Factors influencing deceased organ donation rates in OECD countries: a panel data analysis.

OBJECTIVES: This study aims to investigate factors with a significant influence on deceased organ donation rates in Organisation for Economic Co-operation and Development (OECD) countries and determine their relative importance. It seeks to provide the necessary data to facilitate the development of more efficient strategies for improving deceased organ donation rates. DESIGN: Retrospective study. SETTING: Publicly available secondary annual data. PARTICIPANTS: The study includes 36 OECD countries as panel members for data analysis. OUTCOME MEASURES: Multivariable panel data regression analysis was employed, encompassing data from 2010 to 2018 for all investigated variables in the included countries. RESULTS: The following variables had a significant influence on deceased organ donation rates: 'opt-in' system (ß=-4.734, p<0.001, ref: 'opt-out' system), only donation after brain death (DBD) donors allowed (ß=-4.049, p=0.002, ref: both DBD and donation after circulatory death (DCD) donors allowed), number of hospital beds per million population (pmp) (ß=0.002, p<0.001), total healthcare employment pmp (ß=-0.00012, p=0.012), World Giving Index (ß=0.124, p=0.008), total tax revenue as a percentage of gross domestic product (ß=0.312, p=0.009) and percentage of population aged ≥65 years (ß=0.801, p<0.001) as well as high education population in percentage (ß=0.118, p=0.017). CONCLUSIONS: Compared with the promotion of socioeconomic factors with a positive significant impact on deceased organ donation rates, the following policies have been shown to significantly increase rates of deceased organ donation, which could be further actively promoted: the adoption of an 'opt-out' system with presumed consent for deceased organ donation and the legal authorisation of both DBD and DCD for transplantation.

The combined toxicity of binary mixtures of antibiotics against the cyanobacterium Microcystis is dose-dependent: insight from a theoretical nonlinear combined toxicity assessment method.

The entry of antibiotics into aquatic ecosystems has a serious impact. Antibiotics usually exist as mixtures in natural water bodies. Therefore, it is particularly important to evaluate the mixed toxicity of antibiotic mixtures. The study of the combined toxicity of binary mixtures of antibiotics is the basis for exploring the mixed toxicity of multiple antibiotics. In this investigation, Microcystis aeruginosa (M. aeruginosa) was used as the test organism, and a theoretical nonlinear combined toxicity assessment method was adopted to evaluate the effects of binary mixtures of antibiotics consisting of tetracycline (TC), sulfadiazine (SD), and sulfamethoxazole (SMX) on cell growth, enzymatic activity, and gene expression. The median lethal concentrations of TC, SD, and SMX to M. aeruginosa were 0.52 mg L-1, 1.65 mg L-1, and 0.71 mg L-1, respectively. The results from the theoretical nonlinear combined toxicity assessment method showed that SD + TC was synergistic at low concentrations and antagonistic at high concentrations, while the combinations of SMX + SD and SMX + TC were synergistic. The determination of enzymatic activity and gene expression indicated that the antibiotics could inhibit the growth of M. aeruginosa by destroying the cell membrane structure, inhibiting photosynthesis, impeding the cell division process and the electron transfer process, and destroying the molecular structure of proteins and DNA. Different combinations of antibiotics have different degrees of damage to the antioxidant system and cell membrane self-repair function of M. aeruginosa, which are the reasons for the different combined toxicity effects.

A practical assessment of nano-phosphate on soybean (Glycine max) growth and microbiome establishment.

The efficacy of needle-shaped nano-hydroxyapatite (nHA; Ca10(PO4)6(OH)2) as a phosphate (Pi) fertilizer was evaluated as well as its impact on soil and soybean (Glycine max) bacterial and fungal communities. Microbial communities were evaluated in soy fertilized with nHA using ITS (internal transcribed spacer) and 16S rRNA high-throughput gene sequencing. Separate greenhouse growth experiments using agriculturally relevant nHA concentrations and application methods were used to assess plant growth and yield compared with no Pi (-P), soluble Pi (+P), and bulk HA controls. Overall, nHA treatments did not show significantly increased growth, biomass, total plant phosphorus concentrations, or yield compared with no Pi controls. Soil and rhizosphere community structures in controls and nHA treatment groups were similar, with minor shifts in the nHA-containing pots comparable to bulk HA controls at equal concentrations. The implementation of nHA in an agriculturally realistic manner and the resulting poor soy growth advises that contrary to some reports under specialized conditions, this nano-fertilizer may not be a viable alternative to traditional Pi fertilizers. If nano-phosphate fertilizers are to achieve their conjectured agricultural potential, alternative nHAs, with differing morphologies, physicochemical properties, and interactions with the soil matrix could be investigated using the evaluative procedures described.

A systematic review of decision analytic modeling techniques for the economic evaluation of dental caries interventions.

OBJECTIVES: Dental caries occur through a multifactorial process that may influence all tooth surfaces throughout an individual's life. The application of decision analytical modeling (DAM) has gained an increasing level of attention in long-term outcome assessment and economic evaluation of interventions on caries in recent years. The objective of this study was to systematically review the application of DAM and assess their methodological quality in the context of dental caries. METHODS: A systematic review of the literature published to 31st December 2018 was conducted in Medline, EMBASE, NHSEED, and Web of Science electronic databases. The main information and model characteristics of studies was extracted with the methodological quality of included studies reviewed and assessed using the Philips' checklist. RESULTS: Twenty five studies from different settings were included. Modeling techniques mainly comprised main type of modeling including Markov models (n = 12), Markov/microsimulation mixed model (n = 7), systematic dynamic models (n = 3), microsimulation models (n = 2) and decision tree (n = 1). The mean number of criteria fulfilled was 25.1 out of 60 items, which varied between year of study and research groups. The percentage of criteria fulfilled for data dimension was lower than for the structure and consistency dimension. Critical issues were data quality, incorporation of utility values, and uncertainty analysis in modeling. CONCLUSION: The current review revealed that the methodological quality of DAM in dental caries economic evaluations is unsatisfied. Future modeling studies should adhere more closely to good practice guidelines, especially with respect to data quality evaluation, utility values incorporation, and uncertainty analysis in DAM based studies.

Potential savings in the treatment pathway of liver transplantation: an inter-sectorial analysis of cost-rising factors.

INTRODUCTION: Identification of cost-driving factors in patients undergoing liver transplantation is essential to target reallocation of resources and potential savings. AIM: The aim of this study is to identify main cost-driving factors in liver transplantation from the perspective of the Statutory Health Insurance. METHODS: Variables were analyzed with multivariable logistic regression to determine their influence on high cost cases (fourth quartile) in the outpatient, inpatient and rehabilitative healthcare sectors as well as for medications. RESULTS: Significant cost-driving factors for the inpatient sector of care were a high labMELD-score (OR 1.042), subsequent re-transplantations (OR 7.159) and patient mortality (OR 3.555). Expenditures for rehabilitative care were significantly higher in patients with a lower adjusted Charlson comorbidity index (OR 0.601). The indication of viral cirrhosis and hepatocellular carcinoma resulted in significantly higher costs for medications (OR 21.618 and 7.429). For all sectors of care and medications each waiting day had a significant impact on high treatment costs (OR 1.001). Overall, cost-driving factors resulted in higher median treatment costs of 211,435 €. CONCLUSIONS: Treatment costs in liver transplantation were significantly influenced by identified factors. Long pre-transplant waiting times that increase overall treatment costs need to be alleviated by a substantial increase in donor organs to enable transplantation with lower labMELD-scores. Disease management programs, the implementation of a case management for vulnerable patients, medication plans and patient tracking in a transplant registry may enable cost savings, e.g., by the avoidance of otherwise necessary re-transplants or incorrect medication.

Decision modelling for economic evaluation of liver transplantation.

As the gap between a shortage of organs and the immense demand for liver grafts persists, every available donor liver needs to be optimized for utility, urgency and equity. To overcome this challenge, decision modelling might allow us to gather evidence from previous studies as well as compare the costs and consequences of alternative options. For public health policy and clinical intervention assessment, it is a potentially powerful tool. The most commonly used types of decision analytical models include decision trees, the Markov model, microsimulation, discrete event simulation and the system dynamic model. Analytic models could support decision makers in the field of liver transplantation when facing specific problems by synthesizing evidence, comprising all relevant options, generalizing results to other contexts, extending the time horizon and exploring the uncertainty. For modeling studies of economic evaluation for transplantation, understanding the current nature of the disease is crucial, as well as the selection of appropriate modelling techniques. The quality and availability of data is another key element for the selection and development of decision analytical models. In addition, good practice guidelines should be complied, which is important for standardization and comparability between economic outputs.

Evaluation of published assessment tools for comorbidity in liver transplantation: a systematic review protocol.

INTRODUCTION: Liver transplantation is considered the best therapy option for end-stage liver disease. Different factors including recipient comorbidity at time of transplantation are supposed to have substantial impact on outcomes. Although several studies have focused on comorbidity assessment indices for liver transplant recipients, there is no systematic review available on the methodological details and prognostic accuracy of these instruments. The aim of this study is to systematically review recipient comorbidity assessment indices in the context of liver transplantation. METHODS AND ANALYSIS: PubMed, Embase, Web of Science and PsyINFO databases will be searched. Studies describing, using or evaluating specific assessment tools to predict the effect of comorbidity on clinical outcomes after liver transplantation will be included. The selection will be conducted independently by two reviewers. The study characteristics and methodological information on published comorbidity assessment tools will be extracted into a predefined structural table. This approach will be deployed to systematically extract information on the validity, reliability and practical feasibility of investigated comorbidity assessment tools for comparative evaluation. Narrative information synthesis will be conducted, and additional meta-analytical comparison will be performed, if appropriate. ETHICS AND DISSEMINATION: All data are collected from published literature. Thus, formal ethics review for the research is not required. The findings of this systematic review will be published in a peer-reviewed journal and presented at relevant conferences. The results of this systematic review will be highly relevant for further research on prognostic models, clinical decision making and optimisation of donor organ allocation. PROSPERO REGISTRATION NUMBER: CRD42017074609.

Evolving Healthcare Quality in Top Tertiary General Hospitals in China during the China Healthcare Reform (2010-2012) from the Perspective of Inpatient Mortality.

Healthcare reforms (HR) initiated by many countries impacts on healthcare systems worldwide. Being one of fast developing countries, China launched HR in 2009. Better understanding of its impact is helpful for China and others in further pursuit of HR. Here we evaluate inpatient mortality, a proxy to healthcare quality, in 43 top tertiary hospitals in China during this critical period. This is a hospital-based observational study with 8 million discharge summary reports (DSR) from 43 Chinese hospitals from 2010-2012. Using DSRs, we extract the vita status as the outcome, in addition to age, gender, diagnostic codes, and surgical codes. Nearly all hospitals have expanded their hospitalization capacities during this period. As of year 2010, inpatient mortality (IM) across hospitals varies widely from 2‰ to 20‰. Comparing IM of year 2011 and 2012 with 2010, the overall IM has been substantially reduced (OR = 0.883 and 0.766, p-values<0.001), showing steady improvements in healthcare quality. Surgical IM correlates with the overall IM (correlation = 0.60, p-value <0.001), but is less uniform. Over these years, surgical IM has also been steadily reduced (OR = 0.890 and 0.793, p-values<0.001). Further analyses of treatments on five major diseases and six major surgeries revealed that treatments of myocardial infarction, cerebral hemorrhage and cerebral infarction have significant improvement. Observed temporal and spatial variations demonstrate that there is a substantial disparity in healthcare quality across tertiary hospitals, and that these hospitals are rapidly improving healthcare quality. Evidence-based assessment shed light on the reform impact. Lessons learnt here are relevant to further refining HR.