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\"This timely book describes the details of three real case studies of investigative journalism about health care. Stories include journalists exposing wrongdoing by drug companies, neglect of dying patients in by hospice home-care providers, and lead-poisoning from drinking water in Flint, Michigan. Readers will gain an understanding of the research process, the ethical standards journalists must follow, and the perseverance required to confirm a story and affect change\"-- Provided by publisher.

In an effort to increase price transparency, the Centers for Medicare and Medicaid Services (CMS) began reporting charges for Medicare inpatients treated in ∼3400 hospitals online in 2013. As of 2019, CMS began to require hospitals themselves to publicize a more comprehensive list of their underlying procedure charges. The objective of this study was to assess the responses of hospitals to broad-scale public reporting of their charges for inpatient services. We used descriptive analysis to examine the trend in CMS charge data for high charge hospitals before and after the 2013 intervention. We also applied difference-in-differences analysis to comprehensive inpatient charge data from New York and Florida for the years 2011-2016, defining the reported high-volume diagnosis-related groups (DRGs) as the intervention group. At the national level, the CMS charge data showed relatively lower growth in high charge hospitals following the intervention. From the state data, we found that after 3 years, the growth in charges for reported DRGs in New York hospitals was 4%-9% lower than for unreported diagnosis-related groups. In Florida, it was 2%-8% lower. Public reports of hospital inpatient charges by DRG appear to influence subsequent charges, slowing their growth.

Surveillance and feedback of infection rates to clinicians and other stakeholders is a cornerstone of healthcare-associated infection (HAI) prevention programs. In addition, HAIs are increasingly included in public reporting and payment mandates. Conventional manual surveillance methods are resource intensive and lack standardization. Developments in information technology have propelled a movement toward the use of standardized and semiautomated methods.When developing automated surveillance systems, several strategies can be chosen with regard to the degree of automation and standardization and the definitions used. Yet, the advantages of highly standardized surveillance may come at the price of decreased clinical relevance and limited preventability. The choice among (automated) surveillance approaches, therefore, should be guided by the intended aim and scale of surveillance (eg, research, in-hospital quality improvement, national surveillance, or pay-for-performance mandates), as this choice dictates subsequent methods, important performance characteristics, and suitability of the data generated for the different applications.

Data should be fully and immediately available for public scrutiny

Since the outbreak of COVID-19, the development of dashboards as dynamic, visual tools for communicating COVID-19 data has surged worldwide. Dashboards can inform decision-making and support behavior change. To do so, they must be actionable. The features that constitute an actionable dashboard in the context of the COVID-19 pandemic have not been rigorously assessed. The aim of this study is to explore the characteristics of public web-based COVID-19 dashboards by assessing their purpose and users (\"why\"), content and data (\"what\"), and analyses and displays (\"how\" they communicate COVID-19 data), and ultimately to appraise the common features of highly actionable dashboards. We conducted a descriptive assessment and scoring using nominal group technique with an international panel of experts (n=17) on a global sample of COVID-19 dashboards in July 2020. The sequence of steps included multimethod sampling of dashboards; development and piloting of an assessment tool; data extraction and an initial round of actionability scoring; a workshop based on a preliminary analysis of the results; and reconsideration of actionability scores followed by joint determination of common features of highly actionable dashboards. We used descriptive statistics and thematic analysis to explore the findings by research question. A total of 158 dashboards from 53 countries were assessed. Dashboards were predominately developed by government authorities (100/158, 63.0%) and were national (93/158, 58.9%) in scope. We found that only 20 of the 158 dashboards (12.7%) stated both their primary purpose and intended audience. Nearly all dashboards reported epidemiological indicators (155/158, 98.1%), followed by health system management indicators (85/158, 53.8%), whereas indicators on social and economic impact and behavioral insights were the least reported (7/158, 4.4% and 2/158, 1.3%, respectively). Approximately a quarter of the dashboards (39/158, 24.7%) did not report their data sources. The dashboards predominately reported time trends and disaggregated data by two geographic levels and by age and sex. The dashboards used an average of 2.2 types of displays (SD 0.86); these were mostly graphs and maps, followed by tables. To support data interpretation, color-coding was common (93/158, 89.4%), although only one-fifth of the dashboards (31/158, 19.6%) included text explaining the quality and meaning of the data. In total, 20/158 dashboards (12.7%) were appraised as highly actionable, and seven common features were identified between them. Actionable COVID-19 dashboards (1) know their audience and information needs; (2) manage the type, volume, and flow of displayed information; (3) report data sources and methods clearly; (4) link time trends to policy decisions; (5) provide data that are \"close to home\"; (6) break down the population into relevant subgroups; and (7) use storytelling and visual cues. COVID-19 dashboards are diverse in the why, what, and how by which they communicate insights on the pandemic and support data-driven decision-making. To leverage their full potential, dashboard developers should consider adopting the seven actionability features identified.

Background Preprint manuscripts, rapid publications and opinion pieces have been essential in permitting the lay press and public health authorities to preview data relating to coronavirus disease 2019 (COVID-19), including the range of clinical manifestations and the basic epidemiology early on in the pandemic. However, the rapid dissemination of information has highlighted some issues with communication of scientific results and opinions in this time of heightened sensitivity and global concern. Main text Rapid publication of COVID-19 literature through expedited review, preprint publications and opinion pieces are important resources for the medical scientific community. Yet the risks of unverified information loom large in times when the healthcare community is desperate for information. Information that has not been properly vetted, or opinion pieces without solid evidence, may be used to influence public health policy decisions. We discuss three examples of unverified information and the consequences in this time of high anxiety surrounding COVID-19. Conclusions In an era when information can be widely and swiftly disseminated, it is important to ensure that the scientific community is not an inadvertent source of misinformation. This will require a multimodal approach, with buy-in from editors, publishers, preprint servers, authors and journalists. The landscape of medical publications has changed, and a collaborative approach is required to maintain a high standard of scientific communications.

Americans increasingly post and consult online physician rankings, yet we know little about this new phenomenon of public physician quality reporting. Physicians worry these rankings will become an outlet for disgruntled patients. To describe trends in patients' online ratings over time, across specialties, to identify what physician characteristics influence online ratings, and to examine how the value of ratings reflects physician quality. We used data from RateMDs.com, which included over 386,000 national ratings from 2005 to 2010 and provided insight into the evolution of patients' online ratings. We obtained physician demographic data from the US Department of Health and Human Services' Area Resource File. Finally, we matched patients' ratings with physician-level data from the Virginia Medical Board and examined the probability of being rated and resultant rating levels. We estimate that 1 in 6 practicing US physicians received an online review by January 2010. Obstetrician/gynecologists were twice as likely to be rated (P < .001) as other physicians. Online reviews were generally quite positive (mean 3.93 on a scale of 1 to 5). Based on the Virginia physician population, long-time graduates were more likely to be rated, while physicians who graduated in recent years received higher average ratings (P < .001). Patients gave slightly higher ratings to board-certified physicians (P = .04), those who graduated from highly rated medical schools (P = .002), and those without malpractice claims (P = .1). Online physician rating is rapidly growing in popularity and becoming commonplace with no evidence that they are dominated by disgruntled patients. There exist statistically significant correlations between the value of ratings and physician experience, board certification, education, and malpractice claims, suggesting a positive correlation between online ratings and physician quality. However, the magnitude is small. The average number of ratings per physician is still low, and most rating variation reflects evaluations of punctuality and staff. Understanding whether they truly reflect better care and how they are used will be critically important.

Background To assess both qualitatively and quantitatively the impact of Public Reporting (PR) on clinical outcomes, we carried out a systematic review of published studies on this topic. Methods Pubmed, Web of Science and SCOPUS databases were searched to identify studies published from 1991 to 2014 that investigated the relationship between PR and clinical outcomes. Studies were considered eligible if they investigated the relationship between PR and clinical outcomes and comprehensively described the PR mechanism and the study design adopted. Among the clinical outcomes identified, meta-analysis was performed for overall mortality rate which quantitative data were exhaustively reported in a sufficient number of studies. Two reviewers conducted all data extraction independently and disagreements were resolved through discussion. The same reviewers evaluated also the quality of the studies using a GRADE approach. Results Twenty-seven studies were included. Mainly, the effect of PR on clinical outcomes was positive. Meta-analysis regarding overall mortality included, in a context of high heterogeneity, 10 studies with a total of 1,840,401 experimental events and 3,670,446 control events and resulted in a RR of 0.85 (95 % CI, 0.79-0.92). Conclusions The introduction of PR programs at different levels of the healthcare sector is a challenging but rewarding public health strategy. Existing research covering different clinical outcomes supports the idea that PR could, in fact, stimulate providers to improve healthcare quality.

Public performance reporting (PPR) of physician and hospital data aims to improve health outcomes by promoting quality improvement and informing consumer choice. However, previous studies have demonstrated inconsistent effects of PPR, potentially due to the various PPR characteristics examined. The aim of this study was to undertake a systematic review of the impact and mechanisms (selection and change), by which PPR exerts its influence. Studies published between 2000 and 2020 were retrieved from five databases and eight reviews. Data extraction, quality assessment and synthesis were conducted. Studies were categorised into: user and provider responses to PPR and impact of PPR on quality of care. Forty-five studies were identified: 24 on user and provider responses to PPR, 14 on impact of PPR on quality of care, and seven on both. Most of the studies reported positive effects of PPR on the selection of providers by patients, purchasers and providers, quality improvement activities in primary care clinics and hospitals, clinical outcomes and patient experiences. The findings provide moderate level of evidence to support the role of PPR in stimulating quality improvement activities, informing consumer choice and improving clinical outcomes. There was some evidence to demonstrate a relationship between PPR and patient experience. The effects of PPR varied across clinical areas which may be related to the type of indicators, level of data reported and the mode of dissemination. It is important to ensure that the design and implementation of PPR considered the perspectives of different users and the health system in which PPR operates in. There is a need to account for factors such as the structural characteristics and culture of the hospitals that could influence the uptake of PPR.