The New Intoxication Defense for Ohio Employers

Ohio workers\u27 compensation system has been in a state of emergency for the last two years as labor and business groups battled over a series of employee-oriented Ohio Supreme Court decisions. Labor groups hailed these decisions as the vehicle which would propel Ohio\u27s workers\u27 compensation law into the twentieth century. Conversely, business groups condemned the decisions asserting that they exposed Ohio employers to infinite liability and destroyed Ohio\u27s industrial climate. S.B. 307 has changed the face of Ohio\u27s workers\u27 compensation law by revamping the definition of injury, establishing an intentional tort fund, and creating a new intoxication defense for Ohio employers. The focus of this Note is section 4123.54(B) which sets forth the skeleton of an intoxication defense for Ohio employers by barring from compensation those injuries which are proximately caused by the employee being intoxicated or under the influence of a non-prescription controlled substance. Due to the emergent nature of S.B. 307, the Ohio Legislature failed to define many of the legal standards set forth therein. After examining the historical development of the law of workers\u27 compensation and the intoxication defenses of other jurisdictions, this Note will define the burden which befalls an Ohio employer who attempts to establish that his employee was intoxicated or under the influence of a nonprescription controlled substance when injured and that such conduct was the proximate cause of the injury. The Note will also explore the methods by which an Ohio employee can rebut his employer\u27s intoxication defense

The New Intoxication Defense for Ohio Employers

Ohio workers\u27 compensation system has been in a state of emergency for the last two years as labor and business groups battled over a series of employee-oriented Ohio Supreme Court decisions. Labor groups hailed these decisions as the vehicle which would propel Ohio\u27s workers\u27 compensation law into the twentieth century. Conversely, business groups condemned the decisions asserting that they exposed Ohio employers to infinite liability and destroyed Ohio\u27s industrial climate. S.B. 307 has changed the face of Ohio\u27s workers\u27 compensation law by revamping the definition of injury, establishing an intentional tort fund, and creating a new intoxication defense for Ohio employers. The focus of this Note is section 4123.54(B) which sets forth the skeleton of an intoxication defense for Ohio employers by barring from compensation those injuries which are proximately caused by the employee being intoxicated or under the influence of a non-prescription controlled substance. Due to the emergent nature of S.B. 307, the Ohio Legislature failed to define many of the legal standards set forth therein. After examining the historical development of the law of workers\u27 compensation and the intoxication defenses of other jurisdictions, this Note will define the burden which befalls an Ohio employer who attempts to establish that his employee was intoxicated or under the influence of a nonprescription controlled substance when injured and that such conduct was the proximate cause of the injury. The Note will also explore the methods by which an Ohio employee can rebut his employer\u27s intoxication defense

Use of the bootstrap in analysing cost data from cluster randomised trials: some simulation results

BACKGROUND: This work has investigated under what conditions confidence intervals around the differences in mean costs from a cluster RCT are suitable for estimation using a commonly used cluster-adjusted bootstrap in preference to methods that utilise the Huber-White robust estimator of variance. The bootstrap's main advantage is in dealing with skewed data, which often characterise patient costs. However, it is insufficiently well recognised that one method of adjusting the bootstrap to deal with clustered data is only valid in large samples. In particular, the requirement that the number of clusters randomised should be large would not be satisfied in many cluster RCTs performed to date. METHODS: The performances of confidence intervals for simple differences in mean costs utilising a robust (cluster-adjusted) standard error and from two cluster-adjusted bootstrap procedures were compared in terms of confidence interval coverage in a large number of simulations. Parameters varied included the intracluster correlation coefficient, the sample size and the distributions used to generate the data. RESULTS: The bootstrap's advantage in dealing with skewed data was found to be outweighed by its poor confidence interval coverage when the number of clusters was at the level frequently found in cluster RCTs in practice. Simulations showed that confidence intervals based on robust methods of standard error estimation achieved coverage rates between 93.5% and 94.8% for a 95% nominal level whereas those for the bootstrap ranged between 86.4% and 93.8%. CONCLUSION: In general, 24 clusters per treatment arm is probably the minimum number for which one would even begin to consider the bootstrap in preference to traditional robust methods, for the parameter combinations investigated here. At least this number of clusters and extremely skewed data would be necessary for the bootstrap to be considered in favour of the robust method. There is a need for further investigation of more complex bootstrap procedures if economic data from cluster RCTs are to be analysed appropriately

The Effect of Computerized Physician Order Entry with Clinical Decision Support on the Rates of Adverse Drug Events: A Systematic Review

CONTEXT: Computerized physician order entry (CPOE) with clinical decision support (CDS) has been promoted as an effective strategy to prevent the development of a drug injury defined as an adverse drug event (ADE). OBJECTIVE: To systematically review studies evaluating the effects of CPOE with CDS on the development of an ADE as an outcome measure. DATA SOURCES: PUBMED versions of MEDLINE (from inception through March 2007) were searched to identify relevant studies. Reference lists of included studies were also searched. METHODS: We searched for original investigations, randomized and nonrandomized clinical trials, and observational studies that evaluated the effect of CPOE with CDS on the rates of ADEs. The studies identified were assessed to determine the type of computer system used, drug categories being evaluated, types of ADEs measured, and clinical outcomes assessed. RESULTS: Of the 543 citations identified, 10 studies met our inclusion criteria. These studies were grouped into categories based on their setting: hospital or ambulatory; no studies related to the long-term care setting were identified. CPOE with CDS contributed to a statistically significant (P \u3c or = .05) decrease in ADEs in 5 (50.0%) of the 10 studies. Four studies (40.0%) reported a nonstatistically significant reduction in ADE rates, and 1 study (10.0%) demonstrated no change in ADE rates. CONCLUSIONS: Few studies have measured the effect of CPOE with CDS on the rates of ADEs, and none were randomized controlled trials. Further research is needed to evaluate the efficacy of CPOE with CDS across the various clinical settings

Developing a framework for the ethical design and conduct of pragmatic trials in healthcare: a mixed methods research protocol

Canadian Institutes of Health Research through the Project Grant competition PJT-153045. Jeremy Grimshaw holds a Canada Research Chair in Health Knowledge Transfer and Uptake. Charles Weijer holds a Canada Research Chair in Bioethics. Sarah Edwards is funded by the UCL/UCLH Biomedical Research Centre (BRC). Vipul Jairath hold a personal Endowed Chair at Western University (John and Susan McDonald Endowed Chair). Joanne McKenzie is supported by an NHMRC Career Development Fellowship (1143429). The University of Aberdeen’s Health Services Research Unit is core-funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. Ian D Graham is a CIHR Foundation Grant recipient (FDN# 143237)