A Pilot Study to Screen Fall Risk in Adult Health Care Employees

Background and Purpose: Due to the increasing age of the working population, falls are becoming an escalating problem especially in the healthcare industry. The purpose of this research study is to develop a cost effective quick screen to determine fall risk in healthcare employees. Our overall goal is to take the results gained from this pilot study and apply them on a larger scale in hopes of preventing falls thus decreasing dollars spent by companies on work injury. Subjects: Volunteers from a local Health Care System. Inclusion criteria: permanent employees, over the age of 20, without an assistive device. A total of 76 subjects were included in the sample, age range from 22 to 66 years of age. Methods: Subjects were tested in four balance measures including: the five times sit to stand test (FTSST), single leg stance test (SLST), tandem walking, and the functional reach . Relationships of balance measures and fall history were performed using crosstabulations. Chi-square analysis and independent measures t-test were used with an alpha level of .05 for nominal data. Within the crosstabulations, the standardized residual was used to identify which cells contributed most to the significant chi-square and was set at ~ 11.961 . Results: Pearson chi square tests of independence showed no significant relationships between the individual balance measures and subject\u27s fall history. Medication use illustrated similar trends as in current literature, but was not statistically significant. Discussion and Conclusion: The results of this study did not confirm any one balance measure that would be a good predictor of falls to include in a fall risk assessment in healthcare employees. Due to limited sample size, investigating a relationship between a combination of multiple tests and fall history was not feasible. However, due to the limitations of this study, and the amount of literature that is available confirming that many of these assessments predict fall risk, additional investigation is necessary. Although we did not achieve the desired results, further studies directed towards the development of a quick screen for fall risk in Healthcare employees are warranted in order to attempt to decrease falls in the workplace

EHR-Based Care Coordination Performance Measures in Ambulatory Care

Describes electronic health record-based measures for assessing coordination in referrals, including information communicated with referral, communication to patient, and specialist report to primary care physician. Offers preliminary evaluation findings

A canvas for the ethical design of learning experiences with digital tools

The use of digital tools has drastically increased in engineering education, accelerated by the COVID-19 pandemic. These tools generate important ethical issues, in particular in terms of privacy and fairness. However, very few teacher training programmes address those topics, which means that teachers are often left to figure out by themselves how to address these issues when they want (or have) to use digital tools in their teaching. In this workshop, participants will be introduced to a pragmatic approach to the ethical design of learning experiences that involve digital tools using a visual thinking guide called a ‘canvas’. Applied and hands-on, this workshop will help participants to develop a practical understanding of the specific ethical issues related to the use of digital tools in teaching and to integrate ethical reflection into design processes when digital technology is involved

Evaluating community engagement in global health research: the need for metrics.

CAPRISA, 2015.Abstract available in pdf

The German National Registry of Primary Immunodeficiencies (2012-2017)

Introduction: The German PID-NET registry was founded in 2009, serving as the first national registry of patients with primary immunodeficiencies (PID) in Germany. It is part of the European Society for Immunodeficiencies (ESID) registry. The primary purpose of the registry is to gather data on the epidemiology, diagnostic delay, diagnosis, and treatment of PIDs. Methods: Clinical and laboratory data was collected from 2,453 patients from 36 German PID centres in an online registry. Data was analysed with the software Stata® and Excel. Results: The minimum prevalence of PID in Germany is 2.72 per 100,000 inhabitants. Among patients aged 1–25, there was a clear predominance of males. The median age of living patients ranged between 7 and 40 years, depending on the respective PID. Predominantly antibody disorders were the most prevalent group with 57% of all 2,453 PID patients (including 728 CVID patients). A gene defect was identified in 36% of patients. Familial cases were observed in 21% of patients. The age of onset for presenting symptoms ranged from birth to late adulthood (range 0–88 years). Presenting symptoms comprised infections (74%) and immune dysregulation (22%). Ninety-three patients were diagnosed without prior clinical symptoms. Regarding the general and clinical diagnostic delay, no PID had undergone a slight decrease within the last decade. However, both, SCID and hyper IgE- syndrome showed a substantial improvement in shortening the time between onset of symptoms and genetic diagnosis. Regarding treatment, 49% of all patients received immunoglobulin G (IgG) substitution (70%—subcutaneous; 29%—intravenous; 1%—unknown). Three-hundred patients underwent at least one hematopoietic stem cell transplantation (HSCT). Five patients had gene therapy. Conclusion: The German PID-NET registry is a precious tool for physicians, researchers, the pharmaceutical industry, politicians, and ultimately the patients, for whom the outcomes will eventually lead to a more timely diagnosis and better treatment

How Do Employers Use Compensation History?: Evidence from a Field Experiment

We report the results of a field experiment in which treated employers could not observe the compensation history of their job applicants. Treated employers responded by evaluating more applicants, and evaluating those applicants more intensively. They also responded by changing what kind of workers they evaluated: treated employers evaluated workers with 7% lower past average wages and hired workers with 16% lower past average wages. Conditional upon bargaining, workers hired by treated employers struck better wage bargains for themselves. Using a structural model of bidding and hiring, we find that the selection effects we observe would also occur in equilibrium

ADABase: A Multimodal Dataset for Cognitive Load Estimation

Driver monitoring systems play an important role in lower to mid-level autonomous vehicles. Our work focuses on the detection of cognitive load as a component of driver-state estimation to improve traffic safety. By inducing single and dual-task workloads of increasing intensity on 51 subjects, while continuously measuring signals from multiple modalities, based on physiological measurements such as ECG, EDA, EMG, PPG, respiration rate, skin temperature and eye tracker data, as well as behavioral measurements such as action units extracted from facial videos, performance metrics like reaction time and subjective feedback using questionnaires, we create ADABase (Autonomous Driving Cognitive Load Assessment Database) As a reference method to induce cognitive load onto subjects, we use the well-established n-back test, in addition to our novel simulator-based k-drive test, motivated by real-world semi-autonomously vehicles. We extract expert features of all measurements and find significant changes in multiple modalities. Ultimately we train and evaluate machine learning algorithms using single and multimodal inputs to distinguish cognitive load levels. We carefully evaluate model behavior and study feature importance. In summary, we introduce a novel cognitive load test, create a cognitive load database, validate changes using statistical tests, introduce novel classification and regression tasks for machine learning and train and evaluate machine learning models