The IIASA Health Care Resource Allocation Submodel: Model Calibration for Data from Czechoslovakia

In many developed countries the problem of allocating resources within the Health Care System (HCS) is perennial. Health Care administrators are continually asking what are the consequences of changing the mix of resources. The disaggregated resource allocation model (DRAM) has been developed to assist Health Care administrators with this problem. The model simulates how the HCS in aggregate allocates limited supplies of resources between competing demands. The principal outputs of the model are the numbers of patients treated in different categories, and the modes and quotas of treatment they receive. This paper describes how parameters were estimated for DRAM for Czechoslovakian hospital in-patient care. The model was parameterized for seven patient categories (general surgery, general medicine, obstetrics and gynaecology, traumatic and orthopaedic surgery, otorhinolaryngology, paediatrics, and ophthalmology) and two resource types (hospital beds and hospital doctors). The paper ends with a description of how the model could be used to investigate the consequences of changes in the mix of hospital beds and hospital doctors for Czechoslovakian hospital in-patient care

Performance and Output Measurement: A Joint Meeting of Euro Public Sector and Health Working Groups -- 14-16 January, 1980

Most governmental and public service bodies have developed methods for measuring and controlling the inputs to major programs, in terms of finance, manpower, and other resources. There has, however, been relatively little success in measuring the output of such programs -- except in rather special cases -- and such measurement as takes place is usually on secondary rather than primary measures of output; it is easy to measure the number of patients handled in a clinic, but much more difficult to determine how far their health is improved. The issue of performance and output measurement is thus of major concern to operational research workers and applied systems analysts, much of whose work is directed towards public service programs, and because it cuts across many fields of application. It therefore seemed particularly appropriate that two working groups of the European Association of Operational Research Societies should meet at the International Institute for Applied Systems Analysis in January 1980 to discuss this topic. As the discussion may be of wider interest than to those actually present it all seems appropriate to make these notes more widely available in the form of an IIASA Collaborative Paper. The meeting was the prime responsibility of Peter Turner and Duncan Boldy, chairmen respectively of the Public Sector and Health Working Groups of EURO. At IIASA the coordination was undertaken by Philip Aspden of the Health Care Systems Modeling Task. These three are the joint editors of this report. It was felt that the proceedings were worth recording but that, as they were really part of an ongoing debate, they should be made available as quickly as possible. To avoid further delay some of the papers are therefore presented in note form, and the discussion has been condensed to bring out the main topics of interest. It is too seldom that those engaged in the analytical study of policy issues get together specifically to discuss their problems, rather than to parade their solutions. We hope that this collaborative paper may help to stimulate further such meetings

Dram Balances Care

In many developed countries the problem of allocating resources within the Health Care System is perennial. Health Care planners wish to know the consequences of changing the mix of resources. The Balance of Care (BOC) Model, designed to help Health Care Planners answer this question, has been successfully applied over the past few years in the Department of Health and Social Security, UK. The Disaggregated Resource Allocation Model (DRAM), developed at IIASA, is also designed to help Health Care planners answer the above question. This paper compares the performance of both models in two respects. Firstly, it indicates that DRAM is likely to be able to cope with problems of the same size and complexity as the BOC model. Secondly, the paper demonstrates that DRAM can more accurately model the use of alternative modes of care within treatment categories. Data collected for the allocation of care for the elderly in Devon, UK are used in the comparisons

Modeling Health Care Systems: June 1979 Workshop Proceedings

These Collaborative Papers contain the gapers submitted by the participants of the June 1979 IIASA workshop on modeling Health Care Systems (HCS) and a brief summary of the principal items of discussion that took place. The participants represented 13 countries, the Headquarters of the World Health Organization (WHO), and its Regional Office for Europe. The aims of the workshop included reviewing the HCS modeling that has been done at the participating organizations and discussing the possibility of extending the HCS Task at IIASA to include health-economic models

A comparison of cortical and trabecular bone from C57 Black 6 mice using Raman spectroscopy

Peer reviewedPostprin

The IIASA Health Care Resource Allocation Submodel: DRAM Calibration for Data from the South West Health Region, UK

In many developed countries the problem of allocating resources within the Health Care System (HCS) is perennial. Health care administrators are continually asking what are the consequences of changing the mix of resources. The disaggregated resource allocation model (DRAM) has been developed to assist health care administrators with this problem. The model simulates how the HCS in aggregate allocates limited supplies of resources between competing demands. The principal outputs of the model are the numbers of patients treated in different categories, and the modes and quotas of treatment they receive. Health care planners in the South West Health Region of England are concerned about the consequences for hospital inpatient care of increasing the number of hospital doctors and decreasing the number of hospital beds. This paper indicates how DRAM could be used to assist in the solution of this problem. Parameters were estimated for a model of hospital inpatient care for the region. This model consisted of seven patient categories (general surgery, general medicine, obstetrics and gynaecology, traumatic and orthopaedic surgery, otorhinolarygology, paediatrics and ophthalmology) and two resource types (hospital beds and hospital doctors). The ability with which this model was able to reproduce actual allocations or resources had similarities with a model (of identical structure) of Czechoslovakian hospital in-patient care. It was considered appropriate to reduce the number of patient categories to three (general surgery, general medicine, and obstetrics and gynaecology). Parameters for this three-patient-category model were re-evaluated. Within the assumed predictive accuracy of this model, it successfully predicted health care resource allocation across time and space. The three-patient-category/two-resource type model was then used to explore the consequences of changing the mix of resources in the South West Health Region. Firstly, the consequences of changes from the existing resource levels which involved no estimated increase in running costs were considered. More general changes where this constraint no longer held, were then examined

Testing for entanglement with periodic coarse-graining

Continuous variables systems find valuable applications in quantum information processing. To deal with an infinite-dimensional Hilbert space, one in general has to handle large numbers of discretized measurements in tasks such as entanglement detection. Here we employ the continuous transverse spatial variables of photon pairs to experimentally demonstrate novel entanglement criteria based on a periodic structure of coarse-grained measurements. The periodization of the measurements allows for an efficient evaluation of entanglement using spatial masks acting as mode analyzers over the entire transverse field distribution of the photons and without the need to reconstruct the probability densities of the conjugate continuous variables. Our experimental results demonstrate the utility of the derived criteria with a success rate in entanglement detection of $\sim60\%$ relative to $7344$ studied cases.Comment: V1: revtex4, 10 pages, 4 figures + supp. material (4 pages, 1 figure) V2: Substantial revisions implemented both in theory and experimental data analysi

The influence of the strength of bone on the deformation of acetabular shells : a laboratory experiment in cadavers

Date of Acceptance: 24/08/2014 ©2015 The British Editorial Society of Bone & Joint Surgery. The authors would like to thank N. Taylor (3D Measurement Company) for his work with regard to data acquisition and processing of experimental data. We would also like to thank Dr A. Blain of Newcastle University for performing the statistical analysis The research was supported by the NIHR Newcastle Biomedical Research Centre. The authors P. Dold, M. Flohr and R. Preuss are employed by Ceramtec GmbH. Martin Bone received a salary from the joint fund. The author or one or more of the authors have received or will receive benefits for personal or professional use from a commercial party related directly or indirectly to the subject of this article. This article was primary edited by G. Scott and first proof edited by J. Scott.Peer reviewedPostprin

EPR-based ghost imaging using a single-photon-sensitive camera

Correlated photon imaging, popularly known as ghost imaging, is a technique whereby an image is formed from light that has never interacted with the object. In ghost imaging experiments, two correlated light fields are produced. One of these fields illuminates the object, and the other field is measured by a spatially resolving detector. In the quantum regime, these correlated light fields are produced by entangled photons created by spontaneous parametric down-conversion. To date, all correlated photon ghost imaging experiments have scanned a single-pixel detector through the field of view to obtain spatial information. However, scanning leads to poor sampling efficiency, which scales inversely with the number of pixels, N, in the image. In this work, we overcome this limitation by using a time-gated camera to record the single-photon events across the full scene. We obtain high-contrast images, 90%, in either the image plane or the far field of the photon pair source, taking advantage of the Einstein–Podolsky–Rosen-like correlations in position and momentum of the photon pairs. Our images contain a large number of modes, >500, creating opportunities in low-light-level imaging and in quantum information processing

Developmental regulation of canonical and small ORF translation from mRNAs

Background: Ribosomal profiling has revealed the translation of thousands of sequences outside annotated protein-coding genes, including small open reading frames of less than 100 codons, and the translational regulation of many genes. Here we present an improved version of Poly-Ribo-Seq and apply it to Drosophila melanogaster embryos to extend the catalog of in vivo translated small ORFs, and to reveal the translational regulation of both small and canonical ORFs from mRNAs across embryogenesis. Results: We obtain highly correlated samples across five embryonic stages, with nearly 500 million putative ribosomal footprints mapped to mRNAs, and compare them to existing Ribo-Seq and proteomic data. Our analysis reveals, for the first time in Drosophila, footprints mapping to codons in a phased pattern, the hallmark of productive translation. We propose a simple binomial probability metric to ascertain translation probability. Our results also reveal reproducible ribosomal binding apparently not resulting in productive translation. This non-productive ribosomal binding seems to be especially prevalent amongst upstream short ORFs located in the 5′ mRNA leaders, and amongst canonical ORFs during the activation of the zygotic translatome at the maternal-to zygotic transition. Conclusions: We suggest that this non-productive ribosomal binding might be due to cis-regulatory ribosomal binding and to defective ribosomal scanning of ORFs outside periods of productive translation. Our results are compatible with the main function of upstream short ORFs being to buffer the translation of canonical canonical ORFs; and show that, in general, small ORFs in mRNAs display markers compatible with an evolutionary transitory state towards full coding function