23- Statistics & Medicologeal Aspects Explains Flashcards
What is clinical audit?
Clinical audit is a quality improvement process that aims to improve patient care and outcomes. It involves systematically reviewing care against explicit criteria and implementing changes as needed. It evaluates aspects of care such as structure, processes, and outcomes.
What is the purpose of clinical audit?
The purpose of clinical audit is to improve healthcare delivery by identifying areas for improvement and implementing changes to achieve better patient care and outcomes.
How is clinical audit conducted?
Clinical audit involves selecting specific aspects of care to evaluate against explicit criteria. Changes are implemented at the individual, team, or service level, and further monitoring is used to confirm improvement in healthcare delivery.
What is research?
Research aims to derive new knowledge that has the potential to be generalizable or transferable. It involves conducting systematic investigations and studies to explore and uncover new information or insights.
What is the goal of research?
The goal of research is to contribute to the body of knowledge in a particular field by discovering new information, generating evidence, and advancing understanding. It aims to expand knowledge and potentially improve practices or outcomes in various areas.
What is a financial audit?
A financial audit is a historically oriented evaluation conducted to attest to the fairness, accuracy, and reliability of financial data. It is independent and aims to provide assurance on the financial information of an organization.
What is an operational audit?
An operational audit is a future-oriented evaluation of organizational activities. It is systematic and independent, focusing on assessing operational policies and achievements related to organizational objectives. While financial data may be used, the primary sources of evidence are the operational aspects of the organization. This type of audit may evaluate internal controls and efficiencies.
What is a departmental review?
A departmental review is an analysis of administrative functions during the current period. It aims to evaluate the adequacy of controls, safeguarding of assets, efficient use of resources, compliance with laws and regulations, and the integrity of financial information.
What is a standards-based audit?
A standards-based audit involves comparing care or the passage of care against predefined and widely agreed standards or outcomes. It assesses whether the care provided meets the established standards.
What is a systems-based audit?
A systems-based audit evaluates the processes occurring within an institution. It is an integral part of the clinical governance process and focuses on assessing and improving the systems and processes in place within an organization to ensure quality and safety of care.
What is a Type 1 error in statistics?
A Type 1 error occurs when a statistical test incorrectly rejects a true null hypothesis. In other words, it is a false positive result where the test concludes there is an effect or relationship when, in reality, there is none.
What determines the rate of Type 1 error?
The rate of Type 1 error is determined by the value of α, which is usually equal to the significance level of the test. The significance level sets the threshold for rejecting the null hypothesis and is typically set at 0.05 or 0.01.
What is a Type 2 error in statistics?
A Type 2 error occurs when a statistical test fails to reject a false null hypothesis. In other words, it is a false negative result where the test fails to detect an effect or relationship that actually exists.
What determines the rate of Type 2 error?
The rate of Type 2 error is given by the value of β. It is related to the power of the test, which is the probability of correctly rejecting a false null hypothesis. The power of the test is equal to 1 - β.
How are Type 1 and Type 2 errors related?
Type 1 and Type 2 errors are inversely related. By decreasing the rate of Type 1 error (α), the rate of Type 2 error (β) typically increases, and vice versa. There is a trade-off between the two, and researchers must consider the acceptable levels of both errors based on the context and goals of their study.
What is incidence in relation to a health condition?
Incidence refers to the number of new cases of a health condition that occur within a specific population during a given time period. It represents the rate at which new cases of the condition are diagnosed or reported.
How is incidence calculated?
Incidence is calculated by dividing the number of new cases of a condition by the population at risk during a specified time period. The result is often expressed as a rate or a percentage.
What is prevalence in relation to a health condition?
Prevalence refers to the total number of cases of a health condition within a specific population at a particular point in time. It represents the proportion of individuals in the population who have the condition.
How is prevalence calculated?
Prevalence is calculated by dividing the total number of cases of a condition by the total population during a specific time period. The result is often expressed as a rate or a percentage.
What is the relationship between incidence and prevalence?
The relationship between incidence and prevalence is influenced by the duration of the condition. In chronic diseases, where the condition persists over a long period, the prevalence is typically much greater than the incidence. In acute diseases, where the condition is short-lived, the prevalence and incidence are often similar. For certain conditions like the common cold, the incidence may be greater than the prevalence due to the high occurrence of new cases within a short time period.
What is absolute risk reduction?
Absolute risk reduction refers to the decrease in risk associated with a specific activity or treatment compared to a control activity or treatment. It quantifies the difference in risk between the two options. Absolute risk reduction is calculated as the difference in probabilities or rates of a defined endpoint between the two treatments.
How is absolute risk reduction calculated?
To calculate absolute risk reduction, the probabilities or rates of a defined endpoint for two different treatments are compared. The absolute risk reduction is obtained by subtracting the probability or rate of the endpoint for the control treatment from the probability or rate of the endpoint for the active treatment (pX - pY).
What is the Number Needed to Treat (NNT)?
The Number Needed to Treat (NNT) is the inverse of absolute risk reduction. It represents the number of patients who need to receive a particular treatment to prevent one event (e.g., morbidity, mortality, or adverse outcome). It provides a measure of the impact of a treatment and helps determine the cost-effectiveness and potential benefits of a treatment option.
How is the Number Needed to Treat calculated?
The Number Needed to Treat (NNT) is calculated as the reciprocal of the absolute risk reduction. It is obtained by taking the inverse of the difference in probabilities or rates between two treatments. The NNT indicates the number of patients that need to be treated with a specific intervention to prevent one additional event compared to a control group.
Why is it important to categorize data correctly before statistical analysis?
Categorizing data correctly before statistical analysis is crucial because it determines the appropriate method of analysis to be used. Different types of data require different statistical tests and techniques. By accurately categorizing the data as nominal, ordinal, interval, or continuous, researchers can select the most suitable statistical approach to draw meaningful conclusions from the data.
To calculate absolute risk reduction, the probabilities or rates of a defined endpoint for two different treatments are compared. The absolute risk reduction is obtained by subtracting the probability or rate of the endpoint for the control treatment from the probability or rate of the endpoint for the active treatment (pX - pY).
Absolute risk reduction is important in evaluating the effectiveness of different treatments. It helps quantify the actual reduction in risk associated with a specific treatment compared to an alternative. This information is valuable in making informed decisions about treatment options and assessing the cost versus the potential benefit of a treatment.
What is nominal data?
Nominal data refers to data that can be assigned a numerical code, but the code itself is arbitrary and does not convey any inherent order or magnitude. An example of nominal data is categorizing people as alive or dead using codes of 0 or 1.
What is ordinal data?
Ordinal data involves numbers that can be used to represent a scale or order. It allows for the ranking or categorization of data based on a specific attribute or characteristic. An example of ordinal data is the measurement of pain severity, where numbers are assigned to indicate the level of pain experienced.
What is continuous data?
Continuous data is measured numerically and can take on any real value. It is not limited to specific categories or intervals. Examples of continuous data include measurements such as height, weight, or temperature.
What are some common statistical tests used for analyzing different types of data?
For normally distributed data, parametric tests like the T Test are commonly used. Non-normally distributed data requires non-parametric tests such as the Chi Squared test or Mann Whitney U test. The Fisher’s exact test is often used for small sample sizes. The paired T Test is appropriate when paired samples are taken from the same individuals, such as before and after an intervention.
What is post hoc analysis?
Post hoc analysis refers to the analysis of data after an initial analysis has been performed and unexpected results or differences are observed. It involves examining specific groups or subgroups within the data to identify any patterns or correlations that were not originally anticipated. However, it is important to interpret post hoc analysis with caution as it can increase the likelihood of errors and false rejections of null hypotheses.
How can multiple testing be addressed in statistical analysis?
To address the issue of multiple testing, researchers may apply a Bonferroni correction. This correction adjusts the statistical analysis to account for the increased probability of obtaining a statistically significant result by chance when conducting multiple analyses on the same dataset. The Bonferroni correction helps control the overall Type I error rate and maintain the reliability of the statistical findings.
What are the three types of consent?
The three types of consent are:
1. Informed consent
2. Expressed consent
3. Implied consent
What are the key points of capacity when it comes to consent?
The key points regarding capacity for consent are:
1. Understanding and retaining information
2. Believing the information to be true
3. Weighing the information to make a decision
What is qualitative data?
Qualitative data, also known as categorical data, consists of different descriptions or categories of a characteristic. While it may be possible to assign numbers to these categories, they do not have a numerical scale or inherent order. Examples of qualitative data include gender, occupation, or types of food.
What are the different consent forms used in the UK NHS?
The different consent forms used in the UK NHS are:
1. Form 1: For competent adults who are able to consent for themselves, even when consciousness may be impaired (e.g., under general anesthesia)
2. Form 2: For an adult consenting on behalf of a child when consciousness is impaired
3. Form 3: For an adult or child when consciousness is not impaired
4. Form 4: For adults who lack capacity to provide informed consent
Who can provide consent for minors in the UK?
In the UK, young children and older children who are not deemed Gillick competent cannot provide consent for themselves. The biological mother of the patient can always provide consent. If the parents are married (and the father is the biological father) or if the father is named on the birth certificate (regardless of marital status), the child’s father can also provide consent. However, if the parents are not married and the father is not named on the birth certificate, the father cannot provide consent.
What is quantitative data?
Quantitative data is data that is associated with numerical values on a numerical scale. It involves measurements or counts that can be expressed as numbers. Quantitative data can be organized to create a distribution curve and allows for various statistical analyses. Examples of quantitative data include height, weight, or test scores.
How can quantitative data be analyzed?
Quantitative data can be analyzed by estimating the central tendency using measures such as the mode (most frequently occurring value), median (middle value), and mean (average). The standard deviation provides an estimation of the spread or variability of the data points around the central tendency. Other statistical techniques can also be applied to analyze quantitative data, such as hypothesis testing, correlation analysis, and regression analysis.
How is relative risk calculated?
Relative risk is calculated by dividing the experimental event rate (EER) by the control event rate (CER). The formula for relative risk is: RR = EER / CER.
What is relative risk (RR)?
Relative risk (RR) is the ratio of the risk in the experimental group (experimental event rate, EER) to the risk in the control group (control event rate, CER). It measures the likelihood or probability of an event occurring in the experimental group compared to the control group.
What does a relative risk ratio greater than 1 indicate?
If the relative risk ratio is greater than 1, it indicates that the rate of an event (such as experiencing significant pain relief) is increased in the experimental group compared to the control group.
