Ontology-based Defect Causation Analysis for Urban Tunnel Maintenance

2021 ◽  
Author(s):  
Jiajun Zhang ◽  
Juan Du
Keyword(s):  
Causation Analysis

Apportionment of Impairment from Meniscal Tears and Knee Arthritis

2013 ◽  
Vol 18 (5) ◽  
pp. 1-10 ◽  
Author(s):  
Charles N. Brooks ◽  
James B. Talmage
Keyword(s):  
Medial Meniscus ◽  
Degenerative Joint Disease ◽  
Joint Disease ◽  
Detailed Knowledge ◽  
Meniscal Tears ◽  
Knee Arthritis ◽  
Degenerative Arthritis ◽  
Study Results ◽  
Physical Findings ◽  
Causation Analysis

Abstract Meniscal tears and osteoarthritis (osteoarthrosis, degenerative arthritis, or degenerative joint disease) are two of the most common conditions involving the knee. This article includes definitions of apportionment and causes; presents a case report of initial and recurrent tears of the medial meniscus plus osteoarthritis (OA) in the medial compartment of the knee; and addresses questions regarding apportionment. The authors, experienced impairment raters who are knowledgeable regarding the AMA Guides to the Evaluation of Permanent Impairment (AMA Guides), show that, when instructions on impairment rating are incomplete, unclear, or inconsistent, interrater reliability diminishes (different physicians may derive different impairment estimates). Accurate apportionment of impairment is a demanding task that requires detailed knowledge of causation for the conditions in question; the mechanisms of injury or extent of exposures; prior and current symptoms, functional status, physical findings, and clinical study results; and use of the appropriate edition of the AMA Guides. Sometimes the available data are incomplete, requiring the rating physician to make assumptions. However, if those assumptions are reasonable and consistent with the medical literature and facts of the case, if the causation analysis is plausible, and if the examiner follows impairment rating instructions in the AMA Guides (or at least uses a rational and hence defensible method when instructions are suboptimal), the resulting apportionment should be credible.

Shoulder Pain at Work: Causation Analysis

2017 ◽  
Vol 22 (1) ◽  
pp. 11-16
Author(s):  
Joel Weddington ◽  
Charles N. Brooks ◽  
Mark Melhorn ◽  
Christopher R. Brigham
Keyword(s):  
Epidemiological Data ◽  
Case Law ◽  
Individual Case ◽  
Shoulder Injury ◽  
Work Related ◽  
Clear Cut ◽  
The Individual ◽  
Causation Analysis ◽  
Injury Causation ◽  
Relevant Factors

Abstract In most cases of shoulder injury at work, causation analysis is not clear-cut and requires detailed, thoughtful, and time-consuming causation analysis; traditionally, physicians have approached this in a cursory manner, often presenting their findings as an opinion. An established method of causation analysis using six steps is outlined in the American College of Occupational and Environmental Medicine Guidelines and in the AMA Guides to the Evaluation of Disease and Injury Causation, Second Edition, as follows: 1) collect evidence of disease; 2) collect epidemiological data; 3) collect evidence of exposure; 4) collect other relevant factors; 5) evaluate the validity of the evidence; and 6) write a report with evaluation and conclusions. Evaluators also should recognize that thresholds for causation vary by state and are based on specific statutes or case law. Three cases illustrate evidence-based causation analysis using the six steps and illustrate how examiners can form well-founded opinions about whether a given condition is work related, nonoccupational, or some combination of these. An evaluator's causal conclusions should be rational, should be consistent with the facts of the individual case and medical literature, and should cite pertinent references. The opinion should be stated “to a reasonable degree of medical probability,” on a “more-probable-than-not” basis, or using a suitable phrase that meets the legal threshold in the applicable jurisdiction.

Comparative Analysis: The State of Colorado Study, Part II

2004 ◽  
Vol 9 (2) ◽  
pp. 1-16
Author(s):  
Christopher R. Brigham ◽  
Kathryn Mueller ◽  
Douglas Van Zet ◽  
Debra J. Northrup ◽  
Edward B. Whitney ◽  
...  
Keyword(s):  
Daily Living ◽  
Scientific Evidence ◽  
Pain Syndrome ◽  
Evidence Based ◽  
Clinical Assessments ◽  
Physician Judgment ◽  
History Of ◽  
Key Terms ◽  
Causation Analysis ◽  
Work Interference

Abstract [Continued from the January/February 2004 issue of The Guides Newsletter.] To understand discrepancies in reviewers’ ratings of impairments based on different editions of the AMA Guides to the Evaluation of Permanent Impairment (AMA Guides), users can usefully study the history of the revisions as successive editions attempted to provide a comprehensive, valid, reliable, unbiased, and evidence-based system. Some shortcomings of earlier editions have been addressed in the AMA Guides, Fifth Edition, but problems remain with each edition, largely because of the limited scientific evidence available. In the context of the history of the different editions of the AMA Guides and their development, the authors discuss and contextualize a number of key terms and principles including the following: definitions of impairment and normal; activities of daily living; maximum medical improvement; impairment percentages; conversion of regional impairments; combining impairments; pain and other subjective complaints; physician judgment; and causation analysis; finally, the authors note that impairment is not synonymous with disability or work interference. The AMA Guides, Fifth Edition, contrasts impairment evaluations and independent medical evaluations (this was not done in previous editions) and discusses impairment evaluations, rules for evaluations, and report standards. Upper extremity and lower extremity impairment evaluations are discussed in terms of clinical assessments and rating processes, analyzing important changes between editions and problematic areas (eg, complex regional pain syndrome).

scholarly journals Medicolegal Causation Investigation of Bacterial Endocarditis Associated with an Oral Surgery Practice Using the INFERENCE Approach

2021 ◽  
Vol 18 (14) ◽  
pp. 7530
Author(s):  
Putri Dianita Ika Meilia ◽  
Maurice P. Zeegers ◽  
Herkutanto ◽  
Michael D. Freeman
Keyword(s):  
Oral Surgery ◽  
Invasive Procedure ◽  
Bacterial Endocarditis ◽  
Infection Prevention And Control ◽  
Healthcare Associated Infection ◽  
Department Of Health ◽  
The Individual ◽  
Healthcare Associated ◽  
And Control ◽  
Causation Analysis

Investigating causation is a primary goal in forensic/legal medicine, aiming to establish the connection between an unlawful/negligent act and an adverse outcome. In malpractice litigation involving a healthcare-associated infection due to a failure of infection prevention and control practices, the medicolegal causal analysis needs to quantify the individual causal probabilities to meet the evidentiary requirements of the court. In this paper, we present the investigation of the most probable cause of bacterial endocarditis in a patient who underwent an invasive procedure at a dental/oral surgical practice where an outbreak of bacterial endocarditis had already been identified by the state Department of Health. We assessed the probability that the patient’s endocarditis was part of the outbreak versus that it was an unrelated sporadic infection using the INFERENCE (Integration of Forensic Epidemiology and the Rigorous Evaluation of Causation Elements) approach to medicolegal causation analysis. This paper describes the step-by-step application of the INFERENCE approach to demonstrate its utility in quantifying the probability of causation. The use of INFERENCE provides the court with an evidence-based, transparent, and reliable guide to determine liability, causation, and damages.

scholarly journals Correlation and Causation Analysis Between COVID-19 and Environmental Factors in China

2021 ◽  
Vol 3 ◽  
Author(s):  
Zuofang Zheng ◽  
Junxia Dou ◽  
Conglan Cheng ◽  
Hua Gao
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Regional Climate ◽  
Climate Impact ◽  
Control Measures ◽  
Specific Humidity ◽  
Human Society ◽  
Causality Test ◽  
Low Wind Speed ◽  
Causation Analysis

Coronavirus disease 2019 (COVID-19) is seriously threatening and altering human society. Although prevention and control measures play an important role in preventing the transmission of severe acute respiratory syndrome coronavirus, signals of climate impact can still be detected globally. In this paper, the data of 265 cities in China were analyzed. The results show that the correlations between COVID-19 and air quality index (AQI) and PM2.5 concentration were very weak and that the correlations between COVID-19 and meteorological factors were significantly different in different climate backgrounds. So, a fixed model is not enough to describe the correlations. Overall, high humidity, low wind speed, and relatively lower air temperature are conducive to the spread of COVID-19. The climate background suitable for the spread of COVID-19 in China is air temperature 0~15°C, specific humidity <3 g kg−1, and wind speed <3 m s−1. The Granger causality test shows that there is a causal relationship between daily average air temperature and the number of COVID-19 confirmed cases in some cities of China, and air temperature is indicative of the number of confirmed cases the next day. However, this phenomenon is not universal due to regional climate differences.

Toxicology-based cancer causation analysis of CoCr-containing hip implants: a quantitative assessment of genotoxicity and tumorigenicity studies

2014 ◽  
Vol 34 (9) ◽  
pp. 939-967 ◽  
Author(s):  
Whitney V. Christian ◽  
Lindsay D. Oliver ◽  
Dennis J. Paustenbach ◽  
Marisa L. Kreider ◽  
Brent L. Finley
Keyword(s):  
Quantitative Assessment ◽  
Hip Implants ◽  
Causation Analysis

scholarly journals Causation Analysis of Hazardous Material Road Transportation Accidents Based on the Ordered Logit Regression Model

2020 ◽  
Vol 17 (4) ◽  
pp. 1259 ◽  
Author(s):  
Changxi Ma ◽  
Jibiao Zhou ◽  
Dong Yang
Keyword(s):  
Influence Factors ◽  
Hazardous Materials ◽  
Model Parameters ◽  
Ordered Logit ◽  
Road Transportation ◽  
Hazardous Materials Transportation ◽  
Logit Regression ◽  
Environmental Properties ◽  
The Impact ◽  
Causation Analysis

Understanding the influence factors and related causation of hazardous materials can improve hazardous materials drivers’ safety awareness and help traffic professionals to develop effective countermeasures. This study investigates the statistical distribution characteristics, such as types of hazardous materials transportation accidents, driver properties, vehicle properties, environmental properties, road properties. In total, 343 data regarding hazardous materials accidents were collected from the chemical accident information network of China. An ordered logit regression (OLR) model is proposed to account for the unobserved heterogeneity across observations. Four independent variables, such as hazardous materials drivers’ properties, vehicle properties, environmental properties, and road properties are employed based on the OLR model, an ordered multinomial logistic regression (MLR) is estimated the OLR model parameters. Both parameter estimates and odds ratio (OR) are employed to interpret the impact of influence factors on the severity of hazardous materials accidents. The model estimation results show that 10 factors such as violations, unsafe driving behaviors, vehicle faults, and so on are closely related to accidents severity of hazardous materials transportation. Furthermore, three enforcement countermeasures are proposed to prevent accidents when transporting hazardous materials.

Sign in / Sign up

Export Citation Format

Share Document