Perception of clinical deterioration cues among medical-surgical nurses.

AIM: To examine medical-surgical nurses' capacity and tendency to perceive cues indicating clinical deterioration and nursing characteristics influencing deterioration cue perception. DESIGN: Cross-sectional, explorative study design. METHODS: Data were collected over 10 weeks between September-November 2017. Medical-surgical nurses completed an online survey consisting of a demographic questionnaire, the Occupational Fatigue, Exhaustion Recovery scale and 50 detection trials. Descriptive statistics and statistical tests were used to describe and interpret data. FINDINGS: A significant association was found between nurses' capacity and tendency to perceive deterioration cues. As nurses' capacity to perceive deterioration cues increased, nurses were more likely to classify patient cues as indicators of deterioration. Fatigue, education, and certification were not identified as characteristics associated with deterioration cue perception. However, experience was observed to significantly influence nurses' capacity to perceive deterioration cues based on levels of skills acquisition. CONCLUSION: Study findings imply that future research should be directed at determining whether other individual factors and organizational system dynamics influence deterioration cue perception. IMPACT: To better understand how nurses perceive deterioration cues, this study integrated concepts from the Situation Awareness model and Signal Detection Theory. Novice, advanced beginner and competent nurses were found to have a lower capacity to perceive deterioration cues compared with proficient and expert nurses. With simulation increasingly being used as a primary teaching modality in nursing, the development of a simulation-based signal detection training intervention may be beneficial in enhancing deterioration cue perception.

Passive sensor technology interface to assess elder activity in independent living.

BACKGROUND: The effectiveness of clinical information systems to improve nursing and patient outcomes depends on human factors, including system usability, organizational workflow, and user satisfaction. OBJECTIVE: The aim of this study was to examine to what extent residents, family members, and clinicians find a sensor data interface used to monitor elder activity levels usable and useful in an independent living setting. METHODS: Three independent expert reviewers conducted an initial heuristic evaluation. Subsequently, 20 end users (5 residents, 5 family members, 5 registered nurses, and 5 physicians) participated in the evaluation. During the evaluation, each participant was asked to complete three scenarios taken from three residents. Morae recorder software was used to capture data during the user interactions. RESULTS: The heuristic evaluation resulted in 26 recommendations for interface improvement; these were classified under the headings content, aesthetic appeal, navigation, and architecture, which were derived from heuristic results. Total time for elderly residents to complete scenarios was much greater than for other users. Family members spent more time than clinicians but less time than residents did to complete scenarios. Elder residents and family members had difficulty interpreting clinical data and graphs, experienced information overload, and did not understand terminology. All users found the sensor data interface useful for identifying changing resident activities. DISCUSSION: Older adult users have special needs that should be addressed when designing clinical interfaces for them, especially information as important as health information. Evaluating human factors during user interactions with clinical information systems should be a requirement before implementation.

The state of practice of COVID-19 tracking systems: An inventory study.

In this poster, we report the preliminary results of an inventory of 149 publicly accessible active COVID-19 tracking systems. Key findings include the frequency distribution of the systems' web domain names, the countries where the systems were created, the languages they support, the visual display format, the map platforms, and the data sources. These findings help to advance the knowledge of the data characteristics and design of pandemic surveillance/tracking systems.

Computational modeling of human reasoning processes for interpretable visual knowledge: a case study with radiographers.

Visual reasoning is critical in many complex visual tasks in medicine such as radiology or pathology. It is challenging to explicitly explain reasoning processes due to the dynamic nature of real-time human cognition. A deeper understanding of such reasoning processes is necessary for improving diagnostic accuracy and computational tools. Most computational analysis methods for visual attention utilize black-box algorithms which lack explainability and are therefore limited in understanding the visual reasoning processes. In this paper, we propose a computational method to quantify and dissect visual reasoning. The method characterizes spatial and temporal features and identifies common and contrast visual reasoning patterns to extract significant gaze activities. The visual reasoning patterns are explainable and can be compared among different groups to discover strategy differences. Experiments with radiographers of varied levels of expertise on 10 levels of visual tasks were conducted. Our empirical observations show that the method can capture the temporal and spatial features of human visual attention and distinguish expertise level. The extracted patterns are further examined and interpreted to showcase key differences between expertise levels in the visual reasoning processes. By revealing task-related reasoning processes, this method demonstrates potential for explaining human visual understanding.

Medical calculators: Prevalence, and barriers to use.

BACKGROUND AND OBJECTIVES: Medical calculators synthesize measurable evidence and help introduce new medical guidelines and standards. Some medical calculators can fulfill the role of CDS for Meaningful Use purposes. However, there are barriers for clinicians to use medical calculators in practice. Objectives of this study were to determine whether lack of EHR integration would be a barrier to use of medical calculators, and understand factors that may limit use and perceived usefulness of calculators METHODS: A survey about medical calculators as they relate to clinical efficiency, perceived usefulness, and barriers to effective use was conducted at a medium-sized academic medical center. 819 physicians were invited to participate in an online survey with a 13% response rate. Results were statistically analyzed to highlight factors related to use or non-use of medical calculators. RESULTS: We found a negative correlation between use of medical calculators and years of experience (p < 0.001), with decreasing calculator use as experience goes up. Barriers to using medical calculators by non-users and users of medical calculators show that necessity and integration are significantly different with p < 0.001 and p = 0.037, respectively. 46.7% of non-users reported necessity as a barrier compared to 7.7% of users. Integration was reported as a barrier for 43.6% of users, but only 13.3% of non-users. 61% of users indicated that calculators made them more efficient, and 70% reported that unavailability of normally used calculators make them less efficient. 60% of users indicated that they are somewhat or very likely to use newly published medical calculators. CONCLUSION: The results highlight that medical calculators are important for care delivery by both users and non-users. For non-users, they are seen as having a potentially positive impact on patient care, but unnecessary as part of clinical practice. For medical calculator users, calculators are an important part of regular workflow for efficiency improvement. Clinicians with fewer years of experience show an eagerness to consume newly published calculators, making these kinds of CDS a potentially useful way to disseminate new medical evidence. The survey results suggest that when medical calculators can be automated and integrated into the EHR as part of everyday workflow then efficiency and adoption may increase.