Ebm tool

When results from different studies are combined, only similar outcomes should be combined. Reviews that attempt to convert study results from one scale to another generally will not be considered. Type of Study: Prognosis The main threats to studies of prognosis are initial patient identification and loss of follow-up. Did the investigators identify a specific group and follow it forward in time?

Were the criteria for entry into the study objective and reasonable? Entry criteria must be reproducible and not too restrictive or too broad. Was group follow-up adequate at least 80 percent? Were the patients similar to those in primary care in terms of age, sex, race, severity of disease, and other factors that might influence the course of the disease? Where did the patients come from—was the referral pattern specified? The source of patients will be noted in the review.

Were outcomes assessed objectively and blindly? Decision Analysis Decision analysis involves choosing an action after formally and logically weighing the risks and benefits of the alternatives. Validity questions Were all important strategies and outcomes included?

Analyses evaluating only some outcomes or strategies will not be reviewed. Was an explicit and sensible process used to identify, select, and combine the evidence into probabilities?

Is the evidence strong enough? Were the utilities obtained in an explicit and sensible way from credible sources? Specifically, were utilities obtained from small samples or from groups not afflicted with the disease or outcome. Was the potential impact of any uncertainty in the evidence determined? It must be noted whether a sensitivity analysis was performed to determine how robust the analysis is under different conditions. How strong is the evidence used in the analysis?

Could the uncertainty in the evidence change the result? It will be noted if any given variable unduly influences the analysis. Qualitative Research Qualitative research uses nonquantitative methods to answer questions.

Validity questions Was the appropriate method used to answer the question? Interviews or focus groups should be used to study perceptions. Observation is required to evaluate behaviors. Studies not using the appropriate method will not be reviewed. Was appropriate and adequate sampling used to get the best information? Random sampling is not used in qualitative research.

Instead, patients are selected with the idea that they are best suited to provide appropriate information. Assurance that enough patients were studied to provide sufficient information should be found in the description. Was an iterative process of collecting information used? In qualitative research, the researcher learns about the topic as the research progresses.

The study design should consist of data collection and analysis, followed by more data collection and analysis, in an iterative fashion, until no more information is obtained.

Was a thorough analysis presented? A good qualitative study presents the findings and provides a thorough analysis of the data. Are the background and training of the investigators described? Because investigators are being relied on for analysis of the data, their training and biases must be documented. These characteristics can be used to evaluate the conclusions.

Hill's Criteria for Causation These are a broadly accepted set of nine criteria to establish causality between an exposure or incidence and an effect or consequence.

Strength of association: larger associations are more likely to be causal Consistency of association: repeated observations of the association across different samples and situations Specificity: the absence of other likely explanations or causes Temporal relationship: the effect must occur after the cause Biological gradient dose-response relationship : higher exposure increases likelihood of the effect Plausibility: a physiologic or biologic mechanism exists to explain the relationship limited by current state of knowledge Coherence: laboratory and epidemiologic relationships are congruent Experiment: investigational experiments reproduce effects Analogy: similar factors are known to have similar effects Information from Hill AB.

The most helpful tests generally have a ratio of less than 0. Relative risk reduction RRR The percentage difference in risk or outcomes between treatment and control groups. Absolute risk reduction ARR The arithmetic difference in risk or outcomes between treatment and control groups.

Number needed to treat NNT The number of patients who need to receive an intervention instead of the alternative in order for one additional patient to benefit. A narrow CI is good. A CI that spans 1. Systematic review A type of review article that uses explicit methods to comprehensively analyze and qualitatively synthesize information from multiple studies Meta-analysis A type of systematic review that uses rigorous statistical methods to quantitatively synthesize the results of multiple similar studies.

Disease-Oriented Evidence Statistical Significance vs. A hierarchy exists for clinical decision rules. No clinical decision rule should be widely used until it has been clearly shown to be beneficial in external validity studies.

The level of evidence of clinical guidelines should be reviewed before widespread implementation. Clinical trials should be designed to have only one predesignated primary outcome. Studies with multiple outcomes run the risk that a statistically significant outcome occurred by chance alone.

META-ANALYSES A good meta-analysis requires the following among other things : an analysis of the quality of studies included in the meta-analysis one set of criteria is published by the Cochrane Collaboration ; and data extraction by more than one person in each study do the reviewers agree on something as basic as the data to be analyzed?

A multiple-treatments meta-analysis allows you to compare treatments directly e. Meta-analyses can come to the wrong conclusion for several reasons. First is publication bias—typically only positive trials are published and included in the meta-analysis. The second is the garbage-in, garbage-out phenomenon; to avoid this, the authors of a meta-analysis must evaluate the quality of the trials they are using so that only higher-quality studies are included.

A study using block randomization assigns patients in small groups. This type of randomization is done to decrease the likelihood of too many patients being randomized to a single treatment. In one study, randomization was in blocks of four, so one person in each block was randomized to one of the four treatment protocols.

Because of ethical constraints, randomized controlled trials will not be available to answer all clinical questions, particularly those that explore long-term risks, such as cancer.

For these types of clinical questions, we must rely on mathematical modeling or abstraction of data from other sources. Retrospective studies need to follow common, agreed-upon methods of data abstraction. Propensity matching is used to remove confounders in retrospective studies. The idea is to balance the groups being compared in their likelihood of needing a therapy. These are characteristics that are distributed differently among study groups and that can affect the outcome being assessed.

Exclusion bias. Excluding patients in whom the study drug has already failed biases the study in favor of that drug. If these patients had been included e. History bias. Controlling for temporal trends in disease incidence is important when doing a comparison between contemporary and historical groups. Industry bias. This refers to the fact that studies and reviews published by industry are more likely to present positive favorable outcomes.

Look for non—industry-sponsored studies—they are less likely to have publication bias or use inappropriate comparisons. Interrupted time series design bias. Lack of placebo bias. Failure to use a true placebo may jeopardize the validity of the results of a trial. Almost anything will look better than placebo. A study should compare the study drug with a real-world scenario, such as in the case of another study increasing the dose, switching antidepressants, or using another drug for augmentation.

Lead-time bias is an important consideration when evaluating a screening intervention. Diagnosing disease earlier with a screening test can appear to prolong survival without actually changing outcomes.

The only thing that changes is the period of time during which the patient is diagnosed with the disease, not the actual survival time. Observation bias also known as the Hawthorne effect occurs when individuals temporarily modify their behavior and consequently change study outcomes when they know they are being observed. Gains achieved during the study period often regress when the study ends.

An example is when a researcher is adjudicating an outcome, and knows which treatment group a patient was assigned to. A stronger study is blinded for patients, researchers, and, if used, evaluators.

Publication bias. Studies that show treatments in a positive light are more likely to be submitted for publication. For example, the published studies on levalbuterol look good. But if you look at all of the studies submitted to the U. Food and Drug Administration, levalbuterol and albuterol are equivalent, and albuterol costs less. Negative studies are less likely to get published than positive studies, and this results in the overwhelmingly positive nature of the literature.

Even when negative studies are published, they are less likely to receive the attention by the media and medical establishment that positive studies do. In addition, more and more information is being hidden in online supplemental protocol information or in appendices. Review bias occurs when the reader of a test e. The history may change the way a test is read. Run-in bias. Run-in periods to assess compliance and ensure treatment responsiveness create a bias in favor of the treatment in question, and yield results in a patient population that will not be the same as in your patients.

Thus, the results of these studies may not be generalizable. Sampling bias. Representative inclusion of all possible study participants helps to eliminate differences between groups so that more appropriate comparisons can be made. If only some subsets of patients are included i. Selection bias occurs when the patients in a study are not representative of the patients you see in practice.

Spectrum bias occurs when the group being studied is either sicker or not as sick as the patients you see in your practice. A diagnostic test can perform differently in dissimilar patient populations. You cannot apply a test standardized in an inpatient population to your outpatient population or vice versa and expect it to have the same sensitivity and specificity. Straw man comparison bias. In head-to-head treatment trials, watch out for the straw man comparison.

For example, make sure that an article that evaluates treatments uses equipotent dosages of the drugs being compared. Obviously, if you use an adequate dose of a study drug and a suboptimal comparison, the study drug is going to win.

In one study, the doses of prasugrel and clopidogrel were not equivalent. As a corollary, a placebo-controlled trial should not typically change your practice; any drug comparison should be against a known effective therapy, if one exists.

Verification bias or workup bias exists when not everyone in a study gets the definitive, criterion standard test. This generally makes the new test look better because real cases of disease are missed when patients with a negative new test are sent home.

A risk factor and outcome are associated if they occur together. Case-control studies can suggest an association, but not causation. Causation is more difficult to establish and generally requires a prospective randomized study. Case-control studies may not be able to control for all patient variables.

This is a potential source of error. A good example of this would be case-control studies that suggested that postmenopausal estrogen was cardioprotective. Subsequent randomized controlled trials proved that this is not the case. An association does not confer causation. But when multiple criteria are met e. Reverse causation. A reverse causality error occurs when the outcome, or some component of it, causes the intervention or exposure in question. Be skeptical of industry-sponsored studies.

They tell you the real magnitude of benefit and harm. P values only tell you that there is a difference between two groups; this difference can be clinically meaningless. NNT gives a better sense of the strength of treatment effect. Let your patients know the magnitude of benefit and risk in language that is easy for them to understand.

For instance, in one study, 33 patients need to be treated for one year to prevent one hospitalization, at a risk of one in 41 patients developing pneumonia. Large numbers of patients are typically required to demonstrate a deleterious side effect of a drug or intervention i. They do not meet the same rigorous design and statistical format of traditional superiority trials.

Showing that one drug is noninferior to another does not mean that these drugs are equivalent. Authors of noninferiority trials must declare a margin of how far outside the acceptable outcome the treatment can perform and still be considered noninferior to the standard treatment.

The noninferiority margin allows researchers to choose their own benchmark for what is considered a clinically significant difference between two drugs. This can lead to a drug being called noninferior when other researchers not associated with the study would call it inferior.

The efficacy of the standard treatment for instance, warfarin shown in the trials that established its efficacy must be preserved in any noninferiority trials. In a study comparing warfarin and rivaroxaban, time in therapeutic range was not within established norms for many of the patients—this would make warfarin perform worse and allow rivaroxaban to appear noninferior.

It is usually used in case-control studies and not in randomized trials, where relative risk and absolute risk are used instead. Case-control studies are not interventional studies and are retrospective, so we use odds ratio rather than relative risk as a measure of the association. Odds ratio is calculated by dividing the odds of disease in those who were exposed to a given factor by the odds of disease in those who were not exposed.

Relative risk is the ratio of the probability of an event in an exposed population to the probability in an unexposed population. This calculation is useful in comparisons in which there is a low probability of the event occurring. Attributable risk is the difference in the rate of an event between an exposed population and an unexposed population. This is usually calculated in cohort studies. POEMs refers to clinical outcomes that mean something to patients e.

DOE is an indirect measure of a pathologic or physiologic process that may or may not correlate with clinical outcomes such as changes in blood glucose, electrocardiogram abnormalities, carotid intima thickening. A lot of studies use surrogate markers as outcomes e. These are DOEs. What we care about are POEMs e. Be wary of DOEs; they are surrogate markers of disease and may or may not correlate with important clinical end points, such as morbidity and mortality.

For example, in certain clinical situations, it is possible to lower blood pressure, but not help patients. It could even harm them. A study should change your practice only if it is applicable to your patient population e. Another example: in one study, 23 mg of donepezil was statistically better than 10 mg, but only in one of three tests, and by only two points on a point scale.

This is clinically imperceptible, yet it will be touted as superior by pharmaceutical companies. When reviewing a study, you must know what the scale measures, whether the scale has been validated, and what change in the scale is actually clinically significant. What kind of project do people do for their MSc Dissertation?

Can a short courses completed 'For Credit', count towards a Masters award if enrolled at a later date? Will I get a formal Oxford University Certificate for completing one of the short courses? Can the programme be completed entirely online without attending Oxford?

Will I have an Oxford Email address for the duration of my studies? How many contact hours are there in the face to face 'Oxford weeks'? What kind of time commitment is required in order to undertake the dissertation element of the MSc programme? What is the difference between completing a professional short course 'for credit' or 'not for credit'? Can the MSc be completed in one year? Does the mode of delivery still allow you to be able to work full time? Is there a minimum or maximum number of modules required per year as part of the MSc?

What date do short-course applications close? What is the process for applying for a short course or award?

Do you operate a 'waiting list' for the Short Courses? Is a certain level of English proficiency required to apply for the programme and how does this have to be demonstrated? Its mission is to promote healthy ecosystems and communities by increasing the knowledge and capacity of coastal-marine practitioners to apply tools that help incorporate ecosystem-based thinking into management decisions.

EBM tools are methods and software that help practitioners incorporate scientific and socioeconomic information into decision making. They can help develop models of ecosystems, generate scenarios illustrating the consequences of different management decisions on natural resources and the economy, and facilitate stakeholder involvement in planning processes.

The EBM Tools Network's series of webinars highlights key tools and tool-use case studies to help practitioners learn about tools quickly and determine their suitability for specific projects.

Webinars are held one to three times per month and typically last one hour. Users can also sign up for the EBM Tools Network listserve, an interactive discussion list that allows practitioners to ask questions and share information about tools and methods that can be used for improving coastal and marine conservation and management.

The EBM team can also help plan, develop, and conduct training events in EBM tools, ranging from half-day events to multi-day training workshops anywhere in the world.