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

Developing and enhancing biodiversity monitoring programmes: a collaborative assessment of priorities

1.Biodiversity is changing at unprecedented rates, and it is increasingly important that these changes are quantified through monitoring programmes. Previous recommendations for developing or enhancing these programmes focus either on the end goals, that is the intended use of the data, or on how these goals are achieved, for example through volunteer involvement in citizen science, but not both. These recommendations are rarely prioritized. 2.We used a collaborative approach, involving 52 experts in biodiversity monitoring in the UK, to develop a list of attributes of relevance to any biodiversity monitoring programme and to order these attributes by their priority. We also ranked the attributes according to their importance in monitoring biodiversity in the UK. Experts involved included data users, funders, programme organizers and participants in data collection. They covered expertise in a wide range of taxa. 3.We developed a final list of 25 attributes of biodiversity monitoring schemes, ordered from the most elemental (those essential for monitoring schemes; e.g. articulate the objectives and gain sufficient participants) to the most aspirational (e.g. electronic data capture in the field, reporting change annually). This ordered list is a practical framework which can be used to support the development of monitoring programmes. 4.People's ranking of attributes revealed a difference between those who considered attributes with benefits to end users to be most important (e.g. people from governmental organizations) and those who considered attributes with greatest benefit to participants to be most important (e.g. people involved with volunteer biological recording schemes). This reveals a distinction between focussing on aims and the pragmatism in achieving those aims. 5.Synthesis and applications. The ordered list of attributes developed in this study will assist in prioritizing resources to develop biodiversity monitoring programmes (including citizen science). The potential conflict between end users of data and participants in data collection that we discovered should be addressed by involving the diversity of stakeholders at all stages of programme development. This will maximize the chance of successfully achieving the goals of biodiversity monitoring programmes

Coronary-artery bypass surgery in patients with ischemic cardiomyopathy

BACKGROUND The survival benefit of a strategy of coronary-artery bypass grafting (CABG) added to guideline-directed medical therapy, as compared with medical therapy alone, in patients with coronary artery disease, heart failure, and severe left ventricular systolic dysfunction remains unclear. METHODS From July 2002 to May 2007, a total of 1212 patients with an ejection fraction of 35% or less and coronary artery disease amenable to CABG were randomly assigned to undergo CABG plus medical therapy (CABG group, 610 patients) or medical therapy alone (medical-therapy group, 602 patients). The primary outcome was death from any cause. Major secondary outcomes included death from cardiovascular causes and death from any cause or hospitalization for cardiovascular causes. The median duration of follow-up, including the current extended-follow-up study, was 9.8 years. RESULTS A primary outcome event occurred in 359 patients (58.9%) in the CABG group and in 398 patients (66.1%) in the medical-therapy group (hazard ratio with CABG vs. medical therapy, 0.84; 95% confidence interval [CI], 0.73 to 0.97; P=0.02 by log-rank test). A total of 247 patients (40.5%) in the CABG group and 297 patients (49.3%) in the medical-therapy group died from cardiovascular causes (hazard ratio, 0.79; 95% CI, 0.66 to 0.93; P=0.006 by log-rank test). Death from any cause or hospitalization for cardiovascular causes occurred in 467 patients (76.6%) in the CABG group and in 524 patients (87.0%) in the medical-therapy group (hazard ratio, 0.72; 95% CI, 0.64 to 0.82; P<0.001 by log-rank test). CONCLUSIONS In a cohort of patients with ischemic cardiomyopathy, the rates of death from any cause, death from cardiovascular causes, and death from any cause or hospitalization for cardiovascular causes were significantly lower over 10 years among patients who underwent CABG in addition to receiving medical therapy than among those who received medical therapy alone. (Funded by the National Institutes of Health; STICH [and STICHES] ClinicalTrials.gov number, NCT00023595.

Political Regimes and Sovereign Credit Risk in Europe, 1750-1913

This article uses a new panel data set to perform a statistical analysis of political regimes and sovereign credit risk in Europe from 1750 to 1913. Old Regime polities typically suffered from fiscal fragmentation and absolutist rule. By the start of World War I, however, many such countries had centralized institutions and limited government. Panel regressions indicate that centralized and?or limited regimes were associated with significant improvements in credit risk relative to fragmented and absolutist ones. Structural break tests also reveal close relationships between major turning points in yield series and political transformations

IFNAR1-Signalling Obstructs ICOS-mediated Humoral Immunity during Non-lethal Blood-Stage Plasmodium Infection

Funding: This work was funded by a Career Development Fellowship (1028634) and a project grant (GRNT1028641) awarded to AHa by the Australian National Health & Medical Research Council (NHMRC). IS was supported by The University of Queensland Centennial and IPRS Scholarships. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD