Tearing down walls: opening the border between hospital and ambulatory care for quality improvement in Germany

The hospital benchmarking system in Germany was originally introduced to detect unintended consequences of reimbursement based on diagnosis-related groups. The new nationwide SQG programme aims to provide information on quality and outcomes of health care provided in hospital, ambulatory specialist and primary care settings, including the healthcare delivery across different sectors. In 2010 the topics for indicator development were cataract surgery, cervical conization, colectoral cancer and percutaneous coronary interventions or coronary angiography. A systematic stepwise modified RAND/UCLA procedure is applied to develop quality indicators in each of these domains. A general framework for data collection is implemented. Benchmarking results are fed back to providers on a regular basis

Artificial pancreas systems for people with type 2 diabetes: Conception and design of the european CLOSE project

In the last 10 years tremendous progress has been made in the development of artificial pancreas (AP) systems for people with type 1 diabetes (T1D). The pan-European consortium CLOSE (Automated Glucose Control at Home for People with Chronic Disease) is aiming to develop integrated AP solutions (APplus) tailored to the needs of people with type 2 diabetes (T2D). APplus comprises a product and service package complementing the AP system by obligatory training as well as home visits and telemedical consultations on demand. Outcome predictors and performance indicators shall help to identify people who could benefit most from AP usage and facilitate the measurement of AP impact in diabetes care. In a first step CLOSE will establish a scalable APplus model case working at the interface between patients, homecare service providers, and payers in France. CLOSE will then scale up APplus by pursuing geographic distribution, targeting additional audiences, and enhancing AP functionalities and interconnectedness. By being part of the European Institute of Innovation and Technology (EIT) Health public-private partnership, CLOSE is committed to the EIT “knowledge triangle” pursuing the integrated advancement of technology, education, and business creation. Putting stakeholders, education, and impact into the center of APplus advancement is considered key for achieving wide AP use in T2D care

Early Diagnosis of Vegetation Health From High-Resolution Hyperspectral and Thermal Imagery: Lessons Learned From Empirical Relationships and Radiative Transfer Modelling

[Purpose of Review] We provide a comprehensive review of the empirical and modelling approaches used to quantify the radiation–vegetation interactions related to vegetation temperature, leaf optical properties linked to pigment absorption and chlorophyll fluorescence emission, and of their capability to monitor vegetation health. Part 1 provides an overview of the main physiological indicators (PIs) applied in remote sensing to detect alterations in plant functioning linked to vegetation diseases and decline processes. Part 2 reviews the recent advances in the development of quantitative methods to assess PI through hyperspectral and thermal images.[Recent Findings] In recent years, the availability of high-resolution hyperspectral and thermal images has increased due to the extraordinary progress made in sensor technology, including the miniaturization of advanced cameras designed for unmanned aerial vehicle (UAV) systems and lightweight aircrafts. This technological revolution has contributed to the wider use of hyperspectral imaging sensors by the scientific community and industry; it has led to better modelling and understanding of the sensitivity of different ranges of the electromagnetic spectrum to detect biophysical alterations used as early warning indicators of vegetation health.[Summary] The review deals with the capability of PIs such as vegetation temperature, chlorophyll fluorescence, photosynthetic energy downregulation and photosynthetic pigments detected through remote sensing to monitor the early responses of plants to different stressors. Various methods for the detection of PI alterations have recently been proposed and validated to monitor vegetation health. The greatest challenges for the remote sensing community today are (i) the availability of high spatial, spectral and temporal resolution image data; (ii) the empirical validation of radiation–vegetation interactions; (iii) the upscaling of physiological alterations from the leaf to the canopy, mainly in complex heterogeneous vegetation landscapes; and (iv) the temporal dynamics of the PIs and the interaction between physiological changes.The authors received funding provided by the FluorFLIGHT (GGR801) Marie Curie Fellowship, the QUERCUSAT and ESPECTRAMED projects (Spanish Ministry of Economy and Competitiveness), the Academy of Finland (grants 266152, 317387) and the European Research Council Synergy grant ERC-2013-SyG-610028 IMBALANCE-P.Peer reviewe

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given

Effectiveness of a quality management program in dental care practices

Contains fulltext : 137890.pdf (publisher's version ) (Open Access)BACKGROUND: Structured quality management is an important aspect for improving patient dental care outcomes, but reliable evidence to validate effects is lacking. We aimed to examine the effectiveness of a quality management program in primary dental care settings in Germany. METHODS: This was an exploratory study with a before-after-design. 45 dental care practices that had completed the European Practice Assessment (EPA) accreditation scheme twice (intervention group) were selected for the study. The mean interval between the before and after assessment was 36 months. The comparison group comprised of 56 dental practices that had undergone their first assessment simultaneously with follow-up assessment in the intervention group. Aggregated scores for five EPA domains: 'infrastructure', 'information', 'finance', 'quality and safety' and 'people' were calculated. RESULTS: In the intervention group, small non-significant improvements were found in the EPA domains. At follow-up, the intervention group had higher scores on EPA domains as compared with the comparison group (range of differences was 4.2 to 10.8 across domains). These differences were all significant in regression analyses, which controlled for relevant dental practice characteristics. CONCLUSIONS: Dental care practices that implemented a quality management program had better organizational quality in contrast to a comparison group. This may reflect both improvements in the intervention group and a selection effect of dental practices volunteering for the first round of EPA practice assessment