Pressure Injury and Restraint Prevalence Surveys: Saving Time and Dollars for Patient Care by Automating Manual Chart Abstraction

Bronson Healthcare Group performs quarterly pressure injury and restraint audits as part of the National Database of Nursing Quality Indicators (NDNQI). The chart abstraction portion of the audit previously required nurses to manually abstract 31 data points. To save time and cost, we used Lean and PDSA process improvement tools to automate the chart abstraction portion of the audit, reducing the number of data points requiring manual abstraction to 2. We validated the automated abstraction by comparing it to abstractions done manually by the audit nurses. We found that an automated process has the potential to reduce the impact of human error inherent in manual abstraction

Implicit Measures of Lostness and Success in Web Navigation

In two studies, we investigated the ability of a variety of structural and temporal measures computed from a web navigation path to predict lostness and task success. The user’s task was to find requested target information on specified websites. The web navigation measures were based on counts of visits to web pages and other statistical properties of the web usage graph (such as compactness, stratum, and similarity to the optimal path). Subjective lostness was best predicted by similarity to the optimal path and time on task. The best overall predictor of success on individual tasks was similarity to the optimal path, but other predictors were sometimes superior depending on the particular web navigation task. These measures can be used to diagnose user navigational problems and to help identify problems in website design

Automation of motor dexterity assessment

Motor dexterity assessment is regularly performed in rehabilitation wards to establish patient status and automatization for such routinary task is sought. A system for automatizing the assessment of motor dexterity based on the Fugl-Meyer scale and with loose restrictions on sensing technologies is presented. The system consists of two main elements: 1) A data representation that abstracts the low level information obtained from a variety of sensors, into a highly separable low dimensionality encoding employing t-distributed Stochastic Neighbourhood Embedding, and, 2) central to this communication, a multi-label classifier that boosts classification rates by exploiting the fact that the classes corresponding to the individual exercises are naturally organized as a network. Depending on the targeted therapeutic movement class labels i.e. exercises scores, are highly correlated-patients who perform well in one, tends to perform well in related exercises-; and critically no node can be used as proxy of others - an exercise does not encode the information of other exercises. Over data from a cohort of 20 patients, the novel classifier outperforms classical Naive Bayes, random forest and variants of support vector machines (ANOVA: p <; 0.001). The novel multi-label classification strategy fulfills an automatic system for motor dexterity assessment, with implications for lessening therapist's workloads, reducing healthcare costs and providing support for home-based virtual rehabilitation and telerehabilitation alternatives

Like trainer, like bot? Inheritance of bias in algorithmic content moderation

The internet has become a central medium through which `networked publics' express their opinions and engage in debate. Offensive comments and personal attacks can inhibit participation in these spaces. Automated content moderation aims to overcome this problem using machine learning classifiers trained on large corpora of texts manually annotated for offence. While such systems could help encourage more civil debate, they must navigate inherently normatively contestable boundaries, and are subject to the idiosyncratic norms of the human raters who provide the training data. An important objective for platforms implementing such measures might be to ensure that they are not unduly biased towards or against particular norms of offence. This paper provides some exploratory methods by which the normative biases of algorithmic content moderation systems can be measured, by way of a case study using an existing dataset of comments labelled for offence. We train classifiers on comments labelled by different demographic subsets (men and women) to understand how differences in conceptions of offence between these groups might affect the performance of the resulting models on various test sets. We conclude by discussing some of the ethical choices facing the implementers of algorithmic moderation systems, given various desired levels of diversity of viewpoints amongst discussion participants.Comment: 12 pages, 3 figures, 9th International Conference on Social Informatics (SocInfo 2017), Oxford, UK, 13--15 September 2017 (forthcoming in Springer Lecture Notes in Computer Science

The Automatic Assessment of Multiple Artefacts: An Investigation into Design Diagrams and Their Implementations

As the Higher Education sector has moved towards student-centred learning so too has the growth in electronic support for learning. E-assessment has been a part of this growth as increasingly assessment and its feedback is seen as an integral part of the students’ learning process. Mature e-assessment systems exist, particularly where answers to questions are restricted to a prescribed list of alternatives. However, for free response artefacts, where there is a limited restriction placed on answers to questions, automated assessment systems are embryonic. This dissertation presents an investigation into the automated assessment of free response artefacts. Design diagrams and their accompanying source code implementations are examples of free response artefacts. A case study is developed that investigates how to automatically generate formative feedback for a design diagram by utilizing its accompanying implementation. The dissertation presents a two-staged solution, initially analysing the design diagram in isolation before comparing it with the implementation. A framework for this approach has been developed and tested using a tool applied to coursework submitted by undergraduate computer science students. The tool was evaluated by comparing the formative feedback comments generated by the tool with those produced by a team of computer science educators. Evaluation was undertaken via two Likert questionnaires, one completed by students and one completed by a team of computer scientists. The results presented are favourable, with the majority of comments produced by the tool being seen to be as least as good as those generated by the computer science educators

Identification of drivers, benefits, and challenges of ISO 50001 through case study content analysis

An expanding body of research is defining drivers, benefits, and challenges of adopting ISO 50001 energy management systems. The Clean Energy Ministerial's Energy Management Leadership Awards program requires ISO 50001-certified organizations to develop case studies of their implementation experience. 72 recent case studies spanning multiple economic sectors provide a unique global look at implementation from certified organizations' perspectives. This dataset was investigated through content analysis of phrases related to motivations and goals, the role of management and the organization, benefits achieved, keys to success, and challenges. This paper presents findings from this quantitative analysis of “codes” assigned to phrases that capture their meaning. While organizations adopted ISO 50001 for different motives and saw myriad benefits beyond energy savings and associated greenhouse gas emissions reductions, commonalities exist. The most frequently identified drivers are existing values and goals, environmental sustainability, and government incentives or regulations. Findings also include: obtaining and sustaining top management support is critical; top benefits mentioned are cost savings, productivity, and operational improvements; and the primary barrier is lacking a culture of energy management. Policymakers and others looking to accelerate ISO 50001 uptake can use these findings to highlight benefits and incentives that will resonate with corporate decisionmakers worldwide