ABSTRACT
AIM: Explore key factors influencing future expectations for the production of evidence from comparative effectiveness research for drugs in the USA in 2020 and construct three plausible future scenarios. MATERIALS & METHODS: Semistructured key informant interviews and three rounds of modified Delphi with systematic scenario-building methods. RESULTS & CONCLUSION: Most influential key factors were: health delivery system integration; electronic health record development; exploitation of very large databases and mixed data sources; and proactive patient engagement in research. The scenario deemed most likely entailed uneven development of large integrated health systems with pockets of increased provider risk for patient care, enhanced data collection systems, changing incentives to do comparative effectiveness research and new opportunities for evidence generation partnerships.
Subject(s)
Comparative Effectiveness Research/economics , Comparative Effectiveness Research/methods , Drug Discovery/economics , Drug Discovery/methods , Prescription Drugs/economics , Comparative Effectiveness Research/trends , Databases, Factual , Delivery of Health Care , Delphi Technique , Drug Discovery/trends , Electronic Health Records , Humans , Interviews as Topic , Patient Participation , United StatesABSTRACT
Introducción. El uso clínico del mindfulness ha aumentado en los últimos años, y la Mindful Attention Awareness Scale (MAAS) se ha convertido en uno de los instrumentos más empleados para su medida. El objetivo de esta investigación fue analizar la eficacia del entrenamiento en mindfulness y las propiedades psicométricas de las puntuaciones de la MAAS en una muestra clínica mediante el modelo de Rasch. Métodos. Se seleccionaron 199 sujetos con sintomatología ansioso-depresiva. El grupo experimental (n = 103) recibió un entrenamiento grupal en mindfulness y el grupo control (n = 96) un tratamiento ambulatorio convencional con la misma duración. Se analizaron las puntuaciones pre y pos en la MAAS para valorar la eficacia del entrenamiento, las propiedades psicométricas de las puntuaciones y el funcionamiento diferencial de los ítems (DIF) usando el Modelo de Escalas de Calificación (MEC). Resultados. Los ítems 9 y 12 desajustaron, el ítem 9 mostró DIF, y se observaron problemas de traducción al castellano en los ítems 5, 9 y 12. Se decide repetir el análisis eliminándolos. Los resultados de la versión reducida MAAS-12 mostraron valores adecuados en dimensionalidad, ajuste y fiabilidad. Conclusiones. Contrariamente a los resultados de otros trabajos, la MAAS fue sensible al cambio producido por el entrenamiento. La versión habitualmente empleada presenta problemas métricos y de traducción y debe revisarse. La escala MAAS-12 es métricamente mejor que la habitualmente empleada, pero adolece de infrarrepresentación del constructo. Se recomienda construir instrumentos desde una perspectiva teórica coherente, de modo que todas las facetas del atributo se vean representadas (AU)
Introduction. The clinical use of mindfulness has increased recently, and the Mindful Attention Awareness Scale (MAAS) has become one of the most used tools to measure it. The aim of this study was to test the effectiveness of mindfulness training and analyzing the psychometric properties of the MAAS scores in a clinical sample using the Rasch Model. Methods. One hundred and ninety-nine participants with mood-anxiety clinical symptoms were recruited. The experimental group (n = 103) received mindfulness training, and the control group (n = 96) a conventional outpatient treatment for the same duration. The pre-post MAAS scores were analyzed to test the effectiveness of training, the psychometric properties of the scores, and differential item functioning (DIF) using the Rating Scale Model (RSM). Results. Misfit in items 9 and 12, DIF in item 9, and Spanish translation problems in the items 5, 9 and 12 were observed. The repetition of the analysis without these items was decided. Appropriate dimensionality, fit and reliability values were obtained with the short version, MAAS-12. Conclusions. Contrary to previous studies, the MAAS was sensitive to treatment-associated change. However, the commonly used MAAS has some translation and metric problems, and should be revised. MAAS-12 is a better scale than MAAS but suffers from construct under-representation. Constructing tools from a coherent theoretical perspective is suggested, so that all mindfulness facets are represented (AU)
Subject(s)
Humans , Male , Female , Young Adult , Adult , Middle Aged , Psychometrics/methods , Psychometrics/trends , Anxiety/diagnosis , Depression/diagnosis , Depression/psychology , Psychometrics/instrumentation , Psychometrics/organization & administration , Data Analysis/methods , Analysis of Variance , Manifest Anxiety Scale/standards , Comorbidity , Reproducibility of Results/methods , Evaluation of the Efficacy-Effectiveness of Interventions , Comparative Effectiveness Research/methods , Comparative Effectiveness Research/trendsABSTRACT
Hospital-based comparative effectiveness (CE) centers provide a model that clinical leaders can use to improve evidence-based practice locally. The model is used by integrated health systems outside the US, but is less recognized in the US. Such centers can identify and adapt national evidence-based policies for the local setting, create local evidence-based policies in the absence of national policies, and implement evidence into practice through health information technology (HIT) and quality initiatives. Given the increasing availability of CE evidence and incentives to meaningfully use HIT, the relevance of this model to US practitioners is increasing. This is especially true in the context of healthcare reform, which will likely reduce reimbursements for care deemed unnecessary by published evidence or guidelines. There are challenges to operating hospital-based CE centers, but many of these challenges can be overcome using solutions developed by those currently leading such centers. In conclusion, these centers have the potential to improve the quality, safety and value of care locally, ultimately translating into higher quality and more cost-effective care nationally. To better understand this potential, the current activity and impact of hospital-based CE centers in the US should be rigorously examined.
Subject(s)
Comparative Effectiveness Research/trends , Hospitals/trends , Patient Care/trends , Quality of Health Care/trends , Safety Management/trends , Translational Research, Biomedical/trends , Comparative Effectiveness Research/standards , Hospitals/standards , Humans , Patient Care/methods , Patient Care/standards , Quality of Health Care/standards , Safety , Safety Management/standards , Translational Research, Biomedical/methods , United StatesABSTRACT
While the United States leads the world in many measures of health care innovation, it has been suggested that it lags behind many developed nations in a variety of health outcomes. It has also been stated that the United States continues to outspend all other Organisation for Economic Co-operation and Development (OECD) countries by a wide margin. Spending on health goods and services per person in the United States, in 2007, increased to $7,290 - almost 2(1/2) times the average of all OECD countries. Rising health care costs in the United States have been estimated to increase to 19.1% of gross domestic product (GDP) or $4.4 trillion by 2018. The increases are illustrated in both public and private sectors. Higher health care costs in the United States are implied from the variations in the medical care from area to area around the country, with almost 50% of medical care being not evidence-based, and finally as much as 30% of spending reflecting medical care of uncertain or questionable value. Thus, comparative effectiveness research (CER) has been touted by supporters with high expectations to resolve most ill effects of health care in the United States and provide high quality, less expensive, universal health care. CER is defined as the generation and synthesis of evidence that compares the benefits and harms of alternate methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care. The efforts of CER in the United States date back to the late 1970's even though it was officially born with the Medicare Modernization Act (MMA) and has been rejuvenated with the American Recovery and Reinvestment Act (ARRA) of 2009 with an allocation of $1.1 billion. CER has been the basis for health care decision-making in many other countries. According to the International Network of Agencies for Health Technology Assessments (INAHTA), many industrialized countries have bodies that are charged with health technology assessments (HTAs) or comparative effectiveness studies. Of all the available agencies, the National Institute for Health and Clinical Excellence (NICE) of the United Kingdom is the most advanced, stable, and has provided significant evidence, though based on rigid and proscriptive economic and clinical formulas. While CER is making a rapid surge in the United States, supporters and opponents are expressing their views. Part I of this comprehensive review will describe facts, fallacies, and politics of CER with discussions to understand basic concepts of CER.