Methodologies for determining staffing needs in healthcare: systematic literature review

The determination of staffing needs in healthcare is not just calculating the optimal number of professionals but is defining how the professional contingent accompanies the development of the healthcare organisation and of the population’s care needs. This research investigates the existence of a gold standard for determining health personnel requirements. We perform a systematic literature review to explore several approaches worldwide, examining a wide range of contextual variables, useful for the definition of an omni-comprehensive approach. A total of 557 articles was initially detected, then reduced to 57 after excluding everything not related to healthcare context and staff planning models. Results do not reveal a recognized standard for determining staffing needs. Approaches to the definition of staffing standards are mainly ex-ante (31%), based on the characteristics of specific models and organisational needs, or ex-post (62%), based on production analysis and historical trends. Most of these refer to the medical and nursing category (68.4%), while the minority proposes a multi-professional approach (17.5%). This review highlights innovative approaches based on algorithms which, starting from historical data, are adjusted by moderating key variables such as contextual factors, healthcare organisation models and professional attributes. The review suggests: 1. Develop and share a unique tool for defining standards based on several variables that identify the characteristics of the context 2. Use up-to-date information flows and quality data 3. Consider a multi-professional approach 4. Adopt a long-term vision and continuous dialogue with the training process It is clear the need to develop a tool for the definition of personnel requirements in line with internal and external changes in the health system. Therefore, such models need to account for an adequate number of variables, useful to identify the characteristics of the overall context. Key messages: The development of staffing needs estimates must necessarily rely on a certain level of standardisation, but at the same time must take into account the variability characterising different contexts. In order to respond to recent demographic and epidemiological trends, it is crucial to include in the model skill mix and task shifting strategies involving health professionals as a whole

Acute kidney injury (Aki) before and after kidney transplantation: Causes, medical approach, and implications for the long-term outcomes

Acute kidney injury (AKI) is a common finding in kidney donors and recipients. AKI in kidney donor, which increases the risk of delayed graft function (DGF), may not by itself jeopardize the short-and long-term outcome of transplantation. However, some forms of AKI may induce graft rejection, fibrosis, and eventually graft dysfunction. Therefore, various strategies have been proposed to identify conditions at highest risk of AKI-induced DGF, that can be treated by targeting the donor, the recipient, or even the graft itself with the use of perfusion machines. AKI that occurs early post-transplant after a period of initial recovery of graft function may reflect serious and often occult systemic complications that may require prompt intervention to prevent graft loss. AKI that develops long after transplantation is often related to nephrotoxic drug reactions. In symptomatic patients, AKI is usually associated with various systemic medical complications and could represent a risk of mortality. Electronic systems have been developed to alert transplant physicians that AKI has occurred in a transplant recipient during long-term outpatient follow-up. Herein, we will review most recent understandings of pathophysiology, diagnosis, therapeutic approach, and short-and long-term consequences of AKI occurring in both the donor and in the kidney transplant recipient

Pneumococcal Polysaccharide Vaccine Ameliorates Murine Lupus

Current guidelines encourage administering pneumococcal vaccine Prevnar-13 to patients with lupus, but whether such vaccinations affect disease severity is unclear. To address this issue, we treated 3-month-old MRL-lpr mice, that spontaneously develop a lupus-like syndrome, with Prevnar-13 or vehicle control. After 3 months, we quantified circulating anti-Pneumococcal polysaccharide capsule (PPS) antibodies and signs of disease severity, including albuminuria, renal histology and skin severity score. We also compared immunophenotypes and function of T and B cells from treated and untreated animals. Prevnar-13 elicited the formation of anti-pneumococcal IgM and IgG. Prevnar-13 treated animals showed reduced albuminuria, renal histological lesions, and milder dermatitis compared to vehicle-treated controls. Mitigated disease severity was associated with reduced and increased T follicular helper cells (TFH) and T follicular regulatory cells (TFR), respectively, in Prevnar-treated animals. T cells from Prevnar-13 vaccinated mice showed differential cytokine production after aCD3/aCD28 stimulation, with significantly decreased IL-17 and IL-4, and increased IL-10 production compared to non-vaccinated mice. In conclusion, pneumococcal vaccination elicits anti-pneumococcal antibody response and ameliorates disease severity in MRL-lpr mice, which associates with fewer TFH and increased TFR. Together, the data support use of Prevnar vaccination in individuals with SLE

NetPyNE, a tool for data-driven multiscale modeling of brain circuits.

Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic and graphical interfaces to develop data-driven multiscale network models in NEURON. NetPyNE clearly separates model parameters from implementation code. Users provide specifications at a high level via a standardized declarative language, for example connectivity rules, to create millions of cell-to-cell connections. NetPyNE then enables users to generate the NEURON network, run efficiently parallelized simulations, optimize and explore network parameters through automated batch runs, and use built-in functions for visualization and analysis - connectivity matrices, voltage traces, spike raster plots, local field potentials, and information theoretic measures. NetPyNE also facilitates model sharing by exporting and importing standardized formats (NeuroML and SONATA). NetPyNE is already being used to teach computational neuroscience students and by modelers to investigate brain regions and phenomena

Cost overruns – helping to define what they really mean

Civil engineers are often in the firing line for alleged cost overruns, particularly on major publicly funded infrastructure projects. This usually occurs when the final cost of a project is simply compared with the original estimate, even though this was published a long time ago, in different circumstances and for a quite different project to the one carried out. This paper proposes a systematic approach to ensure that cost overruns, should they occur, are more accurately defined in terms of when the initial and end costs are assessed, from which point of view, at which project stage, and including scope changes and financial assumptions. The paper refers to the UK’s £163 billion nuclear decommissioning programme

autologous pancreatic islet transplantation in human bone marrow diabetes 2013 62 3523 3531

In the article listed above, there is an error in Fig. 3. In panel B , the immunohistochemical staining of insulin ( top middle panel

OpenWorm: an open-science approach to modeling Caenorhabditis elegans.

OpenWorm is an international collaboration with the aim of understanding how the behavior of Caenorhabditis elegans (C. elegans) emerges from its underlying physiological processes. The project has developed a modular simulation engine to create computational models of the worm. The modularity of the engine makes it possible to easily modify the model, incorporate new experimental data and test hypotheses. The modeling framework incorporates both biophysical neuronal simulations and a novel fluid-dynamics-based soft-tissue simulation for physical environment-body interactions. The project's open-science approach is aimed at overcoming the difficulties of integrative modeling within a traditional academic environment. In this article the rationale is presented for creating the OpenWorm collaboration, the tools and resources developed thus far are outlined and the unique challenges associated with the project are discussed