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Patient experience is a complex multidimensional phenomenon that has been linked to constructs that are also complex to conceptualize, such as patient-centeredness, patient expectations and patient satisfaction. The purpose of this paper is to shed light on the different dimensions of patient experience, including those that receive inadequate attention from policymakers such as the patient’s lived experience of illness and the impact of healthcare politics. The paper proposes a simple classification for these dimensions, which differentiates between two types of dimensions: the determinants and the manifestations of patient experience.

This paper uses a narrative review of the literature to explore select constructs and initiatives developed for theorizing or operationalizing patient experience. Literature topics reviewed include healthcare quality, medical anthropology, health policy, healthcare system and public health.

The paper identifies five determinants for patient experience: the experience of illness, patient’s subjective influences, quality of healthcare services, health system responsiveness and the politics of healthcare. The paper identifies two manifestations of patient experience: patient satisfaction and patient engagement.

The paper proposes a classification scheme of the dimensions of patient experience and a concept map that links together heterogeneous constructs related to patient experience. The proposed classification and the concept map provide a holistic view of patient experience and help healthcare providers, quality managers and policymakers organize and focus their healthcare quality improvement endeavors on specific dimensions of patient experience while taking into consideration the other dimensions.

In a context of critical transition such as the COVID-19 pandemic, moral semantics take a prominent role as a form of self-description of society. However, they are not usually observed, but rather assumed as self-evident and necessarily “good.” The purpose of the article is to summarize the theory of morality from the social systems' perspective and illustrate with concrete examples the polemogenous nature of moral communication.

This article presents an analysis of the role of morality in the context of the COVID-19 pandemic, from the perspective of Niklas Luhmann’s social systems theory. Applying the method of second-order observation, it describes three cases of moral semantics disseminated via mass media and social media, and it examines their connection with the structural situation of subsystems of society during the pandemic crisis (particularly healthcare, politics and science).

Second-order observation of moral communication demonstrates to be fruitful to describe the conditions and consequences in which moralization of communication occurs, particularly in a situation of critical transition around the healthcare crisis. The three examples examined, namely, the hero semantics directed to healthcare workers, the semantics of indiscipline and the controversies around pseudo-sciences and conspiracy theories, show how they are based on social attribution of esteem and disesteem, how they try to answer to troublesome situations and contradictions that seem difficult to cope, and how they are close related to the emergence of conflicts, even when they seem positive oriented and well intentioned.

This paper is an attempt to test the usefulness of Luhmann's theory of society to understand the ongoing COVID-19 crisis and particularly the role of moral communication in concrete examples.

Aims to review institutional change in health care and to look for opportunities in what the author sees as a coming crisis.

A consultant on health‐care systems reviews the forces driving transformation in medicine, including new technologies, telemedicine, and prevention.

Finds forces driving transformation in medicine limited in addressing the crisis of spiraling cost and mediocre, overly complex treatment.

Concludes that a dramatic shift in perspective is coming as baby boomers are forced to face the inevitability of death in positive terms.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting‐edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

The traditional view of a leader is of a forceful individual who sets a clear agenda and expects followers to carry out his or her instructions unquestioningly. Like the Captain of a ship, the leader brooks no dissent and indeed Sims et al. point out that the English word to lead is derived from the Old Norse word laed that means to determine the course of a ship. However, in today's fast changing commercial environment, with the added pressures of economic uncertainty, one style of leadership cannot fit all situations. Leaders must learn to adapt their leadership styles and strategies to meet the needs of various complex situations.

The paper provides strategic insights and practical thinking that have influenced some of the world's leading organizations.

This paper demonstrates that different leadership styles are appropriate for various stages of project management.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy‐to‐digest format.

An ever-growing body of knowledge demonstrates the correlation among real-world phenomena and search query data issued on Google, as showed in the literature survey introduced in the following. The purpose of this paper is to introduce a pipeline, implemented as a web service, which, starting with recent Google Trends, allows a decision maker to monitor Twitter’s sentiment regarding these trends, enabling users to choose geographic areas for their monitors. In addition to the positive/negative sentiments about Google Trends, the pipeline offers the ability to view, on the same dashboard, the emotions that Google Trends triggers in the Twitter population. Such a set of tools, allows, as a whole, monitoring real-time on Twitter the feelings about Google Trends that would otherwise only fall into search statistics, even if useful. As a whole, the pipeline has no claim of prediction over the trends it tracks. Instead, it aims to provide a user with guidance about Google Trends, which, as the scientific literature demonstrates, is related to many real-world phenomena (e.g. epidemiology, economy, political science).

The proposed experimental framework allows the integration of Google search query data and Twitter social data. As new trends emerge in Google searches, the pipeline interrogates Twitter to track, also geographically, the feelings and emotions of Twitter users about new trends. The core of the pipeline is represented by a sentiment analysis framework that make use of a Bayesian machine learning device exploiting deep natural language processing modules to assign emotions and sentiment orientations to a collection of tweets geolocalized on the microblogging platform. The pipeline is accessible as a web service for any user authorized with credentials.

The employment of the pipeline for three different monitoring task (i.e. consumer electronics, healthcare, and politics) shows the plausibility of the proposed approach in order to measure social media sentiments and emotions concerning the trends emerged on Google searches.

The proposed approach aims to bridge the gap among Google search query data and sentiments that emerge on Twitter about these trends.

The author studies the determinants of public trust in government doctors and hospitals (DH) – a crucial indicator of the quality of a country's healthcare system – in India by analyzing the India Human Development Survey (IHDS) 2011–2012.

The author uses descriptive statistics and a set of ordered probit regression models controlling for a set of individual-specific, household-level and other covariates and analyze across heterogeneous contexts (national/rural/urban/male heads/female heads/social groups).

Across contexts, people reporting a great deal of trust in private DH (PDH) are significantly more likely to report a great deal of trust in government DH. Those people with a great deal of trust in government schools to provide good education (vis-à-vis people with only some trust in government school) have significantly higher likelihood of reporting a great deal of trust in government DH. Visiting a private doctor last time (vis-à-vis a government doctor) makes reporting higher trust levels in government DH less likely.

India's healthcare system is afflicted with several resource allocation problems and low public trust issues are indicative of misgovernance. In presence of limited state capacity, ubiquitous corruption and underwhelming institutional trust, understanding the factors influencing public trust in healthcare providers is critical to designing appropriate trust-enhancing public health policies.

Given the sparse empirical literature on public trust in healthcare systems in the developing countries such as India, this study is a pertinent contribution as the study explains the determinants of public trust in DH using a comprehensive unit-recorded household survey dataset.