Technology Solutions for Nurse Leaders.

Over the next 10 years, the World Health Organization estimates that there will be global shortage of 18 000 000 health care workers. A perfect storm of an aging demographic, long-term drop in birth rate, and a retiring workforce has all the factors contributing to this impending crisis. In nursing, efforts to narrow the shortage gap through strategies that increase the number of admissions to nursing schools, such as increasing faculty members, clinical sites, preceptors, and scholarships, will likely not be enough to offset the shortfall. Solutions, in part, will be to make nurses more productive by reducing waste through the use of technology. This article evaluates how various types of technology such as electronic health records, data analytics, predictive modeling, artificial intelligence, speech recognition, natural language processing, robotics, the Internet of Things, and others can improve nurse productivity by using a Lean framework to eliminate waste and create value.

Artificial Intelligence and Nursing: The Future Is Now.

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. Since writing my 1st article for Managing Organizational Complexity in 2004, much has happened to further our understanding of complexity in healthcare systems. The growth of new computational methods in the fields of data science and data analytics has allowed scientists to identify signals or patterns in large complex data sets (big data) that in the past were seemingly hidden. Rather than relying on historical statistical methods to infer outcomes, these advanced methods combined with increased computer processing power allow machines to learn the structure of data and create artificial intelligence (AI). In our ongoing efforts to find solutions for complex healthcare problems, AI is becoming more and more an accepted method. The purpose of this edition of Managing Organizational Complexity is to define AI and machine learning, discuss the recent resurgence of AI, and then provide examples of how AI can provide value to healthcare with an emphasis on nursing.

Influence of Patient Characteristics and Psychological Needs on Diabetes Mobile App Usability in Adults With Type 1 or Type 2 Diabetes: Crossover Randomized Trial.

BACKGROUND: More than 1100 diabetes mobile apps are available, but app usage by patients is low. App usability may be influenced by patient factors such as age, sex, and psychological needs. OBJECTIVE: Guided by Self-Determination Theory, the purposes of this study were to (1) assess the effect of patient characteristics on app usability, and (2) determine whether patient characteristics and psychological needs (competence, autonomy, and connectivity)-important for motivation in diabetes care-are associated with app usability. METHODS: Using a crossover randomized design, 92 adults with type 1 or 2 diabetes tested two Android apps (mySugr and OnTrack) for seven tasks including data entry, blood glucose (BG) reporting, and data sharing. We used multivariable linear regression models to examine associations between patient characteristics, psychological needs, user satisfaction, and user performance (task time, success, and accuracy). RESULTS: Participants had a mean age of 54 (range 19-74) years, and were predominantly white (62%, 57/92), female (59%, 54/92), with type 2 diabetes (70%, 64/92), and had education beyond high school (67%, 61/92). Participants rated an overall user satisfaction score of 62 (SD 18), which is considered marginally acceptable. The satisfaction mean score for each app was 55 (SD 18) for mySugr and 68 (SD 15) for OnTrack. The mean task completion time for all seven tasks was 7 minutes, with a mean task success of 82% and an accuracy rate of 68%. Higher user satisfaction was observed for patients with less education (P=.04) and those reporting more competence (P=.02), autonomy (P=.006), or connectivity with a health care provider (P=.03). User performance was associated with age, sex, education, diabetes duration, and autonomy. Older patients required more time (95% CI 1.1-3.2) and had less successful task completion (95% CI 3.5-14.3%). Men needed more time (P=.01) and more technical support than women (P=.04). High school education or less was associated with lower task success (P=.003). Diabetes duration of ≥10 years was associated with lower task accuracy (P=.02). Patients who desired greater autonomy and were interested in learning their patterns of BG and carbohydrates had greater task success (P=.049). CONCLUSIONS: Diabetes app usability was associated with psychological needs that are important for motivation. To enhance patient motivation to use diabetes apps for self-management, clinicians should address competence, autonomy, and connectivity by teaching BG pattern recognition and lifestyle planning, customizing BG targets, and reviewing home-monitored data via email. App usability could be improved for older male users and those with less education and greater diabetes duration by tailoring app training and providing ongoing technical support.

Why Cities Survive and Companies Die.

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This article is the 5th in a series of articles that focuses on why technological complexity is increasing and strategies nurse administrators can use to successfully implement change in the face of it.

Technological Complexity and Emergence of the Entanglement.

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This article is the 3rd in a series of articles that focus on why technological complexity is increasing and strategies nurse administrators can use to successfully implement change in the face of it.

How Information Drives Complexity.

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. This article is the 2nd in a series of articles that focuses on why technological complexity is increasing and strategies nurse administrators can use to successfully implement change in the face of it.

Technological Complexity: Have We Reached a Tipping Point?

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This article focuses on why technological complexity is increasing and strategies nurse administrators can use to successfully implement change in the face of it.

Big Data Cohort Extraction to Facilitate Machine Learning to Improve Statin Treatment.

Health care Big Data studies hold substantial promise for improving clinical practice. Among analytic tools, machine learning (ML) is an important approach that has been widely used by many industries for data-driven decision support. In Big Data, thousands of variables and millions of patient records are commonly encountered, but most data elements cannot be directly used to support decision making. Although many feature-selection tools can help identify relevant data, these tools are typically insufficient to determine a patient data cohort to support learning. Therefore, domain experts with nursing or clinic knowledge play critical roles in determining value criteria or the type of variables that should be included in the patient cohort to maximize project success. We demonstrate this process by extracting a patient cohort (37,506 individuals) to support our ML work (i.e., the production of a proactive strategy to prevent statin adverse events) from 130 million de-identified lives in the OptumLabs™ Data Warehouse.

Big Data, Big Challenges: Implications for Chief Nurse Executives.

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. In this edition, I begin a series of articles on the growing challenge faced by nurse administrators of finding value in the vast amounts of information collected by health systems today.

Accountability of Nursing Interventions vs. Severity of Illness Scores for the Hospital Care Cost Of Total Hip Replacement.

The main purpose of this study was to investigate the extent to which nursing care compared to severity of illness (SOI) accounted for direct hospital costs. The type, frequency, and duration of nursing interventions required for patients undergoing total hip replacement surgery by the SOI stages with independent t-tests were identified. Although patients in Stage 3 generally needed a greater amount of each intervention than patients in Stage 2, the differences in needs for nursing interventions were not consistent using SOI. With hierarchical multiple regression analyses, results indicated nursing interventions explained significantly more variability in hospital care costs than SOI scores. Relying only on SOI scores for reimbursement may not accurately reflect the resource consumption of health care.

Nursing Knowledge: Big Data Science-Implications for Nurse Leaders.

The integration of Big Data from electronic health records and other information systems within and across health care enterprises provides an opportunity to develop actionable predictive models that can increase the confidence of nursing leaders' decisions to improve patient outcomes and safety and control costs. As health care shifts to the community, mobile health applications add to the Big Data available. There is an evolving national action plan that includes nursing data in Big Data science, spearheaded by the University of Minnesota School of Nursing. For the past 3 years, diverse stakeholders from practice, industry, education, research, and professional organizations have collaborated through the "Nursing Knowledge: Big Data Science" conferences to create and act on recommendations for inclusion of nursing data, integrated with patient-generated, interprofessional, and contextual data. It is critical for nursing leaders to understand the value of Big Data science and the ways to standardize data and workflow processes to take advantage of newer cutting edge analytics to support analytic methods to control costs and improve patient quality and safety.

Complexity, flow, and antifragile healthcare systems: implications for nurse executives.

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. In this article, I further discuss the concept of fragility, its impact on system behavior, and ways to reduce it.

It's all about flow in a complex adaptive system.

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. In this article, I discuss the Constructal Law and its impact on nurse workflow.

Ward warriors: the complex nature of nurse mobility.

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. In this article, the authors discuss the impact of complex system behavior on nurse workflow and its broader implications.

Complexity and change in nurse workflows.

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 20th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, the authors discuss how nurse workflow is characteristic of complex adaptive systems and the need for caution when selecting a performance improvement method.

Improving processes through evolutionary optimization.

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies on complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 18th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, I discuss methods to optimize complex healthcare processes through learning, adaptation, and evolutionary planning.

Staying afloat in a sea of digital waves.

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 17th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, Dr Clancy further discusses the similarity in complex system behavior observed between the financial markets and healthcare systems.