Disease-related income and economic productivity loss in New Zealand: A longitudinal analysis of linked individual-level data.

BACKGROUND: Reducing disease can maintain personal individual income and improve societal economic productivity. However, estimates of income loss for multiple diseases simultaneously with thorough adjustment for confounding are lacking, to our knowledge. We estimate individual-level income loss for 40 conditions simultaneously by phase of diagnosis, and the total income loss at the population level (a function of how common the disease is and the individual-level income loss if one has the disease). METHODS AND FINDINGS: We used linked health tax data for New Zealand as a high-income country case study, from 2006 to 2007 to 2015 to 2016 for 25- to 64-year-olds (22.5 million person-years). Fixed effects regression was used to estimate within-individual income loss by disease, and cause-deletion methods to estimate economic productivity loss at the population level. Income loss in the year of diagnosis was highest for dementia for both men (US$8,882; 95% CI $6,709 to $11,056) and women ($7,103; $5,499 to $8,707). Mental illness also had high income losses in the year of diagnosis (average of about $5,300 per year for males and $4,100 per year for females, for 4 subcategories of: depression and anxiety; alcohol related; schizophrenia; and other). Similar patterns were evident for prevalent years of diagnosis. For the last year of life, cancers tended to have the highest income losses, (e.g., colorectal cancer males: $17,786, 95% CI $15,555 to $20,018; females: $14,192, $12,357 to $16,026). The combined annual income loss from all diseases among 25- to 64-year-olds was US$2.72 billion or 4.3% of total income. Diseases contributing more than 4% of total disease-related income loss were mental illness (30.0%), cardiovascular disease (15.6%), musculoskeletal (13.7%), endocrine (8.9%), gastrointestinal (7.4%), neurological (6.5%), and cancer (4.5%). The limitations of this study include residual biases that may overestimate the effect of disease on income loss, such as unmeasured time-varying confounding (e.g., divorce leading to both depression and income loss) and reverse causation (e.g., income loss leading to depression). Conversely, there may also be offsetting underestimation biases, such as income loss in the prodromal phase before diagnosis that is misclassified to "healthy" person time. CONCLUSIONS: In this longitudinal study, we found that income loss varies considerably by disease. Nevertheless, mental illness, cardiovascular, and musculoskeletal diseases stand out as likely major causes of economic productivity loss, suggesting that they should be prioritised in prevention programmes.

Healthcare spending in U.S. emergency departments by health condition, 2006-2016.

BACKGROUND: Healthcare spending in the emergency department (ED) setting has received intense focus from policymakers in the United States (U.S.). Relatively few studies have systematically evaluated ED spending over time or disaggregated ED spending by policy-relevant groups, including health condition, age, sex, and payer to inform these discussions. This study's objective is to estimate ED spending trends in the U.S. from 2006 to 2016, by age, sex, payer, and across 154 health conditions and assess ED spending per visit over time. METHODS AND FINDINGS: This observational study utilized the National Emergency Department Sample, a nationally representative sample of hospital-based ED visits in the U.S. to measure healthcare spending for ED care. All spending estimates were adjusted for inflation and presented in 2016 U.S. Dollars. Overall ED spending was $79.2 billion (CI, $79.2 billion-$79.2 billion) in 2006 and grew to $136.6 billion (CI, $136.6 billion-$136.6 billion) in 2016, representing a population-adjusted annualized rate of change of 4.4% (CI, 4.4%-4.5%) as compared to total healthcare spending (1.4% [CI, 1.4%-1.4%]) during that same ten-year period. The percentage of U.S. health spending attributable to the ED has increased from 3.9% (CI, 3.9%-3.9%) in 2006 to 5.0% (CI, 5.0%-5.0%) in 2016. Nearly equal parts of ED spending in 2016 was paid by private payers (49.3% [CI, 49.3%-49.3%]) and public payers (46.9% [CI, 46.9%-46.9%]), with the remainder attributable to out-of-pocket spending (3.9% [CI, 3.9%-3.9%]). In terms of key groups, the majority of ED spending was allocated among females (versus males) and treat-and-release patients (versus those hospitalized); those between age 20-44 accounted for a plurality of ED spending. Road injuries, falls, and urinary diseases witnessed the highest levels of ED spending, accounting for 14.1% (CI, 13.1%-15.1%) of total ED spending in 2016. ED spending per visit also increased over time from $660.0 (CI, $655.1-$665.2) in 2006 to $943.2 (CI, $934.3-$951.6) in 2016, or at an annualized rate of 3.4% (CI, 3.3%-3.4%). CONCLUSIONS: Though ED spending accounts for a relatively small portion of total health system spending in the U.S., ED spending is sizable and growing. Understanding which diseases are driving this spending is helpful for informing value-based reforms that can impact overall health care costs.

The development of nations conditions the disease space.

Using the economic complexity methodology on data for disease prevalence in 195 countries during the period of 1990-2016, we propose two new metrics for quantifying the disease space of countries. With these metrics, we analyze the geography of diseases and empirically investigate the effect of economic development on the health complexity of countries. We show that a higher income per capita increases the complexity of countries' diseases. We also show that complex diseases tend to be non-ubiquitous diseases that are prevalent in disease-diversified (complex) countries, while non-complex diseases tend to be non-ubiquitous diseases that are prevalent in non-diversified (non-complex) countries. Furthermore, we build a disease-level index that links a disease to the average level of GDP per capita of the countries in which the disease is prevalent. With this index, we highlight the link between economic development and the complexity of diseases and illustrate how increases in income per capita are associated with more complex diseases.

Changing relative and absolute socioeconomic health inequalities in Ontario, Canada: A population-based cohort study of adult premature mortality, 1992 to 2017.

BACKGROUND: This study aimed to characterize trends in absolute and relative socioeconomic inequalities in adult premature mortality between 1992 and 2017, in the context of declining population-wide mortality rates. We conducted a population-based cohort study of all adult premature deaths in Ontario, Canada using provincial vital statistics data linked to census-based, area-level deprivation indices for socioeconomic status. METHODS: The cohort included all individuals eligible for Ontario's single-payer health insurance system at any time between January 1, 1992 and December 31, 2017 with a recorded Ontario place of residence and valid socioeconomic status information (N = 820,370). Deaths between ages 18 and 74 were used to calculate adult premature mortality rates per 1000, stratified by provincial quintile of material deprivation. Relative inequalities were measured using Relative Index of Inequality (RII) measures. Absolute inequalities were estimated using Slope Index of Inequality (SII) measures. All outcome measures were calculated as sex-specific, annual measures for each year from 1992 to 2017. RESULTS: Premature mortality rates declined in all socioeconomic groups between 1992 and 2017. Relative inequalities in premature mortality increased over the same period. Absolute inequalities were mostly stable between 1992 and 2007, but increased dramatically between 2008 and 2017, with larger increases to absolute inequalities seen in females than in males. CONCLUSIONS: As in other developed countries, long-term downward trends in all-cause premature mortality in Ontario, Canada have shifted to a plateau pattern in recent years, especially in lower- socioeconomic status subpopulations. Determinants of this may differ by setting. Regular monitoring of mortality by socioeconomic status is the only way that this phenomenon can be detected sensitively and early, for public health attention and possible corrective action.

US Health Care Spending by Payer and Health Condition, 1996-2016.

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.

Limited alignment of publicly competitive disease funding with disease burden in Japan.

OBJECTIVE: The need to align investments in health research and development (R&D) with public health needs is one of the most important public health challenges in Japan. We examined the alignment of disease-specific publicly competitive R&D funding to the disease burden in the country. METHODS: We analyzed publicly available data on competitive public funding for health in 2015 and 2016 and compared it to disability-adjusted life year (DALYs) in 2016, which were obtained from the Global Burden of Disease (GBD) 2017 study. Their alignment was assessed as a percentage distribution among 22 GBD disease groups. Funding was allocated to the 22 disease groups based on natural language processing, using textual information such as project title and abstract for each research project, while considering for the frequency of information. RESULTS: Total publicly competitive funding in health R&D in 2015 and 2016 reached 344.1 billion JPY (about 3.0 billion USD) for 32,204 awarded projects. About 49.5% of the funding was classifiable for disease-specific projects. Five GDB disease groups were significantly and relatively well-funded compared to their contributions to Japan's DALY, including neglected tropical diseases and malaria (funding vs DALY = 1.7% vs 0.0%, p<0.01) and neoplasms (28.5% vs 19.2%, p<0.001). In contrast, four GDB disease groups were significantly under-funded, including cardiovascular diseases (8.0% vs 14.8%, p<0.001) and musculoskeletal disorders (1.0% vs 11.9%, p<0.001). These percentages do not include unclassifiable funding. CONCLUSIONS: While caution is necessary as this study was not able to consider public in-house funding and the methodological uncertainties could not be ruled out, the analysis may provide a snapshot of the limited alignment between publicly competitive disease-specific funding and the disease burden in the country. The results call for greater management over the allocation of scarce resources on health R&D. DALYs will serve as a crucial, but not the only, consideration in aligning Japan's research priorities with the public health needs. In addition, the algorithms for natural language processing used in this study require continued efforts to improve accuracy.

Disease causing poverty: adapting the Onyx and Bullen social capital measurement tool for China.

BACKGROUND: Disease-causing poverty is a serious problem in rural China, where social capital can mediate the disease-poverty relationship. However, there is no generally accepted reliable, robust and viable measure of social capital for China's unique socio-cultural context. This study adapts for China the widely used Onyx and Bullen social capital measurement scale and tests the validity and reliability of a modified Chinese Onyx-Bullen general scale, the Chinese Onyx-Bullen health scale, for a disease-causing-poverty subpopulation in rural China. METHODS: We conducted the forward and backward translation procedure and cross-cultural adaptation process to derive the 34 item Chinese Onyx-Bullen general scale. Next we collected through face-to face interviews a sample of disease-causing poverty population in rural Shandong province in China to test a 29 item modified Chinese Onyx-Bullen general scale for a health subpopulation. Most of the rural respondents had no formal work, so 5 work-related items in the Onyx-Bullen general scale were deleted in the Chinese Onyx-Bullen health scale. Exploratory factor analysis was conducted to evaluate the structure, validity, internal consistency and reliability of the Chinese Onyx-Bullen health scale. SPSS21.0 software was used for data analysis. RESULTS: A total of 467 people completed the scale. For the 29-item scale, a better simple structure was found when the number of factors was limited to 8. The absolute values of inter-factor correlations were in the range of 0.004 to 0.213 and the Kaiser-Meyer-Olkin value was 0.834. All the eight factors explain a total of 59.51% of the variance. The total scale had a Cronbach's alpha = 0.868, in which seven of the eight factors had Cronbach's α greater than 0.5. CONCLUSION: The Chinese health version of the Onyx-Bullen general social capital scale showed an adequate reliability and validity in a rural disease-causing poverty subpopulation in Shandong province, providing the first general, robust, consistent and reliable measure of social capital in China. The Chinese Onyx-Bullen general social capital scale provides a scale for testing social capital in China or for modification along the lines of the Chinese Onyx-Bullen health scale.

Cost-of-illness studies in nine Central and Eastern European countries.

BACKGROUND: To date, a multi-country review evaluating the cost-of-illness (COI) studies from the Central and Eastern European (CEE) region has not yet been published. Our main objective was to provide a general description about published COI studies from CEE. METHODS: A systematic search was performed between 1 January 2006 and 1 June 2017 in Medline, EMBASE, The Cochrane Library, CINAHL, and Web of Science to identify all relevant COI studies from nine CEE countries. COI studies reporting costs without any restrictions by age, co-morbidities, or treatment were included. Methodology, publication standards, and cost results were analysed. RESULTS: We identified 58 studies providing 83 country-specific COI results: Austria (n = 9), Bulgaria (n = 16), Croatia (n = 3), the Czech Republic (n = 10), Hungary (n = 24), Poland (n = 11), Romania (n = 3), Slovakia (n = 3), and Slovenia (n = 4). Endocrine, nutritional, and metabolic diseases (18%), neoplasms (12%), infections (11%), and neurological disorders (11%) were the most frequently studied clinical areas, and multiple sclerosis was the most commonly studied disease. Overall, 57 (98%) of the studies explicitly stated the source of resource use data, 45 (78%) the study perspective, 34 (64%) the costing method, and 24 (58%) reported at least one unit costs. Regardless of methodological differences, a positive relationship was observed between costs of diseases and countries' per capita GDP. CONCLUSIONS: Cost-of-illness studies varied considerably in terms of methodology, publication practice, and clinical areas. Due to these heterogeneities, transferability of the COI results is limited across Central and Eastern European countries.

Unbiased assessment of disease surveillance utilities: A prospect theory application.

OBJECTIVES: We contribute a new methodological approach to the ongoing efforts towards evaluating public health surveillance. Specifically, we apply a descriptive framework, grounded in prospect theory (PT), for the evaluation of decisions on disease surveillance deployment. We focus on two attributes of any surveillance system: timeliness, and false positive rate (FPR). METHODS: In a sample of 69 health professionals from a number of health related networks polled online, we elicited PT preferences, specifically respondents' attitudes towards gains, losses and probabilities (i.e., if they overweight or underweight extreme probabilities) by means of a series of lotteries for either timeliness or FPR. Moreover, we estimated willingness to pay (WTP) for improvements in the two surveillance attributes. For contextualization, we apply our framework to rabies surveillance. RESULTS: Our data reveal considerable probability weighting, both for gains and losses. In other words, respondents underestimate their chances of getting a good outcome in uncertain situations, and they overestimate their chances of bad outcomes. Moreover, there is convex utility for losses and loss aversion, that is, losses loom larger than gains of the same absolute magnitude to the respondents. We find no differences between the estimated parameters for timeliness and FPR. The median WTP is $7,250 per day gained in detection time and $30 per 1/10,000 reduction in FPR. CONCLUSION: Our results indicate that the biases described by PT are present among public health professionals, which highlights the need to incorporate a PT framework when eliciting their preferences for surveillance systems.

Insomnia and Impaired Quality of Life in the United States.

OBJECTIVE: This analysis characterizes the individual-level and population-level burden of insomnia in relation to other medical conditions and describes the comorbidity of insomnia with other medical conditions, including the dependence of these comorbidities on pain, life events, and mental disorders. METHODS: Information from 34,712 adults in the National Epidemiologic Survey on Alcohol and Related Conditions-III (2012-2013) was analyzed. Quality-adjusted life-years (QALYs) were measured with the SF-6D, a 6-dimensional health state classification derived from the Short-Form-12, version 2. RESULTS: In the last 12 months, 27.3% of adults reported insomnia. The US annual loss of QALYs associated with insomnia (5.6 million; 95% CI, 5.33-5.86 million) was significantly larger than that associated with any of the other 18 medical conditions assessed, including arthritis (4.94 million; 95% CI, 4.62-5.26 million), depression (4.02 million; 95% CI, 3.87-4.17 million), and hypertension (3.63 million; 95% CI, 3.32-3.93 million). After control for demographic factors, all conditions examined from obesity (adjusted odds ratio [aOR] = 1.25) to mania (aOR = 5.04) were associated with an increased risk of insomnia. Further controlling for pain, stressful life events, and mental disorders decreased the odds of the co-occurrence of insomnia with these conditions. The decrease in insomnia comorbidity associated with pain was greatest for fibromyalgia (31.8%) and arthritis (20.1%); the decrease in insomnia comorbidity associated with life events was greatest for mania (13.4%) and drug use disorders (11.2%); and the decrease in insomnia comorbidity associated with mental disorders was greatest for peptic ulcer disease (11.2%) and liver diseases (11.1%). CONCLUSIONS: Insomnia is prevalent and associated with substantial population-level burden in self-assessed health. The co-occurrence of insomnia with common medical conditions is differentially related to pain and to a lesser extent to stressful life events and mental disorders.

Estimating comparable English healthcare costs for multiple diseases and unrelated future costs for use in health and public health economic modelling.

OBJECTIVES: Healthcare interventions, and particularly those in public health may affect multiple diseases and significantly prolong life. No consensus currently exists for how to estimate comparable healthcare costs across multiple diseases for use in health and public health cost-effectiveness models. We aim to describe a method for estimating comparable disease specific English healthcare costs as well as future healthcare costs from diseases unrelated to those modelled. METHODS: We use routine national datasets including programme budgeting data and cost curves from NHS England to estimate annual per person costs for diseases included in the PRIMEtime model as well as age and sex specific costs due to unrelated diseases. RESULTS: The 2013/14 annual cost to NHS England per prevalent case varied between £3,074 for pancreatic cancer and £314 for liver disease. Costs due to unrelated diseases increase with age except for a secondary peak at 30-34 years for women reflecting maternity resource use. CONCLUSIONS: The methodology described allows health and public health economic modellers to estimate comparable English healthcare costs for multiple diseases. This facilitates the direct comparison of different health and public health interventions enabling better decision making.

[ICHI-International Classification of Health Interventions : A balancing act between the demands of statistics and reimbursement]. / ICHI ­ International Classification of Health Interventions : Prozedurenklassifikation im Spagat zwischen Statistik und Abrechnung.

Medical classifications systematize medical concepts (e. g. diagnoses, procedures). They are essential for statistics and reimbursement systems in health care systems. Diagnoses are classified worldwide with the International Classification of Diseases (ICD) of the World Health Organization (WHO). The situation for procedure classifications is quite different. Many countries developed their own procedure classifications in different ways and for different purposes.Since 2007, the International Classification of Health Interventions (ICHI) is been developing as a common tool for reporting and analyzing health interventions for statistical purposes as well as for the use in reimbursement systems.ICHI covers not only medical and surgical procedures but also interventions carried out by a broad range of providers across the full scope of health systems, including rehabilitation, assistance with functioning, prevention and public health.The multiaxial classification is built around three axes: target (the entity on which the action is carried out), action (a deed done by an actor to a target) and means (the processes and methods by which the action is carried out). Extension codes are provided to allow users to describe additional detail about the intervention in addition to the relevant ICHI stem-code. ICHI was designed with a low level of complexity for countries seeking a classification, while also serving as a basis for international comparisons. ICHI can also be used in reimbursement systems, by adding cost-relevant information through extension codes.The recent 2018 ICHI beta version is available on the platform https://mitel.dimi.uniud.it/ichi . This version and further ICHI tools will be tested during later reviews and field testing in 2018 and 2019. Once finalized, probably in 2020, ICHI will be freely available for adoption by member states of the WHO.

Economic impact of medication non-adherence by disease groups: a systematic review.

OBJECTIVE: To determine the economic impact of medication non-adherence across multiple disease groups. DESIGN: Systematic review. EVIDENCE REVIEW: A comprehensive literature search was conducted in PubMed and Scopus in September 2017. Studies quantifying the cost of medication non-adherence in relation to economic impact were included. Relevant information was extracted and quality assessed using the Drummond checklist. RESULTS: Seventy-nine individual studies assessing the cost of medication non-adherence across 14 disease groups were included. Wide-scoping cost variations were reported, with lower levels of adherence generally associated with higher total costs. The annual adjusted disease-specific economic cost of non-adherence per person ranged from $949 to $44 190 (in 2015 US$). Costs attributed to 'all causes' non-adherence ranged from $5271 to $52 341. Medication possession ratio was the metric most used to calculate patient adherence, with varying cut-off points defining non-adherence. The main indicators used to measure the cost of non-adherence were total cost or total healthcare cost (83% of studies), pharmacy costs (70%), inpatient costs (46%), outpatient costs (50%), emergency department visit costs (27%), medical costs (29%) and hospitalisation costs (18%). Drummond quality assessment yielded 10 studies of high quality with all studies performing partial economic evaluations to varying extents. CONCLUSION: Medication non-adherence places a significant cost burden on healthcare systems. Current research assessing the economic impact of medication non-adherence is limited and of varying quality, failing to provide adaptable data to influence health policy. The correlation between increased non-adherence and higher disease prevalence should be used to inform policymakers to help circumvent avoidable costs to the healthcare system. Differences in methods make the comparison among studies challenging and an accurate estimation of true magnitude of the cost impossible. Standardisation of the metric measures used to estimate medication non-adherence and development of a streamlined approach to quantify costs is required. PROSPERO REGISTRATION NUMBER: CRD42015027338.

Costes asociados a la desnutrición previa a la enfermedad y la desnutrición relacionada con la enfermedad en ancianos: una revisión sistemática / Cost associated with malnutrition prior to disease and disease-related malnutrition in the elderly: a systematic review

Introducción: la desnutrición es un problema de salud que afecta en un elevado porcentaje al colectivo de ancianos, ya que los cambios físicos y psicosociales propios de esta etapa de la vida favorecen la aparición de la misma. Además, la población anciana presenta una elevada prevalencia en enfermedades crónicas y patologías agudas que pueden afectar negativamente al estado nutricional, provocando desnutrición relacionada con la enfermedad. Objetivo: el propósito de esta revisión sistemática fue analizar el coste económico relacionado con la desnutrición en personas mayores y si existen diferencias entre los costes de la desnutrición previa a la enfermedad y la desnutrición relacionada con la enfermedad. Método: se realizó una búsqueda bibliográfica en las bases de datos Pubmed, Web of Science y Scopus, para el periodo comprendido entre 2000 y 2016. Resultados: se encontraron un total de 1.001 artículos y, utilizando los criterios de inclusión, se seleccionaron 19. De ellos, once analizaron los costes de la desnutrición previa a la enfermedad; siete, los costes de la desnutrición relacionada con la enfermedad, y uno, ambas situaciones. Conclusiones: la desnutrición en general incrementa el gasto sanitario debido al aumento de estancias hospitalarias, al mayor número de reingresos y a la mayor demanda de recursos sanitarios. Además, en los estudios analizados, la desnutrición previa a la enfermedad implicó mayores costes que la relacionada con la enfermedad, por lo que sería conveniente establecer políticas de cribado y prevención de la desnutrición en los ancianos (AU)

Introduction: Malnutrition is a health problem which affects a high percentage of old people since the physical and psychosocial changes common to this period of life favor it in this group. In addition, aging population has a high prevalence of chronic illnesses and acute pathologies which can affect their nutritional state negatively, leading to malnutrition related to illness. Objective: The aim of this systematic revision was to analyze the economic costs related to malnutrition in old people and to discover whether there were differences between economic costs of pre-existing malnutrition prior to illness and malnutrition because of disease. Method: A bibliographic search was carried out in the databases of Pubmed, Web of Science and Scopus, for the period between 2000 and 2016. Results: A total of 1,001 articles were found and 19 were selected using inclusion criteria. Of these, eleven analyzed the costs of pre-existing malnutrition prior to illness, seven analyzed the costs of malnutrition related to illness and one, both situations. Conclusions: In general, malnutrition increased health costs as a result of hospital admissions, greater number of readmissions and greater demand on health resources. Moreover, in the studies analyzed, pre-existing malnutrition prior to illness implied greater costs than those related to the actual illness; therefore, it would be convenient to establish selection and preventive policies on malnutrition in old people (AU)

Territorial variation in mortality from causes amenable to medical care in Poland.

INTRODUCTION AND OBJECTIVE: This study examines the geographical variation of amenable mortality in Poland, focusing primarily on the role of health care resources at the level of administrative districts and regions, and selected area socioeconomic characteristics as explanatory factors. The concept was used of amenable mortality, based on the assumption that deaths from certain causes should not occur in the presence of timely and effective health care. MATERIAL AND METHODS: Standardized death rates (SDR) from causes considered amenable to health care and, separately, for ischaemic heart disease (IHD), were calculated for each of 379 districts (NUTS 4 level) in Poland in 1991-1995 and 2006-2010, using unit mortality data from the National Causes of Death Register. The analytical procedure involved spatial analysis of the distribution of amenable mortality rates, selection of explanatory variables and fitting multilevel regression models using area-level and regional-level characteristics. RESULTS: The results indicate that mortality from conditions which have become amenable to medical intervention has generally decreased in all districts of Poland in the past two decades. Considerable territorial variation in mortality can be observed. Since the 1990s, these differences have been reduced for IHD-related mortality and have increased for amenable mortality. CONCLUSIONS: The presented analysis only partly confirms the correlation between variables reflecting the infrastructure of health care resources and the territorial variation in mortality from these two categories of causes of death. Significant correlations with variation in mortality are revealed for the number of primary care physicians (at district level) and the number of specialist practitioners (at regional level). However, after controlling for socioeconomic variables, such as education and low income, the effect of the health care infrastructure-related variables was considerably reduced. The multi-level models also revealed a substantial variation at the regional level, which implies that there are other unobserved contextual influences on amenable mortality at this level.

Excess costs from functional somatic syndromes in Germany - An analysis using entropy balancing.

AIM: The aim of this study was to calculate disorder-specific excess costs in patients with functional somatic syndromes (FSS). METHODS: We compared 6-month direct and indirect costs in a patient group with FSS (n=273) to a control group of the general adult population in Germany without FSS (n=2914). Data on the patient group were collected between 2007 and 2009 in a randomized controlled trial (speciAL). Data on the control group were obtained from a telephone survey, representative for the general German population, conducted in 2014. Covariate balance between the patient group and the control group was achieved using entropy balancing. Excess costs were calculated by estimating generalized linear models and two-part models for direct costs and indirect costs. Further, we estimated excess costs according to the level of somatic symptom severity (SSS). RESULTS: FSS patients differed significantly from the control group regarding 6-month costs of outpatient physicians (+€280) and other outpatient providers (+€74). According to SSS, significantly higher outpatient physician costs were found for mild (+€151), moderate (+€306) and severe (+€376) SSS. We also found significantly higher costs of other outpatient providers in patients with mild, moderate and severe SSS. Regarding costs of rehabilitation and hospital treatments, FSS patients did not differ significantly from the control group for any level of SSS. Indirect costs were significantly higher in patients with severe SSS (+€760). CONCLUSION: FSS were of major importance in the outpatient sector. Further, we found significantly higher indirect costs in patients with severe SSS.

Guidelines for Measuring Disease Episodes: An Analysis of the Effects on the Components of Expenditure Growth.

OBJECTIVE: To provide guidelines to researchers measuring health expenditures by disease and compare these methodologies' implied inflation estimates. DATA SOURCE: A convenience sample of commercially insured individuals over the 2003 to 2007 period from Truven Health. Population weights are applied, based on age, sex, and region, to make the sample of over 4 million enrollees representative of the entire commercially insured population. STUDY DESIGN: Different methods are used to allocate medical-care expenditures to distinct condition categories. We compare the estimates of disease-price inflation by method. PRINCIPAL FINDINGS: Across a variety of methods, the compound annual growth rate stays within the range 3.1 to 3.9 percentage points. Disease-specific inflation measures are more sensitive to the selected methodology. CONCLUSION: The selected allocation method impacts aggregate inflation rates, but considering the variety of methods applied, the differences appear small. Future research is necessary to better understand these differences in other population samples and to connect disease expenditures to measures of quality.

US Spending on Personal Health Care and Public Health, 1996-2013.

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.