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This study investigates the stability of the “hospital effect” on performance over time by administrative health data as a source of evidence. Using 78,907 heart failure adult records from 117 hospitals in the Lombardy Region (Northern Italy) over three years (2010–2012), we analyzed hospital performance in terms of 30-day mortality and 30-day unplanned readmissions to gather evidence about the stability of the “hospital effect.” Best/worst performers were identified through multi-level models that combine both patient and hospital covariates. Our results confirm that managerial choices affect hospital performance, and that the “hospital effect” is not, contrary to expectations, stable over the short term. Performance improvement/worsening over the three years has been also analyzed.

A clinical pathway for patients with acute ischemic stroke was implemented in 2014 by one Italian teaching hospital multidisciplinary team. The purpose of this paper is to determine whether this clinical pathway had a positive effect on patient management by comparing performance data.

Volume, process and outcome indicators were analyzed in a pre-post retrospective observational study. Patients’ (admitted in 2013 and 2015) medical records with International Classification of Diseases, ICD-9 code 433.x (precerebral artery occlusion and stenosis), 434.x (cerebral artery occlusion) and 435.x (transient cerebral ischemia) and registered correctly according to hospital guidelines were included.

An increase context-sensitive in-patient numbers with more severe cerebrovascular events and an increase in patient transfers from the Stroke to Neurology Unit within three days (70 percent, p=0.25) were noted. Clinical pathway implementation led to an increase in patient flow from the Emergency Department to dedicated specialized wards such as the Stroke and Neurology Unit (23.7 percent, p<0.001). Results revealed no statistically significant decrease in readmission rates within 30 days (5.7 percent, p=0.85) and no statistically significant differences in 30-day mortality.

The pre-post retrospective observational study design was considered suitable to evaluate likely changes in patient flow after clinical pathway implementation, even though this design comes with limitations, describing only associations between exposure and outcome.

Clinical pathway implementation showed an overall positive effect on patient management and service efficiency owing to the standardized application in time-dependent protocols and multidisciplinary/integrated care implementation, which improved all phases in acute ischemic stroke care.

The purpose of this paper is to identify and analyse the readmission risk prediction tools reported in the literature and their benefits when it comes to healthcare organisations and management.

Readmission risk prediction is a growing topic of interest with the aim of identifying patients in particular those suffering from chronic diseases such as congestive heart failure, chronic obstructive pulmonary disease and diabetes, who are at risk of readmission. Several models have been developed with different levels of predictive ability. A structured and extensive literature search of several databases was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-analysis strategy, and this yielded a total of 48,984 records.

Forty-three articles were selected for full-text and extensive review after following the screening process and according to the eligibility criteria. About 34 unique readmission risk prediction models were identified, in which their predictive ability ranged from poor to good (c statistic 0.5–0.86). Readmission rates ranged between 3.1 and 74.1% depending on the risk category. This review shows that readmission risk prediction is a complex process and is still relatively new as a concept and poorly understood. It confirms that readmission prediction models hold significant accuracy at identifying patients at higher risk for such an event within specific context.

Since most prediction models were developed for specific populations, conditions or hospital settings, the generalisability and transferability of the predictions across wider or other contexts may be difficult to achieve. Therefore, the value of prediction models remains limited to hospital management. Future research is indicated in this regard.

This review is the first to cover readmission risk prediction tools that have been published in the literature since 2011, thereby providing an assessment of the relevance of this crucial KPI to health organisations and managers.

The aim was to test the feasibility of using automated data, and evaluate the impact of an emergency cardiac decision unit (CDU) on the overall outcomes of patients seen for chest discomfort. We used a retrospective, quasi‐experimental design to identify patients who had cardiac enzymes measured and an electrocardiogram performed during an ED visit in two six‐month periods, pre‐CDU (1 January‐30 June 1995) and post‐CDU (1 January‐ 30 June 1996). A total of 4,336 patients had outcomes assessed. After opening, 14.8 per cent of all chest pain cases were treated in the CDU. Hospital admission rates were reduced from 81.1 per cent to 66.7 per cent. Length of stay, myocardial infarction rates, and mortality were unchanged. The 14‐day revisit rates increased from 5.3 per cent to 10.3 per cent. We conclude that cardiac decision units decrease hospital admissions but increase ED revisit rates as a consequence of this now frequently used care pathway.

In recent years, the clinical performance of named cardiac surgeons in England has been disclosed. This paper aims to explore the nature and impact of disclosure of clinical performance.

The paper draws on literature from across the social sciences to assess the impact of disclosure, as a form of transparency, in improving clinical performance. Specifically, it employs the “programme theory” of disclosure.

The “programme theory” of disclosure involves identification, naming, public sanction and recipient response. Named individual (consultant) surgeons have been identified through disclosure but this masks the contribution of the clinical team, including junior surgeons. Mortality is the prime performance measure but given low mortality rates, there are problems interpreting this measure. The naming of surgeons has been achieved through disclosure on web sites, developed between the health‐care regulator and the surgical profession itself. However, participation remains voluntary. The intention of disclosure is that interested parties (especially patients) will shun poorly performing surgeons. However, these parties' willingness and ability to exercise this sanction appears limited. Surgeons' responses are emergent but about a quarter of surgeons are not participating currently. Fears that surgeons would avoid high‐risk patients seem to have been unrealised. While disclosure may have a small effect on individual reputations, the surgical profession as a whole has embraced disclosure.

While the aim of disclosure has been to create a transparent medical system and to improve clinical performance, disclosure may have the opposite effect, concealing some performance issues and possibly strengthening professional autonomy. Disclosure therefore represents greater transparency in health‐care but it is uncertain whether it will improve performance in the ways that the policy intends.

Cardiovascular diseases are the leading cause of death worldwide. In Italy, acute myocardial infarction (AMI) is a major cause of hospitalization and healthcare costs. AMI is a myocardial necrosis event caused by an unstable ischemic syndrome. The Italian government has defined an indicator called “AMI: 30-day mortality” to assess the quality of the overall care pathway of the heart attacked patient. In order to guarantee high standards, all hospitals had to implement techniques to increase the quality of care pathway. The aim of the paper is to identify the root cause and understand the mortality rate for AMI and redesign the patient management process in order to improve it.

A Lean Six Sigma (LSS) approach was used in this study to analyze the patient flow in order to reduce 30-days mortality rate from AMI registered by Complex Operative Unit (COU) of Cardiology of an Italian hospital. Value stream mapping (VSM) and Ishikawa diagrams were implemented as tools of analysis.

Process improvement using LSS methodology made it possible to reduce the overall times from 115 minutes to 75 minutes, with a reduction of 35%. In addition, the corrective actions such as the activation of a post-discharge outpatient clinic and telephone contacts allowed the 30-day mortality rate to be lowered from 16% before the project to 8% after the project. In this way, the limit value set by the Italian government was reached.

The limitation of the study is that it is single-centered and was applied to a facility with a limited number of cases.

The LSS approach has brought significant benefits to the process of managing patients with AMI. Corrective actions such as the activation of an effective shared protocol or telephone interview with checklist can become the gold standard in reducing mortality. The limitation of the study is that it is single-centered and was applied to a facility with a limited number of cases.

LSS, applied for the first time to the management of cardiovascular diseases in Italy, is a methodology which has proved to be strategic for the improvement of healthcare process. The simple solutions implemented could serve as a guide for other hospitals to pursue the national AMI mortality target.

The Royal College of Surgeons published Standards for Unscheduled Surgical Care in response to variable clinical outcomes for emergency surgery. The purpose of this study is to assess for feasibility of a district hospital providing care in accordance to the recommendations.

A total of 100 consecutive patient unscheduled episodes of care were prospectively included. Information regarding demographics, timeliness of investigations, operations, consultant input and clinical outcomes was collated. All patients were risk-adjusted for mortality. The data were compared to the guidelines.

A total of 91 patients were included; 80 patients underwent surgery. There were 18 deaths (22.5 per cent), eight (10 per cent) post-operative within 30 days. There was no statistical difference between deaths and day of admission or surgery. There were 39 critically-ill patients, none were reviewed by a consultant within the recommended 30 minutes. Of the critically-ill patients, 23 underwent CT scanning, none within the recommended 30 minutes. All patients were operated within the recommended timeframe by urgency grading. For those predicted mortality rate >5 per cent, a consultant was present in theatre for 97 per cent of cases. All patients had a consultant review within 24 hours of admission.

To the authors' knowledge this is the first evaluation of the practical difficulties in achieving consultant delivered care in surgery in a district general hospital. These results are interesting to clinicians and service planners involved in developing emergency services. Adhering to these guidelines would require significant re-allocation of resources in most hospitals and may require centralisation of services.

Patient safety indicators (PSIs) were developed as a tool for hospitals to identify potentially preventable complications and improve patient safety performance. The study aimed at measuring the incidence of the Agency for Healthcare Research and Quality (AHRQ) PSI03 (pressure ulcer [PU] rate) and to identify the association between PSI03 and clinical outcomes including death, readmission within 30 days and length of stay (LOS) at the cardiothoracic surgery hospital at Ain Shams University, Cairo, Egypt.

An exploratory prospective cohort study was conducted to follow up patients, who fulfilled the inclusion criteria, from admission until one month after discharge at the cardiothoracic surgery hospital. Data were collected through basic information and follow-up sheets. The total number of included participants in the study was 330.

PSI03 incidence rate was 67.7 per 1,000 discharges. Patients aged 60 years and above had the highest risk among all age groups. In patients who developed PSI03, the risk ratio (RR) of death was 8.8 [95% CI (3.79–20.24)], RR of staying more than 30 days at the hospital was 1.5 [95% CI (1.249–1.872)] and of readmission within 30 days in patients who developed PSI03 was 1.5 [95% CI (0.38–6.15)]. In the study’s hospital, the patients who developed PSI03 were at higher risk of death and stayed longer at the hospital than patients without PSI03. This study demonstrated a clear association between PSI03 and patient outcomes such as LOS and mortality. Early detection, prevention and proper management of PSI03 are recommended to decrease unfavorable clinical outcomes.

The importance of PSIs lies in the fact that they facilitate the recognition of the adverse events and complications which occurred during hospitalization and give the hospitals a chance to improve the possible clinical outcomes. Therefore, the current study aimed at measuring the association between AHRQ PSI03 ( PU rate) and the clinical outcomes including death, readmission within 30 days and the LOS at the cardiothoracic surgery hospital at Ain Shams University. This study will provide the hospital management with baseline data for this type of adverse event and guide them to develop a system for identifying the high-risk group of patients and to upgrade relevant hospital policies and guidelines that lead to improved patient outcomes.

The purpose of this study is to evaluate the association between economic activity in a country, as measured by the gross domestic product (GDP) and the control of the COVID-19 pandemic outcomes, as measured by the rate of incidence and mortality increase per 100,000 population in different countries using up-to-date data, in the light of public health security capacities including prevention, detection, respond, enabling function, operational readiness, as measured by the 2019 State Party self-assessment annual reporting (SPAR) submissions of 100 countries.

For this analytical study, multiple linear regression analyses were performed for each variable with the COVID-19 incidence and mortality rates, while controlling for Human Development Index (HDI) and GDP.

Countries with higher income levels were significantly more likely to have a higher incidence and mortality rate per 100,000 population. Among the public health capacity categories, prevention of the infectious disease and detection of the pathogens were significantly associated with lower incidence and mortality of the COVID-19 pandemic. The country-level income was found to be an important negative predictor of COVID-19 control.

These findings present to decision-makers in organizing mitigation strategies to struggle emerging infectious pandemics and highlight the role of country-level income while trying to control COVID-19. In order to determine the priority settings for the fight against pandemic, national policy-makers and international organizations should notice that countries in a high-income group had better health security capacities than that of other income groups, particularly in low- and lower-middle-income groups. The results of the capabilities of health security by the income group can assist health policy makers and other international agencies in resource allocation decisions and in mitigating risk with more informed resource planning.

The income level of countries may have a positive effect on public health strategies to mitigate the risk of infection of COVID-19. This study may assist the local public authorities to gain a better level of understanding on the relationship country-level income and COVID-19 outcomes in order to take appropriate measures at the local level. The results also highlighted the importance role of public health security capacities for the pandemic control policy.

Although previous studies have examined to assess the public health capability by country-level and to describe cases and deaths by continent and by country, very limited studies have evaluated the rate of incidence and mortality of COVID-19 by country-level income and by health expenditure using the data on the health security capacities with analytical and practical approaches.

Failure to rescue events, or events involving preventable deaths from complications, are a significant contributor to inpatient mortality. While many interventions have been designed and implemented over several decades, this patient safety issue remains at the forefront of concern for most hospitals. In the first part of this study, the development and implementation of one type of highly studied and widely adopted rescue intervention, algorithm-based patient assessment tools, is examined. The analysis summarizes how a lack of systems-oriented approaches in the design and implementation of these tools has resulted in suboptimal understanding of patient risk of mortality and complications and the early recognition of patient deterioration. The gaps identified impact several critical aspects of excellent patient care, including information-sharing across care settings, support for the development of shared mental models within care teams, and access to timely and accurate patient information.

This chapter describes the use of several system-oriented design and implementation activities to establish design objectives, model clinical processes and workflows, and create an extensible information system model to maximize the benefits of patient state and risk assessment tools in the inpatient setting. A prototype based on the product of the design activities is discussed along with system-level considerations for implementation. This study also demonstrates the effectiveness and impact of applying systems design principles and practices to real-world clinical applications.