Dear Colleagues,

The current fast-changing global, socio-economic, medical, and political scenarios pose unprecedented challenges for nursing practice and science. It ought to be self-evident to say how critical it is to invest in the rapid acceleration of nursing education: investments should sustain the development of new careers and opportunities in nursing education, including faculty and professors, infrastructure, educational methods, and students, to meet domestic and global demands of well-educated nurses. In this scenario, it is imperative to strengthen nurse leadership among current and aspiring leaders to ensure that nurses play a significant role in the development and implementation of health policy and decision-making processes, as well as contribute to the effectiveness of the health and social care systems to face the challenges of non-communicable disease and universal health coverage.

This Special Issue of Healthcare aims to connect the “dots” of research, education, workforce, and regulation to transform nursing practice and leadership toward a new era of integrated healthcare. Aspects related to research, education, workforce, and regulations are required to be connected, understood, and studied to unlock the full potential that the nursing profession can bring to the broad healthcare arena by allowing the utilization of new technologies and developing integrated health and social care models. In this Special Issue, we welcome empirical, clinical, and review research and perspective papers focusing on nursing research, education, workforce, regulation, and leadership to uncover the potential of nursing practice and science in meeting domestic demands and global healthcare needs.

Dr. Rosario Caruso
Dr. Arianna Magon
Dr. Irene Baroni
Dr. Alessandro Stievano
Guest Editors

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• nursing-led research
• nursing workforce
• nursing leadership
• nursing education
• nursing regulation
• nursing ethics
• digital health and ehealth
• non-communicable disease
• cutting edge methodologies
• nursing policy
• healthcare models

Title: Empowering the Next Generation to Lead Change through Quality Improvement
Authors: Dolansky, M. A. 1; Lawlor, M. A.; Mitchell, R.; Sfiligoj, R.; Sweetko, J.
Affiliation: 1. Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH USA
Abstract: The complex and dynamic healthcare environment demands continual improvement to reach the quintuple aim that ensures better health, improved outcomes, lower costs, health equity, and clinician well-being. Nurses are positioned to take the lead and have QI competencies including systems-based practice, problem-solving, and teamwork. Ensuring the next generation of nurses are competent and prepared to lead change needs to start in undergraduate education and is supported by the American Association of Colleges of Nursing 2021 Essentials. Using iterative cycles of development, an undergraduate leadership course was established and student outcomes were evaluated. Students completed the Institute for Healthcare Improvement QI modules and participated in applying the principles in an outpatient setting. The QI project was guided by clinical faculty, organizational preceptors, and weekly worksheets. The final project consisted of a poster presentation of the students' QI projects. A pre-post measurement of the Quality Improvement Knowledge Application Tool (QIKAT) demonstrated a significant increase in QI knowledge (t)=12, -2.62, p=0.01. The QI leadership experience in an undergraduate nursing program was feasible and the experience had a positive impact on outpatient clinics’ outcomes and on students’ quality improvement knowledge and application skills.

Title: Pain in preterm before and after Physical Therapy modalities in a neonatal intensive care unit in Amazonas/Brazil: Prospective longitudinal Study
Author: Lopes
Highlights: •Physical Therapy modalities do not cause pain and stress in newborns in the neonatal intensive care unit. •Physiotherapists participate in pain and stress control in neonatal intensive care units. •Facilitated Tucking it was the non-pharmacological measure most used by Physiotherapists in the NICU studied to control pain and stress.

Title: Do Diagnosis-Related Groups and staffing allocations systems reflect actual needs of nursing care? An observational cross-sectional study
Authors: Diletta Fabrizi 1, Davide Bernasconi 2, Giulia Locatelli 3*, Michela Luciani 4, Giorgio Beretta 5, Stefania Di Mauro 6, Paola Rebora 7, and Davide Ausili 8
Affiliation: 1 University of Milano - Bicocca, Department of Medicine and Surgery; diletta.fabrizi@unimib.it 2 University of Milano - Bicocca , Department of Medicine and Surgery; davide.bernasconi@unimib.it 3 University of Milano - Bicocca , Department of Medicine and Surgery; giulia.locatelli@unimib.it 4 University of Milano - Bicocca , Department of Medicine and Surgery; michela.luciani@unimib.it 5 Azienda Socio Sanitaria Territoriale di Lecco, Direzione Aziendale delle Professioni Sanitarie e Sociosanitarie; g.beretta@asst-lecco.it 6 University of Milano - Bicocca , Department of Medicine and Surgery; stefania.dimauro@unimib.it 7 University of Milano - Bicocca , Department of Medicine and Surgery; paola.rebora@unimib.it 8 University of Milano - Bicocca , Department of Medicine and Surgery; davide.ausili@unimib.it * University of Milano - Bicocca , Department of Medicine and Surgery Correspondence: giulia.locatelli@unimib.it
Abstract: In Italy, diagnosis-related groups (DRGs) are used for reimbursing hospital services. Additionally, nurse staffing is determined by the type of ward rather than the nursing care needs. The Information System of Nursing Performance (SIPI) is a valid and reliable tool to assess nursing care complexity as an indicator of the actual demand for nursing care. This study aims to evaluate the association between nursing care complexity and both DRGs and nurse staffing allocation. All patients dis-charged from the acute medical department of the involved center during data collection were in-cluded. To assess the association between SIPI and DRGs, the median DRG rate was compared for cases with high (≥50) and low (<50) complexity. To evaluate the association between SIPI and nurse staffing, the frequency of high complexity within nurse staffing categories was compared. 6872 hospitalizations were included. The median DRG rate for admissions with high and low complexity were very similar (3536 and 3285€, respectively). The proportion of admissions with high com-plexity decreased with increasing staffing categories. The DRG reimbursement system and the nurse staffing allocation criterion were ineffective in providing coherent resources for higher complexity nursing care. The use of SIPI could help identify areas requiring more financial and staffing re-sources for nursing care.

Title: Delirium assessment in hospitalized elderly patients: estima-tion of sensitivity and specificity of the Recognizing Acute De-lirium As part of your Routine Scale
Authors: Diletta Fabrizi 1, Paola Rebora 2, Valentina Spedale 3,*, Giulia Locatelli 4, Giuseppe Bellelli 5, Stefania Di Mauro 6, Davide Ausili 7 and Michela Luciani 8
Affiliation: 1 University of Milano - Bicocca, Department of Medicine and Surgery; diletta.fabrizi@unimib.it 2 University of Milano - Bicocca, Department of Medicine and Surgery; paola.rebora@unimib.it 3 University of Milano - Bicocca, Department of Medicine and Surgery; valentina.spedale@unimib.it 4 University of Milano - Bicocca, Department of Medicine and Surgery; giulia.locatelli@unimib.it 5 University of Milano - Bicocca, Department of Medicine and Surgery; giuseppe.bellelli@unimib.it 6 University of Milano - Bicocca, Department of Medicine and Surgery; stefania.dimauro@unimib.it 7 University of Milano - Bicocca, Department of Medicine and Surgery; davide.ausili@unimib.it 8 University of Milano - Bicocca, Department of Medicine and Surgery; michela.luciani@unimib.it * University of Milano - Bicocca, Department of Medicine and Surgery Correspondence: valentina.spedale@unimib.it
Abstract: Delirium has a high prevalence among the hospitalized elderly and leads to unfavorable clinical outcomes. However, delirium often remains undiagnosed in hospitals. The Confusion Assessment Method (CAM), the most widespread tool to diagnose delirium, is complex and time-consuming. Having a valid, simpler, and faster screening tool could help diagnosing delirium without over-burdening healthcare professionals. Therefore, the aim of this study was to estimate the sensitivity and specificity of the Recognizing Acute Delirium As part of your Routine (RADAR) scale in Italy. We enrolled 150 patients aged ≥70. Receiver operating characteristic (ROC) curves using CAM criterion-defined delirium as gold standard were plotted to evaluate performance of the RADAR. The cut-off score suggested by previous research was used to estimate sensitivity, specificity, posi-tive and negative predictive values of the RADAR. Patients were mostly females (60%; n=90), with a median age of 84 years (I-III quartiles: 8088). According to the CAM and the RADAR, 37 (25%) and 58 (39%) patients were classified with delirium, respectively. The area under the RADAR ROC curve was 0.916. Furthermore, the RADAR showed robust sensitivity, specificity, and predictive values. The RADAR seems to be a valid tool for screening delirium in the hospitalized elderly.