Interprofessional Staffing Pattern Clusters in U.S. ICUs.

OBJECTIVES: To identify interprofessional staffing pattern clusters used in U.S. ICUs. DESIGN: Latent class analysis. SETTING AND PARTICIPANTS: Adult U.S. ICUs. PATIENTS: None. INTERVENTIONS: None. ANALYSIS: We used data from a staffing survey that queried respondents (n = 596 ICUs) on provider (intensivist and nonintensivist), nursing, respiratory therapist, and clinical pharmacist availability and roles. We used latent class analysis to identify clusters describing interprofessional staffing patterns and then compared ICU and hospital characteristics across clusters. MEASUREMENTS AND MAIN RESULTS: We identified three clusters as optimal. Most ICUs (54.2%) were in cluster 1 ("higher overall staffing") characterized by a higher likelihood of good provider coverage (both intensivist [onsite 24 hr/d] and nonintensivist [orders placed by ICU team exclusively, presence of advanced practice providers, and physicians-in-training]), nursing leadership (presence of charge nurse, nurse educators, and managers), and bedside nursing support (nurses with registered nursing degrees, fewer patients per nurse, and nursing aide availability). One-third (33.7%) were in cluster 2 ("lower intensivist coverage & nursing leadership, higher bedside nursing support") and 12.1% were in cluster 3 ("higher provider coverage & nursing leadership, lower bedside nursing support"). Clinical pharmacists were more common in cluster 1 (99.4%), but present in greater than 85% of all ICUs; respiratory therapists were nearly universal. Cluster 1 ICUs were larger (median 20 beds vs. 15 and 17 in clusters 2 and 3, respectively; p < 0.001), and in larger (> 250 beds: 80.6% vs. 66.1% and 48.5%; p < 0.001), not-for-profit (75.9% vs. 69.4% and 60.3%; p < 0.001) hospitals. Telemedicine use 24 hr/d was more common in cluster 3 units (71.8% vs. 11.7% and 14.1%; p < 0.001). CONCLUSIONS: More than half of U.S. ICUs had higher staffing overall. Others tended to have either higher provider presence and nursing leadership or higher bedside nursing support, but not both.

Hospital Nurse Staffing Legislation: Mixed Approaches In Some States, While Others Have No Requirements.

Legislative agendas aimed at regulating nurse staffing in US hospitals have intensified after acute workforce disruptions triggered by COVID-19. Emerging evidence consistently demonstrates the benefits of higher nurse staffing levels, although uncertainty remains regarding whether and which legislative approaches can achieve this outcome. The purpose of this study was to provide a comprehensive updated review of hospital nurse staffing requirements across all fifty states. As of January 2024, seven states had laws pertaining to staffing ratios for at least one hospital unit, including California and Oregon, which had ratios pertaining to multiple units. Eight states required nurse staffing committees, of which six specified a percentage of committee members who must be registered nurses. Eleven states required nurse staffing plans. Five states had pending legislation, and one state, Idaho, had passed legislation banning minimum nurse staffing requirements. The variety of state regulations provides an opportunity for comparative evaluations of efficacy and feasibility to inform new legislation on the horizon.

Intelligent Clinic Nurse Scheduling Considering Nurses Paired with Doctors and Preference of Nurses.

The nurse scheduling problem (NSP) has been a crucial and challenging research issue for hospitals, especially considering the serious deterioration in nursing shortages in recent years owing to long working hours, considerable work pressure, and irregular lifestyle, which are important in the service industry. This study investigates the NSP that aims to maximize nurse satisfaction with the generated schedule subject to government laws, internal regulations of hospitals, doctor-nurse pairing rules, shift and day off preferences of nurses, etc. The computational experiment results show that our proposed hybrid metaheuristic outperforms other metaheuristics and manual scheduling in terms of both computation time and solution quality. The presented solution procedure is implemented in a real-world clinic, which is used as a case study. The developed scheduling technique reduced the time spent on scheduling by 93% and increased the satisfaction of the schedule by 21%, which further enhanced the operating efficiency and service quality.

Staffing Models: Making Increased Acuity Safe in the Pediatric ICU.

Traditional staffing models rely on the productivity metric of hours per patient day, lacking the ability to adequately capture the nursing workload. Acuity-based staffing considers the patient population's acuity for appropriate nursing workload. Using process improvement methodology, a pediatric ICU transitioned to an acuity-based staffing model resulting in an 11.3% ( P < 0.05) reduction in the acuity per nursing assignment and a decrease in reportable safety events by 61.3% ( P < 0.05).

Legislating Nurse Staffing: Projected Impact on Hospital Economics, Process Flow, and Hospital-Associated Infections in Montana.

OBJECTIVE: The aim of this study was to project the impact of legislated nurse staffing ratios on patient-, staff-, and system-level outcomes for Prospective Payment System (PPS) hospitals in Montana. BACKGROUND: In 2023, House Bill 568 was introduced in Montana focused on legislating hospital safe nursing standards. METHODS: A quantitative design was used for a convenience sample of Montana PPS hospitals. Data were gathered through a newly developed survey and from other publicly available sources for the years 2018 to 2022. Independent t tests were conducted when appropriate with the significance threshold set at 0.05. RESULTS: Projections indicate no significant change in patient outcome metrics accompanied by increases in labor requirements, slower emergency department throughput times, and decreases in hospital operating margins. CONCLUSIONS: In Montana, legislating nurse staffing ratios would have downstream implications inconsistent with the intended impact on patient safety, emphasizing the complexity of variables within and external to the healthcare system that drive patient-, staff-, and system-level outcomes.

The Evolution of Board-Certified Emergency Physicians and Staffing of Emergency Departments in Israel.

Introduction: Emergency medicine (EM) was recognized as a specialty in Israel in 1999. Fifty-nine of the 234 (25%) attending physicians working in emergency departments (ED) nationwide in 2002 were board-certified emergency physicians (EP). A 2012 study revealed that 123/270 (45%) of ED attendings were EPs, and that there were 71 EM residents. The EPs primarily worked midweek morning shifts, leaving the EDs mostly staffed by other specialties. Our objective in this study was to re-evaluate the EP workforce in Israeli EDs and their employment status and satisfaction 10 years after the last study, which was conducted in 2012. Methods: We performed a three-part, prospective cross-sectional study: 1) a survey, sent to all EDs in Israel, to assess the numbers, level of training, and specialties of physicians working in EDs; 2) an anonymous questionnaire, sent to EPs in Israel, to assess their demographics, training, employment, and work satisfaction; and 3) interviews of a convenience sample of EPs analyzed by a thematic approach. Results: There were 266 board-certified EPs, 141 (53%) of whom were employed in EDs full-time or part-time. Sixty-two non-EPs also worked in EDs. The EPs were present in the EDs primarily during weekday morning shifts. There were 273 EM residents nationwide. A total of 101 questionnaires were completed and revealed that EPs working part-time in the ED worked fewer hours, received higher salaries, and had more years of experience compared to EPs working full time or not working in the ED. Satisfaction correlated only with working part time. Meaningful work, diversity, and rewarding relationships with patients and colleagues were major positive reasons for working in the ED. Feeling undervalued, carrying a heavy caseload, and having complicated relationships with other hospital departments were reasons against working in the ED. Conclusion: Our study findings showed an increase in the number of trained and in-training EPs, and a decrease in the percentage of board-certified EPs who persevere in the EDs. Emergency medicine in Israel is at a crossroads: more physicians are choosing EM than a decade ago, but retention of board-certified EPs is a major concern, as it is worldwide. We recommend taking measures to maintain trained and experienced EPs working in the ED by allowing part-time ED positions, introducing dedicated academic time, and diversifying EP roles, functioning, and work routine.

The Impact of Changing From a 6+2 to a 3+1 Residency Block Schedule on Patient Access and Other Outcomes.

Background The "X+Y" residency scheduling model includes "X" weeks of uninterrupted inpatient or subspecialty rotations, followed by "Y" week(s) of uninterrupted outpatient rotations. The optimal ratio of X to Y is unclear. Objective Determine the impact of moving from a 6+2 to a 3+1 schedule on patient access to care, perceived quality of care, and resident/faculty satisfaction. Methods Our residency program switched from a 6+2 to a 3+1 scheduling model in July 2018. We measured access to care before and after the change using the "third next available" (TNA) metric. In June 2019, we administered a voluntary, anonymous, 20-item survey to residents, staff, and faculty who worked in resident clinic in both the 6+2 and 3+1 years. Results Patient access to appointments with their resident physician, as measured by TNA, improved significantly after the schedule change (mean 34.1 days in 6+2, mean 26.5 days in 3+1, P<.0001). Fifteen of 17 (88%) eligible residents and 13 of 24 (54%) faculty/staff filled out the voluntary anonymous survey. Surveyed residents and faculty/staff had concordant perception that the schedule change led to improvement in patient continuity, quality of care, and ability of residents to follow up on diagnostic tests and have regular interaction with clinic attendings. However, residents did not report a change in satisfaction with continuity clinic. Conclusions Changing from a 6+2 to a 3+1 schedule was associated with improvement in patient access to care. Residents and faculty/staff perceived that this schedule change improved several aspects of patient care.

Associations of the staffing structure of intensive care units and high care units on in-hospital mortality among patients with sepsis: a cross-sectional study of Japanese nationwide claims data.

OBJECTIVE: The objective was to analyse the associations of intensive care unit (ICU) and high care unit (HCU) organisational structure on in-hospital mortality among patients with sepsis in Japan's acute care hospitals. DESIGN: Multicentre cross-sectional study. SETTINGS: Patients with sepsis aged ≥18 years who received critical care in acute care hospitals throughout Japan between April 2018 and March 2019 were identified using the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB). INTERVENTIONS: None. PARTICIPANTS: 10 968 patients with sepsis were identified. ICUs were categorised into three groups: type 1 ICUs (fulfilling stringent staffing criteria such as experienced intensivists and high nurse-to-patient ratios), type 2 ICUs (less stringent criteria) and HCUs (least stringent criteria). PRIMARY OUTCOME MEASURE: The study's primary outcome measure was in-hospital mortality. Cox proportional hazards regression analysis was performed to examine the impact of ICU/HCU groups on in-hospital mortality. RESULTS: We analysed 2411 patients (178 hospitals) in the type 1 ICU group, 3653 patients (422 hospitals) in the type 2 ICU group and 4904 patients (521 hospitals) in the HCU group. When compared with the type 1 ICU group, the adjusted HRs for in-hospital mortality were 1.12 (95% CI 1.04 to 1.21) for the type 2 ICU group and 1.17 (95% CI 1.08 to 1.26) for the HCU group. CONCLUSION: ICUs that fulfil more stringent staffing criteria were associated with lower in-hospital mortality among patients with sepsis than HCUs. Differences in organisational structure may have an association with outcomes in patients with sepsis, and this was observed by the NDB.

The Art of Delegation.

The nurse staffing crisis requires nurses and administrators to think differently about how to get things done. Delegation is key to doing more work with fewer registered nurses (RNs) and retaining current RN staff. Responsibility for effective delegation does not rest solely with the RN but begins with the institution, and includes both the delegator and delegatee. While effective delegation has often been referred to as an art, knowing the science behind delegation can aid in honing a skill necessary for top of license practice.

Staff Management with AI: Predicting the Nursing Workload.

The effective management of human resources in nursing fundamental to ensuring high-quality care. The necessary staffing levels can beis derived from the nursing-related health status. Our approach is based on the use of artificial intelligence (AI) and machine learning (ML) to recognize key workload-driving predictors from routine clinical data in the first step and derive recommendations for staffing levels in the second step. The study was a multi-center study with data provided by three hospitals. The SPI (Self Care Index = sum score of 10 functional/cognitive items of the epaAC) was identified as a strong predictor of nursing workload. The SPI alone explains the variance in workload minutes with an adjusted R2 of 40% to 66%. With the addition of further predictors such as "fatigue" or "pain intensity", the adjusted R2 can be increased by up to 17%. The resulting model can be used as a foundation for data-based personnel controlling using AI-based prediction models.

Supporting and Retaining Nurses in Trying Times.

The nursing profession has witnessed its share of challenging and trying times including toxic or unhealthy work environments, unsustainable workloads, an aging workforce, inadequate staffing, nurse burnout, staff retention, inadequately trained staff, an increase in workplace violence, and several pandemics. Both individually and collectively, these thorny issues have placed a heavy burden on nurses. Unfortunately, many capable and competent nurses have left the profession altogether, which further compounds an already problematic situation. This article highlights several important strategies for recruiting, retaining, and supporting a high functioning nursing workforce in challenging and trying times.

The Case for Alternative Payment Models for Nursing Care.

A policy solution to improve staffing and patient care.

Impact of changes in anaesthesia staff assignments on billing compliance, financial margins, and costs of anaesthesia services: development and application of a margin-cost estimation tool.

BACKGROUND: The US Centers for Medicare and Medicaid Services provide guidelines for the coverage of anaesthesia residents and certified registered nurse anaesthetists (CRNAs) by anaesthesiologists. We tested the hypothesis that changes in the anaesthesia staffing model increase billing compliance. METHODS: We analysed 13 926 anaesthesia cases performed between September 2019 and November 2019 (baseline), and between September 2020 and November 2020 (after change in staff model) at a US academic medical centre using an estimation tool. The intervention was assignment of additional 12-h weekday CRNAs plus an additional anaesthesiologist who covered weekdays after 17:00, weekends, and holidays. The proportion of cases with billing compliant coverage (covered either by solo anaesthesiologist or anaesthesiologist covering two or fewer residents or four or fewer CRNAs) was analysed using logistic and segmented regression analyses. RESULTS: The change in staff model was associated with a decrease in non-optimal anaesthesia staff assignments from 4.2% to 1.2% of anaesthesia cases (adjusted odds ratio 0.25; 95% confidence interval [CI] 0.20-0.32; P<0.001) and an increase in billable anaesthesia units of 0.6 per anaesthesia case (95% CI 0.4-0.8; P<0.001). An increased revenue margin associated with optimal staffing levels would only be achieved with salary levels at the 25th percentile of relevant benchmark compensation levels. Total staff overtime for all anaesthesia providers decreased (adjusted absolute difference -4.1 total overtime hours per day; 95% CI -7.0 to -1.3; P=0.004). CONCLUSIONS: Implementation of a change in anaesthesia staffing model was associated with improved billing compliance, higher billable anaesthesia units, and reduced overtime. The effects of the anaesthesia staff model on revenue and financial margin can be determined using our web-based margin-cost estimation tool.

Hospital personnel perspectives on factors influencing acute care patient outcomes: a qualitative approach to model refinement.

BACKGROUND: Health systems have long been interested in the best practices for staffing in the acute care setting. Studies on staffing often focus on registered nurses and nurse-to-patient staffing ratios. There were fewer studies on the relationship between interprofessional team members or contextual factors such as hospital and community characteristics and patient outcomes. This qualitative study aimed to refine an explanatory model by soliciting hospital personnel feedback on staffing and patient outcomes. METHODS: We conducted a qualitative study using semi-structured interviews and thematic analysis to understand hospital personnel's perspectives and experiences of factors that affect acute care inpatient outcomes. Interviews were conducted in 2022 with 38 hospital personnel representing 19 hospitals across Washington state in the United States of America. RESULTS: Findings support a model of characteristics impacting patient outcomes to include the complex and interconnected relationships between community, hospital, patient, and staffing characteristics. Within the model, patient characteristics were positioned into hospital characteristics, and in turn these were positioned within community characteristics to highlight the importance of setting and context when evaluating outcomes. Together, these factors influenced both staff characteristics and patient outcomes, but these two categories also share a direct relationship. CONCLUSION: Findings can be applied to hospitals and health systems in a variety of contexts to examine how external factors such as community resource availability impact care delivery. Future research should expand on this work with specific attention to how staffing changes and interprofessional team composition can improve patient outcomes.

Alternative Models of Nurse Staffing May Be Dangerous in High-Stakes Hospital Care.

BACKGROUND: Hospitals are resurrecting the outdated "team nursing" model of staffing that substitutes lower-wage staff for registered nurses (RNs). OBJECTIVES: To evaluate whether reducing the proportion of RNs to total nursing staff in hospitals is in the best interest of patients, hospitals, and payers. RESEARCH DESIGN: Cross-sectional, retrospective. SUBJECTS: In all, 6,559,704 Medicare patients in 2676 general acute-care US hospitals in 2019. MEASURES: Patient outcomes: in-hospital and 30-day mortality, 30-day readmission, length of stay, and patient satisfaction. Avoidable Medicare costs associated with readmissions and cost savings to hospitals associated with shorter stays are projected. RESULTS: A 10 percentage-point reduction in RNs was associated with 7% higher odds of in-hospital death, 1% higher odds of readmission, 2% increase in expected days, and lower patient satisfaction. We estimate a 10 percentage-point reduction in RNs would result in 10,947 avoidable deaths annually and 5207 avoidable readmissions, which translates into roughly $68.5 million in additional Medicare costs. Hospitals would forgo nearly $3 billion in cost savings annually because of patients requiring longer stays. CONCLUSIONS: Reducing the proportion of RNs in hospitals, even when total nursing personnel hours are kept the same, is likely to result in significant avoidable patient deaths, readmissions, longer lengths of stay, and decreased patient satisfaction, in addition to excess Medicare costs and forgone cost savings to hospitals. Estimates represent only a 10 percentage-point dilution in skill mix; however, the team nursing model includes much larger reductions of 40-50 percentage-points-the human and economic consequences of which could be substantial.