Introduction
Evidence-Based Medicine (EBM) is also known as Evidence-Based Practice (EBP) and targets to achieve the application of the finest evidence acquired from scientific methods for the benefit of taking medical decisions. It makes efforts to evaluate the potency of evidence accrued to the risk and the benefit of treatment (which includes treatment deficiencies) and test diagnostics. Otherwise, EBM can be said to be an integration of the most excellent evidence acquired through researches that are for the benefit of the values of patients as well as for clinical expertise. This evidence span application in areas of Medical Trials, Placebo-Control, Double-Blinding, Systematic-Reviews, and Meta-Analyses. This paper will discuss studies and mathematical applications of EBM or EBP in the areas of Diagnosis and Screening, Disease Treatment, and related Medicare and therapy in a bid to accept or disprove the argument of whether EBM is real-life achievable and practically relevant or whether it is symbolic and still requires extra modeling and theoretical advancement for the benefit of diagnostic medicine.
It is worth knowing that EBM evidence does not produce clinical decisions by themselves except they provide ample support for processes of patient care. The complete integration of the various mechanisms of EBM into decisions that are clinically based on augments opportunities is for producing the best clinical outcomes as well as bettering life’s quality. The conduct of Evidence-Based Medicine is fostered by patients’ encounters which produce questions concerning how effective the therapies may be on the diagnosed disorder.
Significance and benefits of the studies
EBM has been defined as:
“The integration of best research evidence with clinical expertise and patient values” (Sackett & Straus, p. 1).
Or:
“…the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of the individual patient. It means integrating individual clinical expertise with the best available external clinical evidence from systematic research.” (Sackett & Straus, p. 2)
Due to the fact of diverse usage of the term in fields such as psychology, nursing, and dentistry, EBM is encompassing and demonstrates the recognition that several integral healthcare aspects are reliant on units that may include life-value and quality judgment that is integrally a subject of analytical methods. It is the fore concern of Evidence-based Medicine, however, to make clear aspects of practices of medicine that are principally subjected to methods that are scientific and applicable for ensuring the most accepted predictions of clinical treatment results, although debates linger on the authenticity of the desirability of these outcomes. It is the advocacy of Evidence-based Medicine to ensure thrives of recent clinical decision-making which must be reliant on the usage of ‘best’ up-to-date scientific evidence. For this school of thought, Evidence-based Medicine offers the following three (3) key merits:
- It gives the most accepted and objective alternatives in the determination and maintenance of consistent and committed qualitative standards which are safer for utilization in the practice of medicine;
- It aids in achieving speed in processes of converting medical researches and findings into medical practices; and
- It avails the potency for the reduction of costs in Medicare or health-care, considerably.
This school of thought which supports EBM is not without opposition as it is otherwise considered that Evidence-based Medicine risks downplay of the vitality of medical experiences and expert opinions. It is also argued that the terms used by clinical trials in the definition of ‘best’ practices are complicated and not routinely replicable and are not practical. Subsequently, there are emergent movements such as the Cochrane Collaboration- which was instrumented to retort Archie Cochrane’s call for the development of instantaneous systematic evaluations of randomly regulated trials that encompass all sectors in health care utilizing the most excellent available evidence in healthcare decision-making processes.
A persistent challenge that has continued to be associated with EBM is a translation of knowledge and how to ensure effective day-to-day clinician decision-making regarding appropriate values on existing ‘best evidence’. Once too occurring, clinicians are ignorant of existing evidence or neglect the applications. Otherwise, the values of clinicians vary considerably from patients, hence even when clinicians are sentient of the evidence there is the tendency that their suggestions would be fellable without the involvement of patients in the processes of making decisions.
The Efficacy of Evidence-Based Medicine (EBM) in Diagnoses and Screening: Mathematical Point of View
Diagnosing and screening of patients in EBM begins with patient assessment; questions are asked for acquiring evidence that could be appraised and applied to the patient through the integration of evidence and clinical expertise. And then, there is the evaluation of the performance with the particular patient. It is mathematically functional to analyze a composite fundamental result of augmented compliance in line with medication through typical numerical approaches. One such approach is addressed through three questions which are fundamental to determining compliance with emergent evidence. First, the authenticity of a diagnostic test and the certainty of evidence must be questioned. Secondly, the specificity of the evidence regarding patient disorder is considered, and then follows the specific-patient applicability of the valid diagnostic test. There is however the complexity of misinterpreting such diagnosis and screening at early-stage disorder since the disorder may be without symptoms in an individual. Mathematical modeling approaches for interpreting data obtained from cellular analyses such as Immersed Boundary have been found utilizable especially where patient disorder involves physical stochastic fluidal quantities –stochastic calculus is found valuable (Agbough, p. 16). Several models on normalcy function and state of diseases have been put in place to check processes that may occur cellularly such as ion flux transmembrane, sleep apnea obstructive, as well as influenza outbreaks.
Studies have shown the potency of pre-test disease probability as found in figure 1:
A test’s impact on uncertainty: from pre-test to post-test probabilities. An expression of the post-test probabilities after positive (upper curve) and negative (lower curve) test results for the range of possible pre-test probabilities of disease. The first question on validity asked if the information in the graph can be believed. The second question, on importance, inquires if the results show clinically worthwhile shifts in uncertainty (the further apart the post-test curves, the larger this shift). The third question means there is a need to understand how the test results might change the diagnostic uncertainty on application, not only for the patients in the study but, more importantly, for a particular patient (Sackett & Straus, p. 68).
Sackett and Straus have based their patient diagnoses and Screening on two boundaries: pre-test and post-test and results are shown in cumulative percentages using the formula c/(c + d) =x% (p. 75). It is also shown that:
‘Patient post-test odds = (study post-test odds) x [(patient pretest odds) (study pretest odds)]’ (p.75).
This is akin to adjusting trials of Number Needed to Treat (NNT) for patients’ PEER. The effectiveness of this is clear with the generation of a number of test-accuracy-measures and applying the same to the probabilities of individual patients’ pre-test.
Application of mathematics, especially probability, has had its way, through pathological and physiological processes, in the validation of medical hypotheses; whereby the knowledge is not just put to use for testing fresh ideas but also in non-invasion for monitoring conditions of patients and then prognostication. Supporting the relevance of the application of mathematics to EBM, studies have revealed that:
‘The use of mathematics in data analysis to determine receiver-operator characteristics, to determine the predictive power of a finding, and the odds ratio of an event occurring has allowed more thorough utilization of the findings of clinical studies’ (Greenhalgh p.1).
Models designed through appropriate utilization of mathematics, apart from helping in the organization of data and materialization of concepts, are effective utilities for analyzing biological systems and permitting the preliminary assessment of the viability of the ideas which could eventually be examined by trials and which are randomized controlled. Furthermore, the models permit for examining severe circumstances which are not vulnerable to examinations through clinical trials. These are of a specialty valuable for analyzing pathological processes which are caught up in syndromes and could have an effect on the activity of manifold organs such as metabolic syndrome.
A second illustration of the applicability of mathematic in Evidence-Based Medicine has to do with analyzing data that is non-invasive and which has accumulated progressively such as the rate of a heart pulse, the frequency of breathing, as well as identifying functional abnormality and developed prognostications, appropriately. A reduction or slow-down in the variability of pulses of the heart, for example, makes it obvious to send signals for extreme stress and augmented vulnerability to trials fibrillating as well as heart attacks. Variability has been identified as key to adapting accommodative abilities. Variability is learned, mathematically, through time domains making effective use of standard deviation or center of tendencies –whereby, the domain’s frequencies are used in studying frequency-band variability. The low/high ratio of frequency is made use of, once very often, in the detection of abnormalities or malfunction in the systematic balances of the Autonomic Nervous. The use of non-linear mathematical indices and approaches in determining chaotically natured output such as approximated entropy is quite obtainable. On a general note, studies have revealed values as being considered fantastic signs (Appelhaus, p. 17). It is noted:
There is a caveat to all this. The success of mathematics, however, should not lead to the neglect of the intuitive nonquantifiable part of medicine i.e. medicine as an art. Not everything in medicine so far can be measured and in our present ignorance, there seem to be many exceptions to mathematical rules (Greenhalgh, p. 2).
Evaluating the Validity of a Therapy Study
With the identification of present data which can be used for answering clinical questions, there are existent fundamental questions that demand answers about specific studies. These questions include confirmation of the validity of the studies, the specificity of the results obtained, and the helpfulness of the result about the identified case of the patient.
The subject or concern for validity expresses how ‘true’ the information obtained is- this information is mathematically considered or regarded as data because is fundamental for instrumentation of appropriate treatment of the patient. Thus it has been suggested that:
The validity criteria should be applied before an extensive analysis of the study data. If the study is not valid, the data may not be useful. The evidence that supports the validity or truthfulness of the information is found primarily in the study methodology (Greenhalgh, p.2).
Presently, studies are concerned about resulting issues of preconception, which may occur from consciousness or unconscious interactions. Such methods of studying Evidence-Based Medicine such as blinding, randomization, and taking accounts for the totality of patients help in insuring that values derived from studies are by no way influenced overly by the personals who are investigating the patients nor by patients themselves.
Evaluation of acquired medical literature poses many challenges and involves mathematical methodologies. One may note that results derived from the questions concerning how valid the data is may sometimes lack clarity as may be stated in the source they are obtained. It may then be very necessary for the clinician to decide on their own what to do concerning the value of the questions.
Once there is the determination concerning the validity of the methodology of the studies, it is appropriate to consider carefully the derived results and then consider how applicable the obtained results may be to the examined patient. It is relevant that clinicians or medical practitioners have extended concern and regards about patients as has been stated:
Clinicians may have additional concerns such as whether the study represented patients similar to his/her patients, whether the study covered the aspect of the problem that is most important to the patient, or whether the study suggested a clear and useful plan of action (Guyatt, p.48 ).
When patients are to be assigned to specific groups (or what is regarded as control or treatment units), it should be carried out in the utilization of random allocation. To help achieve the random selection, such fashioned ways like coin toss (where heads could be for treatments and tails could be for control) may be used or there may be the randomization table utilization (which is mathematical) derived through the use of a computer.
Studies have made clear that allocations that are randomly done have been closer to ensuring the generation of patient collection that may be comparable to their risk of events which may be hoped preventable. The process of randomization pivots a balance as studies have reviewed:
Randomization balances the groups for known prognostic factors (such as age, weight, gender, etc.) and unknown prognostic factors (such as compliance, genetics, socioeconomics, etc.). This reduces the chance of over-representation of any one characteristic within study groups (Agbough, p. 30).
It is also vital that randomization sequences should be obscured through researchers and clinicians who conduct studies on the patients. This will be used for furthering the elimination of conscious and unconscious selective biasness. Concealing (which is a basis of enrolling processes) makes it possible that personals who are conducting research can not suppose or make changes on assigning patients to specific treatment groups. In cases where allocation may not be concealed, it could be necessary to persuade for results (either through conscious or through unconscious acts) by making changes in enrolling order the order of treatment that could be allocated through randomization. The concealed assignment has been noted to be achievable through the use of call-center-remote for the enrollment of the patients as well as through the utilization of transparent envelops conceding allocation. This is not the same as blinding which occurs subsequent to randomization.
The extent of Study Blinding
By blinding, it infers that persons who are concerned with studies relating to EBM do not understand the sort of treatment(s) that were prescribed to the individual patients. Data analysts, persons involved in research, patients, and other persons who are directly concerned with studies do not need a pre-knowledge of the administration of treatment of the patient. This removes all biases and all preconceived ideas regarding what procedure about the treatment’s workability. In instances of difficulty or where there may be unethical instances toward blinding patients for treatment processes, particularly when surgical treatment is involved, there would be the necessity to make use of ‘blinded’ clinicians or ‘blinded’ researchers for data interpretation.
Events that may precede randomization could have an effect on the possibility that patients have events. It has been noted that:
‘Patients who forget or refuse their treatment should not be eliminated from the study results or allowed to change groups’ (Agbough, p.33).
Exclusion of patients who do not give complaints from a particular group may give way for those who are prospectively willing to produce acceptable results, wherefore a compromise with comparisons that are not biased are obtainable from randomization as a process. All patients (in consideration of EBM) should hence be studied within confined groups as they may be assigned.
Conclusion
There are debates on the certainty of Evidence-Based Medicine EBM which is otherwise known as Evidence-Based Practice (EBP). The arguments which emphasize that EBM is merely a book quantity and nonpracticable are refuted in auditing terms from the fore burners of medical care whereby it has been noted that some fundamental aspects of medicine such as surgery and psychiatry have effectively administered treatment to patients using EBM. It is easy to note that the debates concerning the certainty of EBM could emerge from medical practitioners who are research adamant and who may not be willing to incorporate the best available evidence into EBM which is supported by mathematical models.
This paper has discussed studies and mathematical applications of EBM or EBP in the areas of Diagnosis and Screening, Disease Treatment, and related Medicare and therapy and accepts that there is a need to develop certain aspects of EBM in order to make it more ‘real-life’ and achievable. This answers the question as to whether EBM still requires extra modeling and theoretical advancement for the purpose of diagnostic medicine.
References
Agbough, Godwin. The application of Mathematics to Medicine. Ibadan: University Press, 2009. Print.
Appelhaus, Bam. Fundamentals of Evidence Based Medicine. Ibadan: University Presss, 2005. Print.
Greenhalgh Taled. Mathematics and Evidence-Based Medicine: the teaching process. London: BMJ Publishing Group, 1997. Print.
Guyatt, Rennie. Users’ Guide to Medical Literature: A Manual for Evidence-Based Clinical Practice, 2nd Edition. New York: St. Ruis, 2008. Print.
Sackett, David L & Straus, Sharon E. Evidence-Based Medicine: How to Practice and Teach EBM. Edinburgh: Elsevier Churchill Livingstone, 2005. Print.