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Discover how to develop and implement an HR analytics system that benefits employees, as well as your organization The potential of HR analytics is a major discussion among scholars, practitioners, thought leaders, and technology vendors, with companies like Amazon, Apple, Google, and Meta digging deeply into HR research and analytics practices that extend beyond simple metrics, scorecards, and reporting. Additionally, ethical questions have begun to arise about the potential abuses of HR analytics with respect to technological advancements and the \"datafication\" of personal--and often trivial--characteristics, preferences, and behaviors that have little relevance to job performance. As a former chief human resources officer, head of Global HR Research and Analytics at a Fortune 100, and thought leader on this subject, Salvatore Falletta has witnessed first-hand the emergence of \"creepy analytics\" as a hot-button issue. In this one-of-a-kind guide, Falletta delivers a proven step-by-step process for establishing HR analytics capabilities that serve employees and organizations alike. You'll learn how to rethink and redefine HR analytics, determine stakeholder requirements, gather and transform data, communicate intelligence results, and establish an ethical ecosystem to ensure HR analytics remains a force for good.

Legally mandated nurse-to-patient ratios are one of the most controversial topics in health care today. Ratio advocates believe that minimum staffing levels are essential for quality care, better working conditions, and higher rates of RN recruitment and retention that would alleviate the current global nursing shortage. Opponents claim that ratios will unfairly burden hospital budgets, while reducing management flexibility in addressing patient needs. Safety in Numbersis the first book to examine the arguments for and against ratios. Utilizing survey data, interviews, and other original research, Suzanne Gordon, John Buchanan, and Tanya Bretherton weigh the cost, benefits, and effectiveness of ratios in California and the state of Victoria in Australia, the two places where RN staffing levels have been mandated the longest. They show how hospital cost cutting and layoffs in the 1990s created larger workloads and deteriorating conditions for both nurses and their patients-leading nursing organizations to embrace staffing level regulation. The authors provide an in-depth account of the difficult but ultimately successful campaigns waged by nurses and their allies to win mandated ratios.Safety in Numbersthen reports on how nurses, hospital administrators, and health care policymakers handled ratio implementation. With at least fourteen states in the United States and several other countries now considering staffing level regulation, this balanced assessment of the impact of ratios on patient outcomes and RN job performance and satisfaction could not be timelier. The authors' history and analysis of the nurse-to-patient ratios debate will be welcomed as an invaluable guide for patient advocates, nurses, health care managers, public officials, and anyone else concerned about the quality of patient care in the United States and the world.

Previous research in economics shows that compensation based on the pay-for-performance principle is effective in inducing higher levels of effort and productivity. On the other hand, research in psychology argues that performance-based financial incentives inhibit creativity and innovation. How should managerial compensation be structured if the goal is to induce managers to pursue more innovative business strategies? In a controlled laboratory setting, we provide evidence that the combination of tolerance for early failure and reward for long-term success is effective in motivating innovation. Subjects under such an incentive scheme explore more and are more likely to discover a novel business strategy than subjects under fixed-wage and standard pay-for-performance incentive schemes. We also find evidence that the threat of termination can undermine incentives for innovation, whereas golden parachutes can alleviate these innovation-reducing effects. This paper was accepted by David Hsu, entrepreneurship and innovation.

BackgroundAs fire seasons in the Western US intensify and lengthen, fire managers have been grappling with increases in simultaneous, significant incidents that compete for response resources and strain capacity of the current system.AimsTo address this challenge, we explore a key research question: what precursors are associated with ignitions that evolve into incidents requiring high levels of response personnel?MethodsWe develop statistical models linking human, fire weather and fuels related factors with cumulative and peak personnel deployed.Key resultsOur analysis generates statistically significant models for personnel deployment based on precursors observable at the time and place of ignition.ConclusionsWe find that significant precursors for fire suppression resource deployment are location, fire weather, canopy cover, Wildland–Urban Interface category, and history of past fire. These results align partially with, but are distinct from, results of earlier research modelling expenditures related to suppression which include precursors such as total burned area which become observable only after an incident.ImplicationsUnderstanding factors associated with both the natural system and the human system of decision-making that accompany high deployment fires supports holistic risk management given increasing simultaneity of ignitions and competition for resources for both fuel treatment and wildfire response.

The study aimed to identify the common gaps in skills and self-efficacy for diabetes self-management and explore other factors which serve as enablers of, and barriers to, achieving optimal diabetes self-management. The information gathered could provide health professionals with valuable insights to achieving better health outcomes with self-management education and support for diabetes patients. International online survey and telephone interviews were conducted on adults who have type 1 or type 2 diabetes. The survey inquired about their skills and self-efficacy in diabetes self-management, while the interviews assessed other enablers of, and barriers to, diabetes self-management. Surveys were analysed using descriptive and inferential statistics. Interviews were analysed using inductive thematic analysis. Survey participants (N = 217) had type 1 diabetes (38.2%) or type 2 diabetes (61.8%), with a mean age of 44.56 SD 11.51 and were from 4 continents (Europe, Australia, Asia, America). Identified gaps in diabetes self-management skills included the ability to: recognize and manage the impact of stress on diabetes, exercise planning to avoid hypoglycemia and interpreting blood glucose pattern levels. Self-efficacy for healthy coping with stress and adjusting medications or food intake to reach ideal blood glucose levels were minimal. Sixteen participants were interviewed. Common enablers of diabetes self-management included: (i) the will to prevent the development of diabetes complications and (ii) the use of technological devices. Issues regarding: (i) frustration due to dynamic and chronic nature of diabetes (ii) financial constraints (iii) unrealistic expectations and (iv) work and environment-related factors limited patients' effective self-management of diabetes. Educational reinforcement using technological devices such as mobile application has been highlighted as an enabler of diabetes self-management and it could be employed as an intervention to alleviate identified gaps in diabetes self-management. Furthermore, improved approaches that address financial burden, work and environment-related factors as well as diabetes distress are essential for enhancing diabetes self-management.

Controlling for unobserved heterogeneity (or \"common errors\"), such as industry-specific shocks, is a fundamental challenge in empirical research. This paper discusses the limitations of two approaches widely used in corporate finance and asset pricing research: demeaning the dependent variable with respect to the group (e.g., \"industry-adjusting\") and adding the mean of the group's dependent variable as a control. We show that these methods produce inconsistent estimates and can distort inference. In contrast, the fixed effects estimator is consistent and should be used instead. We also explain how to estimate the fixed effects model when traditional methods are computationally infeasible.

Inadequate management of healthcare waste present significant health hazards to healthcare workers, patients, waste handlers, and the whole communities, especially in developing countries. Although various primary studies have been conducted in different countries across the continent, there has been no comprehensive research examining healthcare waste management practices in Sub-Saharan Africa. This review aimed to assess healthcare waste management practices and associated factors among healthcare workers in Sub-Saharan Africa. This systematic review and meta-analysis were performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA 20) guidelines. PubMed, Science-Direct, Google Scholar, Hinari, and Google databases were used to find essential literature. The extracted data were analyzed using statistical software, STATA version 14. Publication bias was assessed using the Egger test and funnel plot, whereas heterogeneity was assessed using the I2 statistic. This review include 29 studies comprising 7588 participants. The pooled estimate of good healthcare waste management practices among participants was 49.74% (95% CI: 43.73-55.76) (I2 = 96.8%, P < 0.000). Sex, knowledge, training on healthcare waste management, use of working manuals/guidelines, and working hours were factors significantly associated with healthcare waste management practices among healthcare workers., Studies done in South Africa reported the highest good healthcare waste management practices with a value of 54.34% (95% CI: 48.05, 60.63), I2 = 0.00%, P < 0.00. The pooled estimate of good healthcare waste management practices before the occurrences of COVID-19 pandemic was 50.49% (95% CI: 40.7, 60.25), (I2 = 97.9%, P < 0.000). Public health facilities also reported having lower waste management practices with a value of 46.86% (95%CI: 39.33, 54.38%), I2 = 96.8%, P < 0.000. This review showed that only half of the healthcare workers practiced good healthcare waste management practices. Sex of the healthcare workers, training status, use of working manuals/guidelines, knowledge towards healthcare waste management, and their daily working hours were factors significantly associated with healthcare waste management practices among healthcare workers. Hence, respective healthcare authorities should develop and implement different healthcare waste management strategies, including ongoing in-service training, provision of healthcare waste management manuals, and conducting regular monitoring to enhance healthcare workers' knowledge and practices towards healthcare waste management practices.

Decisions about health care, such as the effectiveness of new treatments for disease, are regularly made based on evidence from published work. However, poor reporting of statistical methods and results is endemic across health research and risks ineffective or harmful treatments being used in clinical practice. Statistical modelling choices often greatly influence the results. Authors do not always provide enough information to evaluate and repeat their methods, making interpreting results difficult. Our research is designed to understand current reporting practices and inform efforts to educate researchers. Reporting practices for linear regression were assessed in 95 randomly sampled published papers in the health field from PLOS ONE in 2019, which were randomly allocated to statisticians for post-publication review. The prevalence of reporting practices is described using frequencies, percentages, and Wilson 95% confidence intervals. While 92% of authors reported p-values and 81% reported regression coefficients, only 58% of papers reported a measure of uncertainty, such as confidence intervals or standard errors. Sixty-nine percent of authors did not discuss the scientific importance of estimates, and only 23% directly interpreted the size of coefficients. Our results indicate that statistical methods and results were often poorly reported without sufficient detail to reproduce them. To improve statistical quality and direct health funding to effective treatments, we recommend that statisticians be involved in the research cycle, from study design to post-peer review. The research environment is an ecosystem, and future interventions addressing poor statistical quality should consider the interactions between the individuals, organisations and policy environments. Practical recommendations include journals producing templates with standardised reporting and using interactive checklists to improve reporting practices. Investments in research maintenance and quality control are required to assess and implement these recommendations to improve the quality of health research.

Patient safety is an essential component of healthcare quality. Despite enormous advances in medical knowledge, many adverse events continue to endanger patient safety. Although mixed-method studies are necessary to gain a deeper understanding of safety culture, few studies provide practical evidence of patient safety culture and associated factors in Ethiopia. This study aimed to assess patient safety culture and associated factors among healthcare professionals in public hospitals in Bahir Dar City, Northwest Ethiopia. A cross-sectional study design was employed, in triangulation with qualitative methodologies, from March 10 to April 10, 2022. A stratified sampling technique was used to select 420 study participants from three public hospitals. A standardized tool measuring 12 patient safety culture composites was used for data collection. Purposive sampling was employed in the qualitative study. Bi-variable and multivariable linear regression analyses were performed using SPSS version 23, with significance set at a 95% confidence interval and a p-value of <0.05. Content analysis was utilized in the qualitative study. The overall patient safety culture score was 47.6% (95% CI: 42.7, 52.5). Age (β = 1.196, 95% CI: (0.968, 1.322), patient safety training (β = 0.168, 95% CI: 0.040, 0.297), working in pediatric wards (β = 0.236, 95% CI: 0.099, 0.370), and resource availability (β = 0.346, 95% CI: 0.220, 0.473) were significantly associated with patient safety culture. The in-depth interviews identified infrastructure, communication barriers, lack of management support, poor governance, healthcare professionals' knowledge, skills, and attitudes, and patient involvement during treatment as factors affecting patient safety. This study concludes that the patient safety culture in the studied hospitals is suboptimal, falling below the acceptable threshold. Enhancing resource availability, providing continuous patient safety training, improving communication systems, and fostering a supportive management environment are essential steps towards building a safer healthcare system.

Philosophers, psychologists, and economists have long argued that certain decision rights carry not only instrumental value but may also be valuable for their own sake. The ideas of autonomy, freedom, and liberty derive their intuitive appeal—at least partly—from an assumed positive intrinsic value of decision rights. Providing clean evidence for the existence of this intrinsic value and measuring its size, however, is intricate. Here, we develop a method capable of achieving these goals. The data reveal that the large majority of our subjects intrinsically value decision rights beyond their instrumental benefit. The intrinsic valuation of decision rights has potentially important consequences for corporate governance, human resource management, and optimal job design: it may explain why managers value power, why employees appreciate jobs with task discretion, why individuals sort into self-employment, and why the reallocation of decision rights is often very difficult and cumbersome. Our method and results may also prove useful in developing an empirical revealed preference foundation for concepts such as \"freedom of choice\" and \"individual autonomy.\"