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proyectos:tfg:casos:ciencias_de_la_salud:start [2018/01/19 15:32] Joaquín Herrero Pintado [Medicina basada en evidencia] |
proyectos:tfg:casos:ciencias_de_la_salud:start [2019/04/16 16:02] (actual) Joaquín Herrero Pintado [Novedades] |
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| ====== Causalidad en ciencias de la salud ====== | ====== Causalidad en ciencias de la salud ====== | ||
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| + | |||
| + | ===== Novedades ===== | ||
| + | |||
| + | [[https://www.amazon.es/Causality-Probability-Medicine-English-Gillies-ebook/dp/B07GRCNCT7/ref=sr_1_1?__mk_es_ES=%C3%85M%C3%85%C5%BD%C3%95%C3%91&keywords=causality+probability+medicine&qid=1554112038&s=gateway&sr=8-1|Causality, Probability, and Medicine]], Donald Gillies | ||
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| + | * [[http://www.thebsps.org/2019/04/anjum-on-gillies/|Reseña del libro]], por Ranil Lill Anjum | ||
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| + | {{:proyectos:tfg:casos:ciencias_de_la_salud:anjum2018.pdf|Medical scientists and philosophers worldwide appeal to EBM to expand the notion of 'evidence'}} | ||
| ===== Bibliografía ===== | ===== Bibliografía ===== | ||
| + | * [[infocomp:metabiologia|]] | ||
| * [[proyectos:tfg:bibliografia:anjum2011]] | * [[proyectos:tfg:bibliografia:anjum2011]] | ||
| * [[http://thebjps.typepad.com/my-blog/2016/11/causation-in-scientific-methods.html|Anjum, R.L., Causation in Scientific Methods (2016)]] | * [[http://thebjps.typepad.com/my-blog/2016/11/causation-in-scientific-methods.html|Anjum, R.L., Causation in Scientific Methods (2016)]] | ||
| Línea 16: | Línea 26: | ||
| * [[http://onlinelibrary.wiley.com/doi/10.1111/jep.12578/abstract|A philosophical argument against evidence-based policy]] (pages 1045–1050), Rani Lill Anjum and Stephen D Mumford | * [[http://onlinelibrary.wiley.com/doi/10.1111/jep.12578/abstract|A philosophical argument against evidence-based policy]] (pages 1045–1050), Rani Lill Anjum and Stephen D Mumford | ||
| - | ===== Medicina basada en evidencia ===== | + | http://extendedevolutionarysynthesis.com/getting-into-the-weeds-individual-plasticity-and-adaptive-variation/ |
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| + | https://www.researchgate.net/publication/322836323_Everything_Flows_Towards_a_Processual_Philosophy_of_Biology | ||
| + | |||
| + | |||
| + | ==== Biología sintética vs. Biología evolutiva ==== | ||
| + | |||
| + | http://isegoria.revistas.csic.es/index.php/isegoria/article/view/948 | ||
| + | |||
| + | |||
| + | ===== La Medicina Basada en Evidencia implica una ontología de la causalidad ===== | ||
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| + | Rani Lill Anjum: "the more common view is Evidence based medicine (EBM) in methodology plus some person centered healthcare (PCH) in practice. Philosophically, however, I try to show that it also depends on it how we think about causation, probability & complexity. If probabilities are understood as singular and property based (propensities) methodology wouldn’t favour statistical averages (or frequencies). So in that sense ontology can motivate scientific methods & interpretations of results. Contrary to the Standard Probability Theory ((Any standard logistic regression model with a continuous covariate can issue a separate probability for each patient. It's a commonplace of frequentist statistics. Stephen John Senn on [[https://twitter.com/stephensenn/status/953345983051640836|Twitter]])), in the #CauSciBook we argue for a **dispositionalist propensity singularist understanding of probability**." [[https://twitter.com/ranilillanjum/status/953341808767102976|Twitter thread]] | ||
| + | |||
| + | ==== Bibliografía ==== | ||
| [[proyectos:tfg:bibliografia:landes2016]] | [[proyectos:tfg:bibliografia:landes2016]] | ||
| Línea 24: | Línea 48: | ||
| [[http://onlinelibrary.wiley.com/doi/10.1111/jep.12578/full|A philosophical argument against evidence-based policy]]\\ | [[http://onlinelibrary.wiley.com/doi/10.1111/jep.12578/full|A philosophical argument against evidence-based policy]]\\ | ||
| - | + | **Rationale, aims and objectives** \\ | |
| - | Rationale, aims and objectives \\ | + | |
| Evidence-based medicine has two components. The methodological or ontological component consists of randomized controlled trials and their systematic review. This makes use of a difference-making conception of cause. But there is also a policy component that makes a recommendation for uniform intervention, based on the evidence from randomized controlled trials.\\ | Evidence-based medicine has two components. The methodological or ontological component consists of randomized controlled trials and their systematic review. This makes use of a difference-making conception of cause. But there is also a policy component that makes a recommendation for uniform intervention, based on the evidence from randomized controlled trials.\\ | ||
| - | Methods \\ | + | **Methods** \\ |
| The policy side of evidence-based medicine is basically a form of rule utilitarianism. But it is then subject to an objection from Smart that rule utilitarianism inevitably collapses. If one assumes (1) you should recommend the intervention that has brought most benefit (the core of evidence-based policy making), (2) individual variation (acknowledged by use of randomization) and (3) no intervention benefits all (contingent but true), then the objection can be brought to bear.\\ | The policy side of evidence-based medicine is basically a form of rule utilitarianism. But it is then subject to an objection from Smart that rule utilitarianism inevitably collapses. If one assumes (1) you should recommend the intervention that has brought most benefit (the core of evidence-based policy making), (2) individual variation (acknowledged by use of randomization) and (3) no intervention benefits all (contingent but true), then the objection can be brought to bear.\\ | ||
| - | Conclusions\\ | + | **Conclusions**\\ |
| A utility maximizer should always ignore the rule in an individual case where greater benefit can be secured through doing so. In the medical case, this would mean that a clinician who knows that a patient would not benefit from the recommended intervention has good reason to ignore the recommendation. This is indeed the feeling of many clinicians who would like to offer other interventions but for an aversion to breaking clinical guidelines. | A utility maximizer should always ignore the rule in an individual case where greater benefit can be secured through doing so. In the medical case, this would mean that a clinician who knows that a patient would not benefit from the recommended intervention has good reason to ignore the recommendation. This is indeed the feeling of many clinicians who would like to offer other interventions but for an aversion to breaking clinical guidelines. | ||
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| + | [[https://www.pdcnet.org/pdc/bvdb.nsf/purchase?openform&fp=tpm&id=tpm_2017_0077_0035_0040|What Evidence? Whose Medicine? And On What Basis?]]\\ | ||
| + | The Philosophers' Magazine, Issue 77, 2nd Quarter 2017, Paradoxes, Rani Lill Anjum, Pages 35-40, DOI: 10.5840/tpm20177745\\ | ||
| + | What's wrong with Evidence Based Medicine | ||
| + | |||
| + | [[http://www.volunteering.ebmplus.org/evaluating-evidence-in-medicine/|EBM+]]\\ | ||
| + | EBM+ is a consortium taking part in a 3-year, AHRC-funded research project called ‘Evaluating Evidence in Medicine’. Our aim is improve Evidence Based Medicine (EBM) by developing innovative new ways of finding and evaluating different types of clinical evidence, in order to better inform medical decisions. | ||
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| + | [[https://philpapers.org/archive/FULUEM.pdf|Universal etiology, multifactorial diseases and the constitutive model of disease classification]] (PDF online)\\ | ||
| + | Jonathan Fuller\\ | ||
| + | Infectious diseases are often said to have a universal etiology, while chronic and noncommunicable diseases are | ||
| + | said to be multifactorial in their etiology. It has been argued that the universal etiology of an infectious disease | ||
| + | results from its classification using a monocausal disease model. In this article, I will reconstruct the monocausal | ||
| + | model and argue that modern 'multifactorial diseases' are not monocausal by definition. ‘Multifactorial diseases’ are instead defined according to a constitutive disease model. On closer analysis, infectious diseases are also defined using the constitutive model rather than the monocausal model. As a result, our classification models alone cannot explain why infectious diseases have a universal etiology while chronic and noncommunicable diseases lack one. The explanation is instead provided by the Nineteenth Century germ theorists. | ||
| + | |||
| ==== Políticas basadas en evidencia científica ==== | ==== Políticas basadas en evidencia científica ==== | ||
| Línea 46: | Línea 84: | ||
| * [[https://sites.google.com/site/ranilillanjum/home/research/causation-in-science|Mumford, S, Anjum, R.L., Causation in Science (forthcoming) (abstracts available)]] | * [[https://sites.google.com/site/ranilillanjum/home/research/causation-in-science|Mumford, S, Anjum, R.L., Causation in Science (forthcoming) (abstracts available)]] | ||
| + | Ver [[proyectos:tfg:causalidad:causcibook|]] | ||
| ===== Proyecto CauseHealth ===== | ===== Proyecto CauseHealth ===== | ||
proyectos/tfg/casos/ciencias_de_la_salud/start.1516375976.txt.gz · Última modificación: 2018/01/19 15:32 por Joaquín Herrero Pintado
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