Mark Schall

Usability Evaluation and Implementation of a Health Information Technology Dashboard of Evidence-Based Quality Indicators

Health information technology dashboards that integrate evidence-based quality indicators can efficiently and accurately display patient risk information to promote early intervention and improve overall quality of patient care. We describe the process of developing, evaluating, and implementing a dashboard designed to promote quality care through display of evidence-based quality indicators within an electronic health record. Clinician feedback was sought throughout the process. Usability evaluations were provided by three nurse pairs and one physician from medical-surgical areas. Task completion times, error rates, and ratings of system usability were collected to compare the use of quality indicators displayed on the dashboard to the indicators displayed in a conventional electronic health record across eight experimental scenarios. Participants rated the dashboard as “highly usable” following System Usability Scale (mean, 87.5 [SD, 9.6]) and Poststudy System Usability Questionnaire (mean, 1.7 [SD, 0.5]) criteria. Use of the dashboard led to reduced task completion times and error rates in comparison to the conventional electronic health record for quality indicator–related tasks. Clinician responses to the dashboard display capabilities were positive, and a multifaceted implementation plan has been used. Results suggest application of the dashboard in the care environment may lead to improved patient care.

Time-to-contact estimation errors among older drivers with useful field of view impairments

Previous research indicates that useful field of view (UFOV) decline affects older driver performance. In particular, elderly drivers have difficulty estimating oncoming vehicle time-to-contact (TTC). The objective of this study was to evaluate how UFOV impairments affect TTC estimates in elderly drivers deciding when to make a left turn across oncoming traffic. TTC estimates were obtained from 64 middle-aged (n=17, age=46±6years) and older (n=37, age=75±6years) licensed drivers with a range of UFOV abilities using interactive scenarios in a fixed-base driving simulator. Each driver was situated in an intersection to turn left across oncoming traffic approaching and disappearing at differing distances (1.5, 3, or 5s) and speeds (45, 55, or 65mph). Drivers judged when each oncoming vehicle would collide with them if they were to turn left. Findings showed that TTC estimates across all drivers, on average, were most accurate for oncoming vehicles travelling at the highest velocities and least accurate for those travelling at the slowest velocities. Drivers with the worst UFOV scores had the least accurate TTC estimates, especially for slower oncoming vehicles. Results suggest age-related UFOV decline impairs older driver judgment of TTC with oncoming vehicles in safety-critical left-turn situations. Our results are compatible with national statistics on older driver crash proclivity at intersections.

Evaluating the Linear Integration Method of Estimating Cumulative Loading Using an Eccentric Exercise

The ability to quantify cumulative exposure is critically in understanding dose-response relationship in the development of work-related musculoskeletal disorders. Different integration methods have been used in estimating cumulative loading (force or torque). The general objective of cumulative loading integration methods has been to sum the loading exposure for each individual task, calculate by multiplying the magnitude of the task loading times the task duration, and develop an “area under the curve”. An assumption of this linear integration model is that short time exposure to high forces will result in a similar level of damage as relatively long-time exposure to low forces. In this study, three loading groups of eccentric exercise with the same “area under the curve” were performed by thirty participants (ten in each group). Relaxed elbow angle and maximum isometric voluntary contractions (MIVC) were collected before, immediately after, and 2, 4, 8 days after the exercise. The relaxed elbow angle and the changes in MIVC were significantly impacted by the loading group. This result suggests that the linear integration method of estimating cumulative loading may underestimate the impact of high force loading in terms of cumulative muscle damage.

Lumbar Muscle Fatigue Analysis Using Sorensen Test with Different Upper Body Offload Conditions

The Sorensen test has been widely used in assessing the isometric endurance of trunk muscles. In this study, a modified Sorensen test was performed using four different upper body offload conditions (0%, 25% 50% and 75%) and surface EMG (sEMG) was used to determine fatigue characteristics in lumbar muscles. Results showed that the offloading of the upper body has a statistically significant impact on the slope of the EMG median frequency, which is representative of lumbar muscle fatigue responses. The first 25% offloading significantly decreased the fatigue response in the lumbar region. In addition, the 25% offload condition was significantly different from the 75% offload condition. However, the slopes of 25% and 50% offload conditions are not statistically different from each other and same for 50% and 75% offload conditions.

Use of Varied Definitions of Repetition with the Distal Upper Extremity Tool (DUET)

Defining what constitutes a repetition in performance of a task involving exertions of the upper extremity can be difficult due to highly varied activities. In this paper, we examine three different definitions of repetition with the use of the Distal Upper Extremity Tool (DUET). These definitions include Grips Alone (manipulation of an object by the hands), Reps Alone (wrist deviations), and Grips + Reps (manipulations plus deviations). Validation of the DUET tool was performed against an existing cross-sectional epidemiology study for all three definitions. The log of the DUET Cumulative Damage (CD) measure demonstrated strong and consistent associations with five separate distal upper extremity outcomes using each of these definitions of repetition when controlled for covariates including site, gender, age, and BMI (with significant odds ratios ranging from 1.20 – 2.10). Results suggest that DUET may allow for flexibility in the definition of “repetition” and still successfully identify hazardous jobs.

Evaluating the Effectiveness of Estimating Cumulative Loading Using Linear Integration Method

Exposure to cumulative loading is a significant risk factor in the development of musculoskeletal disorders (MSD). To better understand the dose-response relationship, it is critically to quantify the cumulative exposure. Different integration methods have been used in estimating cumulative loading (force or torque). The general objective of the integration methods has been to sum the independently calculated task exposure. Each task was calculated by multiplying the magnitude of the task loading times the task duration which is the “area under the loading curve”. An assumption of this linear integration model is that long-time exposure to low forces will result in a similar level of damage as relatively short time exposure to high forces. To evaluate the effectiveness of this model, three loading groups of eccentric exercise with the same “area under the loading curve” were performed by thirty participants (ten in each group). Maximum isometric voluntary contractions (MIVC) and relaxed elbow angle (REA) were collected before, immediately after, and 2, 4, 8 days after the exercise. The REA and MIVC changes after the eccentric exercise were significantly impacted by the loading group. It suggests that estimating cumulative loading using linear integration method may underestimate the impact of high force loading in terms of cumulative muscle damage.

Accuracy of angular displacements and velocities from inertial-based inclinometers

The objective of this study was to evaluate the accuracy of various sensor fusion algorithms for measuring upper arm elevation relative to gravity (i.e., angular displacement and velocity summary measures) across different motion speeds. Thirteen participants completed a cyclic, short duration, arm-intensive work task that involved transfering wooden dowels at three work rates (slow, medium, fast). Angular displacement and velocity measurements of upper arm elevation were simultaneously measured using an inertial measurement unit (IMU) and an optical motion capture (OMC) system. Results indicated that IMU-based inclinometer solutions can reduce root-mean-square errors in comparison to accelerometer-based inclination estimates by as much as 87%, depending on the work rate and sensor fusion approach applied. The findings suggest that IMU-based inclinometers can substantially improve inclinometer accuracy in comparison to traditional accelerometer-based inclinometers. Ergonomists may use the non-proprietary sensor fusion algorithms provided here to more accurately estimate upper arm elevation.

Validation of the LiFFT Risk Assessment Tool and Guidance on Its Use

The purpose of this paper is to describe a new risk assessment tool for manual lifting (LiFFT), to demonstrate the strong association between LiFFT’s cumulative damage metric with low back outcomes, and to provide recommendations for use in a variety of settings.

easyBLS, a Tool for Querying Nonfatal Injury Information from United States Bureau of Labor Statistics Database

Every year, the United States Bureau of Labor Statistics (BLS) collects and publishes important information on the number and types of occupational injuries and illnesses affecting workers across all industries. Researchers, occupational safety and health professionals, epidemiologists and industry groups rely on this data to make conclusions about past, present, and future injury and illness trends. The data are also very important in determining the root causes of workplace injury and developing effective interventions. The BLS provides two web tools to query nonfatal injury data from the database. However, one of the tools is no longer functioning, while the other has relatively low query efficiency (more than twenty seconds per query) as tested in this study. Furthermore, there is no data visualization tool provided to help display the queried information. easyBLS (Desktop and web version) was developed to query information from the BLS database with relatively high efficiency (less than one second per query). This tool also provides two data visualization tools (line graph and map) to help users to better interpret the queried information. easyBLS web version is available to the public at http://easybls.pythonanywhere.com/.

Application of Inertial Measurement Units to Assess Vehicle Ingress and Egress Characteristics

The increasing number of elderly and overweight drivers in the United States has necessitated that vehicle manufacturers develop automobiles that accommodate these changing demographics. While digital human models have been successfully used to simulate human vehicle interaction (Chaffin, 2005; Ozsoy et al., 2015; Yang et al., 2007), the variability in ingress and egress procedures among drivers with different physical attributes poses a unique challenge to developing accurate models. The objective of this study was to apply inertial measurement units (IMUs) to compare ingress and egress characteristics of individuals of varying age and body type. Ninety-three participants, comprising a control group (aged 21–<65 years with body mass index [BMI] <30 kg/m2), a high-BMI group (aged 21–<65 years with BMI ≥30 kg/m2), and an elderly group (aged ≥65 years), performed ingress and egress trials in three vehicles (compact, sedan, and sport utility vehicle [SUV]) while wearing a wireless IMU system (Xsens MVN BIOMECH Awinda system, Xsens Technologies BV, Enschede, Netherlands). Native protocols of the IMU system were used to estimate the joint centers and motion paths of several bilateral body joints including the ankle, knee, hip, wrist, elbow, and shoulder. The transition of each joint center across the edge of the seating area at the door sill as the subject got into and out of the vehicles was measured. The start of the ingress process was defined as the time when the first joint center passed through the door sill into the driver’s seating area. The end of ingress was considered to be the time when the final joint passed back through the edge of the seating area. Two-way analyses of variance (ANOVA) examining the effects of population (control vs. elderly vs. high-BMI), gender, vehicle model, and their interactions on ingress and egress times were conducted. In general, the right ankle was the first body segment to enter each of the three vehicles followed by the right knee, right hip, right shoulder, left hip, left shoulder, left knee and the left ankle regardless of population group. Ingress time was observed to be affected by population (F2, 28 = 17.97, p < 0.001), and was characterized by a much slower ingress time among the elderly (mean = 4.33 secs), compared with controls (2.97 secs) and high-BMI participants (2.71 secs). Egress was also observed to be affected by population (F2, 28 = 8.85, p < 0.001), but in a slightly different manner. The control group (mean = 2.95 secs) was the fastest to egress the car, followed by the high-BMI group (4.42 secs) and the elderly (5.26 secs). The results indicate that IMUs may be successfully applied to characterize ingress and egress motion paths of different population groups and may be useful when designing seated applications, particularly for elderly and high-BMI populations.