The promise of science lies in expectations of its benefits to societies and is matched by expectations of the realisation of the significant public investment in that science. In this paper, we undertake a methodological analysis of the science of biobanking and a sociological analysis of translational research in relation to biobanking. Part of global and local endeavours to translate raw biomedical evidence into practice, biobanks aim to provide a platform for generating new scientific knowledge to inform development of new policies, systems and interventions to enhance the public’s health. Effectively translating scientific knowledge into routine practice, however, involves more than good science. Although biobanks undoubtedly provide a fundamental resource for both clinical and public health practice, their potentiating ontology—that their outputs are perpetually a promise of scientific knowledge generation—renders translation rather less straightforward than drug discovery and treatment implementation. Biobanking science, therefore, provides a perfect counterpoint against which to test the bounds of translational research. We argue that translational research is a contextual and cumulative process: one that is necessarily dynamic and interactive and involves multiple actors. We propose a new multidimensional model of translational research which enables us to imagine a new paradigm: one that takes us from bench to bedside to backyard and beyond, that is, attentive to the social and political context of translational science, and is cognisant of all the players in that process be they researchers, health professionals, policy makers, industry representatives, members of the public or research participants, amongst others.
Currently, autism cannot be reliably diagnosed before the age of 2 years, which is why longitudinal studies of high-risk populations provide the potential to generate unique knowledge about the development of autism during infancy and toddlerhood prior to symptom onset. Early autism research is an evolving field in child psychiatric science. Key objectives are fine mapping of neurodevelopmental trajectories and identifying biomarkers to improve risk assessment, diagnosis and treatment. ESSEA (Enhancing the Scientific Study of Early Autism) is a COST (European Cooperation in Science and Technology) Action striving to create a European collaboration to enhance the progress of the discovery and treatment of the earliest signs of autism, and to establish European practice guidelines on early identification and intervention by bringing together European expertise from cognitive neuroscience and clinical sciences. The objective of this article is to clarify the state of current European research on at-risk autism research, and to support the understanding of different contexts in which the research is being conducted. We present ESSEA survey data on ongoing European high-risk ASD studies, as well as perceived challenges and opportunities in this field of research. We conclude that although high-risk autism research in Europe faces several challenges, the existence of several key factors (e.g., new and/or large-scale autism grants, availability of new technologies, and involvement of experienced research groups) lead us to expect substantial scientific and clinical developments in Europe in this field during the next few years.
Autism; Europe; Diagnosis; Technology; Infants; High-risk
The US healthcare delivery system is in a state of change. Medical science and technology are advancing at an unprecedented rate, while cost containment and productivity pressures on clinicians make the clinical environment less than ideal for training. Training is one of the vehicles for addressing new knowledge requirements and for enhancing human and system based performance. Yet the theoretical underpinnings and design aspects of training have been largely unrecognized and unexamined in health care. This paper first explores changes in the practice of medicine and the healthcare delivery environment. It then describes how healthcare training and education can benefit from findings in the behavioral and cognitive sciences. It describes the systems approach to training and explores the extent to which a systems approach can be applied to the clinical environment. Finally, the paper examines innovative training and education techniques that are already gaining acceptance in health care.
patient safety; medical education; training; design; cognitive psychology; behavioral psychology
In Germany, clinical trials and comparative effectiveness studies in primary care are still very rare, while their usefulness has been recognised in many other countries. A network of researchers from German academic general practice has explored the reasons for this discrepancy.
Based on a comprehensive literature review and expert group discussions, problem analyses as well as structural and procedural prerequisites for a better implementation of clinical trials in German primary care are presented.
In Germany, basic biomedical science and technology is more reputed than clinical or health services research. Clinical trials are funded by industry or a single national programme, which is highly competitive, specialist-dominated, exclusive of pilot studies, and usually favours innovation rather than comparative effectiveness studies. Academic general practice is still not fully implemented, and existing departments are small. Most general practitioners (GPs) work in a market-based, competitive setting of small private practices, with a high case load. They have no protected time or funding for research, and mostly no research training or experience. Good Clinical Practice (GCP) training is compulsory for participation in clinical trials. The group defined three work packages to be addressed regarding clinical trials in German general practice: (1) problem analysis, and definition of (2) structural prerequisites and (3) procedural prerequisites. Structural prerequisites comprise specific support facilities for general practice-based research networks that could provide practices with a point of contact. Procedural prerequisites consist, for example, of a summary of specific relevant key measures, for example on a web platform. The platform should contain standard operating procedures (SOPs), templates, checklists and other supporting materials for researchers.
All in all, our problem analyses revealed that a substantial number of barriers contribute to the low implementation of clinical research in German general practice. Some issues are deeply rooted in Germany’s market-based healthcare and academic systems and traditions. However, new developments may facilitate change: recent developments in the German research landscape are encouraging.
Clinical trials; General practice; Barriers; Comparative effectiveness research; Research support
Personalized healthcare holds the promise of ensuring that every patient receives optimal wellness promotion and clinical care based upon his or her unique and multi-factorial phenotype, informed by the most up-to-date and contextually relevant science. However, achieving this vision requires the management, analysis, and delivery of complex data, information, and knowledge. While there are well-established frameworks that serve to inform the pursuit of basic science, clinical, and translational research in support of the operationalization of the personalized healthcare paradigm, equivalent constructs that may enable biomedical informatics innovation and practice aligned with such objectives are noticeably sparse. In response to this gap in knowledge, we propose such a framework for the advancement of biomedical informatics in order to address the fundamental information needs of the personalized healthcare domain. This framework, which we refer to as a “4I” approach, emphasizes the pursuit of research and practice that is information-centric, integrative, interactive, and innovative.
Individualized Medicine; Informatics; Organization & Administration
The Canadian Institutes of Health Research (CIHR) has defined knowledge translation (KT) as a dynamic and iterative process that includes the synthesis, dissemination, exchange, and ethically-sound application of knowledge to improve the health of Canadians, provide more effective health services and products, and strengthen the healthcare system. CIHR, the national health research funding agency in Canada, has undertaken to advance this concept through direct research funding opportunities in KT. Because CIHR is recognized within Canada and internationally for leading and funding the advancement of KT science and practice, it is essential and timely to evaluate this intervention, and specifically, these funding opportunities.
The study will employ a novel method of participatory, utilization-focused evaluation inspired by the principles of integrated KT. It will use a mixed methods approach, drawing on both quantitative and qualitative data, and will elicit participation from CIHR funded researchers, knowledge users, KT experts, as well as other health research funding agencies. Lines of inquiry will include an international environmental scan, document/data reviews, in-depth interviews, targeted surveys, case studies, and an expert review panel. The study will investigate how efficiently and effectively the CIHR model of KT funding programs operates, what immediate outcomes these funding mechanisms have produced, and what impact these programs have had on the broader state of health research, health research uptake, and health improvement.
The protocol and results of this evaluation will be of interest to those engaged in the theory, practice, and evaluation of KT. The dissemination of the study protocol and results to both practitioners and theorists will help to fill a gap in knowledge in three areas: the role of a public research funding agency in facilitating KT, the outcomes and impacts KT funding interventions, and how KT can best be evaluated.
The methods for healthcare reform are strikingly underdeveloped, with much reliance on political power. A methodology that combined methods from sources such as clinical trials, experience-based wisdom, and improvement science could be among the aims of the upcoming work in the USA on comparative effectiveness and on the agenda of the Center for Medicare and Medicaid Innovation in the Centers for Medicare and Medicaid Services. Those working in quality improvement have an unusual opportunity to generate substantial input into these processes through professional organisations such as the Academy for Healthcare Improvement and dominant leadership organisations such as the Institute for Healthcare Improvement.
Public policy; quality improvement; comparative effectiveness research; continuous quality improvement; health policy; leadership; randomised controlled trial; research
Shared decision making (SDM) is a process by which a healthcare choice is made jointly by the healthcare professional and the patient. SDM is the essential element of patient-centered care, a core concept of primary care. However, SDM is seldom translated into primary practice. Continuing professional development (CPD) is the principal means by which healthcare professionals continue to gain, improve, and broaden the knowledge and skills required for patient-centered care. Our international collaboration seeks to improve the knowledge base of CPD that targets translating SDM into the clinical practice of primary care in diverse healthcare systems.
Funded by the Canadian Institutes of Health Research (CIHR), our project is to form an international, interdisciplinary research team composed of health services researchers, physicians, nurses, psychologists, dietitians, CPD decision makers and others who will study how CPD causes SDM to be practiced in primary care. We will perform an environmental scan to create an inventory of CPD programs and related activities for translating SDM into clinical practice. These programs will be critically assessed and compared according to their strengths and limitations. We will use the empirical data that results from the environmental scan and the critical appraisal to identify knowledge gaps and generate a research agenda during a two-day workshop to be held in Quebec City. We will ask CPD stakeholders to validate these knowledge gaps and the research agenda.
This project will analyse existing CPD programs and related activities for translating SDM into the practice of primary care. Because this international collaboration will develop and identify various factors influencing SDM, the project could shed new light on how SDM is implemented in primary care.
The interface of engineering and medicine is one of the most productive and promising areas with respect to the future of healthcare here in the US as well as worldwide. However, the scale and complexity of today's biomedical and biological engineering research problems increasingly demand that researchers move beyond the confines of their own discipline and explore new organizational models for team science. While the breadth of knowledge in life and engineering sciences has grown exponentially, technology has become increasingly complex for these different scales. At the same time, the business of delivering sustainable, high-quality health care has become increasingly challenging and expensive. Creating new, cost-effective medicines and healthcare systems that both empower and improve patient care requires a collaborative approach across disciplines. The convergence of Life Sciences and Engineering opens the door to such new possibilities. I will provide specific personal examples involving glycomics, nanotechnology and team science of such possibilities in my talk.
The NIDCR-supported Practice-based Research Network initiative presents dentistry with an unprecedented opportunity by providing a pathway for modifying and advancing the profession. It encourages practitioner participation in the transfer of science into practice for the improvement of patient care. PBRNs vary in infrastructure and design, and sustaining themselves in the long term may involve clinical trial validation by regulatory agencies. This paper discusses the PBRN concept in general and uses the New York University College of Dentistry’s Practitioners Engaged in Applied Research and Learning (PEARL) Network as a model to improve patient outcomes. The PEARL Network is structured to ensure generalizability of results, data integrity, and to provide an infrastructure in which scientists can address clinical practitioner research interests. PEARL evaluates new technologies, conducts comparative effectiveness research, participates in multidisciplinary clinical studies, helps evaluate alternative models of healthcare, educates and trains future clinical faculty for academic positions, expands continuing education to include “benchmarking” as a form of continuous feedback to practitioners, adds value to dental schools’ educational programs, and collaborates with the oral health care and pharmaceutical industries and medical PBRNs to advance the dental profession and further the integration of dental research and practice into contemporary healthcare (NCT00867997, NCT01268605).
Practice-based Research Network; good clinical practice; clinical studies; patient-reported outcomes; Comparative Effectiveness Research (CER); Evidence-based Dentistry (EBD)
Multi-disciplinary and multi-site biomedical research programs frequently require infrastructures capable of enabling the collection, management, analysis, and dissemination of heterogeneous, multi-dimensional, and distributed data and knowledge collections spanning organizational boundaries. We report on the design and initial deployment of an extensible biomedical informatics platform that is intended to address such requirements.
A common approach to distributed data, information, and knowledge management needs in the healthcare and life science settings is the deployment and use of a service-oriented architecture (SOA). Such SOA technologies provide for strongly-typed, semantically annotated, and stateful data and analytical services that can be combined into data and knowledge integration and analysis “pipelines.” Using this overall design pattern, we have implemented and evaluated an extensible SOA platform for clinical and translational science applications known as the Translational Research Informatics and Data-management grid (TRIAD). TRIAD is a derivative and extension of the caGrid middleware and has an emphasis on supporting agile “working interoperability” between data, information, and knowledge resources.
Based upon initial verification and validation studies conducted in the context of a collection of driving clinical and translational research problems, we have been able to demonstrate that TRIAD achieves agile “working interoperability” between distributed data and knowledge sources.
Informed by our initial verification and validation studies, we believe TRIAD provides an example instance of a lightweight and readily adoptable approach to the use of SOA technologies in the clinical and translational research setting. Furthermore, our initial use cases illustrate the importance and efficacy of enabling “working interoperability” in heterogeneous biomedical environments.
Clinical research informatics; data access; data integration; data analysis; standards; workflow; socio-organizational issues
Communities of Practice (CoPs) are promoted in the healthcare sector as a means of generating and sharing knowledge and improving organisational performance. However CoPs vary considerably in the way they are structured and operate in the sector. If CoPs are to be cultivated to benefit healthcare organisations, there is a need to examine and understand their application to date. To this end, a systematic review of the literature on CoPs was conducted, to examine how and why CoPs have been established and whether they have been shown to improve healthcare practice.
Peer-reviewed empirical research papers on CoPs in the healthcare sector were identified by searching electronic health-databases. Information on the purpose of establishing CoPs, their composition, methods by which members communicate and share information or knowledge, and research methods used to examine effectiveness was extracted and reviewed. Also examined was evidence of whether or not CoPs led to a change in healthcare practice.
Thirty-one primary research papers and two systematic reviews were identified and reviewed in detail. There was a trend from descriptive to evaluative research. The focus of CoPs in earlier publications was on learning and exchanging information and knowledge, whereas in more recently published research, CoPs were used more as a tool to improve clinical practice and to facilitate the implementation of evidence-based practice. Means by which members communicated with each other varied, but in none of the primary research studies was the method of communication examined in terms of the CoP achieving its objectives. Researchers are increasing their efforts to assess the effectiveness of CoPs in healthcare, however the interventions have been complex and multifaceted, making it difficult to directly attribute the change to the CoP.
In keeping with Wenger and colleagues' description, CoPs in the healthcare sector vary in form and purpose. While researchers are increasing their efforts to examine the impact of CoPs in healthcare, cultivating CoPs to improve healthcare performance requires a greater understanding of how to establish and support CoPs to maximise their potential to improve healthcare.
Healthcare and medical research in Germany have reached a high standard. The existing competence, however, is scattered across the country. The German Ministry for Research and Technology therefore supports the creation of nationwide networks to encompass these problems. The ”Competence Network on Acute and Chronic Leukemia” aims on the creation of efficient horizontal and vertical communication structures to enhance communication between basic sciences, clinical studies, medical expert groups and general practices by sharing general medical knowledge and electronic patient files. In the first year of the project, the infrastructure was made available to support these tasks.
Healthcare is a complex adaptive system, and efforts to improve through the implementation of best practice are well served by various interacting disciplines within the system. As a transdisciplinary model is new to clinicians, an infrastructure that creates academic-practice partnerships and builds capacity for scientific collaboration is necessary to test, spread, and implement improvement strategies. This paper describes the adoption of best practices from the science of team science in a healthcare improvement research network and the impact on conducting a large-scale network study. Key components of the research network infrastructure were mapped to a team science framework and evaluated in terms of their effectiveness and impact on a national study of nursing operations. Results from this study revealed an effective integration of the team science principles which facilitated the rapid collection of a large dataset. Implications of this study support a collaborative model for improvement research and stress a need for future research and funding to further evaluate the impact on dissemination and implementation.
Continuing challenges to timely adoption of evidence-based clinical practices in healthcare have generated intense interest in the development and application of new implementation methods and frameworks. These challenges led the United States (U.S.) Department of Veterans Affairs (VA) to create the Quality Enhancement Research Initiative (QUERI) in the late 1990s. QUERI's purpose was to harness VA's health services research expertise and resources in an ongoing system-wide effort to improve the performance of the VA healthcare system and, thus, quality of care for veterans. QUERI in turn created a systematic means of involving VA researchers both in enhancing VA healthcare quality, by implementing evidence-based practices, and in contributing to the continuing development of implementation science.
The efforts of VA researchers to improve healthcare delivery practices through QUERI and related initiatives are documented in a growing body of literature. The scientific frameworks and methodological approaches developed and employed by QUERI are less well described. A QUERI Series of articles in Implementation Science will illustrate many of these QUERI tools. This Overview article introduces both QUERI and the Series.
The Overview briefly explains the purpose and context of the QUERI Program. It then describes the following: the key operational structure of QUERI Centers, guiding frameworks designed to enhance implementation and related research, QUERI's progress and promise to date, and the Series' general content. QUERI's frameworks include a core set of steps for diagnosing and closing quality gaps and, simultaneously, advancing implementation science. Throughout the paper, the envisioned involvement and activities of VA researchers within QUERI Centers also are highlighted. The Series is then described, illustrating the use of QUERI frameworks and other tools designed to respond to implementation challenges.
QUERI's simultaneous pursuit of improvement and research goals within a large healthcare system may be unique. However, descriptions of this still-evolving effort, including its conceptual frameworks, methodological approaches, and enabling processes, should have applicability to implementation researchers in a range of health care settings. Thus, the Series is offered as a resource for other implementation research programs and researchers pursuing common goals in improving care and developing the field of implementation science.
Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this research was to form a partnership of healthcare providers, managers, and researchers to review randomized controlled trials assessing the effects of computerized decision support for six clinical application areas: primary preventive care, therapeutic drug monitoring and dosing, drug prescribing, chronic disease management, diagnostic test ordering and interpretation, and acute care management; and to identify study characteristics that predict benefit.
The review was undertaken by the Health Information Research Unit, McMaster University, in partnership with Hamilton Health Sciences, the Hamilton, Niagara, Haldimand, and Brant Local Health Integration Network, and pertinent healthcare service teams. Following agreement on information needs and interests with decision-makers, our earlier systematic review was updated by searching Medline, EMBASE, EBM Review databases, and Inspec, and reviewing reference lists through 6 January 2010. Data extraction items were expanded according to input from decision-makers. Authors of primary studies were contacted to confirm data and to provide additional information. Eligible trials were organized according to clinical area of application. We included randomized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a computerized clinical decision support system compared with patient care without such a system.
Data will be summarized using descriptive summary measures, including proportions for categorical variables and means for continuous variables. Univariable and multivariable logistic regression models will be used to investigate associations between outcomes of interest and study specific covariates. When reporting results from individual studies, we will cite the measures of association and p-values reported in the studies. If appropriate for groups of studies with similar features, we will conduct meta-analyses.
A decision-maker-researcher partnership provides a model for systematic reviews that may foster knowledge translation and uptake.
It is well documented that the translation of knowledge into clinical practice is a slow and haphazard process. This is no less true for dental healthcare than other types of healthcare. One common policy strategy to help promote knowledge translation is the production of clinical guidance, but it has been demonstrated that the simple publication of guidance is unlikely to optimise practice. Additional knowledge translation interventions have been shown to be effective, but effectiveness varies and much of this variation is unexplained. The need for researchers to move beyond single studies to develop a generalisable, theory based, knowledge translation framework has been identified.
For dentistry in Scotland, the production of clinical guidance is the responsibility of the Scottish Dental Clinical Effectiveness Programme (SDCEP). TRiaDS (Translation Research in a Dental Setting) is a multidisciplinary research collaboration, embedded within the SDCEP guidance development process, which aims to establish a practical evaluative framework for the translation of guidance and to conduct and evaluate a programme of integrated, multi-disciplinary research to enhance the science of knowledge translation.
Set in General Dental Practice the TRiaDS programmatic evaluation employs a standardised process using optimal methods and theory. For each SDCEP guidance document a diagnostic analysis is undertaken alongside the guidance development process. Information is gathered about current dental care activities. Key recommendations and their required behaviours are identified and prioritised. Stakeholder questionnaires and interviews are used to identify and elicit salient beliefs regarding potential barriers and enablers towards the key recommendations and behaviours. Where possible routinely collected data are used to measure compliance with the guidance and to inform decisions about whether a knowledge translation intervention is required. Interventions are theory based and informed by evidence gathered during the diagnostic phase and by prior published evidence. They are evaluated using a range of experimental and quasi-experimental study designs, and data collection continues beyond the end of the intervention to investigate the sustainability of an intervention effect.
The TRiaDS programmatic approach is a significant step forward towards the development of a practical, generalisable framework for knowledge translation research. The multidisciplinary composition of the TRiaDS team enables consideration of the individual, organisational and system determinants of professional behaviour change. In addition the embedding of TRiaDS within a national programme of guidance development offers a unique opportunity to inform and influence the guidance development process, and enables TRiaDS to inform dental services practitioners, policy makers and patients on how best to translate national recommendations into routine clinical activities.
The modern biomedical research and healthcare delivery domains have seen an unparalleled increase in the rate of innovation and novel technologies over the past several decades. Catalyzed by paradigm-shifting public and private programs focusing upon the formation and delivery of genomic and personalized medicine, the need for high-throughput and integrative approaches to the collection, management, and analysis of heterogeneous data sets has become imperative. This need is particularly pressing in the translational bioinformatics domain, where many fundamental research questions require the integration of large scale, multi-dimensional clinical phenotype and bio-molecular data sets. Modern biomedical informatics theory and practice has demonstrated the distinct benefits associated with the use of knowledge-based systems in such contexts. A knowledge-based system can be defined as an intelligent agent that employs a computationally tractable knowledge base or repository in order to reason upon data in a targeted domain and reproduce expert performance relative to such reasoning operations. The ultimate goal of the design and use of such agents is to increase the reproducibility, scalability, and accessibility of complex reasoning tasks. Examples of the application of knowledge-based systems in biomedicine span a broad spectrum, from the execution of clinical decision support, to epidemiologic surveillance of public data sets for the purposes of detecting emerging infectious diseases, to the discovery of novel hypotheses in large-scale research data sets. In this chapter, we will review the basic theoretical frameworks that define core knowledge types and reasoning operations with particular emphasis on the applicability of such conceptual models within the biomedical domain, and then go on to introduce a number of prototypical data integration requirements and patterns relevant to the conduct of translational bioinformatics that can be addressed via the design and use of knowledge-based systems.
Acquiring a faculty position in academia is extremely competitive and now typically requires more than just solid research skills and knowledge of one’s field. Recruiting institutions currently desire new faculty that can teach effectively, but few postdoctoral positions provide any training in teaching methods. Fellowships in Research and Science Teaching (FIRST) is a successful postdoctoral training program funded by the National Institutes of Health (NIH) providing training in both research and teaching methodology. The FIRST program provides fellows with outstanding interdisciplinary biomedical research training in fields such as neuroscience. The postdoctoral research experience is integrated with a teaching program which includes a How to Teach course, instruction in classroom technology and course development and mentored teaching. During their mentored teaching experiences, fellows are encouraged to explore innovative teaching methodologies and to perform science teaching research to improve classroom learning. FIRST fellows teaching neuroscience to undergraduates have observed that many of these students have difficulty with the topic of neuroscience. Therefore, we investigated the effects of interactive teaching methods for this topic. We tested two interactive teaching methodologies to determine if they would improve learning and retention of this information when compared with standard lectures. The interactive methods for teaching action potentials increased understanding and retention. Therefore, FIRST provides excellent teaching training, partly by enhancing the ability of fellows to integrate innovative teaching methods into their instruction. This training in turn provides fellows that matriculate from this program more of the characteristics that hiring institutions desire in their new faculty.
action potential; postdoctoral fellowship; interactive teaching; pedagogy; neuroscience; mentoring
The molecular age histopathologist of today is practicing pathology in a totally different scenario than the preceding generations did. Histopathologists stand, as of now, on the cross roads of a traditional 'visible' morphological science and an 'invisible' molecular science. As molecular diagnosis finds more and more applicability in histopathological diagnosis, it is time for the policy makers to reframe the process of accreditation and re-accreditation of the modern histopathologist in context to the rapid changes taking place in this science. Incorporation of such 'molecular' training viv-a-vis information communication technology skills viz. telemedicine and telepathology, digital imaging techniques and photography and a sound knowledge of the economy that the fresh entrant would ultimately become a part of would go a long way to produce the Modern Histopathologist. This review attempts to look at some of these aspects of this rapidly advancing 'art of science.'
The importance of basing health policy and health care practices on the best available international evidence (“evidence-based health care”) and on translating knowledge or evidence into action (“translation science” or “translational research”) is increasingly being emphasized across all health sectors inmost countries. Evidence-based healthcare is a process that identifies policy or clinical questions and addresses these questions by generating knowledge and evidence to effectively and appropriately deliver healthcare in ways that are effective, feasible, and meaningful to specific populations, cultures, and settings. This evidence is then appraised, synthesized, and transferred to service delivery settings and health professionals who then utilize it and evaluate its impact on health outcomes, health systems, and professional practice. Many of the common theories that address this translational process place it apart from the evidence-based practice cycle and most recognise only two translational gaps. This paper seeks to clarify the nature of evidence-based healthcare and translation science and proposes a reconceptualization that both brings together these two dominant ideas in modern healthcare and asserts the existence of a third fundamental gap that is rarely addressed the gap between knowledge need and discovery.
Embracing comparative biology, natural history encompasses those sciences that discover, decipher and classify unique (idiographic) details of landscapes, and extinct and extant biodiversity. Intrinsic to these multifarious roles in expanding and consolidating research and knowledge, natural history endows keystone support to the veracity of law-like (nomothetic) generalizations in science. What science knows about the natural world is governed by an inherent function of idiographic discovery; characteristic of natural history, this relationship is exemplified wherever an idiographic discovery overturns established wisdom. This nature of natural history explicates why inventories are of such epistemological importance. Unfortunately, a Denigration of Natural History weakens contemporary science from within. It expresses in the prevalent, pervasive failure to appreciate this pivotal role of idiographic research: a widespread disrespect for how natural history undergirds scientific knowledge. Symptoms of this Denigration of Natural History present in negative impacts on scientific research and knowledge. One symptom is the failure to appreciate and support the inventory and monitoring of biodiversity. Another resides in failures of scientiometrics to quantify how taxonomic publications sustain and improve knowledge. Their relevance in contemporary science characteristically persists and grows; so the temporal eminence of these idiographic publications extends over decades. This is because they propagate a succession of derived scientific statements, findings and/or conclusions - inherently shorter-lived, nomothetic publications. Widespread neglect of natural science collections is equally pernicious, allied with disregard for epistemological functions of specimens, whose preservation maintains the veracity of knowledge. Last, but not least, the decline in taxonomic expertise weakens research capacity; there are insufficient skills to study organismal diversity in all of its intricacies. Beyond weakening research capacities and outputs across comparative biology, this Denigration of Natural History impacts on the integrity of knowledge itself, undermining progress and pedagogy throughout science. Unprecedented advances in knowledge are set to follow on consummate inventories of biodiversity, including the protists. These opportunities challenge us to survey biodiversity representatively—detailing the natural history of species. Research strategies cannot continue to ignore arguments for such an unprecedented investment in idiographic natural history. Idiographic shortcuts to general (nomothetic) insights simply do not exist. The biodiversity sciences face a stark choice. No matter how charismatic its portrayed species, an incomplete ‘Brochure of Life’ cannot match the scientific integrity of the ‘Encyclopedia of Life’.
Biodiversity knowledge; Denigration of natural history; Taxonomic inventories; Idiographic and nomothetic science; Genomics; Microbosphere; Tentelic specimens; Scientiometrics
Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery.
We developed the Translational Medicine Ontology (TMO) as a unifying ontology to integrate chemical, genomic and proteomic data with disease, treatment, and electronic health records. We demonstrate the use of Semantic Web technologies in the integration of patient and biomedical data, and reveal how such a knowledge base can aid physicians in providing tailored patient care and facilitate the recruitment of patients into active clinical trials. Thus, patients, physicians and researchers may explore the knowledge base to better understand therapeutic options, efficacy, and mechanisms of action.
This work takes an important step in using Semantic Web technologies to facilitate integration of relevant, distributed, external sources and progress towards a computational platform to support personalized medicine.
TMO can be downloaded from http://code.google.com/p/translationalmedicineontology and TMKB can be accessed at http://tm.semanticscience.org/sparql.
Translational medicine has yet to deliver on its vast potential. Obstacles, or “blocks,” to translation at three phases of research have impeded the application of research findings to clinical needs and, subsequently, the implementation of newly developed interventions in patient care. Recent federal support for comparative effectiveness research focuses attention on the clinical relevance of already-developed diagnostic and therapeutic interventions and on translating interventions found to be effective into new population-level strategies for improving health—thereby overcoming blocks at one end of the translational continuum. At the other end, while there is a preponderance of federal funding underwriting basic science research, further improvement is warranted in translating results of basic research into clinical applications and in integrating the basic sciences into the translational continuum. With its focus on the human and interactional aspects of health, medical practice, and healthcare delivery systems, behavioral medicine, itself a component of translational medicine, can inform this process.
Translational medicine; Translation blocks; Translational behavioral medicine
Knowledge Translation (KT) has historically focused on the proper use of knowledge in healthcare delivery. A knowledge base has been created through empirical research and resides in scholarly literature. Some knowledge is amenable to direct application by stakeholders who are engaged during or after the research process, as shown by the Knowledge to Action (KTA) model. Other knowledge requires multiple transformations before achieving utility for end users. For example, conceptual knowledge generated through science or engineering may become embodied as a technology-based invention through development methods. The invention may then be integrated within an innovative device or service through production methods. To what extent is KT relevant to these transformations? How might the KTA model accommodate these additional development and production activities while preserving the KT concepts?
Stakeholders adopt and use knowledge that has perceived utility, such as a solution to a problem. Achieving a technology-based solution involves three methods that generate knowledge in three states, analogous to the three classic states of matter. Research activity generates discoveries that are intangible and highly malleable like a gas; development activity transforms discoveries into inventions that are moderately tangible yet still malleable like a liquid; and production activity transforms inventions into innovations that are tangible and immutable like a solid. The paper demonstrates how the KTA model can accommodate all three types of activity and address all three states of knowledge. Linking the three activities in one model also illustrates the importance of engaging the relevant stakeholders prior to initiating any knowledge-related activities.
Science and engineering focused on technology-based devices or services change the state of knowledge through three successive activities. Achieving knowledge implementation requires methods that accommodate these three activities and knowledge states. Accomplishing beneficial societal impacts from technology-based knowledge involves the successful progression through all three activities, and the effective communication of each successive knowledge state to the relevant stakeholders. The KTA model appears suitable for structuring and linking these processes.