Obstetrics Emergency Labor and Delivery Case Simulations with Normal Vaginal Delivery Demonstration: A Hands-on Simulation for Clerkship Students

Introduction: Simulation is rarely used for medical student education in the field of obstetrics. This method is an effective model of learning for topics that are encountered in clinical situations and for topics that pose significant risk to patients when an untrained individual is involved. Methods: A 2-hour obstetric delivery simulation session was developed and incorporated into the third-year obstetrics and gynecology clerkship rotation at Wright State University Boonshoft School of Medicine. Medical students completed self-guided content reviews with resources provided prior to the session. During the session, each medical student conducted a normal vaginal delivery and one of the emergent cases (umbilical cord prolapse, pre-eclampsia/eclampsia, shoulder dystocia, and postpartum hemorrhage). During each case the Resident facilitator followed a script which included asking questions using gamification strategies to promote a low-stress learning environment. Critical action checklists were used to ensure students gained a strong understanding of topics. Simulation sessions were conducted both remotely and in-person. The simulation experience was evaluated using surveys and quizzes completed prior to and after participating in the simulation session. Results: Students reported that the simulation experience increased their comfort with emergent obstetric situations, increased their medical knowledge, and was beneficial to their education. Discussion: Simulation is an untapped learning method in obstetrics. We developed simulations for obstetric events to provide medical students with hands-on exposure to important obstetric experiences. This simulation session provides the framework for other medical schools to incorporate these obstetric simulations into their clerkship curriculum

What do you do for a living? Toward a more succinct definition of health services research

This commentary discusses the need for, and the advantages of, a more concise, revised definition of the field of health services research. It argues for a definition that includes not only the topics on which health services research focuses but also the goals of health services research. A number of condensed definitions are provided for consideration

The value of health care – a matter of discussion in Germany

BACKGROUND: Interest in assessing the value of health-care services in Germany has considerably increased since the foundation of the Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen, IQWiG (Institute for Quality and Efficiency in Health Care). The practical application of value assessment illustrates how problematic the process can be. In all decisions made for the provision of health care, data concerning the measurable dimensions (quantity and quality of efficacy and effectiveness, validity of the results and costs) flow into a complex and not yet standardized decision-making process concerning public financing. Some of these decisions are based on data of uncertain validity, unknown reproducibility and unclear appropriateness. DISCUSSION: In this paper we describe the theoretical aspects of value from psychological and economic viewpoints and discuss national and international approaches. Methodic details and difficulties in assessing the value of health-care services are analysed. A definition of the intangible value of health-care services will be proposed which contains only three factors: the absolute risk reduction (usually a measure of efficacy), the validity of the scientific papers examined and the type of the expected effectiveness (prevention of death and disability, restitution of well-being). The intangible value describes the additional benefit when comparing two possible actions, like treatment or observation only. CONCLUSION: The description of intangible value from the viewpoint of different stakeholders is a useful measure for subsequent steps (not discussed here) – the evaluation of costs and of patient benefit. A standardised, transparent, fair and democratic evaluation is essential for the definition of a basic benefit package

Conceptualising population health: from mechanistic thinking to complexity science

The mechanistic interpretation of reality can be traced to the influential work by René Descartes and Sir Isaac Newton. Their theories were able to accurately predict most physical phenomena relating to motion, optics and gravity. This paradigm had at least three principles and approaches: reductionism, linearity and hierarchy. These ideas appear to have influenced social scientists and the discourse on population health. In contrast, Complexity Science takes a more holistic view of systems. It views natural systems as being 'open', with fuzzy borders, constantly adapting to cope with pressures from the environment. These are called Complex Adaptive Systems (CAS). The sub-systems within it lack stable hierarchies, and the roles of agency keep changing. The interactions with the environment and among sub-systems are non-linear interactions and lead to self-organisation and emergent properties. Theoretical frameworks such as epi+demos+cracy and the ecosocial approach to health have implicitly used some of these concepts of interacting dynamic sub-systems. Using Complexity Science we can view population health outcomes as an emergent property of CAS, which has numerous dynamic non-linear interactions among its interconnected sub-systems or agents. In order to appreciate these sub-systems and determinants, one should acquire a basic knowledge of diverse disciplines and interact with experts from different disciplines. Strategies to improve health should be multi-pronged, and take into account the diversity of actors, determinants and contexts. The dynamic nature of the system requires that the interventions are constantly monitored to provide early feedback to a flexible system that takes quick corrections

On the relationship between individual and population health

The relationship between individual and population health is partially built on the broad dichotomization of medicine into clinical medicine and public health. Potential drawbacks of current views include seeing both individual and population health as absolute and independent concepts. I will argue that the relationship between individual and population health is largely relative and dynamic. Their interrelated dynamism derives from a causally defined life course perspective on health determination starting from an individual’s conception through growth, development and participation in the collective till death, all seen within the context of an adaptive society. Indeed, it will become clear that neither individual nor population health is identifiable or even definable without informative contextualization within the other. For instance, a person’s health cannot be seen in isolation but must be placed in the rich contextual web such as the socioeconomic circumstances and other health determinants of where they were conceived, born, bred, and how they shaped and were shaped by their environment and communities, especially given the prevailing population health exposures over their lifetime. We cannot discuss the “what” and “how much” of individual and population health until we know the cumulative trajectories of both, using appropriate causal language

Poor glycaemic control is associated with reduced exercise performance and oxygen economy during cardio-pulmonary exercise testing in people with type 1 diabetes

BackgroundTo explore the impact of glycaemic control (HbA1c) on functional capacity during cardio-pulmonary exercise testing in people with type 1 diabetes.MethodsSixty-four individuals with type 1 diabetes (age: 34 ± 8 years; 13 females, HbA1c: 7.8 ± 1% (62 ± 13 mmol/mol), duration of diabetes: 17 ± 9 years) performed a cardio-pulmonary cycle ergometer exercise test until volitional exhaustion. Stepwise linear regression was used to explore relationships between HbA1c and cardio-respiratory data with p ≤ 0.05. Furthermore, participants were divided into quartiles based on HbA1c levels and cardio-respiratory data were analysed by one-way ANOVA. Multiple regression analysis was performed to explore the relationships between changes in time to exhaustion and cardio-respiratory data. Data were adjusted for confounder.ResultsHbA1c was related to time to exhaustion and oxygen consumption at the power output elicited at the sub-maximal threshold of the heart rate turn point (r = 0.47, R2 = 0.22, p = 0.03). Significant differences were found at time to exhaustion between QI vs. QIV and at oxygen consumption at the power output elicited at the heart rate turn point between QI vs. QII and QI vs. QIV (p < 0.05). Changes in oxygen uptake, power output and in oxygen consumption at the power output elicited at the heart rate turn point and at maximum power output explained 55% of the variance in time to exhaustion (r = 0.74, R2 = 0.55, p < 0.01).ConclusionsPoor glycaemic control is related to less economical use of oxygen at sub-maximal work rates and an earlier time to exhaustion during cardio-pulmonary exercise testing. However, exercise training could have the same potential to counteract the influence of poor glycaemic control on functional capacity

A study protocol for applying the co-creating knowledge translation framework to a population health study

BACKGROUND: Population health research can generate significant outcomes for communities, while Knowledge Translation (KT) aims to expressly maximize the outcomes of knowledge producing activity. Yet the two approaches are seldom explicitly combined as part of the research process. A population health study in Port Lincoln, South Australia offered the opportunity to develop and apply the co-KT Framework to the entire research process. This is a new framework to facilitate knowledge formation collaboratively between researchers and communities throughout a research to intervention implementation process. DESIGN: This study employs a five step framework (the co-KT Framework) that is formulated from engaged scholarship and action research principles. By following the steps a knowledge base will be cumulatively co-created with the study population that is useful to the research aims. Step 1 is the initiating of contact between the researcher and the study contexts, and the framing of the research issue, achieved through a systematic data collection tool. Step 2 refines the research issue and the knowledge base by building into it context specific details and conducting knowledge exchange events. Step 3 involves interpreting and analysing the knowledge base, and integrating evidence to inform intervention development. In Step 4 the intervention will be piloted and evaluated. Step 5 is the completion of the research process where outcomes for improvement will be instituted as regular practice with the facilitation of the community. In summary, the model uses an iterative knowledge construction mechanism that is complemented by external evidence to design interventions to address health priorities within the community. DISCUSSION: This is a systematic approach that operationalises the translational cycle using a framework for KT practice. It begins with the local context as its foundation for knowledge creation and ends with the development of contextually applicable interventions. It will be of interest to those involved in KT research, participatory action research, population health research and health care systems studies. The co-KT Framework is a method for embedding the principles of KT into all stages of a community-based research process, in which research questions are framed by emergent data from each previous stage.Kathryn Powell, Alison Kitson, Elizabeth Hoon, Jonathan Newbury, Anne Wilson and Justin Beilb

Analysing key influences over actors' use of evidence in developing policies and strategies in Nigeria: a retrospective study of the Integrated Maternal Newborn and Child Health strategy

Background Evidence-informed policymaking has been promoted as a means of ensuring better outcomes. However, what counts as evidence in policymaking lies within a spectrum of expert knowledge and scientifically generated information. Since not all forms of evidence share an equal validity or weighting for policymakers, it is important to understand the key factors that influence their preferences for different types of evidence in policy and strategy development. Method A retrospective study was carried out at the national level in Nigeria using a case-study approach to examine the Nigerian Integrated Maternal Newborn and Child Health (IMNCH) strategy. Two frameworks were used for conceptualization and data analysis, namely (1) to analyse the role of evidence in policymaking and (2) the policy triangle. They were used to explore the key contextual and participatory influences on choice of evidence in developing the IMNCH strategy. Data was collected through review of relevant national documents and in-depth interviews of purposively selected key policy and strategic decision makers. Thematic analysis was applied to generate information from collected data. Results The breadth of evidence used was wide, ranging from expert opinions to systematic reviews. The choice of different types of evidence was found to overlap across actor categories. Key influences over actors’ choice of evidence were: (1) perceived robustness of evidence – comprehensive, representative, recent, scientifically sound; (2) roles in evidence process, i.e. their degree and level of participation in evidence generation and dissemination, with regards to their role in the policy process; and (3) contextual factors such as global agenda and influence, timeline for strategy development, availability of resources for evidence generation, and lessons learnt from previous unsuccessful policies/plans. Conclusion Actors’ preferences for different types of evidence for policy are influenced not only by the characteristics of evidence itself, but on actors’ roles in the evidence process, their power to influence the policy, and the context in which evidence is used

Staffing and Training Aspects of Hospital Management: Some Issues for Research

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68624/2/10.1177_107755878904600205.pd