Technology has permeated every facet of both nursing knowledge and practice, from implantable patient devices such as pacemakers to the use of machine learning and artificial intelligence in our record systems and patient monitoring. Technology has become our “wise third eye,” overseeing critical components of patient care. Dualism of human and machine as a cyborg ontology was originally described by Haraway in the mid-1980s. Her work has been revisited by nursing theorists who acknowledge the radical and progressive path in nursing science whereby technology is part of humanness as evidenced by use of life-supporting machines that suspend human nature in favor of biotechnologically centered care (Teixeira de Almeida Vieira Montiero, 2015; Lapum et al., 2012). Both philosophically and in practice, technology, and human can no longer be separated. Using medical device spending as a marker, the United States spends upwards of 173 billion dollars per year on healthcare machines. This measure has noted an increase of 6% each year, further emphasizing that our reliance on machines and thus its presence in nursing practice is here to stay.
The nursing metaparadigm, as described by Fawcett in 1984, includes human, health, nursing, and environment. Each of these constructs are used to support theory development by giving direction as to our focus as a scientific body. Nursing scientists have influenced informatics in the forms of biotechnological applications, mobile health, and more granularly with human-technology interface. Despite this advancement of informatics as a nursing science and obvious teathering of technology and humanness, technology has yet to appear within the nursing metaparadigm. Here we propose that to remain consistent with patient-centered care in the age where machine is enmeshed in daily human life, technology must be a component of the metaparadigm. This is both philosophically sound, logical, and necessary to continue advancing nursing science and knowledge. Through technology’s incorporation within the metapharadigm, we challenge nurses to consider approaches within their research and practice as to how technology will not only impact patient care but their personal development within the profession. Incorporation of technology within the metaparadigm signals to other bodies of science our willingness and ability to run at-pace with the novel, exciting new discoveries while adding the nursing perspective. Nurses become active agents in novel developments rather than passive adopters, continuing our legacy of patient advocacy through new knowledge generation.
Learning Outcome: After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and evaluate the potential of implementing the improvements into practice.
Working with our digital health team, an application was developed to use in Microsoft Teams to assist clinicians to conserve PPE/reduce risk of exposure to COVID and still have communication between care team, patients, and families.
The applications that were developed with the digital health team allowed us to place an iPad in the patient’s room and use Microsoft Teams to communicate with the patient from outside the room using audio and video functionality. These applications for clinicians could be used on mobile devices, laptops, or desktop computers. These applications also allowed us to invite family/guests to join in the session to see and hear their loved ones as well as communicate with the clinicians.
We were already using Microsoft Teams to call the patient to communicate via iPads. However, patients were not always tech savvy to answer the call and turn the camera on. Our main task with the digital health team was developing an application that was more user-friendly for patients. The application developed allowed the session once joined on iPad to always remain open/active so the patient did not have to do anything. We created the application so that we could invite families/guests to the sessions/meetings as well. The application had to be pushed out to all the devices. In order to do this push, we had to collect all iPad and mobile device names and passwords. We had to determine which clinicians would use the applications and push to their Microsoft accounts. This was the most intensive task we had to do to make this successful. Once the applications were pushed to the devices it was just a matter of educating end users and patients on how to use the applications.
We were able to see the use of the applications increase and new use cases. On our pilot unit, we did see increase in patient satisfaction scores. Composite patient satisfaction score on the pilot unit increased 4 points. The rating of our hospital on the patient satisfaction score increased by 32 points. Nurse communication score increased by 7 points. We are finalizing the data on PPE cost/conservation for this project. We did get positive feedback from clinicians and families. Application spread through our system.
The applications were easier for patients to manage. We were able to stay connected with patients and their families while also conserving PPE and reducing risk of exposure. This created a safe atmosphere for patients and clinicians during a time of a lot of uncertainty.
Learning Outcome: After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and evaluate the potential of implementing the improvements into practice.
Nurse practitioners’ informatics competencies are not well-understood. Limited evidence alludes to the potential need to improve the informatics competencies of nurse practitioners. The primary purpose of this study was to analyze the informatics competencies of nurse practitioners, including nurses training to become nurse practitioners, before and after completing an online learning module in nursing informatics. Six topics were covered in the investigator-developed learning module. A pre-test/post-test, one-group, quasi-experimental design was used in the study. Link to the study was emailed to members of a local nurse practitioners’ association in California and graduate nursing students at a public university in Missouri. The study was also shared on a professional networking website, LinkedIn. Data were collected from 15 nurse practitioners and two nurse practitioner students, using a demographic questionnaire and an 18-item self-assessment of informatics competency scale. A related-samples sign test was conducted to compare the pre-test and post-test scores. Statistically significant median increases (p = 0.001 to xtagstartz 0.001) were found in five areas. Findings suggest that the online learning module expanded the participants’ competencies in specific areas of informatics. The results also provide an initial understanding of nurse practitioners’ informatics competencies and inform future iterations of the study.
Introduction: Chronic absenteeism (CA) is an administrative term defining extreme failure for students to be present in school. In Minnesota, CA is defined as missing more than 10% of school days in a year. Absenteeism is a national problem that has devastating long-term impacts for students, such as adult substance abuse and poor physical and mental health after graduation. The impact of partial-day absences (PDAs) on student outcomes is less studied, due to diverse policies at the local school district level. However, PDA is much more prevalent than full-day absence (FDA). Leveraging the growing availability of big data, this study applies data-driven research methods to the examination of factors associated with both partial and full-day absences.
Objective: Applying causal discovery analysis techniques to student-level data, this study analyzes the interconnectivity of PDA and FDA by comparing their related factors. Specific student-reported factors were included in the analysis based on components of Bronfenbrenner’s bioecological model of development, which explains children’s development by the environments they are embedded in multiple levels..
Methods: Using TETRAD, a causal discovery analysis (machine-learning method) was conducted on de-identified student-level data (N= 93,329) from the 2016 Minnesota Student Survey. Causal discovery analysis is a data-driven research method that analyzes associations between variables, including the direction of connectivity or pathways between variables when possible.
Results: The analysis produced a model in which both PDA and FDA were linked to student substance use. The study also found disparities between FDA and PDA in their effects and linked factors including the pathways that lead to substance use, parent and adult support and physical condition. For example, PDA was associated with students’ school engagement and relationships with teachers, which wasn’t for FDA. The incomplete list of factors included in the analysis due to restricted computational capacity caused the model to show only the association but not the causal relations which limits the usage of study’s results.
Conclusions: Results suggest that both types of absence ultimately lead to student’s substance use, which highlights PDA’s similarity with FDA. However, PDA was associated with student’s engagement with school or teacher, whereas FDA was related with in-school suspension or students being sent to the office. The similarity of outcomes to students with differences of what they’re associated with calls a need for further study in PDA especially when it’s being inconsistently used in the field of CA. For the important next step, a validation is needed from an expert who is playing an important role in the health of students – which is school nurse. Therefore, next study aims to implement a focus interview to school nurses and acquire better perspective from such experts. The results of both studies will help children who suffer from CA by having a better understanding of the importance of PDA from the perspective of nursing and data science.
Learning Outcome: After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and evaluate the potential of implementing the improvements into practice.
Despite the history of nursing's contributions in helping patients, systems, and facilities achieve high-quality care, nursing-sensitive outcomes have been difficult to quantify. Without a mechanism to enable the selection of data describing nurses' roles as individuals, it is challenging for nurses and nurse leaders to find tangible evidence of patient care provision to demonstrate the impact of nursing care on patient outcomes. The Nursing Knowledge Big Data Science conference and Policy and Advocacy Workgroup convened in 2013 to advance a national action plan to ensure nursing data capture in a sharable and comparable format. This workgroup has identified several workstreams for prioritized focus, including developing health IT policy for the best use of nurse-sensitive data. This poster will highlight the workgroup's efforts over the last seven years to advance the use of a unique nurse identifier. This session will also provide foundational information about the vital role a unique nurse identifier plays in measuring the impact and value of nursing practice and its contribution to improving patient outcomes. Nursing's contribution to individuals' and communities' health and care is difficult to measure and often invisible. This lack of visibility is due, in part, to the absence of a unique identifier for nurses. The Nursing Knowledge: Big Data Policy and Advocacy workgroup has identified the standardized use of a national nurse identifier as a critical element, important to the underlying infrastructure of sharable and comparable nursing data. Without a unique nurse identifier, data aggregation, and data use to improve nursing practice are not possible. Nurses can use documentation to measure their contributions to improvements in individual and population health outcomes, patient safety, operational efficiency, and clinical effectiveness. Nurse leaders have identified the need for a unique nurse identifier, without which the aggregation and use of data to improve nursing practice is not possible. Hospitals and health systems need to uniquely identify nurses in the EHR, enterprise resource planning (ERP) systems, and other technologies and health IT systems for documentation, education, research training, and quality improvement purposes. The Nursing Knowledge: Big Data Science Policy and Advocacy Workgroup is collaborating with key stakeholders to achieve an optimal solution, such as using a unique nurse identifier to demonstrate the value of nursing. This poster session will help learners understand what a unique nurse identifier is. It will also explain why using a unique nurse identifier is essential as the content outlines the benefits and implications of adopting an identifier and policy recommendations.
Learning Outcome: After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and evaluate the potential of implementing the improvements into practice.