The effects of dynamic movement on seated reach arcs.

The objective of this study was to determine the relationship between movement of the low back and shoulder during a normal seated reach and the reach arc estimation equations found in literature. The method consisted of evaluating individuals who were reaching with their right hands for five chess pawns, which were placed at varying distances. Specifically, the pawns were evenly spaced in a straight line directly in front of each participant's shoulder. This study focused on a group of 32 participants, which included both males and females. For each participant, low back, elbow and two shoulder angles were collected using a PEAK motion capture 6.0 system. Angles were collected in both the sagittal and transverse planes to gain a 3-D perspective. Data were summarised and correlated against maximum reach arc estimates. Results from the data suggest that both the shoulder and low back are engaged much earlier in a person's reach cycle than previously believed. Specifically, the results show low back engagement (trunk/lumber flexion) as early as 50% of maximum reach with the angle increasing to 5 degrees at around 80% and 10 degrees at 93%, which allows more pronounced forward angular acceleration. This shifts the shape and effective area of a participant's reach arc to a 'dynamic' state and questions if major muscle recruitment in the torso has initiated. The resulting effect is that dynamic and static reach arcs may vary significantly. While this study is too limited to support formal conclusions, these results strongly suggest a need for further investigation into the limits and impact of dynamic reach.

Geometric probability distribution for modeling of error risk during prescription dispensing.

PURPOSE: The relationship between the number of prescriptions dispensed by individual pharmacy staff during a single workday and the probability of committing at least one dispensing error during that same workday period was evaluated using a geometric probability distribution. SUMMARY: A cross-sectional descriptive study involving 50 pharmacies located in six cities across the United States was conducted. A pharmacist trained to detect dispensing errors recorded the number of prescriptions filled by each pharmacy staff member and noted which prescription represented the staff member's first dispensing error (defined as any deviation from the prescriber's order) made during the observation period. The Kolmogorov-Smirnov tests for discrete distributions revealed that the observed cumulative distribution of dispensing errors could have come from a geometric probability distribution that assumed dispensing error rates of 2-3%. In terms of risk analysis, this study's findings suggest that there can be a quantifiable statistical relationship between a measure of workload and the risk of committing at least one dispensing error. The ability to model dispensing errors using a geometric probability distribution enables the safety and health care practitioner to directly assess dispensing error risk as a function of a pharmacy's accuracy rate and the number of prescriptions a pharmacy staff member should dispense during a work shift. CONCLUSION: A geometric probability distribution effectively modeled the relationship between the number of prescriptions filled and the occurrence of the first dispensing errors.