An important and supposedly impactful form of clinical ethics support is moral case deliberation (MCD). Empirical evidence, however, is limited with regard to its actual impact. With this literature review, we aim to investigate the empirical evidence of MCD, thereby a) informing the practice, and b) providing a focus for further research on and development of MCD in healthcare settings. A systematic literature search was conducted in the electronic databases PubMed, CINAHL and Web of Science (June 2016). Both the data collection and the qualitative data analysis followed a stepwise approach, including continuous peer review and careful documentation of our decisions. The qualitative analysis was supported by ATLAS.ti. Based on a qualitative analysis of 25 empirical papers, we identified four clusters of themes: 1) facilitators and barriers in the preparation and context of MCD, i.e., a safe and open atmosphere created by a facilitator, a concrete case, commitment of participants, a focus on the moral dimension, and a supportive organization; 2) changes that are brought about on a personal and inter-professional level, with regard to professional’s feelings of relief, relatedness and confidence; understanding of the perspectives of colleagues, one’s own perspective and the moral issue at stake; and awareness of the moral dimension of one’s work and awareness of the importance of reflection; 3) changes that are brought about in caring for patients and families; and 4) changes that are brought about on an organizational level. This review shows that MCD brings about changes in practice, mostly for the professional in inter-professional interactions. Most reported changes are considered positive, although challenges, frustrations and absence of change were also reported. Empirical evidence of a concrete impact on the quality of patient care is limited and is mostly based on self-reports. With patient-focused and methodologically sound qualitative research, the practice and the value of MCD in healthcare settings can be better understood, thus making a stronger case for this kind of ethics support.

Using outcome measures to advance healthcare continues to be of widespread interest. The goal is to summarize the results of studies which use outcome measures from clinical registries to implement and monitor QI initiatives. The second objective is to identify a) facilitators and/or barriers that contribute to the realization of QI efforts, and b) how outcomes are being used as a catalyst to change outcomes over time. We searched the PubMed, EMBASE and Cochrane databases for relevant articles published between January 1995 and March 2017. We used a standardized data abstraction form. Studies were included when the following three criteria were fulfilled: 1) they relied on structural data collection, 2) when a structural and comprehensive QI intervention had been implemented and evaluated, and 3) impact on improving clinical and/or patient-reported outcomes was described. Data on QI strategies, QI initiatives and the impact on outcomes was extracted using standardized assessment tools. We included 21 articles, of which eight showed statistically significant improvements on outcomes using data from clinical registries. Out of these eight studies, the Chronic Care Model, IT application as feedback, benchmarking and the Collaborative Care Model were used as QI methods. Encouraging trends in realizing improved outcomes through QI initiatives were observed, ranging from improving teamwork, implementation of clinical guidelines, implementation of physician alerts and development of a decision support system. Facilitators for implementing QI initiatives included a high quality database, audits, frequent reporting and feedback, patient involvement, communication, standardization, engagement, and leadership. This review suggests that outcomes collected in clinical registries are supportive to realize QI initiatives. Organizational readiness and an active approach are key in achieving improved outcomes.

Life expectancy is one of the most important factors in end-of-life decision making. Good prognostication for example helps to determine the course of treatment and helps to anticipate the procurement of health care services and facilities, or more broadly: facilitates Advance Care Planning. Advance Care Planning improves the quality of the final phase of life by stimulating doctors to explore the preferences for end-of-life care with their patients, and people close to the patients. Physicians, however, tend to overestimate life expectancy, and miss the window of opportunity to initiate Advance Care Planning. This research tests the potential of using machine learning and natural language processing techniques for predicting life expectancy from electronic medical records. We approached the task of predicting life expectancy as a supervised machine learning task. We trained and tested a long short-term memory recurrent neural network on the medical records of deceased patients. We developed the model with a ten-fold cross-validation procedure, and evaluated its performance on a held-out set of test data. We compared the performance of a model which does not use text features (baseline model) to the performance of a model which uses features extracted from the free texts of the medical records (keyword model), and to doctors’ performance on a similar task as described in scientific literature. Both doctors and the baseline model were correct in 20% of the cases, taking a margin of 33% around the actual life expectancy as the target. The keyword model, in comparison, attained an accuracy of 29% with its prognoses. While doctors overestimated life expectancy in 63% of the incorrect prognoses, which harms anticipation to appropriate end-of-life care, the keyword model overestimated life expectancy in only 31% of the incorrect prognoses. Prognostication of life expectancy is difficult for humans. Our research shows that machine learning and natural language processing techniques offer a feasible and promising approach to predicting life expectancy. The research has potential for real-life applications, such as supporting timely recognition of the right moment to start Advance Care Planning.

Background The annual incidence of euthanasia in the Netherlands as a percentage of all deaths rose from 1.9% in 1990 to 4.4% in 2017. Scarce literature on regional patterns calls for more detailed insight into the geographical variation in euthanasia and its possible explanations. Objectives This paper (1) shows the geographical variation in the incidence of euthanasia over time (2013–2017); (2) identifies the associations with demographic, socioeconomic, preferential and health-related factors; and (3) shows the remaining variation after adjustment and discusses its meaning. Design, setting and methods This cross-sectional study used national claims data, covering all healthcare claims during 12 months preceding the death of Dutch insured inhabitants who died between 2013 and 2017. From these claims all euthanasia procedures by general practitioners were selected (85% of all euthanasia cases). Rates were calculated and compared at three levels: 90 regions, 388 municipalities and 196 districts in the three largest Dutch cities. Data on possibly associated variables were retrieved from national data sets. Negative binomial regression analysis was performed to identify factors associated with geographical variation in euthanasia. Results There is considerable variation in euthanasia ratio. Throughout the years (2013–2017) the ratio in the three municipalities with the highest incidence was 25 times higher than in the three municipalities with the lowest incidence. Associated factors are age, church attendance, political orientation, income, self-experienced health and availability of voluntary workers. After adjustment for these characteristics a considerable amount of geographical variation remains (factor score of 7), which calls for further exploration. Conclusion The Netherlands, with 28 years of legal euthanasia, experiences large-scale unexplained geographical variation in the incidence of euthanasia. Other countries that have legalised physician-assisted dying or are in the process of doing so may encounter similar patterns. The unexplained part of the variation may include the possibility that part of the euthanasia practice may have to be understood in terms of underuse, overuse or misuse.

Although it is often recommended that general practitioners (GPs) initiate advance care planning (ACP), little is known about their experiences with ACP. This study aimed to identify GP experiences when conducting ACP conversations with palliative patients, and what factors influence these experiences. Dutch GPs (N = 17) who had participated in a training on timely ACP were interviewed. Data from these interviews were analysed using direct content analysis. Four themes were identified: ACP and society, the GP’s perceived role in ACP, initiating ACP and tailor-made ACP. ACP was regarded as a ‘hot topic’. At the same time, a tendency towards a society in which death is not a natural part of life was recognized, making it difficult to start ACP discussions. Interviewees perceived having ACP discussions as a typical GP task. They found initiating and timing ACP easier with proactive patients, e.g. who are anxious of losing capacity, and much more challenging when it concerned patients with COPD or heart failure. Patients still being treated in hospital posed another difficulty, because they often times are not open to discussion. Furthermore, interviewees emphasized that taking into account changing wishes and the fact that not everything can be anticipated, is of the utmost importance. Moreover, when patients are not open to ACP, at a certain point it should be granted that choosing not to know, for example about where things are going or what possible ways of care planning might be, is also a form of autonomy. ACP currently is a hot topic, which has favourable as well as unfavourable effects. As GPs experience difficulties in initiating ACP if patients are being treated in the hospital, future research could focus on a multidisciplinary ACP approach and the role of medical specialists in ACP. Furthermore, when starting ACP with palliative patients, we recommend starting with current issues. In doing so, a start can be made with future issues kept in view. Although the tension between ACP’s focus on the patient’s direction and the right not to know can be difficult, ACP has to be tailored to each individual patient.