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Control charts are designed to be effective in detecting a shift in the distribution of a process. Typically, these charts assume that the data for these processes follow an approximately normal distribution or some known distribution. However, if a data-generating process has a large proportion of zeros, that is, the data is intermittent, then traditional control charts may not adequately monitor these processes. The purpose of this study is to examine proposed control chart methods designed for monitoring a process with intermittent data to determine if they have a sufficiently small percentage of false out-of-control signals. Forecasting techniques for slow-moving/intermittent product demand have been extensively explored as intermittent data is common to operational management applications (Syntetos & Boylan, 2001, 2005, 2011; Willemain, Smart, & Schwarz, 2004). Extensions and modifications of traditional forecasting models have been proposed to model intermittent or slow-moving demand, including the associated trends, correlated demand, seasonality and other characteristics (Altay, Litteral, & Rudisill, 2012). Croston’s (1972) method and its adaptations have been among the principal procedures used in these applications. This paper proposes adapting Croston’s methodology to design control charts, similar to Exponentially Weighted Moving Average (EWMA) control charts, to be effective in monitoring processes with intermittent data. A simulation study is conducted to assess the performance of these proposed control charts by evaluating their Average Run Lengths (ARLs), or equivalently, their percent of false positive signals.

Companies are nowadays called to manage increasingly larger and more complex quantities of data. Making good predictions and estimating a possible risky situation in advance is therefore more important than ever. The statistical tools are a key element to support quality management and production process analyses, allowing managers to anticipate, in various ways, the situations that will arise. After a general introduction to statistics, this chapter discusses the main statistical techniques used to describe, visualize, and analyze data, with particular attention to the methods that allow to verify the quality and consistency of the conclusions (i.e., confidence intervals and hypothesis verification). Finally, some advanced and widespread quality management statistical tools are presented: quality control charts, historical series, and stochastic control.

Adverse events in health care became more evident at the beginning of the 21st century, being an emerging problem worldwide and impacting the lives of people receiving health care, contributing to preventable injuries and deaths. This evidence has motivated the development of specific training in the area of patient safety with a strong focus on the education and training of health professionals, and, more recently, it also aimed at patient, informal caregiver and all citizens. In this sense, the use of digital technology for patient safety training has been an important challenge and proves to be a good solution for training and continuous learning, both for professionals and people in general. The use of multimedia, videos, games, simulators, among others, are effectively essential resources to improve people’s health literacy and safety of care.

This chapter presents a narrative review on patient safety training and the contributions of digital technology. The experience report will also be used, presenting some examples of quality improvement projects developed by Portuguese and Brazilian entities, in training contexts, highlighting the importance of investing in the health literacy of professionals, patients/informal caregivers and civil society, through applying specific techniques and using digital technology.

Storytelling helps clarify the concealed or less visible elements of reality in its authentic context. Story analysis read between the lines of written or oral narratives to obtain richer understanding of an event. However, storytelling practice is a double-edge sword. Skilled storytellers may employ the power of storytelling to reframe an event in a favorable or undesirable way.

In contemporary business world, corporations broadly employ expert authors who proficiently apply storytelling practices in corporate public documents. Accordingly, corporate public documents declare desirable corporate image and promising reflection of business activities hence the corporate attracts more stockholders and obtains extra resources.

In current business world, corporates that do not appropriately employ storytelling would fail to take the opportunity to brainwash stockholders, hence suffer from competitive disadvantage.

This case study analyses Sears Holdings Corporation public report to explore how its business activities are revealed to public stakeholders. This study also proposes hypotheses of the consequences of ineffective storytelling.

W.E.B. DuBois, in his 1903 collection of writings entitled The Souls of Black Folk, describes what he calls “The Veil,” which succinctly sums up the deadly and adverse experiences of African Americans in the US. With DuBois contemplations of a Veil under which US Blacks alone live and die as context, this paper takes a look at the modern condition of African Americans in the US, whether they continue to exist within DuBois Veil in modern times (twentieth and twenty-first centuries), and if so, to what extent. As a routine examination and inspection of the condition of Blacks in the US, focus is placed on black lives lost, beginning with an appraisal of their size in the US population overtime, and in comparison with other racial and ethnic groups in the US. US census data, health data collected from the Centers for Disease Control and Prevention, and crime data collected from the Federal Bureau of Investigation are examined to construct a composite of the condition of contemporary Blacks in the US as compared to other groups in the US, focusing attention specifically on the rates at which their lives are lost compared to others through infant mortality, low fertility rates, abortion, and high rates of homicide. This analysis concludes with a look at death from homicide before, during, and after the post-1990s drop in the crime rate.

Inappropriate cardiac monitoring leads to increased hospital resource utilization and alarm fatigue, which is ultimately detrimental to patient safety. Our institution implemented a continuous cardiac monitoring (CCM) policy that focused on selective monitoring for patients based on the American Heart Association (AHA) guidelines. The primary goal of this study was to perform a three-year median follow-up review on the longitudinal impact of a selective CCM policy on usage rates, length of stay (LOS), and mortality rates across the medical center. A secondary goal was to determine the effect of smaller-scale interventions focused on reeducating the nursing population on the importance of cardiac alarms.

A system-wide policy was developed at The Ohio State University in December 2013 based on guidelines for selective CCM in all patient populations. Patients were stratified into Critical Class I, II, and III with 72 hours, 48 hours, or 36 hours of CCM, respectively. Pre- and post-implementation measures included average cardiac monitoring days (CMD), emergency department (ED) boarding rate, mortality rates, and LOS. A 12-week evaluation period was analyzed prior to, directly after, and three years after implementation.

There was an overall decrease of 53.5% CMDs directly after implementation of selective CCM. This had remained stable at the three-year follow-up with slight increase of 0.5% (p = 0.2764). Subsequent analysis by hospital type revealed that the largest and most stable reductions in CMD were in noncardiac hospitals. The cardiac hospital CMD reduction was stable for roughly one year, then dipped into a lower stable level for nine months, then returned to the previous post-implementation levels. This change coincided with a smaller intervention to further reduce CMD in the cardiac hospital. There was no significant change in mortality rates with a slight decrease of 3.1% at follow-up (p = 0.781). Furthermore, there was no significant difference in LOS with a slight increase of 1.1% on follow-up (p = 0.649). However, there was a significant increase in ED boarding rate of 7.7% (p < 0.001) likely due to other hospital factors altering boarding times.

Implementing selective CCM decreases average cardiac monitoring rate without affecting LOS or overall mortality rate. Selective cardiac monitoring is also a sustainable way to decrease overall hospital resource utilization and more appropriately focus on patient care.