Getting to the Heart of the Matter Evaluation Report: Post-Acute Cardiac Rehabilitation Program to Reduce Hospital Readmissions

Launched in 2013, this innovative program was designed to help cardiac patients achieve success with their post-acute treatment regime, something that is especially important for older cardiac patients who are at an increased risk for complications. By "bridging the gap" between when patients are discharged from acute care until they are ready to start outpatient cardiac rehabilitation, the program aims to improve the quality of care and quality of life for older adults recovering from congestive heart failure, myocardial infarction, bypass surgery, and other heart diseases and reduce hospital readmissions

A Review of Best Practices for Monitoring and Improving Inpatient Pediatric Patient Experiences.

ContextAchieving high-quality patient-centered care requires assessing patient and family experiences to identify opportunities for improvement. With the Child Hospital Consumer Assessment of Healthcare Providers and Systems Survey, hospitals can assess performance and make national comparisons of inpatient pediatric experiences. However, using patient and family experience data to improve care remains a challenge.ObjectiveWe reviewed the literature on best practices for monitoring performance and undertaking activities aimed at improving pediatric patient and family experiences of inpatient care.Data sourcesWe searched PubMed, Cumulative Index to Nursing and Allied Health Literature, and PsychINFO.Study selectionWe included (1) English-language peer-reviewed articles published from January 2000 to April 2019; (2) articles based in the United States, United Kingdom, or Canada; (3) articles focused on pediatric inpatient care; (4) articles describing pediatric patient and family experiences; and (5) articles including content on activities aimed at improving patient and family experiences. Our review included 25 articles.Data extractionTwo researchers reviewed the full article and abstracted specific information: country, study aims, setting, design, methods, results, Quality Improvement (QI) initiatives performed, internal reporting description, best practices, lessons learned, barriers, facilitators and study implications for clinical practice, patient-experience data collection, and QI activities. We noted themes across samples and care settings.ResultsWe identified 10 themes of best practice. The 4 most common were (1) use evidence-based approaches, (2) maintain an internal system that communicates information and performance on patient and family experiences to staff and hospital leadership, (3) use experience survey data to initiate and/or evaluate QI interventions, and (4) identify optimal times (eg, discharge) and modes (eg, print) for obtaining patient and family feedback. These correspond to adult inpatient best practices.ConclusionsBoth pediatric and adult inpatient best practices rely on common principles of culture change (such as evidence-based clinical practice), collaborative learning, multidisciplinary teamwork, and building and/or supporting a QI infrastructure that requires time, money, collaboration, data tracking, and monitoring. QI best practices in both pediatric and adult inpatient settings commonly rely on identifying drivers of overall ratings of care, rewarding staff for successful implementation, and creating easy-to-use and easy-to-access planning and QI tools for staff

Choosing the Right Consultant

The church in North America is in decline. Research indicates that many churches are not growing or even considered “healthy.” More and more churches are addressing their declining attendance through hiring consultants to identify areas of growth and improvement. The key is finding the right consultant or consulting firm for the needs of the local church. This article seeks to help the local church ask the right questions when selecting a consultant or consulting firm

Choosing the Right Consultant

The church in North America is in decline. Research indicates that many churches are not growing or even considered “healthy.” More and more churches are addressing their declining attendance through hiring consultants to identify areas of growth and improvement. The key is finding the right consultant or consulting firm for the needs of the local church. This article seeks to help the local church ask the right questions when selecting a consultant or consulting firm

COVID‐19 Preparedness in Nursing Homes in the Midst of the Pandemic

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155887/1/jgs16520.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155887/2/jgs16520_am.pd

Quantifying the benefit of structural health monitoring: can the value of information be negative?

The benefit of Structural Health Monitoring (SHM) can be properly quantified using the concept of Value of Information (VoI), which is, applied to an SHM case, the difference between the utilities of operating the structure with and without the monitoring system. The aim of this contribution is to demonstrate that, in a decision-making process where two different individuals are involved in the decision chain, i.e. the owner and the manager of the structure, the VoI can be negative. Indeed, even if the two decision makers are both rational and exposed to the same background information, their optimal actions can diverge after the installation of the monitoring system due to their different appetite for risk: this scenario could generate a negative VoI, which corresponds exactly to the amount of money the owner is willing to pay to prevent the manager using the monitoring system. In this paper, starting from a literature review about how to quantify the VoI, a mathematical formulation is proposed which allows one to assess when and under which specific conditions, e.g. appropriate combination of prior information and utility functions, the VoI becomes negative. Moreover, to illustrate how this framework works, a hypothetical VoI is evaluated for the Streicker Bridge, a pedestrian bridge on the Princeton University campus equipped with a fiber optic sensing system: the results show how the predominant factor that determines a negative VoI is the different risk appetite of the two decision makers, owner and manager

Consequences of representativeness bias on SHM-based decision-making

Judging the state of a bridge based on SHM observations is an inference process, which should be rationally carried out using a logical approach. However, it is often observed that real-life decision makers depart from this ideal model of rationality, judge and decide using common sense, and privilege fast and frugal heuristics to rational analytic thinking. For instance, confusion between condition state and safety of a bridge is one of the most frequently observed examples in bridge management. The aim of this paper is to describe mathematically this observed biased judgement, a condition that is broadly described by Kahneman and Tversky’s representativeness heuristic. Particularly, the paper examines how this heuristic affects the interpretation of data, providing a deeper understanding of the differences between a method affected by cognitive biases and the classical rational approach. Based on the literature review, three different models reproducing an individual behaviour distorted by representativeness are identified. These models are applied to the case of a transportation manager who wrongly judges a particular bridge unsafe simply because deteriorated, regardless its actual residual load-carrying capacity. It is demonstrated that the application of any of the three heuristic judgment models correctly predicts that the manager will mistakenly judge the bridge as unsafe based on the observed condition state. It is not objective of the paper to suggest that representativeness should be used instead of rational logic, however, understanding how real-life managers actually behave is of paramount importance when setting a general policy for bridge maintenance

Quantifying the benefit of SHM: can the VoI be negative?

The benefit of Structural Health Monitoring (SHM) can be properly quantified using the concept of Value of Information (VoI), i.e. the difference between the utilities of operating the structure with and without the monitoring system. In calculating the VoI, a commonly understood assumption is that all decisions concerning system installation and operation are taken by the same rational agent. In the real world, the individual who decides on buying a monitoring system, the owner, is often not the same individual, the manager, who will use it, and they may behave differently because of their different risk aversion. We demonstrate that in a decision-making process where the two individuals involved share exactly the same information, but behave differently, the VoI can be negative. Indeed, even if the two agents have an agreement a priori, due to their different behaviors, their optimal actions can diverge after the installation of the monitoring system. This scenario could generate a negative Vol from the owners perspective. In this work, we propose a qualitative and quantitative formulation to evaluate when and under which circumstances the VoI can be negative, if the owner differs from the manager with respect to their risk prioritization. Moreover, we apply this formulation on a real-life case study concerning the Streicker Bridge (Princeton, NJ). The results demonstrate that when the owner, because of the managers different behaviour, is forced to undertake an action he would not chose, his VoI becomes negative, i.e. it is not convenient for him to install the monitoring system. This framework aims to help the owner in quantifying the money saved by entrusting the evaluation of the state of the structure to the monitoring system, even if the managers behavior toward risk is different from the owners own, and so are his management decisions

How heuristic behaviour can affect SHM-based decision problems?

psychologists call these differences cognitive biases. Many heuristic behaviors have been studied and demonstrated, with applications in various fields such as psychology, cognitive science, economics and finance, but not yet to SHM-based decision problems. SHM-based decision making is particularly susceptible to the representativeness heuristic, where simplified rules for updating probabilities can distort the decision makers perception of risk. In this work, we examine how this heuristic affects the interpretation of data, providing a deeper understanding of the differences between a heuristic method affected by cognitive biases and the classical approach. Our study is conducted both theoretically through comparison with formal Bayesian methods as well as empirically through the application to a real-life case study in the field of civil engineering. With this application we demonstrate the heuristic framework and we show how this cognitive bias affects decision-making by distorting the representation of information provided by SHM.The main purpose of structural health monitoring (SHM) is to provide accurate and real-time information about the state of a structure, which can be used as objective inputs for decision-making regarding its management. However, SHM and decision-making occur at various stages. SHM assesses the state of a structure based on the acquisition and interpretation of data, which is usually provided by sensors. Conversely, decision-making helps us to identify the optimal management action to undertake. Generally, the research community recognizes people tend to use irrational methods for their interpretation of monitoring data, instead of rational algorithms such as Bayesian inference. People use heuristics as efficient rules to simplify complex problems and overcome the limits in rationality and computation of the human brain. Even though the results are typically satisfactory, they can differ from results derived from a rational proces

IWSHM 2017 : Quantifying the benefit of structural health monitoring : what if the manager is not the owner?

Only very recently our community has acknowledged that the benefit of structural health monitoring can be properly quantified using the concept of value of information (VoI). The VoI is the difference between the utilities of operating the structure with and without the monitoring system. Typically, it is assumed that there is one decision-maker for all decisions, that is, deciding on both the investment on the monitoring system and the operation of the structure. The aim of this work is to formalize a rational method for quantifying the value of information when two different actors are involved in the decision chain: the manager, who makes decisions regarding the structure, based on monitoring data; and the owner, who chooses whether to install the monitoring system or not, before having access to these data. The two decision-makers, even if both rational and exposed to the same background information, may still act differently because of their different appetites for risk. To illustrate how this framework works, we evaluate a hypothetical VoI for the Streicker Bridge, a pedestrian bridge in Princeton University campus equipped with a fiber optic sensing system, assuming that two fictional characters, Malcolm and Ophelia, are involved: Malcolm is the manager who decides whether to keep the bridge open or close it following to an incident; Ophelia is the owner who decides whether to invest on a monitoring system to help Malcolm making the right decision. We demonstrate that when manager and owner are two different individuals, the benefit of monitoring could be greater or smaller than when all the decisions are made by the same individual. Under appropriate conditions, the monitoring VoI could even be negative, meaning that the owner is willing to pay to prevent the manager to use the monitoring system