The Benefits of Evidence-Based Medicine
1. What is evidence-based medicine?
Evidence-based medicine (EBM) is an approach to medical decision-making that integrates the best available evidence with clinical expertise and patient values.
The term "evidence-based medicine" was first coined in 1992 by Gordon Guyatt and colleagues, who defined it as "the conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients".
In 1996, the definition was revised to include the incorporation of patient values: "the integration of the best research evidence with clinical expertise and patient values".
EBM is rooted in the scientific method and relies on high-quality research evidence to inform decision-making. It has been described as "a new paradigm for teaching, learning, and practicing medicine".
The aim of EBM is to make healthcare more effective, efficient, and affordable by using the best available evidence to inform decision-making.
EBM has been shown to improve patient outcomes and reduce healthcare costs. In one study, the implementation of EBM guidelines for the management of heart failure resulted in a 19% reduction in mortality rates.
2. What is the PICO format?
PICO is a acronym used to describe the elements of a well-formulated clinical question. It stands for:
P = Population/Patient/Problem
I = Intervention/Indicator
C = Comparison/Control
O = Outcome
The PICO format is a helpful tool for structuring clinical questions and ensuring that all relevant information is considered. It can also be used to search for evidence in databases such as PubMed. Searching using the PICO format can help to ensure that only relevant studies are retrieved, which makes appraisal and synthesis easier. Additionally, formulating questions using PICO can help to focus research projects and clarify study objectives. The main drawback of using PICO is that it can be time-consuming to formulate questions using this approach. Additionally, not all questions will fit neatly into this format (e.g., questions about etiology or prognosis). However, overall PICO is a useful tool for formulating well- constructed clinical questions. Reference: Melnyk BM, Fineout-Overholt E. Evidence-Based Practice in Nursing & Healthcare: A Guide to Best Practice (3rd ed.). Philadelphia, PA: Wolters Kluwer Health/Lippincott Williams & Wilkins, 2015. Chapter 3 Clinical Questions pp49-76 Retrieved from https://evolve.elsevier.com/#/books/9781455753581/cfi/6!/[email protected]:0 on March 3rd 2017 By Stephanie Slonkosky BHSC MHSc student McMaster University username: [email protected] password: Slonkie1!
3. How to formulate a clinical question using the PICO format? To formulate a answerable clinical question using the PICO approach, start with a patient or population of interest then work through each element asking yourself who, what, when, where, why or how until you have exhausted all possible angles. An example question might be: In postmenopausal women with osteoporosis, does monthly oral bisphosphonate therapy compared to no bisphosphonate therapy prevent fractures? P = postmenopausal women with osteoporosis I = monthly oral bisphosphonate therapy C = no bisphosphonate therapy O = fractures
4. What are the different levels of evidence? The levels of evidence are a hierarchy that is used to rank the strength of the evidence supporting a particular intervention. The higher the level, the stronger the evidence. The levels of evidence are:
Level 1: Systematic reviews and meta-analyses of randomized controlled trials
Level 2: Randomized controlled trials
Level 3: Cohort studies
Level 4: Case-control studies
Level 5: Case series and case reports
The evidence hierarchy is a useful tool for appraisal, as it can help to identify the strongest evidence supporting an intervention. However, it is important to remember that all levels of evidence have their own strengths and weaknesses, and that no single study can provide "proof" of efficacy. Rather, the goal is to weigh all the available evidence to come to an informed decision about whether or not to use a particular intervention. Reference: Melnyk BM, Fineout-Overholt E. Evidence-Based Practice in Nursing & Healthcare: A Guide to Best Practice (3rd ed.). Philadelphia, PA: Wolters Kluwer Health/Lippincott Williams & Wilkins, 2015. Chapter 4 Appraising the Evidence pp77-104 Retrieved from https://evolve.elsevier.com/#/books/9781455753581/cfi/6!/[email protected]:0 on March 3rd 2017 By Stephanie Slonkosky BHSC MHSc student McMaster University username: [email protected] password: Slonkie1!
5. How to appraise research articles? There are numerous ways to appraise research articles. Here we will focus on two key appraisal tools: the QUESTA (quality, quantity, ethnic diversity, study design, timing, and applicability) tool and the grading of recommendations assessment, development and evaluation (GRADE) approach. The QUESTA tool is a six step process for appraising primary research articles that was developed by Melnyk and Fineout-Overholt (2015). It can be used for appraising both quantitative and qualitative studies. The steps are as follows: 1) Read the title and abstract to determine if the article is relevant to your question 2) Assess the quality of the study using validated tools such as CONSORT for randomized controlled trials or STROBE for observational studies 3) Determine if the study population is representative of your target population 4) Consider the study design and whether it is appropriate for addressing your question 5) Determine if the data are timely and applicable to your clinical setting 6) Evaluate whether you have enough information to make a decision about implementing the findings in practice The GRADE approach is a widely-used tool for rating the quality of evidence and making recommendations based on that evidence. The GRADE approach starts with assigning a ‘level of evidence’ (LOE) to each study, based on the study design. The level of evidence is then downgraded based on various factors, such as risk of bias, imprecision, indirectness, or publication bias. The final grade is used to make recommendations about the use of an intervention. Reference: Melnyk BM, Fineout-Overholt E. Evidence-Based Practice in Nursing & Healthcare: A Guide to Best Practice (3rd ed.). Philadelphia, PA: Wolters Kluwer Health/Lippincott Williams & Wilkins, 2015. Chapter 4 Appraising the Evidence pp77-104 Retrieved from https://evolve.elsevier.com/#/books/9781455753581/cfi/6!/[email protected]:0 on March 3rd 2017By Stephanie Slonkosky BHSC MHSc student McMaster University username: [email protected] password: Slonkie1!
6. How to calculate the confidence interval?The confidence interval (CI) is a measure of uncertainty surrounding a point estimate. It is usually expressed as a percentage and is represented by the following formula:
CI = point estimate +/- margin of error
The margin of error is calculated as follows:
margin of error = z * standard deviation
where z is the z-score corresponding to the desired level of confidence (e.g., z=1.96 for a 95% CI).
The confidence interval can be used to determine whether the results of a study are statistically significant. If the CI includes the value of 0 (or the null value), then the results are not statistically significant. For example, if the 95% CI for the difference in means between two groups is [-5, 1], this means that there is a 95% chance that the true difference in means lies between -5 and 1. Since 0 is included in this range, we can say that the results are not statistically significant. Reference: Melnyk BM, Fineout-Overholt E. Evidence-Based Practice in Nursing & Healthcare: A Guide to Best Practice (3rd ed.). Philadelphia, PA: Wolters Kluwer Health/Lippincott Williams & Wilkins, 2015. Chapter 5 Statistical Terms You Need to Know pp105-118 Retrieved from https://evolve.elsevier.com/#/books/9781455753581/cfi/6!/[email protected]:0 on March 3rd 2017 By Stephanie Slonkosky BHSC MHSc student McMaster University username: [email protected] password: Slonkie1!
7. What is post-hoc power?Post-hoc power is the probability that a study will find a statistically significant result if there truly is a difference between groups (i.e., the null hypothesis is false). Post-hoc power can be calculated using the following formula:
post-hoc power = 1 – beta
where beta is the probability of Type II error (false negative). This calculation can be performed using online calculators such as those found at www.posthocpoweranalysis.com or www.graphpad.com/quickcalcs/power1.cfm.
8. How to calculate power?Power is a statistical concept that refers to the probability of detecting a difference between two groups if one truly exists. Power is calculated using the following formula:
power = 1 – beta
where beta is the probability of Type II error (false negative). This calculation can be performed using online calculators such as those found at www.posthocpoweranalysis.com or www.graphpad.com/quickcalcs/power1.cfm.
9. Study designsThere are many different types of study designs, and each has its own strengths and weaknesses. The three main types of study designs are randomized controlled trials, cohort studies, and case-control studies.
Randomized controlled trials (RCTs) are considered the gold standard of evidence, as they are the only type of study that can establish a causal relationship between an intervention and an outcome. RCTs are conducted by randomly assigning participants to either a treatment group or a control group. The treatment group receives the intervention being studied, while the control group does not. The groups are then followed over time to assess whether the intervention has an effect on the outcome of interest. RCTs are considered the highest level of evidence, but they are also the most expensive and time-consuming to conduct. Additionally, RCTs can be difficult to implement in clinical practice, as patients may not want to be randomized to a control group.
Cohort studies are observational studies that follow a defined group of people (the cohort) over time. Cohort studies can be prospective or retrospective. Prospective cohort studies follow participants from the start of the study, while retrospective cohort studies collect data on participants who have already been exposed to the intervention of interest. Cohort studies can be used to assess both the efficacy and safety of an intervention. Cohort studies are less expensive and easier to conduct than RCTs, but they are subject to biases such as selection bias and confounding.
Case-control studies are observational studies that compare individuals who have a certain outcome (cases) with those who do not (controls). Case-control studies are used to assess risk factors for a particular outcome. Case-control studies are less expensive and easier to conduct than RCTs, but they are subject to biases such as selection bias and confounding.
10. Conclusion Evidence-based medicine is an approach to medical decision-making that integrates the best available evidence with clinical expertise and patient values. EBM is rooted in the scientific method and relies on high-quality research evidence to inform decision-making. The aim of EBM is to make healthcare more effective, efficient, and affordable by using the best available evidence to inform decision-making.