Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care

Hospital nurses are inundated by numerous non-actionable and false telemetry alarms from bedside monitors, central nursing stations, and, in some cases, also from alarms escalated to hospital-provided cellphones after a short time period. There is widespread that patients electing to have DNR/comfort care status do not require telemetry monitoring, and an increasing awareness of the interference of these alarms with valuable end-of-life conversations and interactions with family members. In this project, we instituted policy changes, changes to the electronic health record, and educational interventions for physicians and nurses in order to reduce the proportion of DNR-CC patients with active telemetry monitoring. Overall, we learned that many bedside nurses prefer to turn down the volume or turn off the display inside rooms, which addresses the interference with family interactions but does not reduce the volume of unnecessary alarms and associated documentation requirements and inclusion of alarms in population-based analyses.

Translating validated handover protocols from physicians in non-critical care settings to nursing report in critical care is challenging. Our objectives are to identify information content in verbal reports, where information is documented, and the function of non-documented communication. This is a descriptive study of 20 reports describing 27 patients from two medical intensive care units. Analysis involved unique coding of phrases and emergent themes analysis. Information categories included: Identify patient (51.9%); Narrative history (96.3%); Unusual symptoms (88.9%); Response to care (37%); Status of tasks (100%); Expectations of patients and families (55.6%). Information is documented in progress notes, the medication administration record, nursing flowsheets, lab results, orders, and past medical history. Information not typically documented supports providing patient-centered care, sharing clinical judgments, coordinating work, and mentorship. These objectives may guide nursing administrators in tailoring policies and procedures for nursing report to the needs of registered nurses in a critical care setting.

There is growing interest in implementing whole-slide imaging (WSI) for primary diagnosis. Ten subspecialized pathologists (2-39 years of experience) were interviewed from diverse subspecialty areas in a large academic medical center. Relevant semi-structured interview questions included image quality, workflow, and usability during clinical use. Analysis revealed that WSI implementation would raise some concerns: 1) delaying turn-around time for preliminary diagnoses as well as final reports, 2) delaying access to order ancillary tests, which could impact scheduling for some patients for follow-on surgery, 3) making it hard to track what has been reviewed and at what level of magnification, 4) potentially increase wrist pain from using a mouse or neck pain while viewing the monitor, and 5) increase vulnerability when a computer, monitor, or network goes down. However, WSI implementation would enable 1) increased flexibility for slide access remotely during nights, weekends, and work trips, 2) easier consults among peers and with mentors, 3) easier detection and recovery when images are routed to the wrong person, 4) creating digital libraries, including previous slides from a current patient, and 5) giving greater access to images for presentations, publications, and to other clinical personnel. Implementing digital slides and associated workflow will introduce many challenges and barriers. Studies such as the current one are much needed to explore the pathologist’s perspective on these workflow and implementation challenges prior to and during the installation of the digital pathology systems. These perspectives are important to understand in order to improve the experience of the pathologists and lab personnel as they interact with these systems.

This project’s purpose was to develop cognitively-focused usability evaluation methods for electronic health records (EHRs). This research involved developing a conceptual framework for evaluating EHR usability in terms of clinical cognition and operationalizing the framework in the form of two novel EHR usability evaluation methods. The two evaluation methods - one observational and one lab-based - are described in a suite of protocol materials and recommendations for EHR evaluation and design. This resulting body of work is referred to as CUE-E: Cognitive Usability Evaluation - EHR. This paper describes the process behind the development of the CUE-E evaluation methods, summarizes the use of both, and discusses directions for future work. The two CUE-E evaluation methods are currently ready for pilot applications to assess their reliability and validity and identify opportunities for further improvement.

The Veterans Health Administration (VHA) within the Department of Veterans Affairs (VA) was interested in determining how mobile tablets may be perceived by clinicians for use in clinical settings. Therefore, we conducted an evaluation to assess how performance might differ between two devices and to gather feedback on device use. We conducted a within-subject comparison with 32 clinicians involving a usability test and two questionnaires. Qualitative data was organized around eight themes: facilitators and barriers to tablet use, observations of physical use, device specific advantages and disadvantages, and the Patient Viewer mobile application. Clinicians envisioned many facilitators to tablet use, but also voiced some concerns. Participants rated one device significantly better than the other for questionnaire items related to ‘Access and Efficiency’, ‘Introduction into the Clinical Environment’, ‘Usability and Usefulness’, and ‘Desire to Use’. Results can be used by mobile health app developers, healthcare organizations considering device purchases, and researchers conducting studies on tablets to inform respective work.

Previous research found electronic medical records (EMRs) to have negative impact on patient-provider (PP) communication. However, very few studies were focused on specific age ranges especially young generation. The objectives of this study were to: (1) assess the perception of young adults and healthcare providers regarding the effect of EMRs on PP interaction; and (2) investigate the use of cognitive modeling as an analytical tool to predict the impact of EMRs on PP communication. Findings suggested that young adults have positive opinion regarding the use of EMRs during outpatient visits. Cognitive task perfor-mance modeling has the potential to predict visual, cognitive, and motor demands associated with using EMRs. Future studies should be conducted to improve the generalizability of findings.

There is growing interest in using immersive technology, which includes augmented, virtual, and mixed reality, in medical education. We conducted a narrative literature review to identify elements to consider when using immersive technologies in medical education. Our search revealed clusters of key articles for different applications that point to four categories of elements to consider. We recommend matching learning objectives with choices aligned with these elements for the purchase, implementation, and use of immersive technologies with individuals and groups of medical students.

This research is a first stage in developing a method for modeling the clinician workload associated with an emergency medicine patient in order to display workload for purposes of managing clinician workload and emergency department (ED) flow. We proposed a multi-stage approach of predicting patient-related drivers of clinician’s workload in the emergency department. We trained the model from one month of electronic health record data (EHR) records of an ED. The model predicts the amount of work that individual patients contribute to the workload of clinicians. It can potentially help to manage clinician workload by supporting the decision of assigning new patients.

Fuzzy decision trees represent classification knowledge more naturally to the way of human thinking and are more robust in tolerating imprecise, conflict, and missing information. Decision Making Support Systems are used widely in clinical medicine because decisions play an important role in diagnostic processes. Decision trees are a very suitable candidate for induction of simple decision-making models with the possibility of automatic learning. The goal of this paper is to demonstrate a new approach for predictive data mining models in clinical medicine. This approach is based on induction of fuzzy decision trees. This approach allows us to build decision-making modesl with different properties (ordered, stability etc.). Three new types of fuzzy decision trees (non-ordered, ordered and stable) are considered in the paper. Induction of these fuzzy decision trees is based on cumulative information estimates. Results of experimental investigation are presented. Predictive data mining is becoming an essential instrument for researchers and clinical practitioners in medicine. Using new approaches based on fuzzy decision trees allows to increase the prediction accuracy. Decision trees are a very suitable candidate for induction using simple decision-making models with the possibility of automatic and AI learning.

Expansive and rapid growth of technology creates unprecedented patient access to health information, including timely communication with care providers via patient portals and the ability to access information regarding specific disease(s) (e.g., cancer). However, several forms of digital engagement with health providers require access and use of reliable internet access. A “digital divide” is used to describe demographic differences which contribute to a patient’s use or disuse of patient portals; prior research have noted disparities in lack of reliable internet access. Despite the prevalence of informal caregivers in patient care, little is known about internet access and use among informal caregivers of patients with chronic disease. This study leveraged the 2017 Behavioral Risk Factor Surveillance System (BRFSS) dataset to determine population level characteristics of caregiver factors which may contribute to their internet access and use. Findings illuminate informal caregivers primarily care for patients with illnesses relating to aging, including dementia. We also found that non-use of the internet (NUI) was higher among caregiver groups who informally provided care between 20-39 hours/week as opposed to those with 0-8 hours of provided care each week. Unlike caregivers of asthma, cancer and dementia; caregivers of substance use, diabetes, HIV and chronic respiratory disease patients reported higher NUI. Future studies should target the specific needs of informal caregivers such that tools promoting patient engagement and access to resources do not unintentionally neglect this user group.

Design of health information technology (HIT) that improves patient outcomes is an ongoing process. We propose a methodology that takes a human factors engineering approach to develop systems-engineering-style requirements and design recommendations for both HIT and aspects beyond the scope of the HIT itself (e.g., policies and procedures). Our approach includes: (1) data collection and analysis; (2) preliminary recommendations generation; (3) recommendation review by methodological and domain subject matter experts; (4) revised recommendation review by end users; (5) revised recommendation review by HIT vendors; and (6) final recommendation generation. We illustrate the methodology by presenting a case study focusing on home health care nurses using HIT during the home care admission process.

The focus of this research is to develop and test a new smart glasses application for use in the medical intensive care unit (MICU) to support workflow, patient care, and overall clinical decision-making. The application prototype, mCAREglass, provides clinicians mobility, portability, and hands-free access to real-time patient electronic medical records and bedside data on demand. Five MICU physician volunteers participated in a study consisting of two parts: 1) a usability test with two tasks, and 2) an interview. Part one included usability testing with the use of the tracking pad, followed by the NASA Task Load Index Test and System Usability Scale test. Our findings suggest that mCAREglass has the potential to enhance clinical workflow in the ICU, and that besides providing easy access to patient data, it would improve patient monitoring and surveillance. Participants concurred that for mCAREglass to optimize clinical workflow, it must be well-integrated into one’s daily work as part of decision-making and observation.

The design of digital information management systems for healthcare presents developers with several formidable engineering challenges. These systems must manage huge amounts of data and support communications across disparate platforms and divisions within a healthcare organization. They must ensure that data is kept private, secure, and available to the right people at the right time. However, as shown in other complex systems (e.g., nuclear power), simply making data available may be insufficient. The goals in designing digital healthcare as a ‘cognitive system’ are to present patient information in more meaningful ways, to help healthcare professionals become more productive, and to support healthcare professionals with clinical decision making. This paper describes how principles of cognitive systems engineering (CSE) and user experience (UX) design were applied to Cardiac Consultant, an interactive cardiovascular risk calculator, with those goals in mind.

Health promotion is defined by the World Health Organization as “the process of enabling people to increase control over their health and its determinants, and thereby improve their health.” This is different from the bulk of formal healthcare processes, which are characterized by the treatment of an established disease. Much important human factors research and practice has been done to improve the healthcare delivery process and increasingly human factors professionals are also involved in work on health promotion. Such work has included examining the use and usability of wearable fitness tracking devices, studies of online health information seeking by healthy individuals, and human factors research on social robots for older adults, to name but a few examples. We discuss human factors applications in health promotion, focusing on examples from technology-related research.

Despite noticeable efforts over the last 30 years to try and resolve the clinical alarm problem, the utilization of opinion-based and nonscientific alarm interventions has resulted in ineffective solutions. The field of human factors offers many insights to permanently solving the burdens of this problem, however often times the field’s direct applications are not salient or tangible enough to organizational stakeholders. This has resulted in a utilization deficit of human factors principles in practice today. In order to progress the level of impact human factors has on the clinical alarm problem for the future, this paper discusses how a human factors team tested science-based clinical alarm solutions within a multidisciplinary medical center, and then navigated tradeoffs in order to implement these solutions into practice.

As augmented reality (AR) technology offers enhanced capabilities for medical simulation training, research is required to understand how to best leverage the strengths of AR. We describe a literature review that will provide the foundation for articulating and testing candidate principles for AR adaptive training design. Our goal is to articulate and test design principles for designing recognition skills training as described in the recognition-primed decision model (Klein, 1997). We identified seminal articles from the the Naturalistic Decision Making literature, and used those to seed a systematic review of the medical education and combat medic training literatures. Findings from the literature review suggest three categories of candidate design principles: 1) fidelity and realism, 2) engagement, and 3) scaffolding. Next steps will include articulating specific design principles and designing a series of studies to test them using the VPIT AR training platform.

Monitoring population-level health-risk behaviour is integral to preventing chronic diseases (i.e., diabetes, cardiovascular disease, cancer, etc.). Physical activity and sleep are the key behaviours which influence human health. Smart technologies can be used to improve real-time monitoring of risky behaviours. The objective of this study is to explore population- and individual-level remote monitoring of sleep, indoor physical activity and sedentary behaviours in Canada using data from the Internet of Things (IoT) (ecobee smart thermostat) and fitness trackers. Method: 386 person-hours of data were collected in a pilot study (n =8) to validate the motion sensor data from ecobee smart thermostats. Then, using “Donate your Data” data from ecobee indicators of population-level health were calculated. Results: A positive Spearman correlation coefficient 0.8 (p>0.0001) was found between standard fitness tracker data and ecobee sensors validating its use for population-level analysis. Our results were similar to the Public Health Agency of Canada’s results derived from self-reported surveillance methods. Discussion: This project demonstrates the use of data from non-health sources, like ubiquitous IoT to curate population- and individual-level health indicators. We will deliver novel indicators and insights into health status through the creation of user-centered designed dashboards for individuals, researchers, and policy-makers.

The After Visit Summary (AVS) is provided to patients after clinical visits to summarize what happened during the visit and guide future care. Despite its potential to improve shared decision-making, self-management, and communication, the design of the typical AVS is not optimized to communicate useful information in an understandable way. The AVS usability challenge is magnified in vulnerable patient populations such as those served by community health centers (CHCs). The purpose of this research was to evaluate and refine a redesigned AVS intended to better communicate information to CHC patients.

Simulation is an educational approach well suited to development of knowledge and decision-making skills for emergent or infrequent scenarios. Electronic Health Record (EHR) based simulation, in which participants retrieve information from a simulated EHR, provides an authentic training environment with fidelity to the typical clinical decision-making process and has been associated with enduring changes in EHR use patterns. However, we do not know whether these behavior changes reflect better decision-making. We aimed to develop a measure of pediatric resident performance in an EHR based simulation using the Situation Awareness Global Assessment Technique (SAGAT).

Air pollution is responsible for 4.2 million premature deaths every year. Studies have proven that Ulaanbaatar, the capital city of Mongolia, is one of more polluted cities in the world. As a result, Mongolia is suffering from major public health challenges. Mongolia currently lacks quality data, evidence and information to analyze and understand the full impact of air pollution on maternal and child health. This lack of understand has led to Family Health Centres (FHCs) and hospitals in Mongolia to be overwhelmed and unprepared to adequately treat air pollution related diseases. In response to this problem, UNICEF Mongolia and Ubilab will use User-Centered Design (UCD) and Zero-effort technology to create an online platform that will use predictive analytics to strengthen the understanding of the impact air pollution has on maternal and child health. This platform will better prepare healthcare practitioners to deal with the public health consequences associated with air pollution and the data generated from this platform will be used to inform policy, health care reforms, and develop educational materials. This study is a great opportunity to demonstrate how UCD and ZET can be effective to achieve goals within a global health perspective, but it would be challenging to overcome the economic and cultural barriers in the design and implementation process. However, if successful, this would enhance collaboration between environment and health-related institutions and can be implemented anywhere in the world, especially in areas where air pollution is a major problem.

Valid design of patient-centered digital health or health information technology (IT) systems is based on a thorough and accurate understanding of both “user reality” and “clinical reality.” Type 1 Design Error (User-Reality Error) occurs when designers do not accommodate user characteristics, tasks, context of use, needs, or preferences. Type 2 Design Error (Clinical-Reality Error) occurs when designers do not accommodate the clinical reality, including biomedical knowledge, clinical workflows, and organizational requirements. Both types of errors can invalidate the design, leading to products being rejected by patient end-users or their healthcare delivery systems, product non-use or inappropriate use, and risk of harm. This paper describes our attempts to achieve valid health IT design and avoid the two design errors. We performed iterative, patient-centered design to prototype a mobile application, Power to the Patient (P2P), supporting heart failure self-care management. Our multidisciplinary team of human factors, cardiology, and design experts developed and iteratively refined requirements based on data collection, review, and testing with patient research participants, a patient advisory board, a clinical advisory board, and experts on the team. We describe our process and reflect on working with multiple stakeholders toward the goal of valid health IT design.

The Department of Veterans Affairs’ Human Factors Engineering team recognizes the value of journey maps as a means for communication among stakeholder groups and develops maps to showcase the experience of users with health services and technology systems. The uniqueness of health care environments caused difficulties in following available trade guidance for creating journey maps. Anticipating that other Human Factors Engineers working in health care settings will encounter similar challenges, this paper showcases our lessons learned while creating two distinct journey maps and offers a process for constructing journey maps in health care environments. We learned to selectively limit the content of journey maps, ensure design quality by utilizing a template and rubric, and apply alternate approaches for data gathering. Our improved process includes steps to partner with stakeholders, produce a journey map framework and confirm it with user research, and visualize findings in the completed journey map.

Manikins have traditionally been used to train ultrasound-guided Central Venous Catheterization (CVC), but are static in nature and require an expert observer to provide feedback. As a result, virtual simulation and personalized learning has been increasingly adopted in medical education to efficiently provide quantitative feedback. The Dynamic Haptic Robotic Trainer (DHRT) trains surgical residents in CVC needle insertions by simulating various patient profiles and presenting personalized feedback on objective performance. However, no studies have examined the learning gains of the personalized learning feedback or the relation of feedback to what the user is focusing on during the training. Thus, this study was developed to determine the effectiveness of the current personalized learning interface through a long-term investigation with 7 surgical residents. The eye tracking analysis showed that residents spent significantly more time fixated on percent aspiration throughout the study; the more time participants spent looking at the Number of Insertions, Percent Aspiration and the Angle of Insertion on the DHRT GUI, the better they performed on subsequent trials on the DHRT system.

There is growing interest in using AI-based algorithms to support clinician decision-making. An important consideration is how transparent complex algorithms can be for predictions, particularly with respect to imminent mortality in a hospital environment. Understanding the basis of predictions, the process used to generate models and recommendations, how to generalize models based on one patient population to another, and the role of oversight organizations such as the Food and Drug Administration are important topics. In this paper, we debate opposing positions regarding whether these algorithms are ‘ready yet’ for use today in clinical settings for physicians, patients and caregivers. We report voting results from participating audience members in attendance at the conference debate for each of these positions obtained real-time from a smartphone-based platform.

Precision medicine is driving medicine towards a new era where technology and large amounts of data come together to play an essential role in treatment. Data needed to empower and inform decision-makers can be overwhelming to interpret and poses unique challenges related to the visualization of data generated by machine learning and deep learning algorithms. Therefore, the present study aims to provide an in-depth understanding of the challenges, current trends, and opportunities concerning data visualization for precision medicine.

Given the access to online health information is no longer a problem, continuous growth in health information seeking has been observed. The goal of the study was to explore the triggers, information needs, contemporary technologies and habits of health information search behavior across the lifespan. The population who seeks online health information has increased stably for two decades (Diaz et al., 2002, Tennant et al., 2015). In addition to its prevalence, online health information plays an important role in patient decision-making. Almost half of people who searched for health information online reported that it influenced the way they think about health factors, and more than one third of them said it influenced their decision to see a doctor, or how they managed chronic conditions (Pew Internet Research, 2013). While earlier studies have explored the triggers of online health information seeking (e.g., Flynn, Smith & Freese, 2006), health information seeking behavior may be evolved with the development of new technologies. To explore the triggers of health information seeking across the lifespan, 69 older (mean age = 63.94, 35 female) and 67 younger (mean age = 35.21, 31 female) adults were recruited to a survey study. We found that there was no age difference in the reliance on health information sources. Physicians and the Internet remained the dominant sources of health information, followed by family, friends and pharmacists. Regarding information seeking habits, there was no age difference in the overall frequencies of online health information search despite the fact that more older adults checked health information online daily. Checking medication information was the dominant reason to trigger both younger and older adults to go online, followed by searching online after doctors’ visits, and making treatment decisions. There was also a trend that older users were more likely to go online when they heard about a new or unknown health information compared to younger users. Further, we explored the information needs of online health information search. While older adults were more likely to search for learning new information than younger adults, more younger adults looked up online health information for confirming or clarifying known health information. Taking advantage of social health information, about one half of younger and older adults shared health information online with their family and friends, and went online for checking review comments of medications, healthcare providers, etc. from their peer patients. Further, while desktop computers remained the most used technology for online health information search, an age difference was found in the usage of tablets and smartphones. Older adults used the tablets to do online health information searches more than younger adults; while younger people used the smart phones to do online health information searches more than older people. Overall, we found increasing importance of online health information for adults across the lifespan, especially for older adults who tended to use online information for acquiring new knowledge about health topics. The triggers of online health information seeking were also not only bounded to doctors’ visits but also related to daily health information needs (such as checking medications). Interestingly, the use of tablets for online health information search among older adults could be associated with the perceived ease of use of tablets among older users (portability, bigger font size and the accessibility of interactions) (Jayroe & Wolfram, 2012). As Pew Internet (2017) suggested that over a third of seniors own tablets, when designing elderly-accessible health websites, tailoring the presentation of health information to different media (including tablets) needs to be considered.

As the Internet has become one of the dominant sources of health information, online health information plays an important role for patients to acquire health knowledge and regulate their health behavior (European Commission, 2014). Researchers suggested different ways to nudge public health behavior through environments and policies (Marteau et al., 2011); few studies had explored the potential to use online health information environment to nudge health behavior. While there was established evidence showing the individual differences in online health information search behavior across the lifespan (e.g., Chin et al., 2009; Sharit et al., 2008), the current study was to examine the nudging effects on health behavior through online health information exposure and search. An online mixed-factor-design experiment was conducted on 136 adults across the lifespan (Mean age=49.79, SD=16.00). We examined two kinds of nudging routes, (1) health information exposure (manipulated by the experimenters), and (2) health information search (decided by the participants), on two kinds of health behaviors varying in the costs of taking these health behaviors. Target health behaviors included, (1) self-related health behavior: participants were asked to take a break for doing a stretch (low cost) or a walk (high cost) after long sitting; (2) self-unrelated health behavior: participants were asked to have researchers to donate to the rare disease association through writing down the date (low cost) or a 100-word endorsement article (high cost). In the experiment, each participant was assigned to read four topics (3 articles under each topic) and answer the questions after each health topic. The questions varied in difficulties, which participants could decide to answer the questions based on their own knowledge, their memory from reading, or searching the answers online. To manipulate health information exposure, half of the participants were assigned to read the online articles related to the target health behaviors (such as the harms of long sitting and the target rare disease). Participants were not disclosed about the study goals at the beginning. They were not told that the study goal was to examine whether they took the target health behaviors or not, but to examine how adults learn from online health information. To measure the actions of target health behaviors, for the self-related health behavior, after roughly 40 minutes of the study, participants were requested to take a break for 10 minutes. For the self-unrelated health behavior, at the end of the study, participants were asked whether they would like to show their support to a rare disease association. The manipulations in the costs of health behaviors were assigned in counterbalanced order. Logistic regressions were used to examine the effects of nudging routes and costs of actions on two kinds of target health behaviors. Results suggested that mere information exposure did not affect the likelihood to take the target health behaviors regardless of its relatedness to self-interests or costs of actions. Further, for self-related health behavior, adults were more likely to take actions after a more deliberate engagement with the information - through information search. For health behavior that was unrelated to self-interests, participants were more likely to take actions after they searched the information about this rare disease and only when the costs of actions were low. This study has shown the potentials and limitations of health nudging in different health behaviors, and has its implications on designing effective health nudging strategies on different health behaviors.

Heart failure (HF) is a complex chronic illness that affects the older adult population, requiring medical therapy and day-to-day management to prevent worsening and exacerbation. Patients with HF are often treated with cardiac implanted electronic devices (CIEDs) which capture diagnostic and predictive parameters for HF. In this work we explore how patients would respond to receiving data from an implanted device, using a fictitious scenario interview method with 24 older adults with HF. We applied an uncertainty management lens to better understand how patients face uncertain outcomes and integrate novel data into their decision making. The findings provide insight into how patients would engage and respond to a technology which provides an indicator of their HF status from an implanted device.

We propose a toolkit for objectively evaluating the effectiveness of new technologies for improving human cognitive performance. In complex socio-technical systems such as nuclear power generation and air traffic management, garden path scenarios have been effectively used to anchor initial inaccurate hypotheses that are then monitored for movement towards the correct hypotheses as increasing evidence over time makes it easier to change the diagnosis. The time to come to an accurate diagnosis in a well-crafted simulation scenario with an initial inaccurate anchor hypothesis is an objective, repeatable measure of performance for the macrocognition function of sensemaking. The time to verbalize the recognition of critical cues, which becomes increasingly less subtle over time, as well as the time to move from the inaccurate diagnosis at one of the correct diagnoses in the complete diagnostic set can all be reliably measured and compared in an across-subject study design. Modifications with conceptually matched scenarios using within-subject designs can also be employed if asymmetric learning effects are managed.

In light of our aging population, there is an immediate need for non-obtrusive, continuous, and ubiquitous health monitoring technologies that will enable our population to age with a higher quality of life and independence. Research has demonstrated that gait indicators, such as walking speed, can reflect cognitive and physical functioning. However, gradual changes in such indicators usually go undetected until critical problems arise; being able to detect changes in indicators, such as gait deterioration, of older adults while in their home environments would enable clinicians to tailor more effective and personalized interventions by better understanding user behaviour in real-world settings. Real-world data is essential to enabling our healthcare system to act where patients most need help and to optimize the effect of designed eHealth solutions.

Early implementation of telehealth and mHealth technologies have illustrated the positive potential impact these technologies can have on the healthcare domain. Leveraging mobile device capabilities has the potential to facilitate patient engagement and improve provider-to-patient communication, thus improving patient outcomes. A cross-sectional study surveyed provider and patients to gauge mobile use regarding current mHealth activities as well as concerns and comfort of both parties when using this technology. Results revealed that age, income, type of insurance, and employment mediated either patient comfort and concerns; whereas provider role was the only factor mediating provider concerns. Patients had significantly higher levels of concern when compared to providers. These results can be leveraged to focus effort in implementing and developing telehealth and mHealth technologies.

Changes in alarm perception and response after prolonged daily exposure is not well studied due to the difficulties in setting up rigorous longitudinal studies in real work domains. A prime example of this is the absence of research studying how conveyed urgency and identifiability of auditory alarms change over time. We conducted a three-year study to understand how alarm performance with respect to these two measures changed over time, ostensibly due to prolonged nurse exposure. Gaining a better understanding of the relationship between these two aspects of a sound’s sensory dimension could be extremely valuable to acoustical alarm designers, as it allows them to anticipate changes in the sounds’ sensory performance over time, and not be overly sensitive to first impressions of the auditory alarm set.

The purpose of the study was to identify and assess multiple aspects of patient portal usage behavior in an underserved urban patient population. Given the rise of patient-centered care, patients are required to take active roles to gather health information, make informed health decisions and manage their own healthcare, which behavior were associated with health outcome (Barry & Edgman-Levitan, 2012; Oates, Weston & Jordan, 2000). Patient portals serve as a mean to coordinate patient-centered care by delivering health information to patients (e.g. medical test results), exchanging information with healthcare providers (e.g., messaging providers), and facilitating the delivery of health care services (e.g., scheduling appointments). However, studies often showed that patients in underserved communities did not take full advantages of the patient portals (e.g,. Cazaja et al., 2015, Wallace et al., 2016). These disparities in patient portal usages were associated with many factors, including the complexities of the American healthcare system, lack of internet access, lack of support to navigate through the health systems, and the lack of health literacy among an underserved adult population. To better understand the current use of patient portal of an underserved patient population, we conducted an explorative analysis of portal usage at the University of Illinois Hospitals and Health Sciences System (UIHealth). UIHealth serves throughout the city of Chicago, including areas with high racial segregation (minority population higher than 75%), where patients’ household income is lower than the median of Chicago residents. The majority of patient populations in UIHealth are African Americans (61%) followed by Hispanic/Latino (17%) and White (17%). The study was conducted using a retrospective analysis of Google Analytics portal data from March 2015 to March 2019. User behavior data were extracted to show aspects of usage, including most popular portal functions, language used, time spent on each page, and returning user visits, etc. We used weekly summary data as individual data points (208 data points in total) in the analysis. We found that, over four years, both retuning and new users increased by more than 50%. Regarding the number of users per week, there were local drops in the overall growth which drops were associated with fewer visits to UIHealth during holidays or cold weather. Hence, portal visits were associated with clinic visits. With regards to the most popular functions, writing messages to healthcare providers and viewing medical test results were the most used functions over the years. Results suggested that patients would utilize portal to gather information about their health status (for later discussion with physicians or making informed decisions) and communicate with healthcare providers. Interestingly, we found the dominant devices used to access the portal have shifted from desktop computers (2015-2017) to mobile phones (2017-2019), suggesting the increasing need to present health information in bitable size in smaller screens; and the increasing smartphone adoptions of underserved adults as an alternative solution to get internet access. Overall, improving the accessibility of patient portals remains to be a major issue for empowering patients in contemporary value-based healthcare systems. The explorative study has shed lights on the longitudinal trends of portal usage among an underserved population, which creates practical implications on the design of a more efficient interface between patients and their healthcare providers with the ultimate goal to improve health equity.

Although advancements in home-use technologies have allowed users to take control over how they monitor their health, their likely inexperience with such technologies can lead to use errors. The study aimed to determine the usability of a home-use blood pressure monitor, which included the device and instructional materials. Nineteen participants completed a 45-minute study which included an out-of-the-box handling scenario without moderator facilitation. The primary goal of this scenario was to determine if participants would be able to classify their heart rate reading obtained from the heart rate monitor as either low, average, or high in accordance to the thresholds set by the device. Although a majority of users were able to complete the use scenario, users nonetheless experienced major use errors and had difficulty with correctly placing the blood pressure cuff on their arm or inadvertently inflated the cuff when simply trying to turn on the device. There were also differences in the instructional materials such as how users should place the cuff around their arm. These inconsistencies were exacerbated by ambiguous wording without any pictorial clarifications. Additionally, 10% of users were unable to locate information on how to interpret their blood pressure readings. These findings highlight the importance of studying the usability of at-home blood pressure monitors to ensure more accurate health monitoring of users.

The decision to access healthcare resources and psychiatric treatment may be impacted by information provided in the external environment. For messages about depression, how and where messages are delivered may be critical to whether an individual seeks help. In this study, participants were placed in a simulated environment and asked to provide ratings of state anxiety, message elaboration, psychiatric help-seeking intentions, mental health anxiety, trait anxiety, and attitudes towards psychiatric help-seeking after 30 minutes. Overall, the study revealed that (1) the subjects in a high noise condition reported a higher level of state anxiety than subjects in a low noise condition, and (2) the effect of state anxiety on message elaboration depends on anxiety-relatedness. The study improves our understanding of the relationships between state anxiety, mental health anxiety, and trait anxiety. The results also offer implications for mental health communication as a critical path to depression treatment.

Failure to detect and treat clinical deterioration in patients, either from a medical condition or due to a complication of surgical treatment, is a common life threatening problem. Hospitals have introduced Rapid Response Systems (RRS) to manage patients with catastrophic physiological derangements. The first responders on general medical and surgical wards will nearly always be an ad hoc assembly of available providers with limited experience in managing common emergency situations. Checklists, borrowed from aviation solutions have been used effectively as a routine safety procedure. Studies describing the use of checklists beyond the highly controlled environments of the Intensive Care Unit (ICU) and the operating theatre are rare. Checklist formats similar to the operating theatre checklists, require a team of several responders already at the bedside. However, the first-responder on medicine-surgery wards is often a lone responder, most likely a registered nurse and/or a junior doctor with limited experience in managing emergencies. The successful implementation of crisis emergency checklists has the potential to improve patient care and outcomes. RRS crisis emergency checklists are likely to be effective when they are performed as a team routine in the context and readiness for change. The success of checklists will depend on careful listening to clinicians, uptake and acceptance by providers, supported by a strongly motivated and committed team ethos.

Recent research has explored the use of wearable/hand-free devices, such as smartwatches, in clinical settings. Smart watch, in particular, can display information in different modalities, including visual, auditory and tactile, and thus has the potential to improve communication and notification in clinical environments that are overloaded with sensory information. However, few studies have examined the effectiveness of notifications received on smart watches and the factors that affect the performance while using smartwatches for notifications. This study investigated the effects of type of notifications (multimodal vs. tactile) and the environmental noise level on user performance while receiving notifications on a smart watch in a simulated nursing home setting. Eighteen participants performed four different tasks in a simulated clinical settings while they were asked to respond to tactile and multimodal (tactile and auditory) notifications received on a smartwatch. Results showed that the modality of notification did not affect user performance. However participants rated multimodal notification as more helpful. The noise level and type of task had a significant effect on performance. The results of the study indicate that the effectiveness of smartwatch notifications varies in different clinical settings with varying environmental features and with different of primary task. Adjustment of parameters for each setting would be necessary.

Oxytocin (OT) is a naturally occurring hormone produce by the hypothalamus. While a growing body of work has focused on the role of OT in modulating human social cognition, a somewhat neglected but promising area of study is how OT effects pain perception and pain behavior. Animal studies consistently support OT as an analgesic but human studies are few and somewhat mixed. The current study explores whether the analgesic effect of OT diminish maladaptive decision making associated with pain, both directly and indirectly. At the same time, pain-related positive social behaviors such as trust and cooperation, may be heightened under the influence of oxytocin. Intranasal OT (24 IU) versus placebo trials were separated by a one-week washout period. The primary outcome measures include three indicators of change in social capital, including trust, cooperation, and safety perceptions. Furthermore, the analgesic effect of OT on pain sensitivity is evaluated in the context of interactive effects with pro social decision making. Behavioral rating scales examined delayed discounting, impulsivity, and loss aversion. In addition to behavioral measures, urine samples were collected to assess subject OT saturation and saliva samples were collected to test for genetic markers associated with pain and trust. We first examined if OT has a main effect (i.e., generalized) on pain perception and secondly, if pain-related social behavior is moderated by OT. Results support OT as a potential analgesic. Additionally, OT may not only act to relieve pain but may also reinforce other adaptive social behaviors exhibited by people in pain.

Drowsy driving claims many lives every year. While all drivers are susceptible to the problem of drowsy driving, the nurse population is of particular concern. Studies have shown the severity of drowsiness for night shift nurses both at work and on the drive home. Many work and non-work factors contribute to the drowsiness that nurses experience. This study used a semi-structured interview approach to gain the perception and experiences of nurses concerning drowsy driving and possible interventions. Interviews were conducted at a large hospital in south central Texas with 30 night shift nurses. Visualizations depicting nurses’ responses are presented to aid in the understanding of the themes derived from the interviews. The nurses experience drowsy driving on a regular basis, use ineffective mitigation techniques and have differing preferences for an educational and technological intervention for drowsy driving. An emergent theme was how work and non-work factors work in conjunction to impact the nurses’ experiences of drowsy driving. Potential, implementable solutions regarding some of these factors are presented.

This research examined the usability and effectiveness of wayfinding in multiple large, complex, multi-building hospitals. The initial research explored three large hospitals’ touchscreen wayfinding interfaces. Errors and issues consistently observed were organized and developed into heuristics and design recommendations. In phase two, a promising mobile application was chosen and both a heuristic analysis and an onsite test of effectiveness were conducted by four researchers. Though the application met many requirements and solved many issues from phase one, it did not meet the expectation of real time navigation. For phase three we chose an app that provided real time navigation and conducted a usability test onsite. Results indicate that this problem is multi-faceted and wayfinding solutions must consider the other available aids in the environment. Incorporation of user centered design principles and requiring the evaluations of users in the development of wayfinding aids are needed. Beyond usability, the key learning is that the wayfinding systems cannot be created in a vacuum, rather the interfaces, the placement of the wayfinding system and the environment of the hospital must be considered. The wayfinding kiosk or app information should complement the environmental information such as color coding, landmarks, room and elevator labeling and signage.

Two leading causes of survivable combat deaths are hemorrhage and airway compromise. Although individual medical-training competency requirements are met using human-patient simulation (HPS), the evaluation of fidelity and HPS impact on training outcomes are not well documented. Research has documented physical fidelity concerns when comparing human anatomy to simulators, but has largely overlooked informational needs such as visual, auditory, and tactile cues for patient assessment. Training impact is often characterized by changes in confidence; however, the Dunning-Kruger effect suggests that overconfidence is pervasive. The purpose of this paper is to provide perspective on the research needs to ensure human-patient simulation meets the requirements for combat-medic training.

Work Related Musculoskeletal Disorders (WMSDs) can be a result of complex interactions between physical, psychosocial, biological, and individual characteristics. However, the evidence on specific associations is still inconclusive. A previous study conducted at a Sterile Processing Department (SPD) in a local hospital established an association between perceived job demands and adverse body postures. However, causal inferences were not possible to establish given the study design. Consequently, the objective of this study was to determine if perception of mental workload causes workers to use more risky body postures. Objective and subjective assessment tools (REBA and NASA-TLX scores) were used as indicators of body postures and mental workload. The findings indicated that there is a positive relationship between the perception of workload (NASA-TLX scores) and adverse body postures (REBA scores) suggesting that people tend to adopt more awkward postures when they feel they are in a rush condition or they have more things to do

Sepsis is one of the most deadly and costly diseases. The Emergency Department (ED) is the initial point of care for most patients who become hospitalized due to sepsis. Quantifying the accuracy of ED clinician forecasting regarding patients’ clinical trajectories and outcomes can provide insight into clinical decision making and inform sepsis management.

The study was conducted to understand the effects of having access to different training materials in the interim between training and first use of an injection device for 27 injection-naïve participants. Participants were told they would be giving themselves a real injection of saline in the return session, and were not told that they would use injection pads until after subjective data was gathered during session 2. This deception paradigm was used to increase the external validity of the study. Participants self-trained in one of three conditions based on what they were given to take home: instructions for use, mechanical trainer, and/or a training video. Participants self-trained in session 1, performed a simulated injection in the session 2 two weeks later, and completed three online surveys in the interim. In session 2, a majority of participants were able to achieve minimally acceptable performance to deliver the medication during the simulated use of the autoinjector. Participants who took home a mechanical trainer had fewer use deviations than those who did not have the trainer at home. This difference was only seen in injection specific subtasks; performance on pre- and post-injection subtasks was low across all groups. Intermittent practice with a mechanical trainer was seen to improve performance on subtasks involved in the motor performance of the injection itself but did not impact performance or compliance with other tasks important to the injection. More holistic training solutions may be required to impact other aspects of the injection beyond the injection itself. While performance differed, subjective ratings did not differ, showing an overconfidence bias that may affect a user’s ability to self-report competence in device use.

Mobile health (mHealth) is a fast-growing industry that facilitates the management of healthcare by both patients and healthcare providers (Zapata, et al, 2015). The growing popularity of this platform and general lack of regulatory oversight has led to wide variation in adherence to sound human factors and usability principles. Thus, a set of guiding criteria would help developers streamline their processes through standardization. As part of a project referred to as the Xcertia Guidelines, a workgroup of industry experts and stakeholders developed guidelines for incorporating usability principles into the development of mHealth applications. Using an iterative process, the workgroup conducting research to generate content covering 10 distinct topic areas for a draft publication released in February, 2019. After an open comment period, an updated version of the guidelines will be released to the public.

Team communication challenges compound the complexity of healthcare environments. While there is a significant body of research on team interaction in surgical and operating room settings, there is limited research in more specialized use environments such as the electrophysiology (EP) lab where an interdisciplinary team supports the diagnostics and interventional correction of the heart’s electrical timing. This work proposes a novel framework to uncover and classify team communication pathways in complex healthcare environments via a case study of the EP lab. Designers of integrated medical systems should study the communication practices and communication barriers of intended users to drive better user needs and design inputs.

As the medical device industry establishes more rigorous human factors practices in their design and development process, this is accompanied by an increase in demand in human factors professionals. The human factors activities have been performed by both professionals with formal human factors education and training and those who come from other backgrounds, such as engineering, natural science, medical fields, design and more. Both across those disciplines and the within human factors field, there is no standard curriculum or requirements for educating and preparing human factors engineers/professionals for the medical device/health care domain. To better understand how (well) human factors professionals are prepared for the medical device industry, a survey was administered in the form of an interactive poster at the 2019 International Symposium in Human Factors and Ergonomics in Health Care. Data were collected regarding where symposium attendees, most of whom are human factors professionals in health care/medical device, learned the important knowledge/skills required for human factors practice in the medical device industry. In this paper, the method is described in details, and results from the poster survey are presented and discussed.

Masks are used in daily life, as useful hygiene products, for purposes such as guarding against pollen and facilitating cough etiquette. When worn to prevent and control infection in daily life, it is important that the mask fits the wearer’s face perfectly. Even when the wearer is talking, the mask sheet must adapt to the wearer’s face. Therefore, the present study considers a mask sheet pattern with high fit performance for female wearers based on measured three-dimensional (3D) female facial shapes with the mouth either closed or open. Comparing the closed-mouth facial shapes with open-mouth ones, a mask sheet pattern is sought, deformation amounts of sheet area and length in the pattern while opened mouth.

The stated purpose of this panel was to discuss how the application of human factors science to the design, evaluation and development of medical device labeling and instructions for use is both good business and consistent with the law. Specific examples of the law were briefly discussed in the panel and are described in more detail in this paper. Questions posed by the audience quickly made it apparent that a higher-level conversation around risk was desired. One of the main topics addressed was that of unintended misuse; a summary of that discussion is also included in the paper. The overarching theme of the panel was as follows: The best we can do as human factors professionals is perform good science, document the work that we’ve done and the reasons for decisions that were made. We should also always strive to create the best product which requires balancing numerous constraints and competing goals.

Traditional methods of investigating usability include usability tests, heuristic evaluations, surveys, and field methods. User self-reports of equipment problems such as through the FDA MAUDE database are also available, but there may be limited information reported. Often, people turn to social media to share stories and learn from others. In this study, the authors explored using social media as a means of identifying possible usability issues with medical devices and products. As a proof of concept, the authors focused on insulin pumps, continuous glucose monitors, and sleep apnea machines. Reports of medical equipment use issues were grouped into three categories: 1) correct instructions for product use, 2) apparently inadvertent incorrect instructions for use and 3) instructions that encouraged or could promote deliberate misuse. Each of these has different implications for designers, clinical product review committee members, and clinicians.

As part of a comprehensive Quality System Regulation (QSR), the human factors (HF) validation requirement by the Food and Drug Administration (FDA) is a relatively recent topic. Multiple issues and bottlenecks have emerged since the publication of the draft guidance in 2011. The scientific literature on the topic of ‘FDA HF validation requirement’ is mostly focused on HF methods to ensure success from that perspective. However, the development of across-the-board strategies that can address other critical factors is necessary. No previous scientific research has outlined and addressed the problems considering the QSR and the needs of key stakeholders. For that purpose, this effort presents a narrative review of how the HF requirement for medical devices and combination products developed, as well as the issues and the interventions that have taken place to address the bottlenecks. Some essential considerations such as notorious knowledge-based and process-based gaps are discussed. Similarly, because of the demands of a changing QSR, attention is brought to the need to align key stakeholders, namely manufacturers and HF service providers (HFSPs). Also, the development of an industry (HFSPs) maturity assessment tool and future research for that purpose are proposed.

Recognizing the role of human factors engineering (HFE) in the development of medical devices and combination products that involve devices, the Food and Drug Administration (FDA) now requires human factors (HF) validations before market approval. Manufacturers are responsible for ensuring their products are safe and effective through the application of HFE. However, key stakeholders are still learning and developing capabilities to adapt to the regulatory component. Nonetheless, the lack of the corresponding HF capabilities hinders compliance with the FDA’s expectations, and though ultimate success. No known previous work has looked into FDA HF validation projects to assess the underlying factors and implications of failed submissions. Applying system dynamics (SD), a causal loop diagram (CLD) was developed. CLDs are useful for the exploration of the causal interactions among factors or variables, as well as the underlying feedback structure of a complex system. This work can serve to help manufacturers better understand the FDA’s HF requirement to enable overall product success. Further, with patient safety as a common goal, HF service providers (HFSPs) and regulators should be aware of the need to ensure the consistent quality of the HF element in premarket submissions.

Well-designed instructions for use (IFUs) reduce medical device risk and facilitate regulatory review. This study evaluated two common IFU formats (booklet and foldout) to identify benefits and drawbacks for comprehension and use. In an A/B usability test, 16 adults simulated the preparation of a dose of medicine and were asked to find critical information using instructions in each of the formats. They then compared the two formats and completed a standardized health literacy assessment. Our results showed that the foldout presented an accessible overview of the steps while the booklet showed ease-of-use benefits, particularly for those with lower health literacy scores. Our results indicate that physical design decisions impact the user experience, and that they should be carefully evaluated to provide an optimal IFU.

Safety in healthcare has not significantly improved in the last 20 years with an estimated 5 to 10% of patients admitted to hospital suffering from adverse events. Health care is a service that can encourage optimal health outcomes only through meaningful, collaborative partnerships between patients and clinicians. Co-production of health services can be used as a means to rethink how health care is delivered with patients as co-creators rather than passive recipients of health care assisting healthcare organisations towards safer and more responsive care. Technology can improve patients’ agency over their care when consumers are able to personalize their experience while using an organization’s service and in return undertake specific tasks needed by the organization. Patients can be the pivot point of safer hospital care, not only in the context of face-to-face encounters in which the benefits of working together are obvious, but also in designing systems that can improve patient care, increase satisfaction and enhance the value of care.

The overwhelming number of alarms on medical center floors are false and nonactionable. This leads to delay in alarm response and adverse events. Furthermore, current alarm technology does not have the ability to display patient trends, it only displays one isolated patient event. This paper focuses on describing the methods for creating novel visual displays that incorporates alarm technology and patient decompensation events. Through a multi-disciplinary team approach, that is centered on human factors and system engineers, a novel visual display was created that integrated current alarm technology with patient data. The new displays were better able to predict decompensation and alarm validity. It is crucial to integrate partners from all facets of the medical community and from human factors and system engineering to form an accurate understanding and modeling of patients

Clinicians are constantly forecasting patient trajectories to make critical point of care decisions intended to influence clinical outcomes. Little is known, however, about how providers interpret mortality risk against validated scoring systems. This research aims to understand how providers forecast mortality specifically for that of patients with sepsis. Defined as life-threatening organ dysfunction caused by a dysregulated host response to infection, sepsis is commonly hard to diagnose, progresses rapidly, and lacks a “gold standard” test. Participants were nurses and doctors from the general medical and surgical floors of six different hospitals. Each was presented with ten different patient cases, categorized into low and high severity sepsis, and were asked about care decisions, along with estimations of mortality risk. The resulting data provides a unique look into the differences of risk forecasting between profession and patient severity.

Patients and families play a role in the safety of care provided across clinical settings, highlighting the need to understand clinician perspectives and experiences related to their engagement. Through a panel discussion entitled, The Patient in Patient Safety: Clinicians’ Experiences Engaging Patients as Partners in Safety, we elicited clinician perspectives that have implications for human factors relevance in both, research and solution development/evaluation. We provide an overview of the panel including participants, format and content, and the resulting discussion.

We observed nurse-patient interactions during triage in an emergency department over the course of a two-month period. After 161 observations, we found no significant correlation between the percentage of interaction attributed to the patient and the amount of time the patient spent in triage. Additionally, this study found no correlation between the types of questions the nurse asks and the time patients spend in triage.

Effective hand hygiene among clinicians decreases the incidence of healthcare-associated infections and helps slow the rate of antibiotic resistance, but hand hygiene compliance (HHC) rates among clinicians is often low. Facility-wide HHC monitoring is required by the U.S. Centers for Medicare & Medicaid Services. In general, HHC monitoring is important to identify facility care areas, units or departments that have low HHC rates so that targeted interventions can be implemented. Recently several hand hygiene observation apps (HHOA), which enable observers to use mobile devices to record HHC data, have become available.

The overall goal of our effort was to evaluate how helpful five different HHOAs were in supporting users in collecting and aggregating HHC data. Overall our participants, which included nine individuals with clinical training, and eight biomedical engineers found that all five HHOAs were fairly hard to use given that they have a relatively simple and straightforward function. There was an interesting interaction, however, with the biomedical engineers rating highest the HHOAs that the clinically-trained users rated lowest.

Automatic speech recognition (ASR) systems and speech interfaces are becoming increasingly prevalent. This includes increases in and expansion of use of these technologies for supporting work in health care. Computer-based speech processing has been extensively studied and developed over decades. Speech processing tools have been fine-tuned through the work of Speech and Language Researchers. Researchers have previously and continue to describe speech processing errors in medicine. The discussion provided in this paper proposes an ergonomic framework for speech recognition to expand and further describe this view of speech processing in supporting clinical work. With this end in mind, we hope to build on previous work and emphasize the need for increased human factors involvement in this area while also facilitating the discussion of speech recognition in contexts that have been explored in the human factors domain. Human factors expertise can contribute through proactively describing and designing these critical interconnected socio-technical systems with error-tolerance in mind.

The transfer of anesthesia patient information within a perioperative setting is susceptible to many barriers that prevent effective communication. Several studies have aimed to combat these barriers by successfully developing and implementing structured communication protocols. The purpose of this review is to provide a synthesis of the current state of literature in order to guide practice and future research into the development, implementation, and evaluation of anesthesia patient handoff protocols. Four databases were searched based on inclusion criteria, resulting in 33 studies that were reviewed for this analysis. Results show there are many methods used in current literature to design, implement, and evaluate anesthesia handoff protocols, suggesting little consensus for best practice. Future handoff studies should ensure they fully report all details associated with the development and evaluation of their anesthesia handoff protocols to promote replicability and guidance for other practitioners.

Successful surgery does not just depend on the skills and knowledge of those in the operating room but also on the staff that insure the needed instrumentation is available and sterile. The process that continuously provides reusable medical equipment (RME) to the Operating Room (OR) requires highly specialized expertise over a wide range of instrumentation. The reprocessing team must be familiar with instructions for use (IFU), and how to apply them to process every piece of RME from surgeries, endoscopies, and clinic procedures. Coupled with the limitations of staff, time, and resources and with competing demands to produce sterile instruments and environments that work in almost total isolation from each other, there are several gaps in the process that must be identified and bridged. While the workflow for moving between the Sterile Processing Department (SPD) and the OR is sometimes thought as a fairly simple circular flowchart, the realities of work done versus work imagined are vastly different. In addition, these challenges vary considerably across different departments, even in a single healthcare system, and as such there are no simple solutions. Understanding the demands on the SPD, the needs in the OR for sterile RME, and the patient safety concerns that drive this cycle are critical if we are to improve the process.

The goal of this study was to assess the availability of the criteria of eight sepsis scoring methods (SIRS, NEWS, PRESEP, SOFA, qSOFA, SPEED, MEDS, and PIRO) within six hours of triage in the emergency department (ED). Data was analyzed through a retrospective collection of adult (age >18 years) patients presenting to the MedStar Washington Hospital Center (MWHC) emergency department between June 1, 2017 and May 31, 2018 and admitted with a sepsis or sepsis-related diagnosis that progressed to sepsis before discharge. Vital signs are frequently available upon arrival to the ED, while laboratory values tend to be available within three hours and often are not repeated again within the first six hours after arrival. The availability of patient data at different time points in a patient’s ED visit suggests that different scoring methods could be utilized to more effectively diagnose and accurately risk-stratify patients within the sepsis spectrum as more information about the patient becomes available.