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Evidence-Based Practice: Toward Optimizing Clinical Outcomes pp 3–16Cite as

Introduction: Research Synthesis in Evidence-Based Clinical Decision-Making

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Abstract

As an introduction to the book, we, the editors, present here a brief overview and discussion of the current status of evidence-based health care. In this first chapter, we describe the central role of systematic reviews (SRs) in the process of clinical decision-making in evidence-based health care. Particular emphasis is given to the correspondence of the four fundamental steps of the logic model: inputs, activities, outputs, and impact, to the process of actualizing and evaluating clinical decision-making and policies in evidence-based decision making for optimizing clinical outcomes.

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Notes

  1. 1.

    The American Dental Association (ADA) Board of Trustees examined this new approach to clinical practice and dental care, and adopted resolution (B-18-1999) in February 1999 as: “…an approach to treatment planning and subsequent dental therapy that requires the judicious melding of systematic assessments of scientific evidence relating to the patient’s medical condition and history, the dentist’s clinical experience, training and judgment and the patient’s treatment needs and preferences.” The ADA further states that “…evidence-based clinical recommendations are intended to provide guidance, and are not a standard of care, requirement or regulation…(they serve as) a resource for dentists…”

  2. 2.

    cf., Criteria for the level of evidence, and the “strength of recommendation taxonomy grading (SORT) guidelines” offered in the forward of the Journal of Evidence-Based Dental Practice.

  3. 3.

    This is usually achieved by means of the Markov model-based decision tree. This approach permits to model events that may occur in the future as a direct effect of treatment or as a side effect. The model produces a decision tree that cycles over fixed intervals in time, and incorporates probabilities of occurrence. Even if the difference between the two treatment strategies appears quantitatively small, the Markov model outcome reflects the optimal clinical decision, because it is based on the best possible values for probabilities and utilities incorporated in the tree. The outcome produced by the Markov decision analysis results from the sensitivity analysis to test the stability over a range probability estimates, and thus reflects the most rational treatment choice [55, 59].

  4. 4.

    e.g., Quality of reporting of meta-analysis, QUOROM – The QUOROM criteria were recently revised as the preferred reporting items for systematic reviews and meta-analysis (PRISMA) (cf., [32]).

  5. 5.

    For in depth discussion, see 2.

  6. 6.

    cf., [6, 52].

  7. 7.

    In the context of CEA, one alternative is said to be dominant if offers the more effective and less costly alternative. When this is the case, the dominated alternative normally may be removed from consideration. The use of relative position to infer dominance can be inferred from the analysis of the cost-effectiveness graph: effectiveness increases from left to right, and cost increases from bottom to top. The crossing point of the axes represents one alternative. Its comparators can then be placed on the graph: more costly alternatives above, and more effective alternatives to the right. An alternative is said to be “dominated” if it lies both above and to the left of another alternative.

  8. 8.

    When making certain population-wide policy decisions, two strategies may be used together as a sort of “blended” policy, instead of assigning a single treatment strategy to all patients. Hence, we speak of “extended dominance.” Blending strategies only becomes relevant when the most effective strategy is too costly to prescribe for the entire population.

  9. 9.

    cf., Pareto’s efficiency curve.

  10. 10.

    Arguments are ad hominem when they use factual claims or propositions by attacking or appealing to a characteristic or a belief of the source or origin of the proposition or claim (i.e., the person – argument to the person, Latin: “ad hominem”), rather than by addressing the substance of the argument itself, and producing evidence for or against it following the rules of logic. These arguments may be logically valid, but they also can be logically unsound, because not based on the rules of logic. Therefore, rational decisions may at times appear “illogical.”

  11. 11.

    cf., [3].

  12. 12.

    Purposeful and instrumental type of behaviors that characterize the expectations of the behaviors of others in a social context, and that lead to pondered “rationally pursued and calculated social decisions.”

  13. 13.

    As discussed elsewhere [3], views and perceptions of reality differ. This discordance pertains to a separate and distinct, yet related and pertinent domain of cognitive psychology termed “person-environment fit.” For the implications of this model in the context of evidence-based decision-making in medicine and dentistry, please see: Chiappelli et al. [8].

  14. 14.

    e.g., The consolidated standards of clinical trials, CONSORT.

  15. 15.

    Another noteworthy assessment guideline in the EBR-EBPr spectrum is the “appraisal of guidelines, research and evaluation – Europe” (AGREE) instrument [11].

  16. 16.

    Chiappelli et al., in progress.

  17. 17.

    Note: the critical appraisal skills program (CASP) was developed by Oxford Regional Health, in association with the Evidence Based Medicine Working Group, a group of clinicians at McMaster university, Hamilton, Canada, to promote the skills necessary for critical appraisal of the evidence, and decision-making grounded on the best available evidence (cf., [42]).

  18. 18.

    For example, “…organizational knowledge that constitutes “core-competency” is more than “know-what” explicit knowledge which may be shared by several. A core competency requires the more elusive “know-how” – the particular ability to put know-what into practice…” [48], contrasting to “…Knowledge exists on a spectrum. At one extreme, it is almost completely tacit, that is semiconscious and unconscious knowledge held in peoples’ heads and bodies. At the other end of the spectrum, knowledge is almost completely explicit or codified, structured, and accessible to people other than the individuals originating it. Most knowledge of course exists between the extremes. Explicit elements are objective, rational, and created in the “then and there,” while the tacit elements are subjective experiential and created in the “here and now…” [31]. Hence, the distinction between what people know and can articulate, quantify, or document in conscious cognitive act (knowing what) – considered by some as “hard” knowledge, vs. what people know to know, which can be articulated or quantified, a subconscious knowing how, an innate or acquired quality of knowing by inference, reason and logic, rather than by quantifiable measures – spuriously called “soft” knowledge [26].

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Authors and Affiliations

  1. Divisions of Oral Biology and Medicine, and Associated Clinical Specialties (Joint), University of California at Los Angeles, School of Dentistry, CHS 63-090, Los Angeles, CA, 90095-1668, USA

    Francesco Chiappelli

  2. Rua Aimorés 2480/609, Belo Horizonte-MG, Brazil

    Xenia M. C. Brant

  3. Divisions of Oral Biology and Medicine, University of California, Los Angeles, School of Dentistry, Los Angeles, CA, 90095-1668, USA

    Oluwadayo O. Oluwadara, Negoita Neagos & Manisha Harish Ramchandani

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  1. Francesco Chiappelli
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  2. Xenia M. C. Brant
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  3. Oluwadayo O. Oluwadara
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  4. Negoita Neagos
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  5. Manisha Harish Ramchandani
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Correspondence to Francesco Chiappelli .

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  1. School of Dentistry, Div. Oral Biology & Medicine, University of California, Los Angeles, Los Angeles, 90095-1668, USA

    Francesco Chiappelli

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Chiappelli, F., Brant, X.M.C., Oluwadara, O.O., Neagos, N., Ramchandani, M.H. (2010). Introduction: Research Synthesis in Evidence-Based Clinical Decision-Making. In: Chiappelli, F. (eds) Evidence-Based Practice: Toward Optimizing Clinical Outcomes. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05025-1_1

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  • DOI: https://doi.org/10.1007/978-3-642-05025-1_1

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