IMPORTANCE: US health care spending has continued to increase and now accounts for 18% of the US economy, although little is known about how spending on each health condition varies by payer, and how ...these amounts have changed over time. OBJECTIVE: To estimate US spending on health care according to 3 types of payers (public insurance including Medicare, Medicaid, and other government programs, private insurance, or out-of-pocket payments) and by health condition, age group, sex, and type of care for 1996 through 2016. DESIGN AND SETTING: Government budgets, insurance claims, facility records, household surveys, and official US records from 1996 through 2016 were collected to estimate spending for 154 health conditions. Spending growth rates (standardized by population size and age group) were calculated for each type of payer and health condition. EXPOSURES: Ambulatory care, inpatient care, nursing care facility stay, emergency department care, dental care, and purchase of prescribed pharmaceuticals in a retail setting. MAIN OUTCOMES AND MEASURES: National spending estimates stratified by health condition, age group, sex, type of care, and type of payer and modeled for each year from 1996 through 2016. RESULTS: Total health care spending increased from an estimated $1.4 trillion in 1996 (13.3% of gross domestic product GDP; $5259 per person) to an estimated $3.1 trillion in 2016 (17.9% of GDP; $9655 per person); 85.2% of that spending was included in this study. In 2016, an estimated 48.0% (95% CI, 48.0%-48.0%) of health care spending was paid by private insurance, 42.6% (95% CI, 42.5%-42.6%) by public insurance, and 9.4% (95% CI, 9.4%-9.4%) by out-of-pocket payments. In 2016, among the 154 conditions, low back and neck pain had the highest amount of health care spending with an estimated $134.5 billion (95% CI, $122.4-$146.9 billion) in spending, of which 57.2% (95% CI, 52.2%-61.2%) was paid by private insurance, 33.7% (95% CI, 30.0%-38.4%) by public insurance, and 9.2% (95% CI, 8.3%-10.4%) by out-of-pocket payments. Other musculoskeletal disorders accounted for the second highest amount of health care spending (estimated at $129.8 billion 95% CI, $116.3-$149.7 billion) and most had private insurance (56.4% 95% CI, 52.6%-59.3%). Diabetes accounted for the third highest amount of the health care spending (estimated at $111.2 billion 95% CI, $105.7-$115.9 billion) and most had public insurance (49.8% 95% CI, 44.4%-56.0%). Other conditions estimated to have substantial health care spending in 2016 were ischemic heart disease ($89.3 billion 95% CI, $81.1-$95.5 billion), falls ($87.4 billion 95% CI, $75.0-$100.1 billion), urinary diseases ($86.0 billion 95% CI, $76.3-$95.9 billion), skin and subcutaneous diseases ($85.0 billion 95% CI, $80.5-$90.2 billion), osteoarthritis ($80.0 billion 95% CI, $72.2-$86.1 billion), dementias ($79.2 billion 95% CI, $67.6-$90.8 billion), and hypertension ($79.0 billion 95% CI, $72.6-$86.8 billion). The conditions with the highest spending varied by type of payer, age, sex, type of care, and year. After adjusting for changes in inflation, population size, and age groups, public insurance spending was estimated to have increased at an annualized rate of 2.9% (95% CI, 2.9%-2.9%); private insurance, 2.6% (95% CI, 2.6%-2.6%); and out-of-pocket payments, 1.1% (95% CI, 1.0%-1.1%). CONCLUSIONS AND RELEVANCE: Estimates of US spending on health care showed substantial increases from 1996 through 2016, with the highest increases in population-adjusted spending by public insurance. Although spending on low back and neck pain, other musculoskeletal disorders, and diabetes accounted for the highest amounts of spending, the payers and the rates of change in annual spending growth rates varied considerably.
IMPORTANCE: Health care spending in the United States increased substantially from 1995 to 2015 and comprised 17.8% of the economy in 2015. Understanding the relationship between known factors and ...spending increases over time could inform policy efforts to contain future spending growth. OBJECTIVE: To quantify changes in spending associated with 5 fundamental factors related to health care spending in the United States: population size, population age structure, disease prevalence or incidence, service utilization, and service price and intensity. DESIGN AND SETTING: Data on the 5 factors from 1996 through 2013 were extracted for 155 health conditions, 36 age and sex groups, and 6 types of care from the Global Burden of Disease 2015 study and the Institute for Health Metrics and Evaluation’s US Disease Expenditure 2013 project. Decomposition analysis was performed to estimate the association between changes in these factors and changes in health care spending and to estimate the variability across health conditions and types of care. EXPOSURES: Change in population size, population aging, disease prevalence or incidence, service utilization, or service price and intensity. MAIN OUTCOMES AND MEASURES: Change in health care spending from 1996 through 2013. RESULTS: After adjustments for price inflation, annual health care spending on inpatient, ambulatory, retail pharmaceutical, nursing facility, emergency department, and dental care increased by $933.5 billion between 1996 and 2013, from $1.2 trillion to $2.1 trillion. Increases in US population size were associated with a 23.1% (uncertainty interval UI, 23.1%-23.1%), or $269.5 (UI, $269.0-$270.0) billion, spending increase; aging of the population was associated with an 11.6% (UI, 11.4%-11.8%), or $135.7 (UI, $133.3-$137.7) billion, spending increase. Changes in disease prevalence or incidence were associated with spending reductions of 2.4% (UI, 0.9%-3.8%), or $28.2 (UI, $10.5-$44.4) billion, whereas changes in service utilization were not associated with a statistically significant change in spending. Changes in service price and intensity were associated with a 50.0% (UI, 45.0%-55.0%), or $583.5 (UI, $525.2-$641.4) billion, spending increase. The influence of these 5 factors varied by health condition and type of care. For example, the increase in annual diabetes spending between 1996 and 2013 was $64.4 (UI, $57.9-$70.6) billion; $44.4 (UI, $38.7-$49.6) billion of this increase was pharmaceutical spending. CONCLUSIONS AND RELEVANCE: Increases in US health care spending from 1996 through 2013 were largely related to increases in health care service price and intensity but were also positively associated with population growth and aging and negatively associated with disease prevalence or incidence. Understanding these factors and their variability across health conditions and types of care may inform policy efforts to contain health care spending.
IMPORTANCE: US health care spending has continued to increase, and now accounts for more than 17% of the US economy. Despite the size and growth of this spending, little is known about how spending ...on each condition varies by age and across time. OBJECTIVE: To systematically and comprehensively estimate US spending on personal health care and public health, according to condition, age and sex group, and type of care. DESIGN AND SETTING: Government budgets, insurance claims, facility surveys, household surveys, and official US records from 1996 through 2013 were collected and combined. In total, 183 sources of data were used to estimate spending for 155 conditions (including cancer, which was disaggregated into 29 conditions). For each record, spending was extracted, along with the age and sex of the patient, and the type of care. Spending was adjusted to reflect the health condition treated, rather than the primary diagnosis. EXPOSURES: Encounter with US health care system. MAIN OUTCOMES AND MEASURES: National spending estimates stratified by condition, age and sex group, and type of care. RESULTS: From 1996 through 2013, $30.1 trillion of personal health care spending was disaggregated by 155 conditions, age and sex group, and type of care. Among these 155 conditions, diabetes had the highest health care spending in 2013, with an estimated $101.4 billion (uncertainty interval UI, $96.7 billion-$106.5 billion) in spending, including 57.6% (UI, 53.8%-62.1%) spent on pharmaceuticals and 23.5% (UI, 21.7%-25.7%) spent on ambulatory care. Ischemic heart disease accounted for the second-highest amount of health care spending in 2013, with estimated spending of $88.1 billion (UI, $82.7 billion-$92.9 billion), and low back and neck pain accounted for the third-highest amount, with estimated health care spending of $87.6 billion (UI, $67.5 billion-$94.1 billion). The conditions with the highest spending levels varied by age, sex, type of care, and year. Personal health care spending increased for 143 of the 155 conditions from 1996 through 2013. Spending on low back and neck pain and on diabetes increased the most over the 18 years, by an estimated $57.2 billion (UI, $47.4 billion-$64.4 billion) and $64.4 billion (UI, $57.8 billion-$70.7 billion), respectively. From 1996 through 2013, spending on emergency care and retail pharmaceuticals increased at the fastest rates (6.4% UI, 6.4%-6.4% and 5.6% UI, 5.6%-5.6% annual growth rate, respectively), which were higher than annual rates for spending on inpatient care (2.8% UI, 2.8%–2.8% and nursing facility care (2.5% UI, 2.5%-2.5%). CONCLUSIONS AND RELEVANCE: Modeled estimates of US spending on personal health care and public health showed substantial increases from 1996 through 2013; with spending on diabetes, ischemic heart disease, and low back and neck pain accounting for the highest amounts of spending by disease category. The rate of change in annual spending varied considerably among different conditions and types of care. This information may have implications for efforts to control US health care spending.
IMPORTANCE: Health care spending on children in the United States continues to rise, yet little is known about how this spending varies by condition, age and sex group, and type of care, nor how ...these patterns have changed over time. OBJECTIVE: To provide health care spending estimates for children and adolescents 19 years and younger in the United States from 1996 through 2013, disaggregated by condition, age and sex group, and type of care. EVIDENCE REVIEW: Health care spending estimates were extracted from the Institute for Health Metrics and Evaluation Disease Expenditure 2013 project database. This project, based on 183 sources of data and 2.9 billion patient records, disaggregated health care spending in the United States by condition, age and sex group, and type of care. Annual estimates were produced for each year from 1996 through 2013. Estimates were adjusted for the presence of comorbidities and are reported using inflation-adjusted 2015 US dollars. FINDINGS: From 1996 to 2013, health care spending on children increased from $149.6 (uncertainty interval UI, 144.1-155.5) billion to $233.5 (UI, 226.9-239.8) billion. In 2013, the largest health condition leading to health care spending for children was well-newborn care in the inpatient setting. Attention-deficit/hyperactivity disorder and well-dental care (including dental check-ups and orthodontia) were the second and third largest conditions, respectively. Spending per child was greatest for infants younger than 1 year, at $11 741 (UI, 10 799-12 765) in 2013. Across time, health care spending per child increased from $1915 (UI, 1845-1991) in 1996 to $2777 (UI, 2698-2851) in 2013. The greatest areas of growth in spending in absolute terms were ambulatory care among all types of care and inpatient well-newborn care, attention-deficit/hyperactivity disorder, and asthma among all conditions. CONCLUSIONS AND RELEVANCE: These findings provide health policy makers and health care professionals with evidence to help guide future spending. Some conditions, such as attention-deficit/hyperactivity disorder and inpatient well-newborn care, had larger health care spending growth rates than other conditions.
The use of an HPLC bioactivity profiling/microtiter plate technique in conjunction with capillary probe NMR instrumentation and access to appropriate databases effectively short-circuits conventional ...dereplication procedures, necessarily based on multimilligram extracts, to a single, more rapid submilligram operation. This approach to dereplication is illustrated using fungal or bacterial extracts that contain known compounds. In each case the dereplication steps were carried out on microgram quantities of extract and demonstrate the discriminating power of 1H NMR spectroscopy as a definitive dereplication tool.
In many yeast species, the three genes at the centre of the galactose catabolism pathway, GAL1, GAL10 and GAL7, are neighbours in the genome and form a metabolic gene cluster. We report here that ...some yeast strains in the genus Torulaspora have much larger GAL clusters that include genes for melibiase (MEL1), galactose permease (GAL2), glucose transporter (HGT1), phosphoglucomutase (PGM1) and the transcription factor GAL4, in addition to GAL1, GAL10, and GAL7. Together, these eight genes encode almost all the steps in the pathway for catabolism of extracellular melibiose (a disaccharide of galactose and glucose). We show that a progenitor 5‐gene cluster containing GAL 7‐1‐10‐4‐2 was likely present in the common ancestor of Torulaspora and Zygotorulaspora. It added PGM1 and MEL1 in the ancestor of most Torulaspora species. It underwent further expansion in the T. pretoriensis clade, involving the fusion of three progenitor clusters in tandem and the gain of HGT1. These giant GAL clusters are highly polymorphic in structure, and subject to horizontal transfers, pseudogenization and gene losses. We identify recent horizontal transfers of complete GAL clusters from T. franciscae into one strain of T. delbrueckii, and from a relative of T. maleeae into one strain of T. globosa. The variability and dynamic evolution of GAL clusters in Torulaspora indicates that there is strong natural selection on the GAL pathway in this genus.
Some Torulaspora species have galactose gene clusters that are much larger than the classical S. cerevisiae GAL1‐10‐7 cluster. They contain up to eight different genes, coding for the whole pathway for catabolism of melibiose and galactose, and are very variable in structure. They evolved by fusion of three progenitor clusters, each of which contained GAL7‐1‐10‐4‐2 as well as PGM1, MEL1 or HGT1.
Without appropriate cellular models the etiology of idiopathic Parkinson's disease remains unknown. We recently reported a novel patient-derived cellular model generated from biopsies of the ...olfactory mucosa (termed olfactory neurosphere-derived (hONS) cells) which express functional and genetic differences in a disease-specific manner. Transcriptomic analysis of Patient and Control hONS cells identified the NRF2 transcription factor signalling pathway as the most differentially expressed in Parkinson's disease.
We tested the robustness of our initial findings by including additional cell lines and confirmed that hONS cells from Patients had 20% reductions in reduced glutathione levels and MTS 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt metabolism compared to cultures from healthy Control donors. We also confirmed that Patient hONS cells are in a state of oxidative stress due to higher production of H(2)O(2) than Control cultures. siRNA-mediated ablation of NRF2 in Control donor cells decreased both total glutathione content and MTS metabolism to levels detected in cells from Parkinson's Disease patients. Conversely, and more importantly, we showed that activation of the NRF2 pathway in Parkinson's disease hONS cultures restored glutathione levels and MTS metabolism to Control levels. Paradoxically, transcriptomic analysis after NRF2 pathway activation revealed an increased number of differentially expressed mRNAs within the NRF2 pathway in L-SUL treated Patient-derived hONS cells compared to L-SUL treated Controls, even though their metabolism was restored to normal. We also identified differential expression of the PI3K/AKT signalling pathway, but only post-treatment.
Our results confirmed NRF2 as a potential therapeutic target for Parkinson's disease and provided the first demonstration that NRF2 function was inducible in Patient-derived cells from donors with uniquely varied genetic backgrounds. However, our results also demonstrated that the response of PD patient-derived cells was not co-ordinated in the same way as in Control cells. This may be an important factor when developing new therapeutics.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
There is significant histologic and biochemical overlap between nonalcoholic fatty liver disease (NAFLD) and steatohepatitis associated with choline deficiency.
We sought to determine whether ...subjects with biopsy-proven NAFLD and evidence of an inadequate intake of choline had more severe histologic features.
We performed a cross-sectional analysis of 664 subjects enrolled in the multicenter, prospective Nonalcoholic Steatohepatitis Clinical Research Network (NASH CRN) with baseline data on diet composition (from a recall-based food-frequency questionnaire) within 6 mo of a liver biopsy. Food questionnaires were analyzed with proprietary software to estimate daily intakes of choline. Liver biopsies were centrally read, and consensus was scored with the NASH CRN-developed scoring system. Because choline needs vary by age, sex, and menopausal status, participants were segregated into corresponding categories (children 9-13 y old, males ≥14 y old, premenopausal women ≥19 y old, and postmenopausal women) on the basis of the Institute of Medicine's definition of adequate intake (AI) for choline. Deficient intake was defined as <50% AI.
Postmenopausal women with deficient choline intake had worse fibrosis (P = 0.002) once factors associated with NAFLD (age, race-ethnicity, obesity, elevated triglycerides, diabetes, alcohol use, and steroid use) were considered in multiple ordinal logistic regression models. Choline intake was not identified as a contributor to disease severity in children, men, or premenopausal women.
Decreased choline intake is significantly associated with increased fibrosis in postmenopausal women with NAFLD. The Pioglitazone vs Vitamin E vs Placebo for Treatment of Non-Diabetic Patients With Nonalcoholic Steatohepatitis trial was registered at clinicaltrials.gov as NCT00063622, and the Treatment of Nonalcoholic Fatty Liver Disease in Children trial was registered at clinicaltrials.gov as NCT00063635.
This paper presents the kinematic and static analysis of two mechanisms to improve power throughput for persons with tetra- or paraplegia pedaling a performance tricycle via FES. FES, or functional ...electrical stimulation, activates muscles by passing small electrical currents through the muscle creating a contraction. The use of FES can build muscle in patients, relieve soreness, and promote cardiovascular health. Compared to an able-bodied rider, a cyclist stimulated via FES produces an order of magnitude less power creating some notable pedaling difficulties especially pertaining to inactive zones. An inactive zone occurs when the leg position is unable to produce enough power to propel the tricycle via muscle stimulation. An inactive zone is typically present when one leg is fully bent and the other leg is fully extended. Altering the motion of a cyclist’s legs relative to the crank position can potentially reduce inactive zones and increase power throughput. Some recently marketed bicycles showcase pedal mechanisms utilizing alternate leg motions. This work considers performance tricycle designs based on the Stephenson III and Watt II six-bar mechanisms where the legs define two of the system’s links. The architecture based on the Stephenson III is referred to throughout as the CDT due to the legs’ push acting to coupler-drive the four-bar component of the system. The architecture based on the Watt II is referred to throughout as the CRT due to the legs’ push acting to drive the rocker link of the four-bar component of the system. The unmodified or traditional recumbent tricycle (TRT) provides a benchmarks by which the designs proposed herein may be evaluated. Using knee and hip torques and angular velocities consistent with a previous study, this numerical study using a quasi-static power model of the CRT suggests a roughly 50% increase and the CDT suggests roughly a doubling in average crank power, respectively, for a typical FES cyclist.
The use of client feedback in clinical supervision provides a way for supervisors to access clients' experiences of the treatment process and monitor clinical progress of their trainees' cases. The ...present qualitative study investigated a marriage and family therapy training programme's early experience of introducing the Systemic Therapy Inventory of Change (STIC®; Pinsof et al., 2009) into clinical supervision. Supervisors (N = 8) and trainees (N = 14) were interviewed to elicit their experience using the STIC in supervision with a focus on understanding the frequency of use as well as the facilitators and constraints to implementation. The analysis of the narratives resulted in the development of five themes (time, supervisors' expectations, broader training system influences, client feedback training, and perceived helpfulness) that contributed to decreased usage over time. Recommendations to the field for integrating client feedback into empirically informed training and supervision are provided.
Practitioner points
Training programmes should consider the potential benefits of utilizing client feedback measures for outcome‐based training and supervision
Training programmes adopting a client feedback measure need to be aware of the potential challenges of implementation
The additional time needed to use a client feedback measure in the clinical supervision process must be considered as it is the most notable constraint to implementation
抽象
将来访者反馈引入婚姻家庭治疗督导：考察向实证引导的督导过渡的定性研究
在临床督导中使用来访者反馈为督导提供了了解来访者治疗过程体验的方法, 并掌握学员案例的临床进展。该定性研究调查了一项婚姻家庭治疗培训计划在早期将系统治疗变化量表（STIC）引入临床督导的经历。对督导（N = 8）和学员（N = 14）进行了访谈, 以引出他们在督导中使用STIC的经验, 重点在于了解使用频率以及促进和阻碍实施的因素。分析产生五个主题（时间、督导期望、大培训系统影响、来访者反馈培训和感知帮助）, 而它们导致了使用频率随着时间的推移减少。文末建议这一领域将来访者反馈纳入实证引导的培训和督导
对实务工作者的启示
培训计划应考虑利用来访者反馈措施进行结果导向的培训和督导的潜在优势
采用来访者反馈措施的培训计划需要意识到实施中存在的潜在挑战
必须考虑到在临床督导过程中使用来访者反馈措施所需的额外时间, 因为这是实施过程中最显著的制约因素
o
Introducción de retroalimentación de los clientes en la supervisión de la terapia familiar y de pareja: un estudio cualitativo que examina la transición a una supervisión empíricamente informada.
El uso de retroalimentación de comentarios de los clientes en la supervisión clínica proporciona una forma de que los supervisores accedan a las experiencias de los clientes sobre el proceso de tratamiento y monitoreen así el progreso clínico de los casos de sus supervisados. El presente estudio cualitativo investigó la experiencia inicial de un programa de entrenamiento en terapia de pareja y familia para introducir el Inventario de Cambio de Terapia Sistémica (STIC®; Pinsof et al., 2009) en supervisión clínica. Se entrevistó a supervisores (N = 8) y novatos supervisados (N = 14) para conocer su experiencia con el STIC en supervisión, con un enfoque en la comprensión de la frecuencia de uso, así como de los facilitadores y las dificultades de su aplicación. El análisis de las narrativas extraídas de las entrevistas resultó en el desarrollo de cinco temas (tiempo, expectativas de los supervisores, influencias más amplias del sistema formación, entrenamiento en la retroalimentación de los clientes y percepción de ayuda) que contribuyeron a la disminución del uso del STIC. Se proporcionan recomendaciones para integrar la retroalimentación de comentarios de los clientes en la capacitación y supervisión informadas empíricamente.
Puntos de implicación práctica
Los programas de capacitación deberían considerar los beneficios potenciales de utilizar medidas de retroalimentación de los clientes para la capacitación y supervisión basadas en los resultados
Los programas de capacitación que adoptan una medida de retroalimentación de los clientes deben ser conscientes de los posibles desafíos de su implementación
Se debe considerar el tiempo adicional necesario para usar una medida de retroalimentación del cliente en el proceso de supervisión clínica ya que es la restricción más notable para su implementación.
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