Nursing Knowledge: 2015 Big Data Science.
Comput Inform Nurs. 2015 Oct;33(10):427-31
Authors: Westra BL, Pruinelli L, Delaney CW
PMID: 26468968 [PubMed - indexed for MEDLINE]
Data Visualization Techniques to Showcase Nursing Care Quality.
Comput Inform Nurs. 2015 Oct;33(10):417-26
Authors: Monsen KA, Peterson JJ, Mathiason MA, Kim E, Lee S, Chi CL, Pieczkiewicz DS
PMID: 26468967 [PubMed - indexed for MEDLINE]
Usability of the Clinical Care Classification System for Representing Nursing Practice According to Specialty.
Comput Inform Nurs. 2015 Oct;33(10):448-55
Authors: Feng RC, Chang P
This study examined the ability of the Clinical Care Classification system to represent nursing record data across various nursing specialties. The data comprised nursing care plan records from December 1998 to October 2008 in a medical center. The total number of care plan documentation we analyzed was 2 060 178, and we used a process of knowledge discovery in datasets for data analysis. The results showed that 75.42% of the documented diagnosis terms could be mapped using the Clinical Care Classification system. However, a difference in nursing terminology emerged among various nursing specialties, ranging from 0.1% for otorhinolaryngology to 100% for colorectal surgery and plastic surgery. The top five nursing diagnoses were identified as knowledge deficit, acute pain, infection risk, falling risk, and bleeding risk, which were the most common health problems in an acute care setting but not in non-acute care settings. Overall, we identified a total of 21 established nursing diagnoses, which we recommend adding to the Clinical Care Classification system, most of which are applicable to emergency and intensive care specialties. Our results show that Clinical Care Classification is useful for documenting patient's problems in an acute setting, but we suggest adding new diagnoses to identify health problems in specialty settings.
PMID: 26418298 [PubMed - indexed for MEDLINE]
Use of Simulation to Study Nurses' Acceptance and Nonacceptance of Clinical Decision Support Suggestions.
Comput Inform Nurs. 2015 Oct;33(10):465-72
Authors: Sousa VE, Lopez KD, Febretti A, Stifter J, Yao Y, Johnson A, Wilkie DJ, Keenan GM
Our long-term goal was to ensure nurse clinical decision support works as intended before full deployment in clinical practice. As part of a broader effort, this pilot project explored factors influencing acceptance/nonacceptance of eight clinical decision support suggestions displayed in an electronic health record-based nursing plan of care software prototype. A diverse sample of 21 nurses participated in this high-fidelity clinical simulation experience and completed a questionnaire to assess reasons for accepting/not accepting the clinical decision support suggestions. Of 168 total suggestions displayed during the experiment (eight for each of the 21 nurses), 123 (73.2%) were accepted, and 45 (26.8%) were not accepted. The mode number of acceptances by nurses was seven of eight, with only two of 21 nurses accepting all. The main reason for clinical decision support acceptance was the nurse's belief that the suggestions were good for the patient (100%), with other features providing secondary reinforcement. Reasons for nonacceptance were less clear, with fewer than half of the subjects indicating low confidence in the evidence. This study provides preliminary evidence that high-quality simulation and targeted questionnaires about specific clinical decision support selections offer a cost-effective means for testing before full deployment in clinical practice.
PMID: 26361268 [PubMed - indexed for MEDLINE]
Factors Affecting Nursing Students' Readiness and Perceptions Toward the Use of Mobile Technologies for Learning.
Comput Inform Nurs. 2015 Oct;33(10):456-64
Authors: Zayim N, Ozel D
The purpose of this study was to determine the current usage of mobile devices, preferences of mobile learning environments and examine the readiness of nursing students in a public university. In order to investigate preferences and attitudes with respect to mobile technology use in nursing education, 387 students at a state university have been surveyed. It has been observed that while students preferred their current portable laptops, those in higher classes were more inclined to favor mobile phones. The common problems of battery life and high cost of communication, both in smartphones and tablet systems, suggest that hardware quality and financial constraints seem to be two main factors in determining these technologies. While more than half of students expressed readiness for mobile learning, one quarter indicated indecision. Through multivariate regression analysis, readiness to use mobile learning can be described in terms of perceived ease of use, perceived usefulness, personal innovativeness, self-management of learning, perceived device limitation, and availability. Class level, perceived ease of use, personal innovativeness, and self-management of learning explain intention to use mobile learning. Findings obtained from these results can provide guidance in the development and application of mobile learning systems.
PMID: 26200902 [PubMed - indexed for MEDLINE]
Using the Technology: Introducing Point of View Video Glasses Into the Simulated Clinical Learning Environment.
Comput Inform Nurs. 2015 Oct;33(10):443-7; quiz E1
Authors: Metcalfe H, Jonas-Dwyer D, Saunders R, Dugmore H
The introduction of learning technologies into educational settings continues to grow alongside the emergence of innovative technologies into the healthcare arena. The challenge for health professionals such as medical, nursing, and allied health practitioners is to develop an improved understanding of these technologies and how they may influence practice and contribute to healthcare. For nurse educators to remain contemporary, there is a need to not only embrace current technologies in teaching and learning but to also ensure that students are able to adapt to this changing pedagogy. One recent technological innovation is the use of wearable computing technology, consisting of video recording with the capability of playback analysis. The authors of this article discuss the introduction of the use of wearable Point of View video glasses by a cohort of nursing students in a simulated clinical learning laboratory. Of particular interest was the ease of use of the glasses, also termed the usability of this technology, which is central to its success. Students' reflections were analyzed together with suggestions for future use.
PMID: 26176638 [PubMed - indexed for MEDLINE]
CaseWorld: Authentic Case-Based Learning Simulating Healthcare Practice.
Comput Inform Nurs. 2015 Oct;33(10):436-42
Authors: Tucker K, Parker S, Gillham D, Wright V, Cornell J
Health educators in Australia are challenged by the need to provide clinically relevant education to large numbers of students across a wide range of specialties. This situation is compounded by changed student demographics, new technologies in both the workplace and university, and decreased access to clinical placement opportunities for students. This article describes an innovative response addressing nurse education priorities and implemented in the School of Nursing at Flinders University South Australia, involving the development of CaseWorld, a prototype virtual case-based learning environment. CaseWorld implementation was unique because large-scale innovation occurred as part of routine curriculum development. This was challenging as there was limited opportunity for prototype evaluation before student use, thus necessitating a flexible implementation process. The outcome was the development of scripted unfolding cases that provide students with low-fidelity simulation enhanced by multimedia. Students engage with cases based on real patient experiences, which are modified to protect confidentiality. These authentic cases provide the basis for the development of critical-thinking and decision-making skills as students problem solve issues and identify priorities for nursing care, explain the pathophysiology, and respond to simulated patient complaints. CaseWorld was modified in response to evaluation data from surveys and focus groups, and the revised version is discussed in terms of its implementation in nursing and planned use across multiple health sciences disciplines.
PMID: 26176635 [PubMed - indexed for MEDLINE]
Leaders in Nursing Informatics Education and Research: The University of Utah Celebrates 25 Years.
Comput Inform Nurs. 2015 Sep;33(9):379-81
Authors: Cummins MR, Sward K, Guo JW
PMID: 26381830 [PubMed - indexed for MEDLINE]
Nursing-Centric Technology and Usability A Call to Action.
Comput Inform Nurs. 2015 Aug;33(8):325-32
Authors: Staggers N, Elias BL, Hunt JR, Makar E, Alexander GL
PMID: 26295214 [PubMed - indexed for MEDLINE]
Emergency Department Visit Forecasting and Dynamic Nursing Staff Allocation Using Machine Learning Techniques With Readily Available Open-Source Software.
Comput Inform Nurs. 2015 Aug;33(8):368-77
Authors: Zlotnik A, Gallardo-Antolín A, Cuchí Alfaro M, Pérez Pérez MC, Montero Martínez JM
Although emergency department visit forecasting can be of use for nurse staff planning, previous research has focused on models that lacked sufficient resolution and realistic error metrics for these predictions to be applied in practice. Using data from a 1100-bed specialized care hospital with 553,000 patients assigned to its healthcare area, forecasts with different prediction horizons, from 2 to 24 weeks ahead, with an 8-hour granularity, using support vector regression, M5P, and stratified average time-series models were generated with an open-source software package. As overstaffing and understaffing errors have different implications, error metrics and potential personnel monetary savings were calculated with a custom validation scheme, which simulated subsequent generation of predictions during a 4-year period. Results were then compared with a generalized estimating equation regression. Support vector regression and M5P models were found to be superior to the stratified average model with a 95% confidence interval. Our findings suggest that medium and severe understaffing situations could be reduced in more than an order of magnitude and average yearly savings of up to €683,500 could be achieved if dynamic nursing staff allocation was performed with support vector regression instead of the static staffing levels currently in use.
PMID: 26200901 [PubMed - indexed for MEDLINE]
Health Information Exchange Capabilities in Skilled Nursing Facilities.
Comput Inform Nurs. 2015 Aug;33(8):346-58
Authors: Filipova AA
The purpose of this study is to determine the levels at which health information exchange is used by skilled nursing facilities for clinical functions, the benefits and barriers associated with health information exchange and telehealth/telemonitoring capabilities, and the facility characteristics associated with health information exchange capabilities. A cross-sectional design was implemented. Data were collected from nursing home administrators, using a mail and online survey approach. A total of 156 usable questionnaires were returned of 397 distributed—a 39.30% response rate. The highest level of electronic exchange for clinical functions was within the facility than within corporation/affiliated organization or with nonaffiliated providers. It was also more prevalent in for-profit skilled nursing facilities than nonprofit skilled nursing facilities. More than half of the facilities reported no electronic exchange for functions, such as public health reporting, diagnostic test orders/results, medical orders/e-prescribing, advance directives, lab orders/results, and radiology orders/ results. Similarly, telehealth/telemonitoring was not in wide use by facilities in the state. The greatest barriers to electronic exchange of clinical functions were financial barriers, technological barriers, and connectivity barriers. Faster and accurate billing, improved care planning, and improved quality of documentation were reported as benefits of electronic information exchange of clinical data with affiliated and nonaffiliated providers.
PMID: 26200900 [PubMed - indexed for MEDLINE]
Perspectives of Nurses and Patients on Call Light Technology.
Comput Inform Nurs. 2015 Aug;33(8):359-67
Authors: Galinato J, Montie M, Patak L, Titler M
Call lights are prevalent in inpatient healthcare facilities across the nation. While call light use directly influences the delivery of nursing care, there remain significant gaps both in research and technology that can affect the quality of care and patient satisfaction. This study examines nurse and patient perceptions of the use of a new call communication solution, Eloquence, in the acute care inpatient setting. Eighteen patients were recruited for the study and participated in individual semistructured interviews during their hospital stay. Eighteen nurses were recruited and participated in focus groups for this study. Qualitative descriptive methods were used to analyze the data. Results revealed themes of usability, improved communication, and suggestions for improvement to the alpha prototype design. After a demonstration of the use and capability of Eloquence, nurse and patient participants found Eloquence as a welcomed advancement in nurse call technology that has the potential to improve workflow and patient outcomes. In addition, the participants also proposed ideas on how to further develop the technology to improve its use.
PMID: 26176639 [PubMed - indexed for MEDLINE]
Cognitive Workload of Computerized Nursing Process in Intensive Care Units.
Comput Inform Nurs. 2015 Aug;33(8):339-45; quiz E1
Authors: Dal Sasso GM, Barra DC
The aim of this work was to measure the cognitive workload to complete printed nursing process versus computerized nursing process from International Classification Practice of Nursing in intensive care units. It is a quantitative, before-and-after quasi-experimental design, with a sample of 30 participants. Workload was assessed using National Aeronautics and Space Administration Task-Load Index. Six cognitive categories were measured. The "temporal demand" was the largest contributor to the cognitive workload, and the role of the nursing process in the "performance" category has excelled that of computerized nursing process. It was concluded that computerized nursing process contributes to lower cognitive workload of nurses for being a support system for decision making based on the International Classification Practice of Nursing. The computerized nursing process as a logical structure of the data, information, diagnoses, interventions and results become a reliable option for health improvement of healthcare, because it can enhance nurse safe decision making, with the intent to reduce damage and adverse events to patients in intensive care.
PMID: 26061562 [PubMed - indexed for MEDLINE]
A Novel Approach to Surgical Instructions for Scrub Nurses by Using See-Through-Type Head-Mounted Display.
Comput Inform Nurs. 2015 Aug;33(8):335-8
Authors: Yoshida S, Sasaki A, Sato C, Yamazaki M, Takayasu J, Tanaka N, Okabayashi N, Hirano H, Saito K, Fujii Y, Kihara K
In order to facilitate assists in surgical procedure, it is important for scrub nurses to understand the operation procedure and to share the operation status with attending surgeons. The potential utility of head-mounted display as a new imaging monitor has been proposed in the medical field. This study prospectively evaluated the usefulness of see-through-type head-mounted display as a novel intraoperative instructional tool for scrub nurses. From January to March 2014, scrub nurses who attended gasless laparoendoscopic single-port radical nephrectomy and radical prostatectomy wore the monocular see-through-type head-mounted display (AiRScouter; Brother Industries Ltd, Nagoya, Japan) displaying the instruction of the operation procedure through a crystal panel in front of the eye. Following the operation, the participants completed an anonymous questionnaire, which evaluated the image quality of the head-mounted display, the helpfulness of the head-mounted display to understand the operation procedure, and adverse effects caused by the head-mounted display. Fifteen nurses were eligible for the analysis. The intraoperative use of the head-mounted display could help scrub nurses to understand the surgical procedure and to hand out the instruments for the operation with no major head-mounted-display wear-related adverse event. This novel approach to support scrub nurses will help facilitate technical and nontechnical skills during surgery.
PMID: 26018576 [PubMed - indexed for MEDLINE]
A Multidisciplinary Collaborative Web Site for Cardiovascular Surgery.
Comput Inform Nurs. 2015 Jul;33(7):273-7
Authors: Fredericks S
PMID: 26181305 [PubMed - indexed for MEDLINE]
Nurses' Clinical Decision Making on Adopting a Wound Clinical Decision Support System.
Comput Inform Nurs. 2015 Jul;33(7):295-305
Authors: Khong PC, Hoi SY, Holroyd E, Wang W
Healthcare information technology systems are considered the ideal tool to inculcate evidence-based nursing practices. The wound clinical decision support system was built locally to support nurses to manage pressure ulcer wounds in their daily practice. However, its adoption rate is not optimal. The study's objective was to discover the concepts that informed the RNs' decisions to adopt the wound clinical decision support system as an evidence-based technology in their nursing practice. This was an exploratory, descriptive, and qualitative design using face-to-face interviews, individual interviews, and active participatory observation. A purposive, theoretical sample of 14 RNs was recruited from one of the largest public tertiary hospitals in Singapore after obtaining ethics approval. After consenting, the nurses were interviewed and observed separately. Recruitment stopped when data saturation was reached. All transcribed interview data underwent a concurrent thematic analysis, whereas observational data were content analyzed independently and subsequently triangulated with the interview data. Eight emerging themes were identified, namely, use of the wound clinical decision support system, beliefs in the wound clinical decision support system, influences of the workplace culture, extent of the benefits, professional control over nursing practices, use of knowledge, gut feelings, and emotions (fear, doubt, and frustration). These themes represented the nurses' mental outlook as they made decisions on adopting the wound clinical decision support system in light of the complexities of their roles and workloads. This research has provided insight on the nurses' thoughts regarding their decision to interact with the computer environment in a Singapore context. It captured the nurses' complex thoughts when deciding whether to adopt or reject information technology as they practice in a clinical setting.
PMID: 26066306 [PubMed - indexed for MEDLINE]
Integrating Problem-Based Learning and Simulation: Effects on Student Motivation and Life Skills.
Comput Inform Nurs. 2015 Jul;33(7):278-84
Authors: Roh YS, Kim SS
Previous research has suggested that a teaching strategy integrating problem-based learning and simulation may be superior to traditional lecture. The purpose of this study was to assess learner motivation and life skills before and after taking a course involving problem-based learning and simulation. The design used repeated measures with a convenience sample of 83 second-year nursing students who completed the integrated course. Data from a self-administered questionnaire measuring learner motivation and life skills were collected at pretest, post-problem-based learning, and post-simulation time points. Repeated-measures analysis of variance determined that the mean scores for total learner motivation (F=6.62, P=.003), communication (F=8.27, P<.001), problem solving (F=6.91, P=.001), and self-directed learning (F=4.45, P=.016) differed significantly between time points. Post hoc tests using the Bonferroni correction revealed that total learner motivation and total life skills significantly increased both from pretest to postsimulation and from post-problem-based learning test to postsimulation test. Subscales of learner motivation and life skills, intrinsic goal orientation, self-efficacy for learning and performance, problem-solving skills, and self-directed learning skills significantly increased both from pretest to postsimulation test and from post-problem-based learning test to post-simulation test. The results demonstrate that an integrating problem-based learning and simulation course elicits significant improvement in learner motivation and life skills. Simulation plus problem-based learning is more effective than problem-based learning alone at increasing intrinsic goal orientation, task value, self-efficacy for learning and performance, problem solving, and self-directed learning.
PMID: 26066305 [PubMed - indexed for MEDLINE]
Electronic Personal Health Record Use Among Nurses in the Nursing Informatics Community.
Comput Inform Nurs. 2015 Jul;33(7):306-14
Authors: Gartrell K, Trinkoff AM, Storr CL, Wilson ML
An electronic personal health record is a patient-centric tool that enables patients to securely access, manage, and share their health information with healthcare providers. It is presumed the nursing informatics community would be early adopters of electronic personal health record, yet no studies have been identified that examine the personal adoption of electronic personal health record's for their own healthcare. For this study, we sampled nurse members of the American Medical Informatics Association and the Healthcare Information and Management Systems Society with 183 responding. Multiple logistic regression analysis was used to identify those factors associated with electronic personal health record use. Overall, 72% were electronic personal health record users. Users tended to be older (aged >50 years), be more highly educated (72% master's or doctoral degrees), and hold positions as clinical informatics specialists or chief nursing informatics officers. Those whose healthcare providers used electronic health records were significantly more likely to use electronic personal health records (odds ratio, 5.99; 95% confidence interval, 1.40-25.61). Electronic personal health record users were significantly less concerned about privacy of health information online than nonusers (odds ratio, 0.32; 95% confidence interval, 0.14-0.70) adjusted for ethnicity, race, and practice region. Informatics nurses, with their patient-centered view of technology, are in prime position to influence development of electronic personal health records. Our findings can inform policy efforts to encourage informatics and other professional nursing groups to become leaders and users of electronic personal health record; such use could help them endorse and engage patients to use electronic personal health records. Having champions with expertise in and enthusiasm for the new technology can promote the adoptionof electronic personal health records among healthcare providers as well as their patients.
PMID: 26061563 [PubMed - indexed for MEDLINE]
Adaptation and Evaluation of Online Self-learning Modules to Teach Critical Appraisal and Evidence-Based Practice in Nursing: An International Collaboration.
Comput Inform Nurs. 2015 Jul;33(7):285-94; quiz E1
Authors: Gagnon J, Gagnon MP, Buteau RA, Azizah GM, Jetté S, Lampron A, Simonyan D, Asua J, Reviriego E
Healthcare professionals need to update their knowledge and acquire skills to continually inform their practice based on scientific evidence. This study was designed to evaluate online self-learning modules on critical appraisal skills to promote the use of research in clinical practice among nurses from Quebec (Canada) and the Basque Country (Spain). The teaching material was developed in Quebec and adapted to the Basque Country as part of an international collaboration project. A prospective pre-post study was conducted with 36 nurses from Quebec and 47 from the Basque Country. Assessment comprised the administration of questionnaires before and after the course in order to explore the main intervention outcomes: knowledge acquisition and self-learning readiness. Satisfaction was also measured at the end of the course. Two of the three research hypotheses were confirmed: (1) participants significantly improved their overall knowledge score after the educational intervention; and (2) they were, in general, satisfied with the course, giving it a rating of seven out of 10. Participants also reported a greater readiness for self-directed learning after the course, but this result was not significant in Quebec. The study provides unique knowledge on the cultural adaptation of online self-learning modules for teaching nurses about critical appraisal skills and evidence-based practice.
PMID: 25978538 [PubMed - indexed for MEDLINE]
Nursing Needs Big Data and Big Data Needs Nursing.
J Nurs Scholarsh. 2015 Sep;47(5):477-84
Authors: Brennan PF, Bakken S
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.
PMID: 26287646 [PubMed - indexed for MEDLINE]