INTRODUÇÃO: Os transtornos mentais psicóticos são condições frequentes na população em geral e estão associados à grande morbidade e elevadas taxas de comprometimento funcional, tornando-os um grave problema de saúde pública. O desenvolvimento de novos métodos de auxílio diagnóstico e prognóstico a pratica clínica psiquiátrica possibilitando que intervenções efetivas sejam feitas precocemente na história natural da doença são, dessa forma, desejáveis. A classificação de padrões neuroanatômicos é uma robusta técnica para processamento e análise de imagens médicas que permite tanto a realização de comparações voxel-a-voxel entre grupos com alta dimensionalidade de variáveis, como a classificação individualizada das imagens. OBJETIVOS: Avaliar o desempenho diagnóstico de um classificador de padrões morfológicos complexos baseado em support vector machine (SVM) na discriminação entre diferentes transtornos psicóticos no momento do primeiro episódio, utilizando-se uma abordagem epidemiológica para a seleção de casos e controles, bem como na determinação de prognóstico de 1 ano em pacientes com primeiro episódio de esquizofrenia. MÉTODOS: Uma amostra de 62 pacientes com primeiro episódio de esquizofrenia/ transtorno esquizofreniforme, 23 casos de primeiro episódio de mania psicótica (transtorno bipolar tipo I, TB-I), e 19 indivíduos com depressão maior (DM) psicótica foram estudados com ressonância magnética (RM) estrutural de 1.5T, assim como um total de 89 controles residentes na mesma região dos casos. As imagens T1 foram inicialmente registradas a uma imagem molde comum através de um método com preservação de massa, permitindo a obtenção de volumes cerebrais regionais. Um classificador neuroanatômico multivariado baseado em redução de dimensionalidade e SVM foi utilizado para identificar o melhor conjunto de características morfológicas que diferencia cada transtorno psicótico (esquizofrenia/ transtorno esquizofreniforme, TB-I e DM psicótica) de subgrupos de controles saudáveis pareados por idade, gênero e anos de escolaridade. Os resultados obtidos pelo classificador foram, então, analisados com o auxílio de uma curva ROC, e um mapa espacial de alta dimensionalidade daquelas regiões cerebrais que constituem um padrão de distribuição tecidual cerebral característico de cada transtorno psicótico em relação aos controles foi gerado. RESULTADOS: O classificador obteve uma discriminação apenas modesta entre pacientes com primeiro episódio de esquizofrenia/ transtorno esquizofreniforme e controles saudáveis, com uma medida de área sob a curva (AUC) de 0,75 e acurácia de 73,4%. O mapa espacial discriminatório resultante mostrou um padrão complexo de alterações volumétricas comprometendo regiões fronto-límbicas tanto de substância cinzenta como de substância branca cerebral bilateralmente, fascículos cerebrais associativos, terceiro ventrículo e o ventrículo lateral esquerdo. Um desempenho diagnóstico pobre foi observado nas comparações entre pacientes com TB-I e MD psicótica e controles. Além disso, o classificador baseado em SVM não conseguiu predizer satisfatoriamente o prognóstico de 1 ano (evolução de remissão versus não remissão) dos pacientes com primeiro episódio de esquizofrenia. CONCLUSÃO: Utilizando uma amostra de pacientes com psicoses afetivas e não afetivas com características clínicas semelhantes aos pacientes vistos na nossa prática psiquiátrica (comorbidade com transtornos de uso de substâncias e curso clínico variável) e selecionados através de uma abordagem epidemiológica populacional, o classificador de padrões neuroanatômicos não obteve bom desempenho diagnóstico na discriminação entre as formas esquizofreniformes e afetivas de primeiro episódio psicótico, e também não conseguiu predizer satisfatoriamente o prognóstico de 1 ano em primeiro episódio de esquizofrenia, utilizando apenas imagens estruturais de RM / INTRODUCTION: Psychotic disorders are prevalent medical conditions in the general population, and are usually associated with high morbidity and functional impairment rates, which make them a major concern for public health. The development of new methods aiming to aid diagnostic and prognostic value in clinical psychiatric practice thus allowing effective interventions at an early course of the illness are, therefore, desirable. Neuroanatomical pattern classification is a powerful technique for image processing and analysis which allows both high-dimensional voxelwise group comparisons and classification of images at an individual basis. OBJECTIVES: To evaluate the diagnostic performance of a support vector machine (SVM)-based complex morphological pattern classifier was used to discriminate different non-affective and affective psychotic disorders at the first episode using a population-based approach to recruit both cases and healthy controls, and also to predict 1-year prognosis (i.e., remitting versus non-remitting course) in a group of patients with first-episode schizophrenia. METHODS: A sample of 62 patients with first-episode schizophrenia/ schizophreniform disorder, 23 cases presenting with their first-episode of psychotic mania (bipolar I disorder, BD-I) and 19 individuals with psychotic major depressive disorder (MDD) was studied with 1.5T structural magnetic resonance imaging (MRI), as well as a pool of 89 epidemiologically recruited controls. T1-weighted images were first registered to a common template through a robust mass-preserving routine allowing regional volumetric analysis. A high-dimensional multivariate classification method based on dimensionality reduction and SVM was employed to identify the best and most parsimonious set of morphological features that discriminate each psychotic group (schizophrenia/ schizophreniform disorder, BD-I & psychotic MDD) from subgroups of age, gender and educationally-matched healthy controls. The abnormalities scores generated by the classifier were analyzed with a ROC curve analysis and a high-dimensional spatial map of the brain regions that constitute a pattern of brain tissue distribution characteristic of each of the non-affective and affective groups relative to controls was created. RESULTS: The SVM-classifier afforded modest discrimination between subjects with first-episode schizophrenia/ schizophreniform disorder and controls, with an area under the curve (AUC) value of 0.75 and overall accuracy of 73.4%. The resulting discriminative spatial map revealed a complex pattern of regional volumetric abnormalities affecting both gray and white matter fronto-limbic regions bilaterally, long associative fasciculi, besides the third and lateral ventricles. A poor diagnostic performance was observed in the pairwise comparisons between BD-I and psychotic MDD versus controls. Also, the SVM-classifier failed to predict 1-year prognosis (remitting versus non-remitting course) in the first-episode schizophrenia group. CONCLUSION: The present results suggest that at the population level and using a real world sample of affective and non-affective psychotic patients with comorbid substance use disorders and variable disease course, we failed to achieve good discrimination between schizophreniform and affective forms of first-episode psychosis, and also in predicting 1-year prognosis of first-episode schizophrenia patients, using structural images

Background: Bipolar disorder (BD) is a significant cause of perinatal morbidity and mortality. Because BD is hard to detect and treat, these individuals often go without care. This dissertation was designed to: (1) identify the prevalence rates of BD and bipolar-spectrum mood episodes in perinatal individuals, (2) understand pertinent barriers to mental healthcare, and (3) elucidate how to bridge healthcare gaps. Methods: Data sources included: primary qualitative and quantitative data from obstetric clinicians, encounter data from Massachusetts Child Psychiatry Access Program (MCPAP) for Moms, a program aimed at helping clinicians to provide mental healthcare to perinatal patients. Analyses included: descriptive statistics, systematic review and meta-analysis, qualitative data analyses, longitudinal regression analyses, and group-based trajectory modeling. Results: The prevalence of BD in perinatal individuals was 2.6% (95% CI: 1.2 to 4.5%). Twenty to 54.9% were found to have a bipolar-spectrum mood episode. Barriers to mental healthcare for perinatal patients with BD included the paucity of psychiatric resources, difficulties in assessing BD, and stigma towards pharmacotherapy. Obstetric clinicians reported that MCPAP for Moms has helped them feel more comfortable in treating patients with BD. Longitudinal analyses of encounter data corroborated these findings - utilization of the program predicted increased clinician capacity to treat BD. Conclusion: Clinicians for perinatal individuals are being called upon and stepping up to care for complex illnesses like BD. Programs like MCPAP for Moms can help them feel more confident in this role, helping to bridge gaps in perinatal mental healthcare and ensuring that individuals with BD are able to receive appropriate care.

[ES] La investigación de la presente tesis está motivada por el interés en conocer el impacto en el uso de las Tecnologías de la Información y la Comunicación (TIC's) en pacientes con una enfermedad mental grave y crónica, mediante la experimentación realizada con la aplicación web e-Terapia para el control y seguimiento de la sintomatología de pacientes con un Trastorno Bipolar. Esta aplicación ha sido desarrollada por el Servicio de Psiquiatría y Psicología Clínica del Hospital Universitario y Politécnico la Fe de Valencia y se emplea actualmente en el tratamiento psicosocial de pacientes que reúnen una serie de requisitos como estar en estado estable al inicio de la participación, el compromiso de seguir el programa psicoterapéutico programado por el Hospital, disponer de un dispositivo ubicuo inteligente y estar familiarizado con el uso de aplicaciones móviles. Los estudios previos realizados por el doctorando han intentado valorar por un lado, el grado de satisfacción de un grupo de pacientes con una enfermedad mental de carácter crónico al enfrentarse al manejo de herramientas digitales multimedia para su formación educacional, laboral y terapéutica, y por otro, valorar el grado de usabilidad y accesibilidad empleados en aplicaciones informáticas para evaluar y analizar las limitaciones concretas de este tipo de personas, con la finalidad de comprender mejor las barreras que potencian la Brecha Digital para estos colectivos, y buscarles una solución a través de los criterios de usabilidad y accesibilidad adaptados a las necesidades de personas con una enfermedad mental, que complementen las pautas generales de diseño y programación utilizados actualmente. Si bien es cierto que existen numerosas investigaciones en el ámbito médico y sanitario sobre las necesidades, adecuación e impacto de las TIC en colectivos con alguna discapacidad física, existe aún una importante carencia de estudios científicos que valoren y analicen la accesibilidad real en la utilización de las nuevas tecnologías en personas con algún tipo de discapacidad mental, y más concretamente en personas con una enfermedad mental grave y crónica como el Trastorno Bipolar. A nivel social, es muy importante desarrollar herramientas y aplicaciones interactivas que permitan el control directo y eficaz de las personas con trastornos relacionados con la Salud Mental. Estas herramientas o aplicaciones deben estar orientadas a cumplir con una serie de requisitos funcionales y estéticos de interfaz de comunicación hombre-máquina desde el punto de vista de la usabilidad, la accesibilidad y la Experiencia de Usuario (UX), proporcionando así una información valiosa tanto para diseñadores, ingenieros informáticos y programadores como para el personal sanitario involucrado en el desarrollo de nuevos instrumentos de ayuda y control. Mediante el presente trabajo de tesis, no solo se ha recopilado una serie de pautas a seguir para mejorar la Experiencia de Usuario (UX) con e-Terapia que se aplicarán en un futuro próximo para actualizar esta herramienta imprescindible para el tratamiento psicosocial de pacientes con Trastorno Bipolar. La importancia de aumentar la adherencia de los pacientes a dicha aplicación, repercute directamente en su estado mental y en su calidad de vida, lo que obliga a ir mejorando poco a poco este tipo de aplicaciones con la ayuda de los propios pacientes para conocer de primera mano, cómo se sienten al utilizarla. / [CA] La investigació de la present tesi està motivada per l'interés a conéixer l'impacte en l'ús de les Tecnologies de la Informació i la Comunicació (TIC's) en pacients amb una malaltia mental greu i crònica, per mitjà de l'experimentació realitzada amb l'aplicació web e-Terapia per al control i seguiment de la simptomatologia de pacients amb un Trastorn Bipolar. Esta aplicació ha sigut desenvolupada pel Servei de Psiquiatria i Psicologia Clínica de l'Hospital Universitari i Politècnic la Fe de València i s'empra actualment en el tractament psicosocial de pacients que reunixen una sèrie de requisits com estar en estat estable a l'inici de la participació, el compromís de seguir el programa psicoterapèutic programat per l'Hospital, disposar d'un dispositiu intel·ligent i estar familiaritzat amb l'ús d'aplicacions mòbils. Els estudis previs realitzats pel doctorand han intentat valorar d'una banda, el grau de satisfacció d'un grup de pacients amb una malaltia mental de caràcter crònic a l'enfrontar-se al maneig de ferramentes digitals multimèdia per a la seua formació educacional, laboral i terapèutica, i d'un altre, valorar el grau d'usabilitat i accessibilitat empleats en aplicacions informàtiques per a avaluar i analitzar les limitacions concretes d'este tipus de persones, amb la finalitat de comprendre millor les barreres que potencien la Bretxa Digital per a estos col·lectius, i buscar una solució a través dels criteris d'usabilitat i accessibilitat adaptats a les necessitats de persones amb una malaltia mental, que complementen les pautes generals de disseny i programació utilitzats actualment. Si bé és cert que hi ha nombroses investigacions en l'àmbit mèdic i sanitari sobre les necessitats, adequació i impacte de les TIC en col·lectius amb alguna discapacitat física, existix encara una important carència d'estudis científics que valoren i analitzen l'accessibilitat real en la utilització de les noves tecnologies en persones amb algun tipus de discapacitat mental, i més concretament, en persones amb una malaltia mental greu i crònica com el Trastorn Bipolar. A nivell social, és molt important desenvolupar ferramentes i aplicacions interactives que permeten el control directe i eficaç de les persones amb trastorns relacionats amb la Salut Mental. Estes ferramentes o aplicacions han d'estar orientades a complir amb una sèrie de requisits funcionals i estètics d'interfaç de comunicació home-màquina des del punt de vista de la usabilitat, l'accessibilitat i l'Experiència d'Usuari (UX), proporcionant així una informació valuosa tant per a dissenyadors, enginyers informàtics i programadors com per al personal sanitari involucrat en el desenvolupament de nous instruments d'ajuda i control. Per mitjà del present treball de tesi, no sols s'ha recopilat una sèrie de pautes que s'han de seguir per a millorar l'Experiència d'Usuari (UX) amb e-Terapia que s'aplicaran en un futur pròxim per a actualitzar esta ferramenta imprescindible per al tractament psicosocial de pacients amb Trastorn Bipolar. La importància d'augmentar l'adherència dels pacients a la dita aplicació, repercutix directament en el seu estat mental i en la seua qualitat de vida, la qual cosa obliga a anar millorant a poc a poc este tipus d'aplicacions amb l'ajuda dels propis pacients per a conéixer de primera mà, com se senten a l'utilitzar-la. / [EN] The research of this thesis is motivated by an interest in understanding the impact of the use of Information and Communication Technology (ICT) for patients with severe and chronic mental illness, through experimentation carried out with the web application e-Therapy for the control and monitoring of the symptoms of patients with Bipolar Disorder. This application was developed by the Psychiatry and Clinical Psychology Service of La Fe University and Polytechnic Hospital of Valencia, and is currently used in the psychosocial treatment of patients who meet a series of requirements such as being in a stable state at the beginning of participation, having the commitment to follow the psychotherapeutic program programmed by the Hospital, having unrestricted access to a smart device, and being familiar with the use of mobile applications. Previous studies carried out by the doctoral student have attempted to assess, on the one hand, the degree of satisfaction of a group of patients with chronic mental illness when facing the use of digital multimedia tools for their educational, occupational and therapeutic training, and on the other hand, the degree of usability and accessibility of computer applications used to evaluate and analyze the specific limitations of this type of person in order to better understand the barriers that increase the Digital Divide for these groups, and seek a solution through the usability and accessibility criteria adapted to the needs of people with mental illness, which complement the general design and programming guidelines currently in place. Although it is true that there are numerous investigations in the medical and health field on the needs, adequacy and impact of ICT in groups with some physical disability, there is still a significant lack of scientific studies that assess and analyze real accessibility in the use of new technologies in people with some type of mental disability, and more specifically in people with a severe and chronic mental illness such as Bipolar Disorder. At a social level, it is extremely important to develop interactive tools and applications that allow direct and effective control of people with disorders related to Mental Health. These tools or applications must be aimed at meeting a series of functional and aesthetic human-machine communication interface requirements from the point of view of usability, accessibility and User Experience (UX), thus providing valuable information both for designers, computer engineers and programmers as well as healthcare personnel involved in the development of new instruments for help and control. As a result of this thesis project, a series of guidelines has been compiled which can be followed to improve the User Experience (UX) with e-Therapy. These guidelines will be applied in the near future to update this essential tool for the psychosocial treatment of patients with Bipolar Disorder. The importance of increasing patients' adherence to this application has a direct impact on their mental state and quality of life, which means that this type of application is gradually improving with the help of the patients themselves by allowing researchers to get to know how patients feel when they are using it. / Prefasi Gomar, S. (2020). Evaluación de la experiencia de usuario (UX) mediante la aplicación móvil e-terapia orientada al control de la sintomatología en personas con trastorno bipolar [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/158556 / TESIS

Bipolêre versteuring is ‘n kroniese, herhalende en ernstige siekte met ‘n voorkoms van 1 % wêreldwyd. Pasiënte kan psigoties word, selfmoordideasie hê en ook soms aggressief raak. Dikwels moet hulle gehospitaliseer word - ook teen hulle wil, want hulle mag soms geen insig toon nie. Pasiënte mag presenteer met ‘n ko-morbiede toestand, byvoorbeeld substansmisbruik of ‘n persoonlikheidsversteuring. Dit gebeur dikwels dat hulle nie hulle toegewysde rolle, byvoorbeeld dié van gade, broodwinner, ouer of volwasse kind, kan vervul nie. Versorgers van pasiënte gediagnoseer met bipolêre versteuring, word eweneens beïnvloed deur die siekte en die gepaardgaande stigma daarvan. Dit kan vir hulle baie moeilik wees wanneer hulle die verantwoordelikhede en rolle van die pasiënt moet oorneem. Beskou vanuit die oogpunt van ‘n ekologiese sisteemperspektief is die aard van hierdie impak op die maatskaplike funksionering van die versorgers relevant vir maatskaplike werk in die geestesgesondheidsveld. Die verkenning van hierdie impak en die ontwikkeling van ‘n intervensie om die impak aan te spreek het dus die rasionaal van hierdie studie gevorm. Die geïntegreerde biopsigososiale model, binne ‘n ekologiese sisteem perspektief, word aangewend by die psigiatriese instelling waar die navorser werk. Hierdie benadering het dus ook gedien as die vertrekpunt vir die betrokke studie. Die gemengde-metode navorsingsbenadering is tydens hierdie studie benut ten einde ‘n uitgebreide analise van die navorsingsprobleem te verskaf. Die voorgenome studie het binne die kategorie van toegepaste navorsing geval, want die doel daarvan was om ‘n program te ontwikkel om hulp te verleen aan versorgers van individue gediagnoseer met bipolêre versteuring. Die navorser het haar navorsing gerig aan die hand van Rothman en Thomas (1994) se intervensie ontwerp en ontwikkelingsmodel (D&D) deur gebruik te maak van kwalitatiewe en kwantitatiewe metodes. Na afloop van die analise van die kwalitatiewe data, is ‘n unieke psigo-maatskaplike opvoedkundige program, die SEE-SAW program, ontwikkel en toe geïmplementeer. Die konsep van balans versus wanbalans binne die sisteem is essensieel; die navorser se program het ten doel gehad om beter balans binne die sisteem van die pasiënt en versorger te bewerkstellig. Die gevolgtrekkings het duidelik getoon dat die versorger van die bipolêre pasiënt blootgestel is aan ‘n wye spectrum van behoeftes en uitdagings, maar dat intervensies soos die SEE-SAW program van groot waarde mag wees. / Bipolar disorder (BD) is a chronic, recurrent, serious illness that occurs in 1 % of people globally. Patients might become psychotic, suicidal and sometimes violent. They often need to be hospitalised, even against their will because they may have no insight. Patients may have a comorbid condition such as substance abuse or a personality disorder. They are frequently unable to fulfil their assigned roles of spouse, breadwinner, parent or adult child. Caregivers of patients diagnosed with BD are also affected by the illness and the associated stigma. It becomes very difficult for them when they have to take over the responsibilities and roles of the patient. The nature of this impact on the social functioning of the caregivers, understood from an ecological systems perspective, is relevant for social work in the mental health care field. Discovering more about this impact and developing an intervention to curb it therefore formed the rationale for this study. The integrated biopsychosocial model, within an ecological systems perspective, is being used at the psychiatric institution where the researcher works. This approach therefore also served as the point of departure from which this research was conducted. A mixed methods research approach was utilised to provide a comprehensive analysis of the research problem. The proposed study fell into the category of applied research, due to its aim of designing a programme to assist caregivers of people diagnosed with BD. The researcher directed the study according to Rothman and Thomas’s (1994) intervention design and development model (D&D), using qualitative and quantitative methods. After the analysis of the qualitative data a unique psychosocial educational programme, the SEE-SAW programme, was developed and then implemented. The concept of equilibrium versus disequilibrium in the system is central; the researcher’s programme therefore strove towards better equilibrium within the system of patient and caregiver. From the conclusions it is apparent that the caregiver of the BD patient is exposed to a wide spectrum of needs and challenges, but that interventions such as the SEE-SAW programme may be very helpful. / Thesis (PhD)--University of Pretoria, 2014. / Social Work and Criminology / PhD (Social Work) / Unrestricted

No description available.

This study aims to investigate how dimensionality reduction of neuroimaging data prior to training support vector machines (SVMs) affects the classification accuracy of bipolar disorder. This study uses principal component analysis (PCA) for dimensionality reduction. An open source data set of 19 bipolar and 31 control structural magnetic resonance imaging (sMRI) samples was used, part of the UCLA Consortium for Neuropsychiatric Phenomics LA5c Study funded by the NIH Roadmap Initiative aiming to foster breakthroughs in the development of novel treatments for neuropsychiatric disorders. The images underwent smoothing, feature extraction and PCA before they were used as input to train SVMs. 3-fold cross-validation was used to tune a number of hyperparameters for linear, radial, and polynomial kernels. Experiments were done to investigate the performance of SVM models trained using 1 to 29 principal components (PCs). Several PC sets reached 100% accuracy in the final evaluation, with the minimal set being the first two principal components. Accumulated variance explained by the PCs used did not have a correlation with the performance of the model. The choice of kernel and hyperparameters is of utmost importance as the performance obtained can vary greatly. The results support previous studies that SVM can be useful in aiding the diagnosis of bipolar disorder, and that the use of PCA as a dimensionality reduction method in combination with SVM may be appropriate for the classification of neuroimaging data for illnesses not limited to bipolar disorder. Due to the limitation of a small sample size, the results call for future research using larger collaborative data sets to validate the accuracies obtained. / Syftet med denna studie är att undersöka hur dimensionalitetsreduktion av neuroradiologisk data före träning av stödvektormaskiner (SVMs) påverkar klassificeringsnoggrannhet av bipolär sjukdom. Studien använder principalkomponentanalys (PCA) för dimensionalitetsreduktion. En datauppsättning av 19 bipolära och 31 friska magnetisk resonanstomografi(MRT) bilder användes, vilka tillhör den öppna datakällan från studien UCLA Consortium for Neuropsychiatric Phenomics LA5c som finansierades av NIH Roadmap Initiative i syfte att främja genombrott i utvecklingen av nya behandlingar för neuropsykiatriska funktionsnedsättningar. Bilderna genomgick oskärpa, särdragsextrahering och PCA innan de användes som indata för att träna SVMs. Med 3-delad korsvalidering inställdes ett antal parametrar för linjära, radiala och polynomiska kärnor. Experiment gjordes för att utforska prestationen av SVM-modeller tränade med 1 till 29 principalkomponenter (PCs). Flera PC uppsättningar uppnådde 100% noggrannhet i den slutliga utvärderingen, där den minsta uppsättningen var de två första PCs. Den ackumulativa variansen över antalet PCs som användes hade inte någon korrelation med prestationen på modellen. Valet av kärna och hyperparametrar är betydande eftersom prestationen kan variera mycket. Resultatet stödjer tidigare studier att SVM kan vara användbar som stöd för diagnostisering av bipolär sjukdom och användningen av PCA som en dimensionalitetsreduktionsmetod i kombination med SVM kan vara lämplig för klassificering av neuroradiologisk data för bipolär och andra sjukdomar. På grund av begränsningen med få dataprover, kräver resultaten framtida forskning med en större datauppsättning för att validera de erhållna noggrannheten.

Background: Shifting the healthcare payment system from a volume-based to a value-based model has been a significant effort to improve the quality of care and reduce healthcare costs in the US. In 2018, Massachusetts Medicaid launched Accountable Care Organizations (ACOs) as part of the effort. Constructing, assessing, and risk-adjusting quality measures are integral parts of the reform process. Methods: Using data from the MassHealth Data Warehouse (2016-2019), we assessed the loss of community tenure (CTloss) as a potential quality measure for patients with bipolar, schizophrenia, or other psychotic disorders (BSP). We evaluated various statistical models for predicting CTloss using deviance, Akaike information criterion, Vuong test, squared correlation and observed vs. expected (O/E) ratios. We also used logistic regression to investigate risk factors that impacted medication nonadherence, another quality measure for patients with bipolar disorders (BD). Results: Mean CTloss was 12.1 (±31.0 SD) days in the study population; it varied greatly across ACOs. For risk adjustment modeling, we recommended the zero-inflated Poisson or doubly augmented beta model. The O/E ratio ranged from 0.4 to 1.2, suggesting variation in quality, after adjusting for differences in patient characteristics for which ACOs served as reflected in E. Almost half (47.7%) of BD patients were nonadherent to second-generation antipsychotics. Patient demographics, medical and mental comorbidities, receiving institutional services like those from the Department of Mental Health, homelessness, and neighborhood socioeconomic stress impacted medication nonadherence. Conclusions: Valid quality measures are essential to value-based payment. Heterogeneity implies the need for risk adjustment. The search for a model type is driven by the non-standard distribution of CTloss.