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William M. Briggs

Bio: William M. Briggs is an academic researcher from Houston Methodist Hospital. The author has contributed to research in topics: Population & Emergency department. The author has an hindex of 25, co-authored 82 publications receiving 9300 citations. Previous affiliations of William M. Briggs include Central Michigan University & NewYork–Presbyterian Hospital.


Papers
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Journal ArticleDOI
TL;DR: In this article, statistical methods in the Atmospheric Sciences are used to estimate the probability of a given event to be a hurricane or tropical cyclone, and the probability is determined by statistical methods.
Abstract: (2007). Statistical Methods in the Atmospheric Sciences. Journal of the American Statistical Association: Vol. 102, No. 477, pp. 380-380.

7,052 citations

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TL;DR: The adapted comorbidity index can be used to predict resource utilization and may help to identify targets for reducing high costs, by prospectively identifying those at high risk.

714 citations

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TL;DR: A PLUS-inclusive protocol significantly decreased time to operative care in patients with suspected torso trauma, with improved resource use and lower charges.

321 citations

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TL;DR: D outperformed S but may require more training and personnel, and all central cannula placement should be conducted with ultrasound assistance.
Abstract: Context:A 2001 Agency for Healthcare Research and Quality Evidence Report on patient safety addressed point-of-care limited ultrasonography guidance for central venous cannulation and strongly recommended real-time, dynamic guidance for all central cannulas. However, on the basis of one limited stud

294 citations

Journal ArticleDOI
TL;DR: The clinical characteristics and health care expenditures of patients most likely to be targeted by disease management programs are examined and the overwhelming impact of comorbidity on costs raises significant concerns about the potential ability of disease management Programs to limit the costs of care.
Abstract: Context Disease management programs are increasingly used to manage costs of patients with chronic disease.

116 citations


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6,278 citations

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TL;DR: The theory of proper scoring rules on general probability spaces is reviewed and developed, and the intuitively appealing interval score is proposed as a utility function in interval estimation that addresses width as well as coverage.
Abstract: Scoring rules assess the quality of probabilistic forecasts, by assigning a numerical score based on the predictive distribution and on the event or value that materializes. A scoring rule is proper if the forecaster maximizes the expected score for an observation drawn from the distributionF if he or she issues the probabilistic forecast F, rather than G ≠ F. It is strictly proper if the maximum is unique. In prediction problems, proper scoring rules encourage the forecaster to make careful assessments and to be honest. In estimation problems, strictly proper scoring rules provide attractive loss and utility functions that can be tailored to the problem at hand. This article reviews and develops the theory of proper scoring rules on general probability spaces, and proposes and discusses examples thereof. Proper scoring rules derive from convex functions and relate to information measures, entropy functions, and Bregman divergences. In the case of categorical variables, we prove a rigorous version of the ...

4,644 citations

01 Jan 2020
TL;DR: Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future.
Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

4,408 citations

BookDOI
01 Jan 2006
TL;DR: Regression models are frequently used to develop diagnostic, prognostic, and health resource utilization models in clinical, health services, outcomes, pharmacoeconomic, and epidemiologic research, and in a multitude of non-health-related areas.
Abstract: Regression models are frequently used to develop diagnostic, prognostic, and health resource utilization models in clinical, health services, outcomes, pharmacoeconomic, and epidemiologic research, and in a multitude of non-health-related areas. Regression models are also used to adjust for patient heterogeneity in randomized clinical trials, to obtain tests that are more powerful and valid than unadjusted treatment comparisons.

4,211 citations

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TL;DR: In this article, the authors found that anomalous warming events different from conventional El Nino events occur in the central equatorial Pacific, where a horseshoe pattern is flanked by a colder sea surface temperature anomaly (SSTA) on both sides along the equator.
Abstract: [1] Using observed data sets mainly for the period 1979–2005, we find that anomalous warming events different from conventional El Nino events occur in the central equatorial Pacific. This unique warming in the central equatorial Pacific associated with a horseshoe pattern is flanked by a colder sea surface temperature anomaly (SSTA) on both sides along the equator. empirical orthogonal function (EOF) analysis of monthly tropical Pacific SSTA shows that these events are represented by the second mode that explains 12% of the variance. Since a majority of such events are not part of El Nino evolution, the phenomenon is named as El Nino Modoki (pseudo-El Nino) (“Modoki” is a classical Japanese word, which means “a similar but different thing”). The El Nino Modoki involves ocean-atmosphere coupled processes which include a unique tripolar sea level pressure pattern during the evolution, analogous to the Southern Oscillation in the case of El Nino. Hence the total entity is named as El Nino–Southern Oscillation (ENSO) Modoki. The ENSO Modoki events significantly influence the temperature and precipitation over many parts of the globe. Depending on the season, the impacts over regions such as the Far East including Japan, New Zealand, western coast of United States, etc., are opposite to those of the conventional ENSO. The difference maps between the two periods of 1979–2004 and 1958–1978 for various oceanic/atmospheric variables suggest that the recent weakening of equatorial easterlies related to weakened zonal sea surface temperature gradient led to more flattening of the thermocline. This appears to be a cause of more frequent and persistent occurrence of the ENSO Modoki event during recent decades.

2,340 citations