Implementation science in healthcare: Introduction and perspective

Transcription

1 Z. Evid. Fortbild. Qual. Gesundh. wesen (ZEFQ) (2015) 109, Available online at ScienceDirect journal homepage: SCHWERPUNKT science in healthcare: Introduction and perspective Implementierungsforschung im Gesundheitswesen: Einführung und Ausblick Michel Wensing Radboud University Medical Centre, Radboud Institute for Health Sciences, Nijmegen, The Netherlands Submitted/eingegangen 18 July 2014; revised/überarbeitet 26 February 2015; accepted/akzeptiert 27 February 2015 KEYWORDS science; evidence-based practice; health services research Summary science is the scientific study of the methods to promote the uptake of research findings into routine healthcare in clinical, organisational, or policy contexts. The presence of gaps between knowledge and practice is well documented and a range of strategies is available to overcome these gaps. To optimize their impact, it is recommended that implementation strategies are tailored to the target population, setting and goals for improvement. Themes for future research in the field are: implementation of personalized medicine, the economics of implementation, knowledge implementation in various health professions, patient involvement in implementation, and a better understanding of the determinants of implementation. Addressing these challenges requires dedicated training programs, research funding, and networks for effective collaboration with stakeholders in healthcare. SCHLÜSSELWÖRTER Implementierungsforschung; evidenzbasierte Praxis; Versorgungsforschung Zusammenfassung Implementierungsforschung ist die wissenschaftliche Forschung der Methoden zur Förderung der Umsetzung von Forschungsergebnissen in der klinischen Praxis sowie organisatorischen und politischen Bereichen. Das Vorhandensein von Lücken zwischen Wissen und Praxis ist ausführlich dokumentiert, und es gibt eine Reihe von Strategien, mit denen sich diese Lücken schließen lassen. Um ihre Wirkung zu optimieren, ist es empfehlenswert, die Implementierungsstrategien auf Zielpopulation, Einstellungen und Ziele der Verbesserung zuzuschneiden. Themen für zukünftige Studien auf dem Gebiet sind: Implementierung der personalisierten Medizin, wirtschaftliche Aspekte, Implementierung in verschiedenen Gesundheitsberufe, Patientenbeteiligung und ein besseres Verständnis der Determinanten der Implementierung. Diese Herausforderungen erfordern spezielle Trainingsprogramme, Forschungsförderung und Netzwerke für eine effektive Zusammenarbeit mit den Akteuren im Gesundheitswesen. Corresponding author: Prof.Dr. Michel Wensing, Radboud University Medical Centre, Scientific Institute for Quality in Healthcare, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands. Michel.Wensing@Radboudumc.nl /

2 98 M. Wensing Introduction It is well documented that not all patients receive recommended healthcare, and that some receive clinical or preventive interventions that are not indicated [1]. Likewise, not all managerial and policy decisions in healthcare are guided by the best available research knowledge. Variations in decisions and practices across patients, healthcare providers and geographic regions can help to identify in healthcare delivery. Practice variation can be interpreted in terms of knowledge-practice gaps, if the evidence on recommended practice is sufficiently strong. For instance, anti-platelet therapy has shown to reduce risk for cardiovascular events in patients with coronary heart diseases, but only 83% of 2960 patients with coronary heart disease from 10 countries received it [2]. Investments in basic and clinical research remain wasted if effective clinical or preventive interventions, medical devices or organizational models are not applied in practice. On the other hand, resistance to change is appropriate if it helps to preserve good practices [3]. science is the scientific study of the methods to promote the uptake of research findings into routine healthcare in clinical, organisational, or policy contexts [1,4]. In other words, it concerns the translation of research knowledge into practice. This translation has been referred to as T2, with T1 concerning the translation of basic science into clinical or preventive applications [1]. T2 is the focus of this contribution. science is based on the assumption that research findings, which were generated in a particular population and setting (e.g. clinical trial), can be generalized and applied to a similar population and setting elsewhere. It also assumes that this transfer of knowledge can be studied and developed in a scientific way, and that knowledge of implementation helps to improve health outcomes in patients and populations. The appropriate unit of implementation is the synthesised body of evidence, not a single study, as single studies can be highly misleading [1]. Traditionally, implementation science has focused on continuing education of physicians, which remains a crucial method for promoting the uptake of knowledge in practice. The range of implementation strategies has broadened substantially in recent decades and includes educational, organizational, financial, and regulatory interventions and policies. The overall research questions in implementation science can be summarized as follows: (1) what knowledge from research needs to be made available for translation, and how is this best done? (e.g. what are high-quality clinical guidelines); (2) what are current knowledge-practice gaps and their determinants? (e.g. using quality indicators); (3) which strategies to enhance knowledge uptake are effective?; (4) how can large-scale and sustainable implementation of recommended practice be achieved? It should be noted that implementation science is known under different names, which partly reflect subtle differences in focus, such as knowledge translation and improvement science. science can be positioned simultaneously within clinical research and health services research. Like clinical research, implementation science has a strong focus on outcomes of interventions for patients. The interventions for enhancing uptake of recommended clinical interventions are often complex, so the measures in implementation research often include aspects of professional performance and organisational changes, which are related to patient outcomes. science may address the prevention of disease or health promotion in populations, in which case it can be positioned within public health. An interest in the organisation and processes of healthcare delivery is shared with health services research, which addresses a broader range of organisational and societal issues that are only indirectly linked to implementation science. The implementation of findings from health services research is one focus of implementation science, but so far most of implementation research has focused on the uptake of findings from clinical research and public health. It does not have unique research methods. Rather, a range of research methods from the population sciences is used, including cluster randomized trials, clinical audits, qualitative research, case studies, systematic literature reviews, and economic modelling. Research evidence The journal Science (www. implementationscience.com) and the Cochrane Effective Professional Practice and Organization of Care group ( are two important sources of knowledge in the field, but many other journals and groups have contributed to implementation science in healthcare. Several hundreds of randomized trials of implementation strategies have been published in medical journals as well as thousands of observational studies that are relevant to the field. Comprehensive overviews and summaries of research evidence are available [5]. Focusing on randomized trials of implementation strategies, such as professional education and clinical decision support, it can be concluded that these have variable and, on average, modest impact on professional performance and patient outcomes. For many strategies, these effects are in the range of 5 to 10% absolute change of relevant aspects of professional performance [5]. The outcomes of some widely used programs to improve healthcare, such as quality management programs, have rarely been examined in rigorous evaluation designs. As an example, research on audit and feedback to healthcare professionals is presented in some more detail. Audit and feedback, for instance focused on prescribed medication or complications after surgical procedures, is one of the most widely applied methods for enhancing the uptake of knowledge in practice. It is also an important component of many quality improvement and accreditation programs in healthcare, so it has high practical relevance to understand the impact of this method. The most recent version of the Cochrane review on audit and feedback identified 140 randomized trials [6]. Looking at dichotomous aspects of professional performance, a median effect of 4.3% absolute change was found, albeit with high variation across studies (interquartile range: 0.5% to 16%). Cumulative meta-analysis of this body of evidence suggested that the average effect size has not changed in the previous decade, despite several dozens of new trials in recent years [7]. It was not possible to identify strong predictors of outcomes of audit and feedback, but low performance at baseline, verbal formats,

3 science in healthcare: Introduction and perspective 99 delivery by superior or colleagues, and repeated delivery were associated with higher effects in a meta-regression analysis [6]. The implication of these findings is that further controlled studies of audit and feedback interventions are wasted, and potentially unethical, if these do not explicitly aim to identify which factors contribute to outcomes. Tailored implementation Many experts in the field of implementation science have argued that implementation strategies need to be tailored to the target population, setting and goals for improvement [8]. This is similar to patient care, where a diagnosis usually precedes the choice of treatment. A systematic, planned approach to implementation comprises of a series of steps: (a) clear specification of the knowledge that is to be implemented, such as a clinical practice guideline or organizational model, (b) careful analysis of current practice, including determinants of knowledge-practice gaps, (c) matching of strategies to targeted determinants of practice, (d) application and evaluation of strategies, if necessary followed by (e) adaptation of targets for improvement and/or implementation strategies, and finally (g) organization of wide-scale and sustainable implementation. This stepwise model for implementation is obviously an abstraction from reality, which is often complex and dynamic, so that deviations and repeated loops are needed. Nevertheless, it provides practical guidance and reminds practitioners to reflect before acting. Although tailored implementation is recommended, little is known about the validity of different tailoring methods. For instance, it is unclear what the most appropriate level is for tailoring (geographic region, hospital or practice, clinician, or specific behaviours), which stakeholders should be involved in the tailoring process (clinicians, patients, health insurers), and which methods are best used to collect data on barriers for change (group interviews, etc.). In the Tailored in Chronic Diseases (TICD) project, an international research project funded by the European Commission, we developed and tested several tailoring methods. As a preparation for five cluster randomized trials of tailored implementation programs in different chronic diseases, we performed studies to identify barriers for change and to match strategies to identified barriers [9]. These showed, for instance, that 115 individuals from different stakeholders in group sessions of 2 hours each, generated 812 ideas for strategies to improve healthcare practice. The ideas largely mapped onto three domains: individual health professional factors (52% of items), patient factors (29%), and professional interactions (12%). The relative numbers of items in the different domains were similar across stakeholder categories within each of the countries. Given the scarcity of research, more studies are needed on the validity and effectiveness of tailoring methods, before firm recommendations can be given on tailored implementation. Theories on implementation A range of scientific disciplines contribute theories, which are potentially useful for the design and evaluation of knowledge implementation in healthcare [10]. For instance, a number of psychological theories focus on individual behaviour change; economic theory focuses on costs and revenues of changes in volume of services, as well as on the impact of economic structures; and organizational theories elaborate on the impact of organizations on change, considering issues such as leadership and organizational culture. A classic theory for implementation science is the Diffusion of Innovation theory, which was originally developed to explain the spread of innovations in agriculture [11,12]. Theories can offer new perspectives, which broaden the range of issues considered, building on knowledge generated by previous research. Some theories also suggest specific determinants and causal mechanisms of change, which can be instrumentally used to design interventions. An example of the latter is the Behaviour Change Wheel, which links interventions to determinants of change [13]. In addition to theories, there is a large number of conceptual frameworks, many of which integrate theories in an attempt to make these practically useful for practitioners, managers and policy makers [14,15]. Table 1 provides examples of some theories and frameworks, which are currently used in implementation science. Emerging themes A number of themes is emerging in international implementation science in healthcare. Personalized medicine offers the perspective that treatments will be tailored to individuals on the basis of a fundamental understanding of genetic factors, biomarkers and possibly also other characteristics of individuals. In clinical areas in which this perspective has become reality, the character of what comprises research evidence has changed. Clinical guidelines with broad recommendations are replaced by complex sets of clinical decision rules, which integrate all relevant knowledge and are continuously updated when necessary. Clinical decision support systems have been an important area of implementation science for a long time. The research evidence on their impact suggests that they can improve healthcare delivery and, to a lesser extent, health outcomes [16]. However, they are not consistently effective. Important challenges are to optimize the clinical relevance of computerized decision support is provided and to improve the actual use of alerts and reminders by clinicians. The economics of implementation comprises another new theme, partly as the result of macro-economic problems and rising costs of healthcare in recent years. A preventive and clinical intervention may be cost-effective in a clinical trial, but its large-scale implementation requires additional resources that are often ignored in traditional health technology assessment (e.g. education of professionals on new knowledge). If the implementation costs are high, the total cost-effectiveness of an intervention is less good than suggested by the clinical trial. A further issue is the savings after implementation are not necessarily received by the organizations who actually implement the intervention. For instance, primary care physicians can provide additional care which reduce the number of hospital admissions, but often they do not receive the savings. Stopping practices that are not effective, or have questionable

4 100 M. Wensing Table 1 Examples of theories and frameworks used in science. Short label Discipline or field of origin Key ideas Behaviour change theory [1] Psychology Behaviour is determined by individual motivation, capability and opportunity. Diffusion of innovations theory [2] Sociology Innovations spread in social networks, influenced by innovation characteristics and change agents, according to a S-shaped curve. Normalisation process theory [2] Sociology Practices are determined by perceived coherence of intervention, cognitive participation of target group, collective action, and reflexive monitoring. Organisational readiness theory [3] Organisational science Change is dependent on organisational members shared commitment and efficacy for change. Standard theory of the firm [4] Economics Supply of a service is dependent on price and demand, and influenced by transparency of service characteristics. Framework for planned change [5] Consolidated Framework for Research [6] Framework for the knowledge to action process [7] Framework for tailored implementation in chronic diseases [8] Quality improvement in healthcare science in nursing science in healthcare science in primary care Planning of change needs to take into account the nature of the innovation; characteristics of the professionals and patients involved; and the social, organisational, economic and political context. is determined by intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Translation of knowledge to action depends on a cyclic process, involving tailored strategies and outcomes monitoring, around knowledge creation. is influenced by guideline factors, individual health professional factors, patient factors, professional interactions, incentives and resources, capacity for organisational change, and social, political, and legal factors. References: [1] Michie et al. The behavior change wheel: a new method for characterising and designing behaviour change interventions. Implem Sci 2011;6:42. [2] Rogers EM. Diffusion of innovations. First-second-third edition. New York: The Free Press, [3] May CR et al. Development of a theory of implementation and integration: Normalization Process Theory. Implem Sci 2009;4:29. [4] Weiner B. A theory of organizational readiness for change. Implem Sci 2009;4:67. [5] Grol R, Wensing M. What drives change: barriers and incentives to achieving evidence based practice. Med J Austr 2004;180:S [6] Damschröder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implem Sci 2009; 4:50. [7] Graham ID, Logan J, Harrison MB, Straus SE, Tetroe J, Caswell W, Robinson N. Lost in knowledge translation: time for a map? J Contin Educ Health Prof 2006;26: [8] Flottorp SA, Oxman AD, Krause J, Musila NR, Wensing M, Godycki-Cwirko M, Baker R, and Eccles MP. A checklist for identifying determinants of practice: a systematic review and synthesis of frameworks and taxonomies of factors that prevent or enable improvements in healthcare professional practice. Implem Sci 2013;8:35. effectiveness ( de-implementation ), is also an important aspect of the economics of implementation. Studies of the implementation of research knowledge in healthcare have largely focused on physicians and nurses. Much less research has focused on other implementation by nonphysician clinical professionals, such as pharmacists, psychologists or dentists. Obviously, the development and implementation of a body of research knowledge is equally important for other professions. Likewise, relatively little research has focused on healthcare managers and policy-makers, although evidence-based policy making is an emerging field [17]. While the principles and methods of remain the same, it is likely that knowledge implementation in these groups has specific features that differ from those of physicians and nurses in clinical practice. of evidence-based practice has mostly focused on healthcare professionals, but patients may contribute to it as well. Patient involvement in implementation is a particularly relevant case for patients with chronic diseases, who influence their health outcomes through their use of treatments and life-styles. The boundaries between interventions to enhance patients treatment adherence or self-management and patient-mediated strategies for the implementation of evidence-based practice can be blurry. Also, knowledge implementation may be perceived as successful, if a patient is well informed and involved in the decision-making process, regardless of the actual decision or practice. An implication is that we need better indicators for successful implementation of evidence-based practice, because currently most indicators focus on decisions and practices.

5 science in healthcare: Introduction and perspective 101 Better understanding of the determinants of implementation is the last emerging theme that is mentioned here. Broadly, these determinants can be sought in the individual decision-makers (cognitions and behaviours) or in the context in which they work (organizations, financial structures, culture, and regulations). A related issue is that a better understanding of implementation strategies is needed, starting with a more detailed description of their components than is currently done [18]. There is no shortage of theories, frameworks and models in implementation science (see Table 1) [19,20]. The development of the Theoretical Domains Framework, which summaries many theories on behaviour change, is a major achievement in recent years [13]. There is range of other theories and frameworks, which provide insight into contextual determinants of knowledge implementation, but there is no similarly comprehensive framework for these theories on contextual determinants of implementation. Furthermore, there are few head-to-head tests of competing theories in implementation research, because many researchers limit themselves to a specific theory. More rigorous theory-orientated empirical research would therefore contribute to the development of implementation science. Training and funding science in healthcare is an applied health science, which focuses on important problems and needs as defined by practitioners, managers and policy makers in healthcare. These differ across settings and over time, and as a logical consequence of this, so does the focus of implementation science. The field has provided a substantial body of scientific knowledge and to some extent it has its internal dynamics, which drive innovation of its concepts and methods. Nevertheless, there have been calls for more well-trained researchers in the field [21] as well as for research funders support for implementation science [22]. Dedicated funding programs and training schemes for implementation science in healthcare have been created in several countries, such as Canada and the United States. In other countries, including Germany and Switzerland, the announced programs for health services research hold the promise that they will support implementation science in healthcare. Conclusion science in healthcare has become an internationally established academic field, which has provided a body of knowledge that has practical relevance for decision makers. Developments in healthcare provide questions whose require new research in this field. This requires dedicated training academic programs, research funding, collaboration with health professionals and clinical researchers as well as quality managers at different levels in healthcare. Conflict of Interest No conflict of interest. References [1] Grimshaw JM, Eccles MP, Lavis JN, Hill SJ, Squires JE. Knowledge translation of research findings. Implem Sci 2012; 7:50. [2] Van Lieshout J, Grol R, Campbell S, Falchoff H, Frigola Capell E, Glehr M, et al. Cardiovascular risk management in patients with coronary heart disease in primary care: variation across countries and practices. an observational study based on quality indicators. BMC Fam Pract 2012;13:96. [3] Dixon-Woods M, Amalberti R, Goodman S, Bergman B, Glasziou P. Problems and promises of innovation: why healthcare needs to rethink its love/hate relationship with the new. BMJ Qual Saf 2011;20:i [4] Proctor EK, Landsverk J, Aarons G, Chambers D, Glisson C. Mittman. research in mental health services: an emerging science with conceptual, methodological, and training challenges. Adm Policy Ment Health 2009;36: [5] Grol R, Wensing M, Eccles M. Davies. Improving patient care. The implementation of change in clinical practice. Second edition London: Wiley, BMJ Books; [6] Ivers N, Jamtvedt G, Flottorp S, Young JM, Odgaard-Jensen J, French SD, et al. Audit and feedback: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev 2012;6:CD [7] Ivers NM, Grimshaw JM, Jamtvedt G, Flottorp S, O Brien MA, French SD, et al. Growing literature, stagnant science? Systematic review, meta-regression and cumulative meta-analysis of audit and feedback interventions in healthcare. J Gen Intern Med 2014 (in press). [8] Wensing M, Bosch M, Grol R. Developing and selecting interventions for translating knowledge to action. Can Med Assoc J 2010;182:E85 8. [9] Wensing M, Huntink E, Van Lieshout J, Godycki-Cwirko M, Kowalczyk A, Jäger C, Steinhäuser J, Aakhus E, Flottorp S, Eccles M, Baker R. Tailored implementation of evidence-based practice for patients with chronic diseases. PLoS ONE 9(7): e [10] Grol R, Bosch M, Hulscher M, Eccles M, Wensing M. Planning and studying improvement in patient care: the use of theoretical perspectives. Milbank Quaterly 2006;85: [11] Rogers EM. Diffusion of innovations. Fourth edition New York: The Free Press; [12] Estabrooks CA, Derksen L, Winther C, Lavis JN, Scott SD, Wallin L, et al. The intellectual structure and substance of the knowledge utilization field: a longitudinal author co-citation analysis, 1945 to Implem Sci 2008;3:49. [13] Michie S, Van Stralen MM, West R. The behaviour change wheel: a new method for characterizing and designing behavior change interventions. Implem Sci 2011;6:42. [14] Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implem Sci 2009;4:50. [15] Flottorp SA, Oxman AD, Krause J, Musila NR, Wensing M, Godycki-Cwirko M, et al. A checklist for identifying determinants of practice: a systematic review and synthesis of frameworks and taxonomies of factors that prevent or enable improvements in healthcare professional practice. Implem Sci 2013;8:35. [16] Jones SS, Rudin RS, Perry T, Shekelle PG. Health information technology: an updated systematic review with a focus on meaningful use. Ann Intern Med 2014;160: [17] Lavis JN, Rottingen JA, Bosch-Capblanch X, Atun R, El-Jardali F, Gilson L, et al. Guidance for evidence-based policies about health systems: linking guidance development to policy development. PLOS Med 2012;9,

6 102 M. Wensing [18] Proctor EK, Powell BJ, McMillen JC. strategies: recommendations for specifying and reporting. Implem Sci 2013;8:139. [19] Greenhalgh T, Robert G, MacFarlane F, Bate P, Kyriakidou O. Diffusion of innovations in service organizations: systematic review and recommendations. Milbank Q 2004;82: [20] Tabak RG, Khoong EC, Chambers DA, Brownson RC. Bridging research and practice. Models for dissemination and implementation research. Am J Prev Med 2012;43: [21] Grol R, Berwick DM, Wensing M. On the trail of quality and safety in health care. BMJ 2008;336:74 6. [22] Tetroe JM, Graham ID, Foy R, Robinson N, Eccles M, Ward J, et al. Health Research Funding Agencies Support and Promotion of Knowledge Translation: an International Study. Milbank Quarterly 2008;86: Journalistenpreis,,Evidenzbasierte Medizin in den Medien für Daniela Remus AUS DEN GESELLSCHAFTEN Am 13. März 2015 wurde Daniela Remus mit dem Journalistenpreis,,Evidenzbasierte Medizin in Medien ausgezeichnet. Bereits zum siebten Mal verlieh das Deutsche Netzwerk Evidenzbasierte Medizin e.v. den Journalistenpreis,,Evidenzbasierte Medizin in den Medien. Mit diesem Euro dotierten Preis können Arbeiten aus dem Print-, TV-, Hörfunk- oder Onlinebereich ausgezeichnet werden, die in deutschsprachigen Medien die Prinzipien der Evidenzbasierten Medizin in ihren journalistischen Arbeiten umsetzen. Für die Ausschreibung 2015 wurde eine Rekordzahl von 41 Beiträgen eingereicht. Preisträgerin 2015 ist die Journalistin Daniela Remus für ihren Hörfunkbeitrag,,Gesellschaft von Kranken? Umstrittene Grenzwerte in der Medizin, der am 7. Oktober 2014 bei Bayern 2 gesendet wurde. Daniela Remus hat einen interessanten, spannenden und handwerklich großartig gelungenen Hörfunkbeitrag produziert, der die Stellschraube Grenzwert als Indikation von medizinischen Interventionen zum Inhalt hat. Sie wirft Fragen auf wie: Worum geht es eigentlich in der Behandlung? Geht es darum, das Wohlbefinden wiederherzustellen, oder geht es um die Optimierung physiologischer Parameter? Und wenn ja, wann gelten diese Parameter als optimal? Und vor allem: Wer legt das fest und mit welchen Methoden? Grenzwerte für Blutdruck, Cholesterin, Blutzucker aber auch für Traurigkeit oder Schüchternheit können selbst zur Krankheit werden. Die Macht der Grenzwerte steht dem subjektiven Empfinden der Patientin bzw. des Patienten gegenüber. Wird ein Grenzwert abgesenkt, kann für einen, sich völlig gesund fühlenden, Menschen eine Behandlungsbedürftigkeit erwachsen. Die Autorin Remus weist darauf hin, dass Erkrankungen durch eine Summe von Risikofaktoren ausgelöst werden. Die ärztliche Diagnostik darf deshalb nicht an einzelnen starren Grenzwerten ausgerichtet sein. Diagnosen haben nur dann einen Wert, wenn sie zu wirkungsvollen Interventionen führen, die das Wohlbefinden der Patientin bzw. des Patienten tatsächlich verbessern können. Von der ersten bis zur 25. Minute dieses Hörfunkbeitrages gelingt es Daniela Remus den Spannungsbogen aufrecht zu erhalten. Der Hintergrund der evidenzbasierten Medizin wird anhand vieler Beispiele sehr gut erklärt. Patientinnen und Patienten, die diesen Beitrag gehört haben, werden Ärztinnen und Ärzten nach dem Lesen sicher skeptischer und nachfragender gegenübertreten. Wer in Zeiten von Facebook, Youtube, Twitter und Co. Hörfunkbeiträge für einen Anachronismus hält, wird mit diesem Beitrag eines Besseren belehrt. Die Jury war der Meinung, dass der Hörfunkbeitrag von Daniela Remus es wert ist, sich Zeit zum Zuhören zu nehmen. Eine Eigenschaft, die auch Ärztinnen und Ärzte immer wieder trainieren sollten, statt sich an aus den Fugen geratenen Grenzwerten zu orientieren. Der Journalistenpreis,,Evidenzbasierte Medizin in den Medien wurde anlässlich der 16. Jahrestagung des Deutschen Netzwerks Evidenzbasierte Medizin e.v. in Berlin feierlich an Frau Remus überreicht. Korrespondenzadresse: Karsta Sauder Master Organizational Psychology Leiterin der Geschäftsstelle Deutsches Netzwerk Evidenzbasierte Medizin e. V. Kuno-Fischer-Straße Berlin Tel: +49 (0) sauder@ebm-netzwerk.de