#Online Therapy Eases #Depression, #Anxiety in #Primary Care Setting

Postado em

Meg Barbor, MPH

Online computerized cognitive-behavioral therapy (CCBT), both alone and in combination with an Internet support group (ISG), is more effective than usual primary care for the treatment of depression and anxiety, new research shows.

Investigators at the University of Pittsburgh, in Pennsylvania, found that CCBT, when managed by a care manager and when utilized either alone or in combination with ISG, significantly improved depression and anxiety symptoms compared to usual care. However, the addition of an ISG provided no further benefit.

The study is the first randomized trial to evaluate the effectiveness of providing these technologies through a collaborative care program. The model is now up and running in 26 practices in the Pittsburgh area.

“We were able to show this model can be used where there aren’t enough mental health professionals, such as inner cities or rural areas,” lead investigator Bruce Rollman, MD, MPH, University of Pittsburgh School of Medicine, told Medscape Medical News. “I hope this will be practice changing in the US.

“But I want to stress that it’s not just about technology; it’s also about the people,” he said. “What our study showed is that these programs work, but it’s really important to have a human involved.”

The study was published online November 8 in JAMA Psychiatry.

Lack of Data

Numerous trials have proven the effectiveness of collaborative care strategies in the treatment of depression and anxiety, and this approach is known to be superior to usual care from primary care physicians for these conditions.

These programs usually involve nonphysician care managers who contact patients to promote evidence-based treatment protocols for chronic conditions and to monitor patients’ clinical response under the supervision of a primary care physician.

However, challenges have limited the provision of collaborative care in routine clinical practice, and until now, advances in technology that have the potential to overcome these barriers have not been tested. Use of ISGs have grown in popularity around the world, and though anecdotal evidence of their effectiveness has been widely circulated, their effectiveness has not been established in randomized trials.

Eligible patients were required to have Internet and email access. They were also required to have scored 10 or greater on either the seven-item Generalized Anxiety Disorder scale or the nine-item Patient Health Questionnaire and to be free of alcohol dependence, active suicidality, or other serious mental illness.

In response to an electronic medical record prompt, primary care physicians from 26 practices in Pittsburgh referred 2884 patients aged 18 to 75 years to the trial from August 2012 to September 2014.

The study utilized the Beating the Blues CCBT program, which consists of a 10-minute introductory video followed by eight 50-minute interactive sessions that care managers encourage patients to complete every 1 to 2 weeks.

The ISG was password protected, could be accessed by patients via computer or smartphone, and offered discussion boards and links to external resources. The duration of the program was 6 months, and care managers informed primary care physicians of their patients’ progress.

A total of 704 patients met eligibility criteria and were randomly assigned to CCBT alone (n = 301), CCBT+ISG (n = 302), or usual care (n = 101). The majority of patients were white; about 80% were women; and the mean age was 42.7 years.

At 6-month assessment, about 84% of patients who received CCBT alone had started the program, and 37% had completed all eight sessions. In the CCBT+ISG group, 75% had logged into the ISG at least once, of whom 62% provided one or more comments or posts.

At 6-month follow-up, mental health–related quality of life was measured with the 12-Item Short-Form Health Survey Mental Health Composite Scale. Depression and anxiety symptoms were measured with the Patient-Reported Outcomes Measurement Information System (PROMIS). Treatment durability was assessed 6 months later.

Improved Mood, Anxiety

The investigators observed similar 6-month improvements in mental health–related quality of life, mood, and anxiety symptoms in the CCBT+ISG and CCBT-alone cohorts.

However, when compared to patients who received usual care, patients in the CCBT-alone cohort were found to have significant 6-month effect size improvements in PROMIS mood symptoms (effect size, 0.31) and PROMIS anxiety symptoms (effect size, 0.26). The improvements persisted 6 months later.

The investigators also found a dose effect such that the more CCBT sessions a patient completed, the stronger the improvement in effect size (PROMIS mood symptoms in patients who completed ≥4 sessions: effect size, 0.41; patients who completed all eight sessions: effect size, 0.52).

This dose effect confirms the importance of patient engagement, said Dr Rollman. He cited a 2015 study by Prof Simon Gilbody and colleagues in which the investigators found no differences in mood symptoms among 691 primary care patients with depression. The patients were randomly assigned to receive either CCBT or usual care, and the study employed the same CCBT program that Dr Rollman’s team used.

In Dr Gilbody’s study, staff offered minimal support but did not monitor patients’ symptoms or send recommendations to primary care providers. As a result, patient adherence to CCBT was low (median sessions completed, <2).

“This was, predictably, a negative study,” said Dr Rollman. He noted the importance of utilizing a collaborative care model: “Gilbody had the program, but there wasn’t enough human support.”

Dr Rollman predicted that in the near future, CCBT programs will be used increasingly for other conditions, including heart disease, insomnia, tobacco addiction, and substance abuse. He said that an ideal time to use these programs is when patients are undergoing treatments such as dialysis. “These programs are scalable and allow us to mass-customize interventions to provide care to patients,” he said.

“Our report confirms the effectiveness of guided CCBT, highlights the critical importance of patient engagement with online interventions, and provides high-quality evidence about the limits and potential benefits of these emerging technologies,” the authors note.

Important Implications

Commenting on the findings for Medscape Medical News, Lori Raney, MD, who was not involved in the study, noted that there is a national shortage of individuals trained to deliver collaborative care, so technology that extends “the reach of our limited behavioral health workforce ― we call them practice extenders ― allows care managers to take on larger caseloads.

“This is exciting research, and we need more of it,” said Dr Raney, who is a leading authority on the collaborative care model and is chair of the American Psychiatric Association’s Workgroup on Integrated Care. “Now that integrated care is getting ready to take off, we don’t have a workforce to do it. Studies like this are extremely helpful in guiding us to where we need to go.”

However, adherence to online programs remains a barrier to care, she said. She noted that only 37% of patients in the study who received CCBT alone completed all eight sessions.

“That’s one of the drawbacks of the technology. For whatever reason, about half the patients don’t go all the way through the sessions,” she said. “So the question remains: What else is it going to take to get people to engage, or is the fact that they did half of the sessions sufficient?

“There are flaws in our thinking around this, because patients aren’t engaging like we want them to with the technology,” she added. “Maybe we need to have patients involved in the development of the technology. That’s one of the frontiers of research right now ― patients telling us what works for them.”

The study authors note that these findings “have important implications for transforming the way mental health care is delivered in primary care and focus further attention to the emerging field of e-mental health.”

This trial was funded by the National Institute of Mental Health. The computer program used in the study was donated by the University of Pittsburgh Medical Center. The authors, Dr Rollman, and Dr Raney have disclosed no relevant financial relationships.

JAMA Psychiatry. Published online November 8, 2017. Full text



#Robots, #chips y# aplicaciones mejorarán la #calidad de vida de las #personas mayores

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Robots, chips y aplicaciones mejorarán la calidad de vida de las personas mayores en las próximas décadas gracias a los avances de la bioingeniería, según han concluido expertos reunidos en la jornada B-Debate centrada en mejorar la calidad de vida de los ancianos y que ha estado promovida por Biocat y la Obra Social La Caixa.

Expertos de diferentes ámbitos han presentado proyectos como robots asistenciales, aplicaciones móviles, nuevas herramientas de diagnóstico y soluciones en medicina regenerativa encarados a mejorar los sistemas y el bienestar de las personas.

Los mayores sufren más enfermedades que el resto y muy a menudo son patologías crónicas, “que en los próximos años harán aumentar en más de cuatro puntos del PIB los gastos del bienestar de la gente mayor”, ha explicado el director corporativo de Investigación y Estrategia de la Fundació Bancaria La Caixa, Àngel Font.

Ante estas cifras, ve necesario apostar por la investigación con la unión de las ciencias básicas y las ciencias de la vida junto a la ingeniería, pero también promover los esfuerzos éticos y sociales para que las mejoras puedan aplicarse en el día a día de los enfermos.

Según la Organización Mundial de la Salud (OMS) entre los años 2000 y 2050 se duplicará el número actual de personas de más de 60 años, implicando que una de cada cinco superará esta edad dentro de 30 años.

El envejecimiento es uno de los retos más importantes de la sociedad y el paradigma de la tercera edad está cambiando, implicando la necesidad de personalizar más el diagnóstico, ha explicado el director del Instituto de Bioingeniería de Catalunya (IBEC), Josep Samitier.

La opción de los trasplantes de órganos es cada vez menos factible, ya que actualmente hay menos donantes de calidad; ante esta realidad la bioingeniería opta por la medicina regenerativa para reparar tejidos y órganos dañados a causa del envejecimiento.

Investigadores del IBEC trabajan con una bioimpresora 3D para conseguir crear riñones e injertos cardíacos que puedan regenerar las partes muertas de los corazones que hayan sufrido infartos.

Samitier ha explicado que la investigación avanza para que las personas mayores no tengan que desplazarse al hospital con tanta frecuencia, apostando por la monitorización de la salud a partir de las aplicaciones móviles.

El IBEC y el Hospital Clínic han creado la app Health4Sleep para que las personas que sufren apneas de sueño puedan seguir las características de su respiración, movimientos y ronquidos incorporando un dispositivo móvil en su abdomen.

La investigadora Belén Rubio ha presentado el juego Rehabilitation Gaming System, un sistema que mejora la recuperación de pacientes que han sufrido un ictus y que apuesta por la realidad virtual para hacer un seguimiento de la motricidad de las extremidades de las personas.

En la jornada también se presentó un chip para detectar diferentes enfermedades que permite saber si el origen de un ictus es una hemorragia o una trombosis.

#Reconstrucción informática de #fracturas óseas en 3D para facilitar la cirugía (Comput Methods Programs Biomed)

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Investigadores del grupo de investigación Informática Gráfica y Geomática de la Universidad de Jaén han desarrollado un software que permite la reproducción mediante imágenes tridimensionales de una fractura ósea. Los cirujanos podrán obtener información precisa antes de una operación a través de las indicaciones que ofrece el programa. El método identifica de manera automática las distintas partes del hueso dañado y señala las zonas de contacto entre ellos para ayudar a determinar cómo debe ser la reparación.

De esta manera, el cirujano conoce de forma más precisa cómo debe tratar cada fragmento del hueso roto en la planificación preoperatoria, evitando errores de cálculo o incertidumbres que suelen presentarse en intervenciones de gran complejidad. En un estudio, publicado en Computer Methods and Programs in Biomedicine, los investigadores han confirmado el éxito de este método en casos de fractura por impacto en huesos de tobillo, que suelen ser las lesiones de mayor complicación por la cantidad de piezas afectadas. El objetivo es recomponer la fractura de manera automática o semiautomática. Concretamente, el método aumenta la probabilidad de obtener resultados satisfactorios, ya que a los especialistas se les proporciona información adicional antes de la cirugía.

“Una fractura compleja es como la resolución de un rompecabezas 3D en el que se debe colocar cada trozo en su posición correcta. Las aplicaciones informáticas pueden ayudar en este proceso, ya que, mediante imágenes, se identifica la cantidad de piezas y su ubicación. También se detectan cuáles son las zonas de contacto y la posición correcta de cada fragmento”, explica Félix Paulano, investigador de la Universidad de Jaén, autor del artículo.

El método identifica las heridas de una manera exacta partiendo de una imagen obtenida por tomografía axial computarizada (TAC), una prueba diagnóstica de rayos X que permite observar el interior del organismo en forma de cortes transversales o tridimensionales. Así, se puede conocer a priori y de forma precisa si se observan solo partes óseas o también hay músculos, tendones u otro tipo de tejidos blandos que no se diferencian en una radiografía convencional.

Con estas imágenes y la aplicación creada por los investigadores se muestra el número de piezas, la orientación y separación y se marcan las zonas de contacto entre ellas, incluso si la imagen aparece rotada, es decir, que alguna parte no sea visible desde la representación inicial. El sistema completo podría compararse con la marca por separado de cada parte de un puzzle para conocer previamente cómo recomponer la totalidad. El algoritmo creado calcula la zona de unión entre dos fragmentos óseos que se separan y etiquetan desde las imágenes del TAC generándose una serie de puntos para cada trozo de hueso, lo que permite que las partes puedan alinearse de dos en dos.

El enfoque que se muestra en este artículo se aplicó con éxito en diferentes casos de traumas en el área del tobillo, una de las más complicadas en cirugía traumatológica. El sistema calculó de manera precisa en todos los casos clínicos probados que no existían solapamientos o espacios visibles entre los fragmentos.

Además, las pruebas realizadas demostraron que se resuelven también los pequeños desplazamientos que pueden darse de manera inicial en este tipo de fracturas. “La determinación de la zona de contacto solo toma unos segundos para los casos más complejos y podría mejorarse adaptando el algoritmo para su ejecución eficiente de manera más compleja, ya que se basa en el procesamiento individual de cada punto de los fragmentos óseos. De esta forma, el tiempo global podría reducirse considerablemente”, añade el investigador. Los expertos también han verificado este método en otro tipo de daños óseos, como fracturas en hombros.

#Programa de navegação de #pacientes oncológicos quer garantir o cumprimento da# “lei dos 60 dias”

Postado em

Fábio de Oliveira

Em vigor desde maio de 2013, a lei nº 12.732/12 estabelece que o paciente com câncer tem direito a tratamento no Sistema Único de Saúde (SUS) no prazo de 60 dias a partir do diagnóstico em laudo patológico. Mas a “lei dos 60 dias”, como ficou conhecida, ainda está longe de ser cumprida. Uma pesquisa do Datafolha realizada para a ONG Fundação Laço Rosa este ano mostra que, em média, as mulheres com câncer de mama esperam até 4,4 meses para obter o diagnóstico da doença, 3,5 meses entre o diagnóstico e o início do tratamento e 2,6 meses para começar o tratamento com radioterapia na rede pública.

Com o objetivo de promover uma maior adesão à lei no SUS, a ONG americana Global Cancer Institute (GCI) iniciou em agosto o Programa de Navegação de Paciente (PNP) no Rio Imagem, um grande polo de diagnóstico que atende pacientes do SUS provenientes de todos os 92 municípios do estado do Rio de Janeiro. Trata-se de uma parceria entre o GCI e o governo fluminense. O projeto busca resolver as disparidades de saúde e reduzir os obstáculos para o tratamento do câncer em um prazo adequado.

Segunda a mastologista Dra. Sandra Gioia, embaixadora do Global Cancer Institute no Brasil, os chamados navegadores de pacientes, ou NPs, são profissionais de saúde treinados que facilitam a tramitação dos doentes, ajudando-os a superar as barreiras institucionais, socioeconômicas e pessoais para o acesso ao sistema de saúde.

“No nosso caso, escolhemos enfermeiro e assistente-social, porque eles já conhecem o sistema e sabem lidar com o público”, explica ela, que também pertence aos quadros do Instituto Nacional de Câncer, e do Hospital São Francisco, ambos no Rio. Ainda de acordo com a Dra. Sandra, não há experiência de navegação no SUS.

“Cada profissional faz sua parte e joga para o próximo. São múltiplas as barreiras a serem enfrentadas pela regulação no âmbito do SUS. A ausência de transparência nas filas de espera para marcar um exame ou consulta é uma delas, e isso contribui para falta de discernimento sobre o que deve ser priorizado”, diz a Dra. Sandra.

“Atualmente, observamos carência e dificuldades de financiamento de vários serviços em oncologia pelo SUS, desde de exames de rastreamento e diagnósticos, até tratamentos adequados em tempo hábil. A curto prazo, isso só irá agravar as desigualdades encontradas no Brasil.”

A cargo dos navegadores estão serviços como agendamento de compromissos, de diagnóstico e de acompanhamento. Eles também são responsáveis por coordenar a comunicação entre pacientese profissionais de saúde.

“Eles ajudam os pacientes a receber cuidados médicos em tempo hábil, a reduzir os atrasos nos cuidados e taxas de perda de seguimento”, diz a especialista.

No Rio Imagem, um navegador auxiliará as pacientes com câncer de mama a iniciar o tratamento sem muitas delongas.

“Um protocolo específico de NP foi criado para identificar métricas importantes de sucesso, e planejar o treinamento e a implementação do projeto”, revela a mastologista. O grande propósito é fazer valer na prática o que preconiza lei nº 12.732/12 , ou seja, que todos os pacientes com câncer dentro do sistema público comecem o tratamento dentro de 60 dias a partir do diagnóstico.

No polo de diagnóstico, os exames são programados pelo sistema informático nos respectivos departamentos de saúde ou nos centros de saúde dos municípios fluminenses por meio do Sistema de Regulação (SISREG). Cada município tem um número de vagas mensal que é renovado e oferecido pelo sistema. A cidade do Rio de Janeiro tem o maior número de vagas no estado pelo fato de ser a mais populosa.

A paciente recebe uma confirmação de data e hora do procedimento, e chega ao Rio Imagem no dia programado levando os documentos. Após o exame, ela recebe um protocolo de entrega para obter o resultado do teste em 10 dias. No caso das biópsias realizadas no Rio Imagem, todos os fragmentos são enviados para o laboratório da Secretaria Estadual de Saúde, e o resultado é encaminhado diretamente para o Rio Imagem, onde a paciente o receberá.

“No caso de resultado positivo para câncer, ela se reunirá com um assistente-social para obter o resultado pessoalmente, e saber da importância de continuar o acompanhamento clínico”, explica a Dra. Sandra.

“Porém não há nenhuma supervisão para saber se a paciente conseguirá ser encaminhada para tratamento em local especializado.” Essa mulher fica responsável pelo próprio retorno ao SISREG, que deve inseri-la no Sistema de Regulação do Estado (SER), para encaminhamento ao serviço de atenção terciária.

“Existe uma grande preocupação com o tempo para diagnóstico no Rio Imagem porque, além das biópsias de mama realizadas para os municípios, todas as mamografias realizadas no polo com categorias BI-RADS 4 ou 5 são diretamente marcadas para biópsias no próprio Rio Imagem”, prossegue a mastologista.

“As pacientes não são encaminhadas de volta para o SISREG, a fim de melhorar o tempo até o diagnóstico.” Ainda segundo a médica, o Rio Imagem ainda não tem um mecanismo para acelerar o prazo entre o diagnóstico e o tratamento do câncer de mama.

“A introdução do navegador de paciente pode ser uma alternativa para essa lacuna no cuidado da paciente com a doença.”

Para isso, uma das metas é estabelecer a viabilidade do programa no contexto do polo de diagnóstico. Outra é assegurar que pelo menos 70% das pacientes recrutadas com câncer de mama comecem o tratamento dentro do período de 60 dias, auxiliando nas referências hospitalares, fazendo consultas e acompanhando-as para garantir que começaram a receber os recursos terapêuticos.

“O limiar de sucesso é fixado em 70% dos pacientes navegados com sucesso, a fim de alcançar o padrão de risco clínico de aproximadamente 0,70 considerado significativo”, diz.

Segundo a Dra. Sandra, mais de 70% dos pacientes com câncer de mama no Rio de Janeiro não iniciam o tratamento dentro do prazo de 60 dias.


“Portanto, se pudermos melhorar essa estatística para pelo menos 70% das mulheres que iniciam o tratamento dentro de 60 dias, nosso estudo de viabilidade será considerado bem-sucedido”, conclui.

Da experiência no Rio Imagem, a Dra. Sandra observa quatro pontos importantes:

“O PNP está auxiliando na educação das usuárias, influenciando na reflexão dos processos de trabalho dos profissionais de saúde, contribuindo para melhorar a comunicação entre os serviços de saúde, e otimizando tempo e recursos do sistema de saúde”.

O projeto de navegação de pacientes pioneiro foi realizado no Harlem, em Nova York, na década de 1990. O objetivo foi melhorar o acesso ao tratamento do câncer num prazo razoável entre os pacientes afro-americanos, hispânicos e pobres com baixos níveis educacionais. Um dos resultados obtidos foi o aumento da taxa de sobrevida de cinco anos para o câncer de mama, de 39% para 70%. Conforme a mastologista, outras experiências semelhantes a essa no Brasil não vingam porque não estão ligadas à estrutura do governo do estado, a exemplo do Rio Imagem. Já há até o interesse em contratar a navegadora que está participando da pesquisa, segundo ela.

Minas Gerais

Em Belo Horizonte, o Projeto de Navegação de Pacientes é resultado de uma parceria do GCI com a Universidade Federal de Minas Gerais (UFMG).

“O principal objetivo é avaliar se a implementação de um navegador de pacientes consegue melhorar o tempo para início e conclusão do tratamento radioterápico de pacientes oncológicos”, diz a oncologista Dra. Angélica Nogueira Rodrigues, que é professora e pesquisadora da UFMG. Outros quesitos que também serão verificados são: se houve diminuição do nível de estresse e aumento do grau de satisfação por meio de questionários de qualidade de vida, além da identificação e da descrição dos principais empecilhos observados.

#Empoderamento do #paciente: um caminho sem volta

Postado em

Roxana Tabakman

Os dispositivos médicos são, cada vez mais, destinados aos pacientes consumidores. Os vestíveis (wearables), os produtos on-line que garantem atendimento de saúde a distância, e os aplicativos para smartphones são apenas a parte mais visível da mudança.

“A mudança do e-health (como saúde por meio eletrônico) para o i-health (de IA, ou inteligência artificial), e na sequência para x-health (sendo o x, nesse contexto, sinônimo de experiência/usabilidade) mostra que os dispositivos médicos são pensados nos consumidores. E que o maior desafio agora não é o processo nem a tecnologia: é mudar a cultura”, disse Lucien Engelen, diretor do REshape Center for Health(care) Innovation da Radboud University, da Holanda, um dos gurus da inovação no cuidado da saúde, em palestra no HIS Healthcare Innovation Show, realizado em outubro, em São Paulo.

O paciente como foco está em todas as indústrias que compõem o ecossistema de cuidado da saúde.

“Depois da consulta com o médico, 80% das pessoas procuram informações no Google. Essa visão está dentro das empresas, e para nós significa que falar para os médicos não é tudo”, disse Reinaldo Capezzuto, líder de inovação e chefe dos programas voltados a pacientes, da MSD.

“O que os médicos querem? Eles reclamam que 50% do que recebem da força de vendas hoje está on-line, eles não precisam disso. O que eles nos dizem que apreciariam é ajuda para se conectar melhor com os pacientes.”

Capezzuto expressa a ideia de forma bem clara. “A caixinha de remédios é commodity. A força de vendas (da indústria farmacêutica) vai ser logo um prestador de serviços na relação entre médico e paciente”.

Visão centrada no paciente

Na indústria farmacêutica se fala muito de patient centricity(do inglês, centralização no paciente). O conceito não tem ainda definição acadêmica, mas uma das propostas[1] é “colocar o paciente primeiro lugar, em um engajamento aberto e sustentável, para obter de maneira respeitosa e com compaixão, a melhor experiência e o melhor resultado para ele e para a família.” O conceito essencial é “engajamento do usuário ao longo do ciclo de vida do produto” um aspecto considerado chave para os produtos farmacêuticos.

O relacionamento dos pacientes com a indústria, que até agora se limitou à participação em ensaios clínicos ou educação por meio dos profissionais da saúde, está mudando. As empresas decidiram virar parceiras dos pacientes para enfrentar junto com eles os fatores que influem negativamente a adesão ao tratamento.

Na feira da inovação onde se exibiu o que está chegando ao mercado em termos de tecnologia e inovação para a saúde, não se fala mais em produtos, como antigamente, mas em soluções para os usuários. O Ricoh Smart Doctor, por exemplo, é oferecido para simplificar o dia-a-dia dos profissionais de saúde automatizando todo o processo de atenção, desde a recepção até o diagnóstico e a definição do tratamento. Com recursos de computação cognitiva, ele faz cruzamento da literatura científica com os dados clínicos do paciente. Um ponto interessante do sistema é que, segundo foi ressaltado, ele recebe a informação por áudio, na linguagem coloquial; ou seja, pode-se dizer dor de cabeça, não é necessário usar o termo médico cefaleia.

Uma outra pista sobre como provavelmente será o futuro do setor foi oferecida pelo português Miguel Duarte, líder de estratégia e práticas de consumo da EY Brasil. Duarte falou em “uberização”, o que para ele é “colocar a informação nas mãos dos pacientes e obrigar os médicos a falar com outros médicos e com todas as empresas que compõem o ecossistema do paciente”.

“O foco no paciente é dinâmico, e as empresas oferecem o que o indivíduo conectado quer”, disse Alexandre Grandini, diretor da área de Healthcare da Cognizant. A empresa, de tecnologia e negócios, apresentou a solução HealthActivate, que possibilita monitorar, por meio de relógios e pulseiras inteligentes, a ocorrência de situações de risco relacionadas à saúde, e promete contribuir para evitar internações, por meio da análise de dados.

“A ideia é proporcionar os melhores resultados para o paciente, de forma personalizada.”

Os novos pacientes

Uma pesquisa do Medscape[2] feita com médicos e pacientes mostrou que os consumidores desejam ser mais autônomos, realizar mais autodiagnósticos, ter aceso aos próprios dados em prontuários, e ver os resultados de exames de laboratório de maneira imediata, sem grande preocupação com a privacidade e a segurança dos dados médicos.

Durante o evento, Luciana Holtz, do Oncoguia — portal interativo voltado a pacientes e familiares de pacientes com câncer —, falou do perfil dos novos pacientes. “Alguns apenas acessam, outros são engajados, outros empoderados. Mas sem dúvida eles se preparam para a consulta médica e já começam a tomar decisões compartilhadas.”

Lucien Engelem, que abraça a causa “patients included” com forca de militante, dedica-se a criar consciência de que os pacientes devem fazer parte de todo o processo. Um exemplo: desde 2015, no centro médico da universidade onde ele trabalha, os alunos têm aulas também com pacientes. Ele alerta: “não se enganem. Muitas vezes pensamos que sabemos o que os nossos pacientes querem, mas com frequência não temos ideia.”[3]

Muitos exemplos sustentam a mudança no setor, e o próprio evento era uma materialização das escolhas permanentes que a internet passou a oferecer nos últimos anos. O HIS Healthcare Innovation Show foi uma grande arena, onde ocorriam quatro palestras de forma simultânea. Comodamente sentado na poltrona, o público tinha aceso visual a todas elas, e passava o som de uma conferência para outra simplesmente mudando a frequência dos fones de ouvido. Em um dos lados do quadrilátero, por exemplo, o presidente do Hospital Israelita Albert Einstein, Sidney Klajner, destacava.

“Temos no hospital um aplicativo que informa ao paciente sobre a dose de insulina a ser tomada”. Mas ele, como quase todos os palestrantes da feira de inovação em saúde fez questão de repetir: nenhuma tecnologia vai substituir o médico.
O maior empecilho enfrentado por esta revolução parece mesmo não ser tecnológico, segundo destacado em várias das palestras. Gustavo Gusso, diretor de Amil, mencionou que a empresa tenta mudar a cultura de que o médico deve tomar a decisão sozinho.

“Queremos colocar na cabeça dele que ele precisa perguntar se os pacientes concordam”, disse Gusso, numa alusão ao projeto “Decisão Compartilhada e Segurança do Paciente”, da Amil, que este ano ganhou um prêmio de reconhecimento da Agência Nacional de Saúde Suplementar (ANS). Trata-se, entre outras iniciativas, de um sistema de remuneração variável, que paga melhor ao médico que envolve o paciente nas decisões. Um projeto que mexeu (e segue mexendo) com culturas enraizadas.

“Foi preciso humildade, foi preciso perceber que o que a gente estava fazendo não era o melhor”, disse Gusso ao Medscape.

#12 Apps That Could Help Your Practice

Postado em

Paul Cerrato, MA

More Mobile Medical Apps Have FDA Approval

Over 165,000 mobile health apps are estimated to be on the market.[1] Despite their popularity, few physicians recommend them to patients because they question their reliability and suspect many of being little more than digital snake oil. One survey suggests that only 15% of doctors encourage patients to use health apps.[2]

The same cannot be said of mobile apps for physicians, which are used by many clinicians to accomplish a variety of clinical and practice management tasks. Eighty-six percent of healthcare professionals say that mobile apps will improve their efficiency in providing patient care, and 59% use smartphones to access medical research.[3]

Despite the popularity of these apps, clinicians still face the challenge of separating the wheat from the chaff. The guidelines on mobile medical apps issued by the US Food and Drug Administration (FDA) can help them make an informed choice.

The agency has established a risk-based approach to regulating medical apps to ensure their safety and effectiveness.[4,5] Class I apps are deemed to be low-risk. Class II apps pose a moderate risk. Certain apps are labeled class III if they pose a high risk for harm when poorly developed.

The agency is focusing most of its attention on a subset of mobile apps that meet the regulatory definition of medical devices, which “are intended to be used as an accessory to a regulated medical device” or “transform a mobile platform into a regulated medical device.”

Popular Apps Among Physicians

Apps from several companies that have met FDA standards are worth considering. AirStrip Technologies, for example, has received FDA clearance for its remote patient monitoring mobile app. The app, which is intended for professional use only, allows physicians to see patient data on bedside monitors, ECG machines, and a facility’s electronic medical record (EHR) from virtually anywhere in the world, assuming a reliable wireless Internet connection is available. The mobile app lets clinicians review patients’ vital signs, cardiac waveforms, labs, medications, intakes and outputs, and allergies, among other essentials.

Withings, a division of Nokia, has developed a smart body scale and a blood pressure device that are accompanied by mobile apps. Both have the FDA seal of approval, and both can be prescribed by a physician, knowing that they have met safety and effectiveness standards. These digital tools enable a patient with congestive heart failure to track dangerous changes in body weight, or alert the patient to hypertensive spikes.

WellDoc has also gained traction among physicians with a FDA-cleared mobile app called BlueStar, the first diabetes monitoring system that requires a prescription. When patients input blood glucose readings from their meter into the system, the software wirelessly sends clinicians summarized statistics and analytics to help them personalize the advice they give to patients.

But many medical apps that may meet the FDA’s regulatory definition of a medical device pose little or no risk to the public. Apps that automate simple tasks for a clinician is one such category. So are mobile apps that let providers interact more easily with an EHR. Some apps help clinicians track or manage patient immunizations by assessing the need for immunization and providing a consent form and immunization lot numbers.

Tools for Patient and Practice Management

Countless mobile apps don’t fall into the medical device category, and many of these solve everyday problems. The Dragon Medical 360/Mobile Recorder from a company called Nuance has been well received by physicians because it lets them securely dictate notes at the point of care using a smartphone or tablet. Once the notes have been dictated, they can be sent wirelessly to a transcription service.

Clinicians can view their schedule and their patients’ names in the Dragon app and then tap on an appointment to begin recording, choosing a report type, such as discharge summary, history, progress note, or physical consultation. The recording is automatically synchronized with the patient’s name. The dictated notes are then put into a queue so that they can be sent for transcription through a wireless Health Insurance Portability and Accountability Act-compliant electronic “tunnel.” The app also removes appointments from the list once the dictations are finished.

Medscape also offers a wide variety of practice management and clinical resources on its mobile app. The app offers access to Medscape Consult, a physician-only community with 250,000 members that lets them view thousands of real, ongoing cases across specialties; crowdsource answers to clinical questions; and share insights with their peers. The Medscape app also provides a comprehensive set of tools to support clinicians’ professional needs, including decision-making support at the point of care, medical news and perspectives from thought leaders across medicine, and continuing medical education courses to support professional development. Digital tools include medical calculators, formulary information, a drug interaction checker, a drug reference, Medline, practice guidelines from medical associations and government agencies, and FDA announcements.

Mobile apps from 3D4Medical, on the other hand, meet a different need among clinicians. Complete Anatomy, for example, is a collection of anatomical drawings that go way beyond the flat images most physicians are accustomed to seeing in medical textbooks. The company also offers apps on orthopedic patient education and rehabilitation medicine for lower limbs, and an app called Content Builder, intended for educators who want to create interactive anatomy lessons for students. Clinicians, students, and educators praise these apps because they provide three-dimensional views of the human body that previously were possible only through surgery or cadaver dissection.

AthenaCollector from Athena Health, an app-based practice management and medical billing service, has become popular with many medical office managers because it does much of the heavy lifting that staffers were once expected to do. The system lets office staff see claims and appointments in real time on a “workflow dashboard.” The tool displays patients’ demographics, insurance information, appointment history, outstanding balances, payment plans, billing summaries, and e-payment activities. Office staff will find the program’s ability to verify a patient’s insurance eligibility a timesaver as well. The app also alerts users to any insurance issues before the patient’s visit.

Athenacollector uses a patented rules engine that contains the claim submission requirements of most third-party payers, helping to catch billing errors early on and reducing the odds of the claim bouncing back because someone in the office forgot to do everything just so. The company claims this feature reduces denials and ensures faster payment. Athena Health also has a back-office services division that sends out claims, posts payments, and helps providers resolve claim denials.

Finding the Best Apps for Doctors

The reviewers and analysts at SoftwareAdvice, a software reviewer company based in Austin, Texas, provide helpful advice to clinicians looking to choose the best practice management apps. Although clinicians often turn to a handful of colleagues for their opinions on the best business-related apps, SoftwareAdvice has collected hundreds of user reviews that can help a practice reach a more informed opinion.

For instance, an app from Kareo Billing earned a 4-star rating (out of 5) on the basis of over 400 user reviews. Kareo’s web-based and mobile system includes scheduling, task and patient record management, and medical billing, among other practical features. Software Advice provides links to demo videos for each of the vendors it reviews, as well as the number of times that Software Advice has recommended the program to users.

Other apps that have received high ratings from Software Advice include drchrono, an EHR system that also offers scheduling, billing, and patient reminders; NueMD, which provides billing and claims processing, scheduling, and patient registration; and Aprima EHR, which, in addition to offering many of the features mentioned above, does revenue cycle management, customizable reports, and integration with clearinghouses.

To arrive at their recommendations, Software Advice uses methodology based on a product’s capability and value, ranking products and services considered frontrunners into four quadrants: Leaders (all-around strong apps), Masters (apps with specialized functionality), Pacesetters (apps with strong features, but that don’t rate as highly on value as apps designated Leaders), and Contenders (apps that offer specialized capabilities at a high price).[6]

For example, when a EHR is evaluated, the scores are generated by Software Advice’s methodology are based on feedback from clinicians and staffers who use the system, along with the product’s features and how many customers the vendor has.

Mobile apps may not be the godsend entrepreneurs would like us to believe, but they have the potential to make major inroads in many medical practices, helping your team be more productive.

#Machine Learning, #MRI #Accurately Identify Suicidal Intent

Postado em

Pauline Anderson

Machine learning combined with fMRI accurately identifies young adults with suicidal thoughts, new research shows.

Using fMRI and computer-generated algorithms to measure the brain’s response to death, suicide, and other concepts, researchers reliably distinguished youth with suicidal thoughts from control persons and accurately identified individuals who had made a suicide attempt.

This is important because most people do not report suicidal feelings. Research shows that almost 80% of patients who die by suicide denied they had suicidal thoughts during their last contact with a mental healthcare professional.

“The biological processes that are involved in suicidal thinking and behavior reflect changes in the way people feel and think about related concepts,” study author David Brent, MD, a child and adolescent psychiatrist and professor of psychiatry, University of Pittsburgh Medical Center and School of Medicine, told Medscape Medical News.

Dr David Brent

“This approach gives us hope that we will be able to more precisely target those issues and be able to help more people.”

The study was published online October 30 in Nature Human Behavior.

Machine Learning Classifier

The study included 17 patients with suicidal thoughts, many of whom had been recently discharged from an inpatient facility, and 17 healthy volunteers who had no personal or family history of psychiatric disorder or suicide attempts.

The groups were matched with respect to intelligence, sex ratio (24% male) and age (mean age, about 22 years).

The researchers assessed history of suicide attempt with the Suicide History Form and Suicide Intent Scale. They assessed severity of suicidal ideation using the interviewer-rated Columbia-Suicide Severity Rating Scale (C-SSRS) and the self-reported Adult Suicide Ideation Questionnaire (ASIQ).

While the participants were exposed to various stimuli, researchers used fMRI to view various brain regions.

The stimuli included three word groups, each of which had 10 words. The word groups were related to suicide, negative affect, and positive affect.

The 30 stimulus items were presented six times in random order. Each item was displayed for 3 seconds. The 3-second display was followed by a four-second interval, and longer intervals were included periodically.

Participants were asked to actively think about the concepts to which the stimulus words referred.

A psychiatrist was present during testing of the patients with suicidal ideation “to ensure they were safe when they were invited to think about these things,” said Dr Brent.

The researchers distinghished the groups through the use of computer-generated algorithms.

“When you’re looking at patterns of brain activation, you’re talking about a huge amount of data,” said Dr Brent. “So in order to separate the responses and classify them, you can’t use conventional methods very effectively.”

The machine-learning classifier identified suicidal individuals with a very high accuracy rate (0.90; P < .000001), correctly identifying 15 of the 17 suicidal participants and 16 of the 17 control persons (sensitivity = 0.88, specificity = 0.94, positive predictive value [PPV] = 0.94, negative predictive value [NPV] = 0.89).

Key Brain Regions

The investigators found that the high degree of accuracy in classification remained after statistically controlling for group differences, such as variations in anxiety and history of childhood trauma.

The concepts that most strongly distinguished the groups were death, cruelty, trouble, carefree, good, and praise.

The most discriminating brain regions included the left superior medial frontal area, the medial frontal/anterior cingulate, the right middle temporal area, the left inferior parietal area, and the left inferior frontal area. All these regions have repeatedly been strongly associated with self-referential thought.

“It seemed to indicate that if you gave a word like ‘suicide’ or ‘death,’ the ideators would think about ‘my death,’ whereas the controls would just think of the concepts of death without necessarily thinking of themselves,” said Dr Brent.

For individuals with suicidal thoughts, there also appeared to be some disconnection in prefrontal activation, said Dr Brent.

“When healthy people experience a negative thought or a negative emotion, they are able to effectively redirect it by activating parts of the prefontal cortex to modify things. We didn’t see that to the same extent in the people who were suicidal.”

An intervention such as cognitive-behavioral therapy may help change the way a patient thinks about these concepts, said Dr Brent.

He noted that researchers have developed a game that conditions people to associate “self” with positive thoughts and words related to “suicide” with negative thoughts. Use of this game has resulted in decreased self-harm and suicidal behavior, he said.

“So you may be able to try to help people uncouple things that are driving them towards unhealthy conclusions and behavior.”

The machine-learning approach could also identify when patients are improving and are becoming less fixated on suicide. “In that way, it could also have a therapeutic benefit,” said Dr. Brent.

Neural Signatures

The authors noted that the six concepts that were altered in those with suicidal ideation include items from all three stimulus categories ― one related to suicide, two negative concepts, and three positive concepts.

“The valuation of what is important and good in life and what is not seems to be altered in ideators,” the authors write. “Our results provide a neurally based, quantitative measure of this alteration.”

In previous research, the study’s lead author, Marcel Adam Just, PhD, DO Hebb Professor, Department of Psychiatry, Carnegie Mellop University, Pittsburgh, identified the neural “signatures” of different emotions.

Using those algorithms, he and his colleagues identified the “signatures” for “sadness,” “shame,” “anger,” and “pride” within the neural representations of the six concepts.

In the group with suicidal ideation, the concept of “death” evoked more shame than in the control group, whereas the concept of “trouble” evoked more sadness. In addition, “trouble” evoked less anger and the positive concept “carefree” evoked less pride in the group with suicidal ideation.

This type of neurally acquired information may provide specific targets for intervention. For example, said Dr Brent, if a suicidal patient is feeling a lot of shame, a psychotherapist could talk about this with the patient.

“It may give us a sense of things that are driving people toward suicide that they may or may not be able to express explicitly.”

Within the suicidal ideation group, the machine-learning classifier was able to distinguish the nine patients who had made a suicide attempt from participants who had not attempted suicide.

The concepts that best discriminated between those who attempted suicide and those who did not were “death,” “lifeless,” and “carefree.” These terms include two suicide-related concepts and one positive concept. The most discriminating brain regions here were the left superior medial frontal area, the medial frontal/anterior cingulate, and the right middle temporal area.

“Fascinating” Finding

There were also differences in emotional signatures between those who had attempted suicide and those who had not. For example, the concept of death evoked less sadness in those who attempted suicide.

“We speculate that for those who are conflicted about engaging in a suicidal act, the thought of facilitating death is shameful, whereas those ideators who have made an attempt show greater attraction to and acceptance of death, and hence less sadness in thinking about it,” the authors note.

The ability of the machine-learning approach to identify people who had attempted suicide and the fact that they had a different emotional experience than those with suicidal thoughts who had not made an attempt were “the most fascinating” aspects of the study.

Again, this may point to some therapeutic possibilities, he said.

The researchers did not investigate sex differences in patterns of thinking when exposed to the various concepts.

Dr Brent acknowledged that some suicidal patients may not want others to know what they are planning and so might simply block out thoughts that would give away their intentions.

At present, it is not practical to use fMRI clinically to identify patients with suicidal ideation. But Dr Brent and his colleagues hope to eventually develop a simple computer task or screening test to identify people at risk.

Dr Just is investigating the use of EEG instead of fMRI, which would be less expensive and more widely accessible.

Other researchers are using machine-learning and data from electronic health records to identify patients who are at risk of attempting suicide within the following 7-day period, said Dr Brent

He noted that using machine-learning of neural representations of suicide is “not a silver bullet.” He described the new research as “proof of concept.”

“It’s a way of opening a window into how people think, and possible mechanisms, but in terms of public health ways of identification, I think that screening either though electronic health record or other kinds of self-report, or through computer tasks, will be a much more efficient way to go.”

Pioneering Research

Commenting on the study for Medscape Medical News, E. David Klonsky, PhD, professor, Department of Psychology, University of British Columbia, Vancouver, Canada, whose research interests include suicide, described it as “fascinating” and “pioneering.”

“It combines two promising technologies ― machine learning and brain imaging ― to advanced knowledge about suicide risk and prediction.”

However, said Dr Klonsky, like many studies of new approaches, there are considerable obstacles to applying these methods to improve risk detection and prevention.

For example, he said, in real-world clinical settings, most patients have depression or another psychiatric disorder, and health professionals try to identify those at heightened risk for suicide “above and beyond their psychiatric diagnosis.”

But this study compared individuals with suicidal ideation to healthy control persons who had no history of suicidal ideation and no personal or family history of a psychiatric disorder.

“As a result, differences observed in the study between suicide ideators and controls could be due to differences between one group with psychiatric disorders ― the ideators ― and one group without such disorders ― the controls.”

Like Dr Brent, Dr Klonsky also found the ability of the machine-learning approach to distinguish suicidal ideators who had attempted suicide from those who had not was “the most exciting” finding.

“Most commonly cited risk factors for suicide, such as depression and hopelessness, are strong correlates of suicidal ideation but are poor predictors of attempts among ideators. If the study’s technique can illuminate differences between attempters and ideators, that could advance both suicide theory and prevention.”

The research was partially supported by the National Institute of Mental Health and an Endowed Chair in Suicide Studies at the University of Pittsburgh School of Medicine. The study authors and Dr Klonsky have disclosed no relevant financial relationships.

Nat Hum Behav. Published online October 30, 2017. Abstract