Designing Immersive Virtual Reality Environments for Supporting Patients at Home: Translating Input From Home Care Nurse Experts to Design Requirements.

Immersive virtual reality computer programs provide new experimental and treatment interventions that hold great promise for nursing. Immersive virtual reality uses sensory cues to represent real-world environments in a way that makes participants feel as if they are in a physical space different from the one in which they currently exist. As the acceptance of immersive virtual reality as a clinical and experimental tool has grown, so has the need to ensure that the context depicted in the environment mirrors both the sensory and the task requirements of the real-world situation. Here, we describe the use of nurse expert key informant group interviews to generate requirements that must be fulfilled in immersive virtual reality environments designed to evoke and engage participants in self-management tasks. An expert panel of four home care nurses participated in three sessions designed to elicit details of common home care challenges, frequency of variation, and typical participants. More than 20 potential scenarios were identified. The design team later used this information to create design requirements for two key scenarios and subsequently develop immersive virtual reality environments for use in research studies, mapping sensory and functional expectations to immersive virtual reality implementations. Challenges in mapping from key informant group findings to requirements are addressed.

Usability and Effectiveness of Immersive Virtual Grocery Shopping for Assessing Cognitive Fatigue in Healthy Controls: Protocol for a Randomized Controlled Trial.

BACKGROUND: Cognitive fatigue (CF) is a human response to stimulation and stress and is a common comorbidity in many medical conditions that can result in serious consequences; however, studying CF under controlled conditions is difficult. Immersive virtual reality provides an experimental environment that enables the precise measurement of the response of an individual to complex stimuli in a controlled environment. OBJECTIVE: We aim to examine the development of an immersive virtual shopping experience to measure subjective and objective indicators of CF induced by instrumental activities of daily living. METHODS: We will recruit 84 healthy participants (aged 18-75 years) for a 2-phase study. Phase 1 is a user experience study for testing the software functionality, user interface, and realism of the virtual shopping environment. Phase 2 uses a 3-arm randomized controlled trial to determine the effect that the immersive environment has on fatigue. Participants will be randomized into 1 of 3 conditions exploring fatigue response during a typical human activity (grocery shopping). The level of cognitive and emotional challenges will change during each activity. The primary outcome of phase 1 is the experience of user interface difficulties. The primary outcome of phase 2 is self-reported CF. The core secondary phase 2 outcomes include subjective cognitive load, change in task performance behavior, and eye tracking. Phase 2 uses within-subject repeated measures analysis of variance to compare pre- and postfatigue measures under 3 conditions (control, cognitive challenge, and emotional challenge). RESULTS: This study was approved by the scientific review committee of the National Institute of Nursing Research and was identified as an exempt study by the institutional review board of the National Institutes of Health. Data collection will begin in spring 2021. CONCLUSIONS: Immersive virtual reality may be a useful research platform for simulating the induction of CF associated with the cognitive and emotional challenges of instrumental activities of daily living. TRIAL REGISTRATION: ClinicalTrials.gov NCT04883359; http://clinicaltrials.gov/ct2/show/NCT04883359. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/28073.

Leveraging the health information technology infrastructure to advance federal research priorities.

Ensuring that federally funded health research keeps pace with the explosion of health data depends on better information technology (IT), access to high-quality electronic health data, and supportive policies. Because it prominently funds and conducts health research, the U.S. federal government needs health IT to rapidly evolve and has the ability to drive that evolution. The Office of the National Coordinator for Health Information Technology developed the National Health IT Priorities for Research: A Policy and Development Agenda (the Agenda) that identifies health IT priorities for research in consultation with relevant federal agencies. This article describes support for the Agenda from the Food and Drug Administration, the National Institutes of Health, and the Veterans Health Administration. Advancing the Agenda will benefit these agencies and support their missions as well as the entire ecosystem leveraging the health IT infrastructure or using data from health IT systems for research.

Correlated gamma-based hidden Markov model for the smart asthma management based on rescue inhaler usage.

Asthma is a very common chronic disease that affects a large portion of population in many nations. Driven by the fast development in sensor and mobile communication technology, a smart asthma management system has become available to continuously monitor the key health indicators of asthma patients. Such data provides opportunities for healthcare practitioners to examine patients not only in the clinic (on-site) but also outside of the clinic (off-site) in their daily life. In this paper, taking advantage from this data availability, we propose a correlated gamma-based hidden Markov model framework, which can reveal and highlight useful information from the rescue inhaler-usage profiles of individual patients for practitioners. The proposed method can provide diagnostic information about the asthma control status of individual patients and can help practitioners to make more informed therapeutic decisions accordingly. The proposed method is validated through both numerical study and case study based on real world data. Copyright © 2017 John Wiley & Sons, Ltd.

The Effects of an Online Theory-Based Bone Health Program for Older Adults.

An estimated 10 million Americans age 50 and older have osteoporosis, and many experience associated fractures. Although several interventions have been shown to be effective in preventing osteoporosis, their impact on bone health among older adults was limited. The aim of this study was, therefore, to examine the effects of a theory-based online bone health program (Bone Power program) for a large number of older adults. The 8-week program included learning modules, discussion boards, and other resources. Participants ( N = 866; M age = 62.5 years) were recruited online and randomized into a Bone Power or control group. At the end of the intervention, the Bone Power group showed significantly greater improvement over the control group in osteoporosis knowledge, self-efficacy/outcome expectations for calcium intake and exercise, and calcium intake and exercise behaviors. This study's findings suggest that online health programs can be effective in improving older adults' knowledge, beliefs, and health behaviors.

Biomedical informatics advancing the national health agenda: the AMIA 2015 year-in-review in clinical and consumer informatics.

The field of biomedical informatics experienced a productive 2015 in terms of research. In order to highlight the accomplishments of that research, elicit trends, and identify shortcomings at a macro level, a 19-person team conducted an extensive review of the literature in clinical and consumer informatics. The result of this process included a year-in-review presentation at the American Medical Informatics Association Annual Symposium and a written report (see supplemental data). Key findings are detailed in the report and summarized here. This article organizes the clinical and consumer health informatics research from 2015 under 3 themes: the electronic health record (EHR), the learning health system (LHS), and consumer engagement. Key findings include the following: (1) There are significant advances in establishing policies for EHR feature implementation, but increased interoperability is necessary for these to gain traction. (2) Decision support systems improve practice behaviors, but evidence of their impact on clinical outcomes is still lacking. (3) Progress in natural language processing (NLP) suggests that we are approaching but have not yet achieved truly interactive NLP systems. (4) Prediction models are becoming more robust but remain hampered by the lack of interoperable clinical data records. (5) Consumers can and will use mobile applications for improved engagement, yet EHR integration remains elusive.

Nursing Needs Big Data and Big Data Needs Nursing.

PURPOSE: Contemporary big data initiatives in health care will benefit from greater integration with nursing science and nursing practice; in turn, nursing science and nursing practice has much to gain from the data science initiatives. Big data arises secondary to scholarly inquiry (e.g., -omics) and everyday observations like cardiac flow sensors or Twitter feeds. Data science methods that are emerging ensure that these data be leveraged to improve patient care. ORGANIZING CONSTRUCT: Big data encompasses data that exceed human comprehension, that exist at a volume unmanageable by standard computer systems, that arrive at a velocity not under the control of the investigator and possess a level of imprecision not found in traditional inquiry. Data science methods are emerging to manage and gain insights from big data. METHODS: The primary methods included investigation of emerging federal big data initiatives, and exploration of exemplars from nursing informatics research to benchmark where nursing is already poised to participate in the big data revolution. We provide observations and reflections on experiences in the emerging big data initiatives. CONCLUSIONS: Existing approaches to large data set analysis provide a necessary but not sufficient foundation for nursing to participate in the big data revolution. Nursing's Social Policy Statement guides a principled, ethical perspective on big data and data science. There are implications for basic and advanced practice clinical nurses in practice, for the nurse scientist who collaborates with data scientists, and for the nurse data scientist. CLINICAL RELEVANCE: Big data and data science has the potential to provide greater richness in understanding patient phenomena and in tailoring interventional strategies that are personalized to the patient.

Virtualizing living and working spaces: Proof of concept for a biomedical space-replication methodology.

The physical spaces within which the work of health occurs - the home, the intensive care unit, the emergency room, even the bedroom - influence the manner in which behaviors unfold, and may contribute to efficacy and effectiveness of health interventions. Yet the study of such complex workspaces is difficult. Health care environments are complex, chaotic workspaces that do not lend themselves to the typical assessment approaches used in other industrial settings. This paper provides two methodological advances for studying internal health care environments: a strategy to capture salient aspects of the physical environment and a suite of approaches to visualize and analyze that physical environment. We used a Faro™ laser scanner to obtain point cloud data sets of the internal aspects of home environments. The point cloud enables precise measurement, including the location of physical boundaries and object perimeters, color, and light, in an interior space that can be translated later for visualization on a variety of platforms. The work was motivated by vizHOME, a multi-year program to intensively examine the home context of personal health information management in a way that minimizes repeated, intrusive, and potentially disruptive in vivo assessments. Thus, we illustrate how to capture, process, display, and analyze point clouds using the home as a specific example of a health care environment. Our work presages a time when emerging technologies facilitate inexpensive capture and efficient management of point cloud data, thus enabling visual and analytical tools for enhanced discharge planning, new insights for designers of consumer-facing clinical informatics solutions, and a robust approach to context-based studies of health-related work environments.

Informatics to support the IOM social and behavioral domains and measures.

Consistent collection and use of social and behavioral determinants of health can improve clinical care, prevention and general health, patient satisfaction, research, and public health. A recent Institute of Medicine committee defined a panel of 11 domains and 12 measures to be included in electronic health records. Incorporating the panel into practice creates a number of informatics research opportunities as well as challenges. The informatics issues revolve around standardization, efficient collection and review, decision support, and support for research. The informatics community can aid the effort by simultaneously optimizing the collection of the selected measures while also partnering with social science researchers to develop and validate new sources of information about social and behavioral determinants of health.

Exploring patients' health information communication practices with social network members as a foundation for consumer health IT design.

BACKGROUND: There is a need to ensure that the growing number of consumer health information technologies designed to support patient engagement account for the larger social context in which health is managed. Basic research on how patients engage this larger social context is needed as a precursor to the development of patient-centered consumer health information technology (IT) solutions. PURPOSE: The purpose of this study was to inform the broader design of consumer health IT by characterizing patients' existing health information communication practices with their social network members. METHODS: This qualitative study took place between 2010 and 2012 in a Midwestern city. Eighteen patients with chronic conditions participated in a semi-structured interview that was analyzed using qualitative content analysis and descriptive statistics. Emphasis was placed on recruiting a sample representing diverse cultural groups and including participants of low socioeconomic status. RESULTS: Participants' social networks included a wide range of individuals, spanning biological relatives, divinities, and second-degree relationships. Participants' rationales for health information communication reflected seven themes: (1) characteristics and circumstances of the person, (2) characteristics and circumstances of the relationship, (3) structure and composition of the social network, (4) content of the message, (5) orientation of the goal, (6) dimensions of the context, and (7) adaptive practices. CONCLUSIONS: This study demonstrates that patients' health information communication practices are multidimensional, engaging individuals beyond formal and informal caregivers and driven by characteristics of their personal lives and larger social contexts in addition to their health problem. New models of consumer health IT must be created to better align with the realities of patients' communication routines.

Envisioning the future of home care: applications of immersive virtual reality.

Accelerating the design of technologies to support health in the home requires 1) better understanding of how the household context shapes consumer health behaviors and (2) the opportunity to afford engineers, designers, and health professionals the chance to systematically study the home environment. We developed the Living Environments Laboratory (LEL) with a fully immersive, six-sided virtual reality CAVE to enable recreation of a broad range of household environments. We have successfully developed a virtual apartment, including a kitchen, living space, and bathroom. Over 2000 people have visited the LEL CAVE. Participants use an electronic wand to activate common household affordances such as opening a refrigerator door or lifting a cup. Challenges currently being explored include creating natural gesture to interface with virtual objects, developing robust, simple procedures to capture actual living environments and rendering them in a 3D visualization, and devising systematic stable terminologies to characterize home environments.