The systematic review of evidence is the research method which underpins the traditional approach to evidence-based healthcare. There is currently no uniform methodology for conducting a systematic review of association (etiology). This study outlines and describes the Joanna Briggs Institute's approach and guidance for synthesizing evidence related to association with a predominant focus on etiology and contributes to the emerging field of systematic review methodologies. It should be noted that questions of association typically address etiological or prognostic issues.The systematic review of studies to answer questions of etiology follows the same basic principles of systematic review of other types of data. An a priori protocol must inform the conduct of the systematic review, comprehensive searching must be performed and critical appraisal of retrieved studies must be carried out.The overarching objective of systematic reviews of etiology is to identify and synthesize the best available evidence on the factors of interest that are associated with a particular disease or outcome. The traditional PICO (population, interventions, comparators and outcomes) format for systematic reviews of effects does not align with questions relating to etiology. A systematic review of etiology should include the following aspects: population, exposure of interest (independent variable) and outcome (dependent variable).Studies of etiology are predominantly explanatory or predictive. The objective of reviews of explanatory or predictive studies is to contribute to, and improve our understanding of, the relationship of health-related events or outcomes by examining the association between variables. When interpreting possible associations between variables based on observational study data, caution must be exercised due to the likely presence of confounding variables or moderators that may impact on the results.As with all systematic reviews, there are various approaches to present the results, including a narrative, graphical or tabular summary, or meta-analysis. When meta-analysis is not possible, a set of alternative methods for synthesizing research is available. On the basis of the research question and objectives, narrative, tabular and/or visual approaches can be used for data synthesis. There are some special considerations when conducting meta-analysis for questions related to risk and correlation. These include, but are not limited to, causal inference.Systematic review and meta-analysis of studies related to etiology is an emerging methodology in the field of evidence synthesis. These reviews can provide useful information for healthcare professionals and policymakers on the burden of disease. The standardized Joanna Briggs Institute approach offers a rigorous and transparent method to conduct reviews of etiology.

The concept of second victims (SV) was introduced 20 years ago to draw attention to healthcare professionals involved in patient safety incidents. The objective of this paper is to advance the theoretical conceptualization and to develop a common definition. A literature search was performed in Medline, EMBASE and CINAHL (October 2010 to November 2020). The description of SV was extracted regarding three concepts: (1) involved persons, (2) content of action and (3) impact. Based on these concepts, a definition was proposed and discussed within the ERNST-COST consortium in 2021 and 2022. An international group of experts finalized the definition. In total, 83 publications were reviewed. Based on expert consensus, a second victim was defined as: “Any health care worker, directly or indirectly involved in an unanticipated adverse patient event, unintentional healthcare error, or patient injury and who becomes victimized in the sense that they are also negatively impacted”. The proposed definition can be used to help to reduce the impact of incidents on both healthcare professionals and organizations, thereby indirectly improve healthcare quality, patient safety, person-centeredness and human resource management.

High levels of hospital readmission (rehospitalisation rates) is widely used as indicator of a poor quality of care. This is sometimes also referred to as recidivism or heavy utilization. Previous studies have examined a number of factors likely to influence readmission, although a systematic review of research on post-discharge factors and readmissions has not been conducted so far. The main objective of this review was to identify frequently reported post-discharge factors and their effects on readmission rates. Studies on the association between post-discharge variables and readmission after an index discharge with a main psychiatric diagnosis were searched in the bibliographic databases Ovid Medline, PsycINFO, ProQuest Health Management, OpenGrey and Google Scholar. Relevant articles published between January 1990 and June 2014 were included. A systematic approach was used to extract and organize in categories the information about post-discharge factors associated with readmission rates. Of the 760 articles identified by the initial search, 80 were selected for this review which included a total number of 59 different predictors of psychiatric readmission. Subsequently these were grouped into four categories: 1) individual vulnerability factors, 2) aftercare related factors, 3) community care and service responsiveness, and 4) contextual factors and social support. Individual factors were addressed in 58 papers and were found to be significant in 37 of these, aftercare factors were significant in 30 out of the 45 papers, community care and social support factors were significant in 21 out of 31 papers addressing these while contextual factors and social support were significant in all seven papers which studied them. This review represents a first attempt at providing an overview of post-discharge factors previously studied in association with readmission. Hence, by mapping out the current research in the area, it highlights the gaps in research and it provides guidance future studies in the area.

We aimed to map the resource use during systematic review (SR) production and reasons why steps of the SR production are resource intensive to discover where the largest gain in improving efficiency might be possible. We conducted a scoping review. An information specialist searched multiple databases (e.g., Ovid MEDLINE, Scopus) and implemented citation-based and grey literature searching. We employed dual and independent screenings of records at the title/abstract and full-text levels and data extraction. We included 34 studies. Thirty-two reported on the resource use-mostly time; four described reasons why steps of the review process are resource intensive. Study selection, data extraction, and critical appraisal seem to be very resource intensive, while protocol development, literature search, or study retrieval take less time. Project management and administration required a large proportion of SR production time. Lack of experience, domain knowledge, use of collaborative and SR-tailored software, and good communication and management can be reasons why SR steps are resource intensive. Resource use during SR production varies widely. Areas with the largest resource use are administration and project management, study selection, data extraction, and critical appraisal of studies.

Mental health care is a critical area to better understand integrated care and to pilot the different components of the integrated care model. However, there is an urgent need for better tools to compare and understand the context of integrated mental health care in Europe. The REMAST tool (REFINEMENT MApping Services Tool) combines a series of standardised health service research instruments and geographical information systems (GIS) to develop local atlases of mental health care from the perspective of horizontal and vertical integrated care. It contains five main sections: (a) Population Data; (b) the Verona Socio-economic Status (SES) Index; (c) the Mental Health System Checklist; (d) the Mental Health Services Inventory using the DESDE-LTC instrument; and (e) Geographical Data. The REMAST tool facilitates context analysis in mental health by providing the comparative rates of mental health service provision according to the availability of main types of care; care placement capacity; workforce capacity; and geographical accessibility to services in the local areas in eight study areas in Austria, England, Finland, France, Italy, Norway, Romania and Spain. The outcomes of this project will facilitate cooperative work and knowledge transfer on mental health care to the different agencies involved in mental health planning and provision. This project would improve the information to users and society on the available resources for mental health care and system thinking at the local level by the different stakeholders. The techniques used in this project and the knowledge generated could eventually be transferred to the mapping of other fields of integrated care.