Promoting data harmonization to evaluate vaccine hesitancy in LMICs: approach and applications.

BACKGROUND: Factors influencing the health of populations are subjects of interdisciplinary study. However, datasets relevant to public health often lack interdisciplinary breath. It is difficult to combine data on health outcomes with datasets on potentially important contextual factors, like political violence or development, due to incompatible levels of geographic support; differing data formats and structures; differences in sampling procedures and wording; and the stability of temporal trends. We present a computational package to combine spatially misaligned datasets, and provide an illustrative analysis of multi-dimensional factors in health outcomes. METHODS: We rely on a new software toolkit, Sub-National Geospatial Data Archive (SUNGEO), to combine data across disciplinary domains and demonstrate a use case on vaccine hesitancy in Low and Middle-Income Countries (LMICs). We use data from the World Bank's High Frequency Phone Surveys (HFPS) from Kenya, Indonesia, and Malawi. We curate and combine these surveys with data on political violence, elections, economic development, and other contextual factors, using SUNGEO. We then develop a stochastic model to analyze the integrated data and evaluate 1) the stability of vaccination preferences in all three countries over time, and 2) the association between local contextual factors and vaccination preferences. RESULTS: In all three countries, vaccine-acceptance is more persistent than vaccine-hesitancy from round to round: the long-run probability of staying vaccine-acceptant (hesitant) was 0.96 (0.65) in Indonesia, 0.89 (0.21) in Kenya, and 0.76 (0.40) in Malawi. However, vaccine acceptance was significantly less durable in areas exposed to political violence, with percentage point differences (ppd) in vaccine acceptance of -10 (Indonesia), -5 (Kenya), and -64 (Malawi). In Indonesia and Kenya, although not Malawi, vaccine acceptance was also significantly less durable in locations without competitive elections (-19 and -6 ppd, respectively) and in locations with more limited transportation infrastructure (-11 and -8 ppd). CONCLUSION: With SUNGEO, researchers can combine spatially misaligned and incompatible datasets. As an illustrative example, we find that vaccination hesitancy is correlated with political violence, electoral uncompetitiveness and limited access to public goods, consistent with past results that vaccination hesitancy is associated with government distrust.

Is Hospital Nurse Staffing Legislation in the Public's Interest?: An Observational Study in New York State.

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.

A guide for social science journal editors on easing into open science.

Journal 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 ).

Chronic hospital nurse understaffing meets COVID-19: an observational study.

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.

How Collaborative Practice Agreements Impede the Administration of Vital Women's Health Services.

INTRODUCTION: Women's health services delivered by nurse practitioners (NP) and certified nurse-midwives (CNM) are safe and effective, often providing a crucial point of access in underserved regions. However, restrictive and unnecessary regulatory requirements, such as collaborative practice agreements, create artificial barriers to practice. METHODS: This analysis used a subsample of respondents from a large national study focused on the common challenges and practice restrictions introduced by collaborative practice agreements. This cohort included respondents licensed in all 22 states that place some level of restriction on one or both roles. This study used univariable and multivariable logistic regression to examine the financial and administrative constraints collaborative practice agreements place on NPs and CNMs. RESULTS: The median fee to establish a collaborative agreement was $500 (n = 25; interquartile range [IQR], $175-$1200; range, $30-$3000). The monthly median fee to maintain a collaborative agreement was $500 (n = 29; IQR, $250-$1200; range, $100-$2000). NPs and CNMs working in rural areas and remotely are more likely to encounter barriers to practice. Similarly, the loss or lack of supervising physicians and fees were also identified as impediments to care. DISCUSSION: Removing unnecessary regulatory requirements permits NPs and CNMs to be full market participants, thereby allowing them to address health care disparities in women's health and primary care settings. Targeted legislative efforts should seek to improve access to these vital services and re-establish evidence-based patient care and safety best practices as the drivers of health care regulation.