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The purpose of this paper is to provide international data on the occurrence (and rates) of clinical errors, identified by type and consequence in the Lombardy region, and to assess empirically the association between hospital accreditation‐type measures and clinical error rates by merging hospital discharge records and medical malpractice claim data in the Lombardy region (Italy).

Data were drawn from the regional database collecting claims and demands for reimbursement declared by patients hospitalized in regional healthcare structures and regional archives collecting hospital discharge records. To model the variability of clinical errors rates, binomial negative regression models were applied. For improved interpretation of the results, a regression tree methodology was used.

The results demonstrated that the rate of readmission for the same major diagnostic category and the rate of discharges against medical advice significantly affect the incidence of errors causing patient death, whereas the rate of unscheduled surgical readmission in the operating room significantly affects the rate of surgical error.

The findings confirm that claims data is problematic in nature because of the limited number of claims generally emerging from administrative sources. The article proposes using proper regression models for count data, taking into account over‐dispersion and excess zeroes and classification tree methods for a better interpretation of empirical evidence.

Health structures where quality outcomes have a significant impact on clinical error rates should be monitored in depth, investigating the medical charts of involved patients to identify quality problems and problematic areas.

As a risk management strategy, the combined use of claims data and clinical administrative data is proposed to shed light on the more problematic, error‐prone areas, allowing regional stakeholders to receive relevant, highly cost‐effective and timely information and an in‐depth understanding of the problematic areas in the assessment of risk.

This study aims to fathom the role of nursing governance as a mechanism to activate the chain effect from corporate social responsibility (CSR) through psychological contract to knowledge sharing, which in turn reduces clinical errors in hospitals in the Vietnam context. Clinical errors not merely result from human factors but also from mechanisms which influence human factors.

The clues for the research model were established through structural equation modeling-based analysis of cross-sectional data from 233 nurses of Vietnam-based hospitals.

Research findings unveiled the positive correlation between nursing governance and ethical CSR as well as the negative correlations between nursing governance and legal CSR or economic CSR. Ethical CSR was found to have positive effect on psychological contract, whereas legal or economic CSR was found to have negative effect on psychological contract. The chain effects from psychological contract through knowledge sharing to clinical error control were also attested in this inquiry.

Research results have contributed to literature in some ways, for example, expanding health-care quality and patient safety literature through the chain of antecedents (nursing governance, CSR, psychological contract and knowledge sharing) to clinical error control, underscoring the role of psychological contract in cultivating knowledge sharing and adding organizational outcomes such as knowledge sharing and clinical error control to the nursing governance literature.

Notwithstanding the rising magnitude of system factors in patient safety improvement, “human factors” such as idiosyncratic deals (i-deals) which also contribute to the adjustment of system deficiencies should not be neglected. The purpose of this paper is to investigate the role of value-based HR practices in catalyzing i-deals, which then influence clinical error control. The research further examines the moderating role of corporate social responsibility (CSR) on the effect of value-based HR practices on i-deals.

The data were collected from middle-level clinicians from hospitals in the Vietnam context.

The research results confirmed the effect chain from value-based HR practices through i-deals to clinical error control with CSR as a moderator.

The HRM literature is expanded through enlisting i-deals and clinical error control as the outcomes of HR practices.

If the use of information technology (IT) supporting clinical trial projects offers opportunities to optimize the underlying information management process, the intricacy of the identification and evaluation of relevant IT options is generally seen as a complex task in healthcare. Hence, the purpose of this paper is to examine the problem of ex ante information system evaluation, and assess the impact of IT on the information management process underlying clinical trials.

Combining Unified Modeling Language (UML) and system dynamics modeling, a simulation model for evaluating IT was developed. This modeling effort relies on a case study conducted in a clinical research organization, which, at that time, faced an IT investment dilemma.

Some illustrative results of sensitivity analyzes conducted on error rates in clinical data transmission are presented. These simulation results allow for quantifying the impact of different IT options on human resources' efforts, time delays and costs of clinical trials projects. Notably, the results show that although the technology has no real influence on the duration of a clinical trial project, it impacts the number of projects that can be carried out simultaneously.

The research provides insights into the development of an innovative approach appropriate to the evaluation of IT supporting clinical trials, through the use of a mixed‐method based on qualitative and quantitative modeling. The results illustrate two critical issues addressed in the IS literature: the necessity to extend IT evaluation beyond the quantitative‐qualitative dichotomy; and the role of evaluation in organizational learning, and in learning about business dimensions.

The purpose of this paper is to assess National Medical Care Survey data quality.

Data completeness and representativeness were computed for all observations while other data quality measures were assessed using a 10 per cent sample from the National Medical Care Survey database; i.e., 12,569 primary care records from 189 public and private practices were included in the analysis.

Data field completion ranged from 69 to 100 per cent. Error rates for data transfer from paper to web-based application varied between 0.5 and 6.1 per cent. Error rates arising from diagnosis and clinical process coding were higher than medication coding. Data fields that involved free text entry were more prone to errors than those involving selection from menus. The authors found that completeness, accuracy, coding reliability and representativeness were generally good, while data timeliness needs to be improved.

Only data entered into a web-based application were examined. Data omissions and errors in the original questionnaires were not covered.

Results from this study provided informative and practicable approaches to improve primary health care data completeness and accuracy especially in developing nations where resources are limited.

Primary care data quality studies in developing nations are limited. Understanding errors and missing data enables researchers and health service administrators to prevent quality-related problems in primary care data.

The purpose of this paper is to present a review of health information system (HIS)-induced errors and its management. This paper concludes that the occurrence of errors is inevitable but it can be minimised with preventive measures. The review of classifications can be used to evaluate medical errors related to HISs using a socio-technical approach. The evaluation could provide an understanding of errors as a learning process in managing medical errors.

A literature review was performed on issues, sources, management and approaches to HISs-induced errors. A critical review of selected models was performed in order to identify medical error dimensions and elements based on human, process, technology and organisation factors.

Various error classifications have resulted in the difficulty to understand the overall error incidents. Most classifications are based on clinical processes and settings. Medical errors are attributed to human, process, technology and organisation factors that influenced and need to be aligned with each other. Although most medical errors are caused by humans, they also originate from other latent factors such as poor system design and training. Existing evaluation models emphasise different aspects of medical errors and could be combined into a comprehensive evaluation model.

Overview of the issues and discourses in HIS-induced errors could divulge its complexity and enable its causal analysis.

This paper helps in understanding various types of HIS-induced errors and promising prevention and management approaches that call for further studies and improvement leading to good practices that help prevent medical errors.

Classification of HIS-induced errors and its management, which incorporates a socio-technical and multi-disciplinary approach, could guide researchers and practitioners to conduct a holistic and systematic evaluation.

For the modernisation of the NHS and successful implementation of clinical governance there must be a new curriculum, with new educational goals for the education of clinicians, managers and consumers. Whilst many elements to that end have been introduced in recent years, a missing element is the study of the system of health care as a system, its properties and risks. The study of safety of and adverse outcomes from error in the “Quality of Australian health care”, highlighted not only preventable error in individual clinical decision and actions, but more importantly the hidden flaws, the latent errors within the system of health care that can lead to such errors. The study of system error in health care is greatly enhanced by the experience of comparable studies of safety in industry. These issues are explored in postgraduate vocational education and training. Perhaps they should be core curriculum for all undergraduate health profession and management education.

The purpose of this paper is to investigate connections and overlaps between health lean management (HLM) and clinical risk management (CRM) understanding whether and how these two approaches can be combined together to pursue efficiency and patient safety improvements simultaneously.

A systematic literature review has been carried out. Searching in academic databases, papers that focus not only on HLM, but also on clinical errors and risk reduction, were included. The general characteristics of the selected papers were analysed and a content analysis was conducted.

In most of the papers, pursing objectives of HLM and CRM and adopting tools and practices of both approaches, results of quality and, particularly, of safety improvements were obtained. A two-way arrow between HLM and CRM emerged but so far, none of the studies has been focused on the relationship between HLM and CRM.

Results highlight an emerging research stream, with many useful theoretical and practical implications and opportunities for further research.

One way of defining the character of clinicians is to examine their moment-to-moment actions during the course of clinical care. These small actions, cumulatively, describe the clinician as a practitioner and moral agent. In this chapter, using clinical examples, I explore the possibility that professional competence and virtue are based, in part, on clinicians’ ability to engage in a “mindful” practice in which they can be attentive to their own actions, curious enough to examine them and present and flexible enough to change them.

Many people have been dying as a result of medical errors. Offering clinical learning can lead to better medical care. Clinics have conventionally incorporated direct modality to teach personnel. However, they are now starting to take electronic learning (e-learning) mechanisms to facilitate training at work or other suitable places. The objective of this study is to identify and prioritize the medical learning system in developing countries. Therefore, this paper aims at describing a line of research for developing medical learning systems.

Nowadays, organizations face fast markets' changing, competition strategies, technological innovations and accessibility of medical information. However, the developing world faces a series of health crises that threaten millions of people's lives. Lack of infrastructure and trained, experienced staff are considered essential barriers to scaling up treatment for these diseases. Promoting medical learning systems in developing countries can meet these challenges. This study identifies multiple factors that influence the success of e-learning systems from the literature. The authors have presented a systematic literature review (SLR) up to 2019 on medical learning systems in developing countries. The authors have identified 109 articles and finally selected 17 of them via article choosing procedures.

The paper has shown that e-learning systems offer significant advantages for the medical sector of developing countries. The authors have found that executive, administrative and technological parameters have substantial effects on implementing e-learning in the medical field. Learning management systems offer a virtual method of augmented and quicker interactions between the learners and teachers and fast efficient instructive procedures, using computer and Internet technologies in learning procedures and presenting several teaching-learning devices.

The authors have limited the search to Scopus, Google Scholar, Emerald, Science Direct, IEEE, PLoS, BMC and ABI/Inform. Many academic journals probably provide a good picture of the related articles, too. This study has only reviewed the articles extracted based on some keywords such as “medical learning systems,” “medical learning environment” and “developing countries.” Medical learning systems might not have been published with those specific keywords. Also, there is a requirement for more research with the use of other methodologies. Lastly, non-English publications have been removed. There could be more potential related papers published in languages other than English.

This paper helps physicians and scholars better understand the clinical learning systems in developing countries. Also, the outcomes can aid hospital managers to speed up the implementation of e-learning mechanisms. This research might also enable the authors to have a role in the body of knowledge and experience, so weakening the picture of the developing country's begging bowl is constantly requesting help. The authors hoped that their recommendations aid clinical educators, particularly in developing countries, adopt the trends in clinical education in a changing world.

This paper is of the pioneers systematically reviewing the adoption of medical learning, specifically in developing countries.