Robust wavebuoys for the marginal ice zone: Experiences from a large persistent array in the Beaufort Sea

An array of novel directional wavebuoys was designed and deployed into the Beaufort Sea ice cover in March 2014, as part of the Office of Naval Research Marginal Ice Zone experiment. The buoys were designed to drift with the ice throughout the year and monitor the expected breakup and retreat of the ice cover, forced by waves travelling into the ice from open water. Buoys were deployed from fast-and-light air-supported ice camps, based out of Sachs Harbour on Canada’s Banks Island, and drifted westwards with the sea ice over the course of spring, summer and autumn, as the ice melted, broke up and finally re-froze. The buoys transmitted heave, roll and pitch timeseries at 1 Hz sample frequency over the course of up to eight months, surviving both convergent ice dynamics and significant waves-in-ice events. Twelve of the 19 buoys survived until their batteries were finally exhausted during freeze-up in late October/November. Ice impact was found to have contaminated a significant proportion of the Kalman-filter-derived heave records, and these bad records were removed with reference to raw x/y/z accelerations. The quality of magnetometer-derived buoy headings at the very high magnetic field inclinations close to the magnetic pole was found to be generally acceptable, except in the case of four buoys which had probably suffered rough handling during transport to the ice. In general, these new buoys performed as expected, though vigilance as to the veracity of the output is required

Comparison of Rx-defined morbidity groups and diagnosis- based risk adjusters for predicting healthcare costs in Taiwan

<p>Abstract</p> <p>Background</p> <p>Medication claims are commonly used to calculate the risk adjustment for measuring healthcare cost. The Rx-defined Morbidity Groups (Rx-MG) which combine the use of medication to indicate morbidity have been incorporated into the Adjusted Clinical Groups (ACG) Case Mix System, developed by the Johns Hopkins University. This study aims to verify that the Rx-MG can be used for adjusting risk and for explaining the variations in the healthcare cost in Taiwan.</p> <p>Methods</p> <p>The Longitudinal Health Insurance Database 2005 (LHID2005) was used in this study. The year 2006 was chosen as the baseline to predict healthcare cost (medication and total cost) in 2007. The final sample size amounted to 793 239 (81%) enrolees, and excluded any cases with discontinued enrolment. Two different kinds of models were built to predict cost: the concurrent model and the prospective model. The predictors used in the predictive models included age, gender, Aggregated Diagnosis Groups (ADG, diagnosis- defined morbidity groups), and Rx-defined Morbidity Groups. Multivariate OLS regression was used in the cost prediction modelling.</p> <p>Results</p> <p>The concurrent model adjusted for Rx-defined Morbidity Groups for total cost, and controlled for age and gender had a better predictive R-square = 0.618, compared to the model adjusted for ADGs (R²= 0.411). The model combined with Rx-MGs and ADGs performed the best for concurrently predicting total cost (R²= 0.650). For prospectively predicting total cost, the model combined Rx-MGs and ADGs (R²= 0.382) performed better than the models adjusted by Rx-MGs (R²= 0.360) or ADGs (R²= 0.252) only. Similarly, the concurrent model adjusted for Rx-MGs predicting pharmacy cost had a better performance (R-square = 0.615), than the model adjusted for ADGs (R²= 0.431). The model combined with Rx-MGs and ADGs performed the best in concurrently as well as prospectively predicting pharmacy cost (R²= 0.638 and 0.505, respectively). The prospective models showed a remarkable improvement when adjusted by prior cost.</p> <p>Conclusions</p> <p>The medication-based Rx-Defined Morbidity Groups was useful in predicting pharmacy cost as well as total cost in Taiwan. Combining the information on medication and diagnosis as adjusters could arguably be the best method for explaining variations in healthcare cost.</p

Pharmaceutical Cost Management in an Ambulatory Setting Using a Risk Adjustment Tool

© 2014 Vivas-Consuelo et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.Background Pharmaceutical expenditure is undergoing very high growth, and accounts for 30% of overall healthcare expenditure in Spain. In this paper we present a prediction model for primary health care pharmaceutical expenditure based on Clinical Risk Groups (CRG), a system that classifies individuals into mutually exclusive categories and assigns each person to a severity level if s/he has a chronic health condition. This model may be used to draw up budgets and control health spending. Methods Descriptive study, cross-sectional. The study used a database of 4,700,000 population, with the following information: age, gender, assigned CRG group, chronic conditions and pharmaceutical expenditure. The predictive model for pharmaceutical expenditure was developed using CRG with 9 core groups and estimated by means of ordinary least squares (OLS). The weights obtained in the regression model were used to establish a case mix system to assign a prospective budget to health districts. Results The risk adjustment tool proved to have an acceptable level of prediction (R2 0.55) to explain pharmaceutical expenditure. Significant differences were observed between the predictive budget using the model developed and real spending in some health districts. For evaluation of pharmaceutical spending of pediatricians, other models have to be established. Conclusion The model is a valid tool to implement rational measures of cost containment in pharmaceutical expenditure, though it requires specific weights to adjust and forecast budgets.This study was financed by a grant from the Fondo de Investigaciones de la Seguridad Social Instituto de Salud Carlos III, the Spanish Ministry of Health (FIS PI12/0037). The authors would like to thank members (Juan Bru and Inma Saurf) of the Pharmacoeconomics Office of the Valencian Health Department. The opinions expressed in this paper are those of the authors and do not necessary reflect those of the afore-named. Any errors are the authors' responsibility. We would also like to thank John Wright for the English editing.Vivas Consuelo, DJJ.; Usó Talamantes, R.; Guadalajara Olmeda, MN.; Trillo Mata, JL.; Sancho Mestre, C.; Buigues Pastor, L. (2014). Pharmaceutical Cost Management in an Ambulatory Setting Using a Risk Adjustment Tool. 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