Race and Health Outcomes: Historical Perspectives and Implications for Aphasia Outcomes • 2000 – Congress passed the Minority Health and Health Disparities Research and Education Act of 2000 (Public Law 106‐525) • Authorized the Institute of Medicine’s (IOM) landmark study “Unequal Treatment” documenting longstanding disparities in healthcare across a variety of settings and health conditions. • The report also noted that racial minorities were far less likely to receive routine medical procedures, were more likely to experience lower quality healthcare services, but more likely to receive lower limb amputations and other less desirable treatment options for diabetes and other conditions.

Unequal Treatment—Confronting Racial and Ethnic Disparities in Healthcare

Objective:The present guidelines address the pharmacotherapy of schizophrenia in adults across different stages, phases, and symptom domains.Method:Guidelines were developed using the ADAPTE proces...

https://journals.sagepub.com/doi/pdf/10.1177/0706743717720448

Guidelines for the Pharmacotherapy of Schizophrenia in Adults.

Suicide is a leading cause of death. A substantial proportion of the people who die by suicide come into contact with the health care system in the year before their death. This observation has resulted in the development of numerous suicide prediction tools to help target patients for preventive interventions. However, low sensitivity and low positive predictive value have led critics to argue that these tools have no clinical value. We review these tools and critiques here. We conclude that existing tools are suboptimal and that improvements, if they can be made, will require developers to work with more comprehensive predictor sets, staged screening designs, and advanced statistical analysis methods. We also conclude that although existing suicide prediction tools currently have little clinical value, and in some cases might do more harm than good, an even-handed assessment of the potential value of refined tools of this sort cannot currently be made because such an assessment would depend on evidence that currently does not exist about the effectiveness of preventive interventions. We argue that the only way to resolve this uncertainty is to link future efforts to develop or evaluate suicide prediction tools with concrete questions about specific clinical decisions aimed at reducing suicides and to evaluate the clinical value of these tools in terms of net benefit rather than sensitivity or positive predictive value. We also argue for a focus on the development of individualized treatment rules to help select the right suicide-focused treatments for the right patients at the right times. Challenges will exist in doing this because of the rarity of suicide even among patients considered high-risk, but we offer practical suggestions for how these challenges can be addressed.

Suicide prediction models: a critical review of recent research with recommendations for the way forward

Embodied Conversational Agents (ECAs) are promising software to communicate with patients but no study has tested them in the diagnostic field of mental disorders. The aim of this study was 1) to test the performance of a diagnostic system for major depressive disorders (MDD), based on the identification by an ECA of specific symptoms (the MDD DSM 5 criteria) in outpatients; 2) to evaluate the acceptability of such an ECA. Patients completed two clinical interviews in a randomized order (ECA versus psychiatrist) and filled in the Acceptability E-scale (AES) to quantify the acceptability of the ECA. 179 outpatients were included in this study (mean age 46.5 ± 12.9 years, 57.5% females). Among the 35 patients diagnosed with MDD by the psychiatrist, 14 (40%) patients exhibited mild, 12 (34.3%) moderate and 9 (25.7%) severe depressive symptoms. Sensitivity increased across the severity level of depressive symptoms and reached 73% for patients with severe depressive symptoms, while specificity remained above 95% for all three severity levels. The acceptability of the ECA evaluated by the AES was very good (25.4). We demonstrate here the validity and acceptability of an ECA to diagnose major depressive disorders. ECAs are promising tools to conduct standardized and well-accepted clinical interviews.

/pdf/virtual-human-as-a-new-diagnostic-tool-a-proof-of-concept-ndl2npw8fo.pdf

Virtual human as a new diagnostic tool, a proof of concept study in the field of major depressive disorders.

Importance Receiving a preferred treatment has previously been associated with lower dropout rates and better clinical outcomes, but this scenario has not been investigated specifically for psychosocial interventions for patients with a mental health diagnosis. Objective To assess the association of patient treatment preference with dropout and clinical outcomes in adult psychosocial mental health interventions via a systematic review and meta-analysis. Data Sources The Cochrane Library, Embase, PubMed, PsychINFO, Scopus, Web of Science, Nice HDAS (Healthcare Databases Advanced Search), Google Scholar, BASE (Bielefeld Academic Search Engine), Semantic Scholar, and OpenGrey were searched from inception to July 20, 2018, and updated on June 10, 2019. Study Selection Studies were eligible if they (1) were a randomized clinical trial; (2) involved participants older than 18 years; (3) involved participants with mental health diagnoses; (4) reported data from a group of participants who received their preferred treatment and a group who received their nonpreferred treatment or who were not given a choice; and (5) offered at least 1 psychosocial intervention. Data Extraction and Synthesis Two researchers extracted study data for attendance, dropout, and clinical outcomes independently. Both assessed the risk of bias according to the Cochrane tool. Data were pooled using random-effects meta-analyses. Main Outcomes and Measures The following 7 outcomes were examined: attendance, dropout, therapeutic alliance, depression and anxiety outcomes, global outcomes, treatment satisfaction, and remission. Results A total of 7341 articles were identified, with 34 eligible for inclusion. Twenty-nine articles were included in the meta-analyses comprising 5294 participants. Receiving a preferred psychosocial mental health treatment had a medium positive association with dropout rates (relative risk, 0.62; 0.48-0.80;P  Conclusions and Relevance This is the first review, to our knowledge, examining the association of receiving a preferred psychosocial mental health treatment with both engagement and outcomes for patients with a mental health diagnosis. Patients with mental health diagnoses who received their preferred treatment demonstrated a lower dropout rate from treatment and higher therapeutic alliance scores. These findings underline the need to accommodate patient preference in mental health services to maximize treatment uptake and reduce financial costs of premature dropout and disengagement.

/pdf/association-of-patient-treatment-preference-with-dropout-and-1c1ahwr4c4.pdf

Association of Patient Treatment Preference With Dropout and Clinical Outcomes in Adult Psychosocial Mental Health Interventions: A Systematic Review and Meta-analysis.

These Practice Guidelines for the Psychiatric Evaluation of Adults mark a transition in the American Psychiatric Association’s Practice Guidelines. Since the publication of the 2011 Institute of Medicine report Clinical Practice Guidelines We Can Trust, there has been an increasing focus on using clearly defined, transparent processes for rating the quality of evidence and the strength of the overall body of evidence in systematic reviews of the scientific literature. These guidelines were developed using a process intended to be consistent with the recommendations of the Institute of Medicine (2011), the Principles for theDevelopment of Specialty Society Clinical Guidelines of the Council of Medical Specialty Societies (2012), and the requirements of the Agency for Healthcare Research andQuality (AHRQ) for inclusion of a guideline in the National Guideline Clearinghouse. Parameters used for the guidelines’ systematic review are included with the full text of the guidelines; the development process is fully described in a document available on the APA website: http:// www.psychiatry.org/File%20Library/Practice/APA-GuidelineDevelopment-Process–updated-2011-.pdf. To supplement the expertise of members of the guideline work group, we used a “snowball” survey methodology to identify experts on psychiatric evaluation and solicit their input on aspects of the psychiatric evaluation that they saw as likely to improve specific patient outcomes (Yager 2014). Results of this expert survey are included with the full text of the practice guideline.

https://ajp.psychiatryonline.org/doi/pdf/10.1176/appi.ajp.2015.1720501

Richard S. Rhoads

Papers

The American Psychiatric Association Practice Guidelines for the Psychiatric Evaluation of Adults

The American Psychiatric Association Practice Guidelines for the Psychiatric Evaluation of Adults