Statistical Measures to Quantify Similarity between Molecular Dynamics Simulation Trajectories.

Molecular dynamics simulation is commonly employed to explore protein dynamics. Despite the disparate timescales between functional mechanisms and molecular dynamics (MD) trajectories, functional differences are often inferred from differences in conformational ensembles between two proteins in structure-function studies that investigate the effect of mutations. A common measure to quantify differences in dynamics is the root mean square fluctuation (RMSF) about the average position of residues defined by Cα-atoms. Using six MD trajectories describing three native/mutant pairs of beta-lactamase, we make comparisons with additional measures that include Jensen-Shannon, modifications of Kullback-Leibler divergence, and local p-values from 1-sample Kolmogorov-Smirnov tests. These additional measures require knowing a probability density function, which we estimate by using a nonparametric maximum entropy method that quantifies rare events well. The same measures are applied to distance fluctuations between Cα-atom pairs. Results from several implementations for quantitative comparison of a pair of MD trajectories are made based on fluctuations for on-residue and residue-residue local dynamics. We conclude that there is almost always a statistically significant difference between pairs of 100 ns all-atom simulations on moderate-sized proteins as evident from extraordinarily low p-values.

Improving Compliance of Physicians in Reporting and Documenting Critical Alerts in a Cancer Hospital.

Introduction: A critical result of an investigation is considered a representation of a pathophysiological state deemed to be high risk or life threatening for the patient. Therefore, such results should be addressed in an appropriate and timely manner. Unfortunately, routine closed chart audits suggested that the compliance of physicians in documenting critical alerts in patient notes was poor. This prompted the hospital to conduct a continuous quality improvement (CQI) project to improve the physicians' compliance. Materials and Methods: A cause-and-effect analysis was conducted using a fishbone diagram to identify the reasons for poor compliance. Based on the analysis, several modifications were made, including, but not limited to, hospital-wide educational sessions on the standard operating procedures of receiving and documenting critical alerts for the physicians, daily audit of critical alerts to review the appropriateness of documentation and introduction of a new module in the hospital electronic medical record to acknowledge and document receiving critical alerts. Results: Before implementing the strategies to improve physicians' documentation compliance, the average compliance rate was 57% in April 2020, and the median compliance rate was 52% (January 2020-April 2020). However, afterward, within a couple of months of implementing changes, the average compliance rate increased to 88%. This improvement was sustained for the next 8 months (median of 89%). Conclusion: This study found that CQI approach can be used to improve the compliance of the physicians for appropriately and timely documenting critical alerts, in this case, by continued education and training process and incorporating changes into the electronic hospital information system.