When doing medical research with human subjects, which four limitations are unavoidable
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Abstract
We explore some philosophical and scientific underpinnings of clinical research and evidence at the patient-clinician encounter scale. Insufficient evidence and a common failure to use replicable and sound research methods limit us. Both patients and health care may be, in part, complex nonlinear chaotic systems, and predicting their outcomes is a challenge. When trustworthy (credible) evidence is lacking, making correct clinical choices is often a low-probability exercise. Thus, human (clinician) error and consequent injury to patients appear inevitable. Individual clinician decision-makers operate under the philosophical influence of Adam Smith’s “invisible hand” with resulting optimism that they will eventually make the right choices and cause health benefits. The presumption of an effective “invisible hand” operating in health-care delivery has supported a model in which individual clinicians struggle to practice medicine, as they see fit based on their own intuitions and preferences (and biases) despite the obvious complexity, errors, noise, and lack of evidence pervading the system. Not surprisingly, the “invisible hand” does not appear to produce the desired community health benefits. Obtaining a benefit at the patient-clinician encounter scale requires human (clinician) behavior modification. We believe that serious rethinking and restructuring of the clinical research and care delivery systems is necessary to assure the profession and the public that we continue to do more good than harm. We need to evaluate whether, and how, detailed decision-support tools may enable reproducible clinician behavior and beneficial use of evidence.
Obtaining favorable outcomes is a long-standing goal of medicine and health care, tightly linked to the Hippocratic principles of beneficence (to do good-ὠφελέειν) and nonmaleficence (to do no harm-μὴ βλάπτειν).1,2 Beneficence can either mean producing benefit (a utilitarian viewpoint, according to Mill) or simply intending to produce benefit (a deontologic viewpoint, according to Kant).3 Utilitarianism is defensible in spite of critiques.4,5Patients want to benefit at the end of the day.6
Intentions to do good are widespread but frequently inadequate for producing benefit, as suggested by the well-known aphorism, “The road to hell is paved with good intentions.” Besides, current health care involves many influential corporate and other stakeholders whose prime motive and intentions are not beneficent, but rather are monetary. Even physicians and health researchers themselves may be driven by less lofty intentions like financial gains or academic prestige. Regardless, reasonable people would prefer benefit more than just good intentions in the patient-clinician encounter.
There are two broad categories of response to these Hippocratic principles.1 The first is provision of compassion. The second is consistent application of scientific results proved to confer more clinical benefit than harm (a favorable outcome).
Compassion is always possible in the patient-clinician encounter. However, we do not always have interventions documented to provide more benefit than harm. Interventions may be unavailable, their harms may exceed benefits, or evidence may incorrectly suggest more benefit than harm because study results reflect biases and are not trustworthy.7,8 If so, offering compassion is worthy, while offering anything more would be detrimental to the patient. Both seasoned and young physicians are often tempted to do more. This includes using unjustified tests (eg, prostate specific antigen screening) or giving untested or poorly tested therapies (eg, antiarrhythmics to suppress asymptomatic arrhythmia).9 We often do not want to accept that there is nothing to do and that medicine is not omnipotent. It would be useful to resist these temptations. Medicine is not omnipotent.
Trustworthy Favorable Effects
Some outcome predictability is a prerequisite for favorable impact in medicine and health care: Based on some prior knowledge of intervention effects and risk factors, we can expect the effect in newly treated patients. Interestingly, predictability does not require full understanding of causal mechanisms. Our inability to fully understand causality is not an unsurpassable barrier.10 However, outcome predictability requires trustworthy scientific results. Trustworthy or credible results require robust study methods that separate true effect from noise, and reliably estimate effect size. Science requires this true effect to be reproducible,11,12 although reproducibility is sometimes difficult to establish, or is absent in medicine, and in other scientific domains.
We explore some philosophical and scientific underpinnings of clinical research and evidence at the patient-clinician encounter scale. Insufficient evidence and a common failure to use replicable and sound research methods limit us. Both patients and health care may be, in part, complex nonlinear chaotic systems, and predicting their outcomes is a challenge. When trustworthy (credible) evidence is lacking, making correct clinical choices is often a low-probability exercise. Thus, human (clinician) error and consequent injury to patients appear inevitable. Individual clinician decision-makers operate under the philosophical influence of Adam Smith’s “invisible hand” with resulting optimism that they will eventually make the right choices and cause health benefits. The presumption of an effective “invisible hand” operating in health-care delivery has supported a model in which individual clinicians struggle to practice medicine, as they see fit based on their own intuitions and preferences (and biases) despite the obvious complexity, errors, noise, and lack of evidence pervading the system. Not surprisingly, the “invisible hand” does not appear to produce the desired community health benefits. Obtaining a benefit at the patient-clinician encounter scale requires human (clinician) behavior modification. We believe that serious rethinking and restructuring of the clinical research and care delivery systems is necessary to assure the profession and the public that we continue to do more good than harm. We need to evaluate whether, and how, detailed decision-support tools may enable reproducible clinician behavior and beneficial use of evidence.
Obtaining favorable outcomes is a long-standing goal of medicine and health care, tightly linked to the Hippocratic principles of beneficence (to do good-ὠφελέειν) and nonmaleficence (to do no harm-μὴ βλάπτειν).1,2 Beneficence can either mean producing benefit (a utilitarian viewpoint, according to Mill) or simply intending to produce benefit (a deontologic viewpoint, according to Kant).3 Utilitarianism is defensible in spite of critiques.4,5Patients want to benefit at the end of the day.6
Intentions to do good are widespread but frequently inadequate for producing benefit, as suggested by the well-known aphorism, “The road to hell is paved with good intentions.” Besides, current health care involves many influential corporate and other stakeholders whose prime motive and intentions are not beneficent, but rather are monetary. Even physicians and health researchers themselves may be driven by less lofty intentions like financial gains or academic prestige. Regardless, reasonable people would prefer benefit more than just good intentions in the patient-clinician encounter.
There are two broad categories of response to these Hippocratic principles.1 The first is provision of compassion. The second is consistent application of scientific results proved to confer more clinical benefit than harm (a favorable outcome).
Compassion is always possible in the patient-clinician encounter. However, we do not always have interventions documented to provide more benefit than harm. Interventions may be unavailable, their harms may exceed benefits, or evidence may incorrectly suggest more benefit than harm because study results reflect biases and are not trustworthy.7,8 If so, offering compassion is worthy, while offering anything more would be detrimental to the patient. Both seasoned and young physicians are often tempted to do more. This includes using unjustified tests (eg, prostate specific antigen screening) or giving untested or poorly tested therapies (eg, antiarrhythmics to suppress asymptomatic arrhythmia).9 We often do not want to accept that there is nothing to do and that medicine is not omnipotent. It would be useful to resist these temptations. Medicine is not omnipotent.
Trustworthy Favorable Effects
Some outcome predictability is a prerequisite for favorable impact in medicine and health care: Based on some prior knowledge of intervention effects and risk factors, we can expect the effect in newly treated patients. Interestingly, predictability does not require full understanding of causal mechanisms. Our inability to fully understand causality is not an unsurpassable barrier.10 However, outcome predictability requires trustworthy scientific results. Trustworthy or credible results require robust study methods that separate true effect from noise, and reliably estimate effect size. Science requires this true effect to be reproducible,11,12 although reproducibility is sometimes difficult to establish, or is absent in medicine, and in other scientific domains.
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One limitation is trust worthy favourable effects.The other one is human decision-making limitations,unnecessary variation,nonlinear or chaotic systems.All these limitations are unavoidable when doing medical research with human subjects.In breaking down this phenomenon variation and non linear or chaotic systems cause intense trouble .Therefore it is a limitation .When medical research is done there is a likely hood that any of this is going to take place .
BM
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