The effect of traumatic brain injury on drivers’ hazard perception

Individuals recovering from traumatic brain injury (TBI) often experience perceptual, cognitive, and motor deficits that adversely affect their driving. However, many individuals with TBI return to driving, despite evidence that they are at increased risk. This study examined the effects of TBI on drivers’ hazard perception, i.e. the ability to search the road ahead and quickly identify potentially dangerous traffic situations. Slower hazard perception has been associated with higher crash rates (e.g. Quimby et al., 1986), but hazard perception has never been assessed after TBI. A convenience sample of adults recovering from mild, moderate and severe TBI was recruited from the rehabilitation unit of a tertiary level hospital. Uninjured controls were recruited from the community. Participants completed a hazard perception test, in which they viewed videos of genuine traffic scenes filmed from the driver’s perspective and indicated as soon as they detected a potential traffic hazard (mean response latency was the main dependent measure). Participants also completed a simple spatial reaction time task, a digit symbol substitution task and several measures related to pre- and post-injury functioning. Preliminary results indicate that individuals with TBI were significantly slower to detect traffic hazards than controls. The findings may signify the need for hazard perception testing or training post-TBI before return to driving

A recent mild traumatic brain injury can slow drivers’ perception of traffic hazards

Driving a vehicle is probably the most dangerous activity that most people do every day. No research has examined whether individuals recovering from a recent mild traumatic brain injury (MTBI) are safe to drive, despite cognitive impairment being a common consequence soon after MTBI. This study examined the acute effect of MTBI on drivers’ hazard perception (defined as drivers’ ability to search the road ahead to rapidly identify potentially dangerous traffic situations). Poorer hazard perception has been associated with higher car crash rates in a number of studies, and consequently several Australian states and the United Kingdom now test hazard perception in their driver licensing programs. Forty-two patients with MTBI and 43 patients with minor orthopedic injuries were recruited from the emergency department of a large metropolitan hospital within 24 hours of injury. Participants completed a computerized hazard perception test, in which they watched videos of genuine traffic scenes filmed from the drivers’ point of view. They were required to use the computer mouse to click on potential traffic hazards as early as possible. Participants with MTBI were significantly slower to detect traffic hazards than participants with minor orthopedic injuries. This study provides the first indication that within the acute stage post-injury, MTBI can be associated with impairment in a crash-related component of driving. The practical implication is that patients with MTBI should perhaps be advised to refrain from driving for at least the first 24 hours after injury

The development of the adult deterioration detection system (ADDS) chart

The Adult Deterioration Detection System (ADDS) observation chart described in this short report was developed as part of a research project carried out at The University of Queensland for Queensland Health and the Australian Commission on Safety and Quality in Health Care (ACSQHC). The aim of the project was to investigate the design and use of observation charts in recognising and managing patient deterioration, including the design and evaluation of a new adult observation chart that incorporated human factors principles

Paper-based patient chart design information sheet

The purpose of this document is to help those involved in creating paper-based patient charts improve the human factors aspects of the design of their charts. It is based on the outcomes of a research project (“Human Factors Research Regarding Observation Charts”) carried out at the University of Queensland for the Australian Commission on Safety and Quality in Health Care, the Queensland Health Patient Safety and Quality Improvement Service and the Clinical Skills Development Service. Copies of the reports associated with this project are available online from the Commission’s website (www.safetyandquality.gov.au). As part of this project, we systematically reviewed 25 existing patient observation charts and developed a new chart (the “ADDS chart”) designed to identify patient deterioration, which was then evaluated in behavioural experiments. In this document, we will use some of the issues arising from this process to illustrate human factors design considerations for paper-based patient charts in general

Detecting abnormal vital signs on six observation charts: An experimental comparison

Paper-based observation charts are the principal means of monitoring changes to patients’ vital signs. There is considerable variation in the design of observation charts and a lack of empirical research on the performance of different designs. This report describes the results of a study carried out as part of a project funded by the Australian Commission for Safety and Quality in Health Care and Queensland Health to investigate the design and use of observation charts in recognising and managing patient deterioration, including the design and evaluation of a new adult observation chart that incorporated human factors principles. The first phase of this project involved using a procedure known as heuristic analysis to review 25 observation charts from Australia and New Zealand. 1,189 usability problems, which could lead to errors in recording data and identifying patient deterioration, were identified in the charts. The results from the heuristic analysis were used to design a new chart (the Adult Deterioration Detection System [ADDS] chart) based on human factors principles and current best practice. The study described in this report involved an empirical comparison of six charts (two versions of the ADDS chart, two existing charts rated as “well designed” in the heuristic analysis, one existing chart rated as being of “average design”, and one existing chart rated as “poorly designed”). Novices (individuals who were unfamiliar with using patient charts) and health professionals (doctors and nurses) were recruited as participants. Each chart design was shown to each participant four times displaying different physiological data with one abnormal vital sign (e.g. a high systolic blood pressure), and four times displaying different normal physiological data. After memorising the normal ranges for each vital sign, participants had to classify the physiological data on the charts as “normal” or “abnormal”. Error rates (the proportion of trials where participants made an incorrect normal/abnormal judgement) and response time (the time to read the chart and make the judgement) were measured. Results indicated that chart design had a statistically significant effect on both error rates and response time, with the charts identified as having better design tending to yield fewer errors and shorter decision times. Specifically, the two versions of the ADDS chart outperformed all the existing charts on both metrics, where the other charts yielded between 2.5 and 3.3 times as many errors as the ADDS chart. There was no significant difference between novices and health professionals in error rates for any chart, but the health professionals were significantly faster than novices at making their decisions for the charts rated as “average” and “poor”. There was no significant difference between doctors and nurses on either of the two performance measures for any of the charts. These data indicate that differences in the design of observation charts have a profound impact on chart users’ decisions regarding patients’ vital signs as well as the time it takes to make such decisions. Based on the current data, it appears that the ADDS chart is significantly better at signalling patient deterioration than other currently available charts

An Online Survey of Health Professionals’ Opinions Regarding Observation Charts

The current study was the second stage of a project funded by the Australian Commission for Quality and Safety in Health Care and Queensland Health to investigate the design and use of observation charts in recognising and managing patient deterioration, including the design and evaluation of a new adult observation chart that incorporated human factors principles. Improving the recognition and management of patients who deteriorate whilst in hospital is a frequently cited goal for patient safety. Changes in physiological observations or ‘vital signs’ commonly precede serious adverse medical events. Paper-based observation charts are the chief means of recording and monitoring changes to patients’ vital signs. One approach to improve the recognition and management of deteriorating patients is to improve the design of paper-based observation charts (note that the management of patient deterioration can potentially be affected by chart design if, for example, action plans are included on the chart). There is considerable variation in the design of observation charts in current use in Australia and a lack of empirical research on the performance of observation charts in general. The aim of the current study was to gauge the opinions of the population who actually use observation charts. We recruited a large sample of health professionals (N = 333) to answer general questions about the design of observation charts and specific questions about nine observation charts. The participants reported using observation charts daily, but only a minority reported having received any formal training in the use of such charts. In our previously-reported heuristic analysis of observation charts (1), we found that the majority of charts included a large number of abbreviations. In this survey, participants were asked to nominate which term they first thought of when seeing a particular abbreviation. Most abbreviations were overwhelmingly assigned the same meaning. However, some abbreviations had groups of participants nominating different terms for the same abbreviation. Participants were also asked to nominate their preferred terms for nine vital signs that commonly appear on observation charts. For some vital signs, there was a high level of agreement as to which term was easiest to understand; however, for other vital signs, there was no clearly preferred term. Participants were also asked about their chart design preferences both in terms of (a) recording observations and (b) detecting deterioration. In both instances, participants preferred the option to “Plot the value on a graph with graded colouring, where the colours correspond to a scoring system or graded responses for abnormality”. Participants’ preference was in line with what a human factors approach would recommend (i.e. charts with a colour-coded track and trigger system). In the final sections of the survey, participants were first asked to respond to 13 statements regarding the design of their own institution’s current observation chart, and then to respond to the same 13 statements for one of nine randomly-assigned observation charts. The nine observation charts included the new Adult Deterioration Detection System (ADDS) chart and eight charts of “good”, “average”, or “poor” design quality from the heuristic analysis. Participants’ mean aggregated rating across the 13 items for their institution’s current observation chart was close to the scale’s mid-point, 3 = neutral. For the assigned charts, there was a statistically significant effect of chart type on the aggregated rating. The a priori “poor” quality charts were each rated as having a significantly poorer design compared with each of the other charts (collectively, the a priori “average” and “good” quality charts). There was partial support for our hypothesis that health professionals would rate the “good” charts as having better design, compared to the “average” and “poor” charts. In conclusion, the online survey served two main purposes. First, it collected quantitative data on health professionals’ general preferences regarding aspects of the design of observation charts. This information informed the design of the ADDS chart and could also be used by other chart designers to produce more user-friendly hospital charts. Second, the online survey enabled health professionals to rate the design of the new ADDS chart as well as eight existing charts of varying quality. Overall, health professionals agreed with our human factors-based rating with regards to the “poor” quality charts. However, the health professionals did not differentiate between the “average” and “good” quality charts in their ratings

Interplay of Staphylococcal and Host Proteases Promotes Skin Barrier Disruption in Netherton Syndrome.

Netherton syndrome (NS) is a monogenic skin disease resulting from loss of function of lymphoepithelial Kazal-type-related protease inhibitor (LEKTI-1). In this study we examine if bacteria residing on the skin are influenced by the loss of LEKTI-1 and if interaction between this human gene and resident bacteria contributes to skin disease. Shotgun sequencing of the skin microbiome demonstrates that lesional skin of NS subjects is dominated by Staphylococcus aureus (S. aureus) and Staphylococcus epidermidis (S. epidermidis). Isolates of either species from NS subjects are able to induce skin inflammation and barrier damage on mice. These microbes promote skin inflammation in the setting of LEKTI-1 deficiency due to excess proteolytic activity promoted by S. aureus phenol-soluble modulin α as well as increased bacterial proteases staphopain A and B from S. aureus or EcpA from S. epidermidis. These findings demonstrate the critical need for maintaining homeostasis of host and microbial proteases to prevent a human skin disease