carry a disproportionately high medical disease burden.With only a few exceptions, the proportion of BHD patients with a medical illness, including common chronic conditions, was significantly higher than non-BHD patients. Risk of 10-year mortality as calculated by the Charlson Index was found to be significantly higher for those with any of the BHDs examined compared to their matched controls. Thus, similar to studies of other patient sub-populations, BHDs in a largely commercially insured, employment-based health system are common and associated with a higher burden of chronic medical disease. At the same time, these results differ from some of the other large data sets. For example, disabled Medicaid beneficiaries have a prevalence rate of psychiatric illness ranging from nearly 29% to 49%, depending on whether the claims-based data include pharmacy data in addition to diagnostic codes . This higher proportion likely reflects both a more vulnerable patient population and methodology that better captures patients being treated for a psychiatric illness without an associated diagnostic code. In that same data set, the Medicaid aged population’s prevalence of psychiatric illness more closely mirrored the prevalence in this study: 10.4% or 35.9% . Our encounter data were based on ICD-9 coding and therefore are more similar to the diagnosis-only data from the Medicaid data set. The US National Comorbidity Survey Replication, which is based on a face-to-face household survey, reported a 26% any Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, disorder prevalence, and others have reported around 30%. Given that fewer than half of people with a psychiatric illness receive treatment, these estimates are fairly consistent with the 15% prevalence observed in this study, which includes a patient population more representative of the general US population but only captures those who made a health plan visit. This study has several limitations. As with other studies that have used claims-based data, our study only captures patients with behavioral health disorders noted in their visits during the study period. This methodology is vulnerable to under-estimation especially with regards to behavioral health disorders.