Suchergebnisse

INTRODUCTION: Efforts to enact nurse staffing legislation often lack timely, local evidence about how specific policies could directly impact the public's health. Despite numerous studies indicating better staffing is associated with more favourable patient outcomes, only one US state (California) sets patient-to-nurse staffing standards. To inform staffing legislation actively under consideration in two other US states (New York, Illinois), we sought to determine whether staffing varies across hospitals and the consequences for patient outcomes. Coincidentally, data collection occurred just prior to the COVID-19 outbreak; thus, these data also provide a real-time example of the public health implications of chronic hospital nurse understaffing. METHODS: Survey data from nurses and patients in 254 hospitals in New York and Illinois between December 2019 and February 2020 document associations of nurse staffing with care quality, patient experiences and nurse burnout. RESULTS: Mean staffing in medical-surgical units varied from 3.3 to 9.7 patients per nurse, with the worst mean staffing in New York City. Over half the nurses in both states experienced high burnout. Half gave their hospitals unfavourable safety grades and two-thirds would not definitely recommend their hospitals. One-third of patients rated their hospitals less than excellent and would not definitely recommend it to others. After adjusting for confounding factors, each additional patient per nurse increased odds of nurses and per cent of patients giving unfavourable reports; ORs ranged from 1.15 to 1.52 for nurses on medical-surgical units and from 1.32 to 3.63 for nurses on intensive care units. CONCLUSIONS: Hospital nurses were burned out and working in understaffed conditions in the weeks prior to the first wave of COVID-19 cases, posing risks to the public's health. Such risks could be addressed by safe nurse staffing policies currently under consideration.

BACKGROUND: The Safe Staffing for Quality Care Act under consideration in the New York (NY) state assembly would require hospitals to staff enough nurses to safely care for patients. The impact of regulated minimum patient-to-nurse staffing ratios in acute care hospitals in NY is unknown. OBJECTIVES: To examine variation in patient-to-nurse staffing in NY hospitals and its association with adverse outcomes (ie, mortality and avoidable costs). RESEARCH DESIGN: Cross-sectional data on nurse staffing in 116 acute care general hospitals in NY are linked with Medicare claims data. SUBJECTS: A total of 417,861 Medicare medical and surgical patients. MEASURES: Patient-to-nurse staffing is the primary predictor variable. Outcomes include in-hospital mortality, length of stay, 30-day readmission, and estimated costs using Medicare-specific cost-to-charge ratios. RESULTS: Hospital staffing ranged from 4.3 to 10.5 patients per nurse (P/N), and averaged 6.3 P/N. After adjusting for potential confounders each additional patient per nurse, for surgical and medical patients, respectively, was associated with higher odds of in-hospital mortality [odds ratio (OR)=1.13, P=0.0262; OR=1.13, P=0.0019], longer lengths of stay (incidence rate ratio=1.09, P=0.0008; incidence rate ratio=1.05, P=0.0023), and higher odds of 30-day readmission (OR=1.08, P=0.0002; OR=1.06, P=0.0003). Were hospitals staffed at the 4:1 P/N ratio proposed in the legislation, we conservatively estimated 4370 lives saved and $720 million saved over the 2-year study period in shorter lengths of stay and avoided readmissions. CONCLUSIONS: Patient-to-nurse staffing varies substantially across NY hospitals and higher ratios adversely affect patients. Our estimates of potential lives and costs saved substantially underestimate potential benefits of improved hospital nurse staffing.

AbstractJournal editors have a large amount of power to advance open science in their respective fields by incentivising and mandating open policies and practices at their journals. The Data PASS Journal Editors Discussion Interface (JEDI, an online community for social science journal editors:www.dpjedi.org) has collated several resources on embedding open science in journal editing (www.dpjedi.org/resources). However, it can be overwhelming as an editor new to open science practices to know where to start. For this reason, we created a guide for journal editors on how to get started with open science. The guide outlines steps that editors can take to implement open policies and practices within their journal, and goes through the what, why, how, and worries of each policy and practice. This manuscript introduces and summarizes the guide (full guide:https://doi.org/10.31219/osf.io/hstcx).