Objective: To construct the underlying value structure of shared decision making (SDM) models. Method: We included previously identified SDM models (n = 40) and 15 additional ones. Using a thematic analysis, we coded the data using Schwartz’s value theory to define values in SDM and to investigate value relations. Results: We identified and defined eight values and developed three themes based on their relations: shared control, a safe and supportive environment, and decisions tailored to patients. We constructed a value structure based on the value relations and themes: the interplay of healthcare professionals’ (HCPs) and patients’ skills [Achievement], support for a patient [Benevolence], and a good relationship between HCP and patient [Security] all facilitate patients’ autonomy [Self-Direction]. These values enable a more balanced relationship between HCP and patient and tailored decision making [Universalism]. Conclusion: SDM can be realized by an interplay of values. The values Benevolence and Security deserve more explicit attention, and may especially increase vulnerable patients’ Self-Direction. Practice implications: This value structure enables a comparison of values underlying SDM with those of specific populations, facilitating the incorporation of patients’ values into treatment decision making. It may also inform the development of SDM measures, interventions, education programs, and HCPs when practicing.
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During the past two decades the implementation and adoption of information technology has rapidly increased. As a consequence the way businesses operate has changed dramatically. For example, the amount of data has grown exponentially. Companies are looking for ways to use this data to add value to their business. This has implications for the manner in which (financial) governance needs to be organized. The main purpose of this study is to obtain insight in the changing role of controllers in order to add value to the business by means of data analytics. To answer the research question a literature study was performed to establish a theoretical foundation concerning data analytics and its potential use. Second, nineteen interviews were conducted with controllers, data scientists and academics in the financial domain. Thirdly, a focus group with experts was organized in which additional data were gathered. Based on the literature study and the participants responses it is clear that the challenge of the data explosion consist of converting data into information, knowledge and meaningful insights to support decision-making processes. Performing data analyses enables the controller to support rational decision making to complement the intuitive decision making by (senior) management. In this way, the controller has the opportunity to be in the lead of the information provision within an organization. However, controllers need to have more advanced data science and statistic competences to be able to provide management with effective analysis. Specifically, we found that an important skill regarding statistics is the visualization and communication of statistical analysis. This is needed for controllers in order to grow in their role as business partner..
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Introduction: Shared decision-making is considered to be a key aspect of woman-centered care and a strategy to improve communication, respect, and satisfaction. This scoping review identified studies that used a shared decision-making support strategy as the primary intervention in the context of perinatal care. Methods: A literature search of PubMed, CINAHL, Cochrane Library, PsycINFO, and SCOPUS databases was completed for English-language studies conducted from January 2000 through November 2019 that examined the impact of a shared decision-making support strategy on a perinatal decision (such as choice of mode of birth after prior cesarean birth). Studies that only examined the use of a decision aid were excluded. Nine studies met inclusion criteria and were examined for the nature of the shared decision-making intervention as well as outcome measures such as decisional evaluation, including decisional conflict, decisional regret, and certainty. Results: The 9 included studies were heterogeneous with regard to shared decision-making interventions and measured outcomes and were performed in different countries and in a variety of perinatal situations, such as women facing the choice of mode of birth after prior cesarean birth. The impact of a shared decision-making intervention on women’s perception of shared decision-making and on their experiences of the decision-making process were mixed. There may be a decrease in decisional conflict and regret related to feeling informed, but no change in decisional certainty. Discussion: Despite the call to increase the use of shared decision-making in perinatal care, there are few studies that have examined the effects of a shared decision-making support strategy. Further studies that include antepartum and intrapartum settings, which include common perinatal decisions such as induction of labor, are needed. In addition, clear guidance and strategies for successfully integrating shared decision-making and practice recommendations would help women and health care providers navigate these complex decisions.
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