Applied Healthcare Statistics (C784)

Correct Answer

C. Wilcoxon signed-rank test

Explanation

The Wilcoxon signed-rank test is a non-parametric test that is similar to the paired t-test. It is used when the data is not normally distributed or when the scale of measurement is ordinal. Like the paired t-test, the Wilcoxon signed-rank test compares two related samples or measurements, but it is used when the data cannot meet the assumptions of normality required for a paired t-test.

Why other options are wrong

A. Chi-square test

The chi-square test is used for categorical data to assess whether there is a significant association between two variables. It is not used for comparing paired measurements, so it is not similar to the paired t-test.

B. Mann-Whitney U test

The Mann-Whitney U test is a non-parametric test used to compare two independent groups. Unlike the paired t-test, which compares related groups, the Mann-Whitney U test is used for unpaired data and is not similar to the paired t-test.

D. ANOVA

ANOVA (Analysis of Variance) is used to compare the means of three or more groups, not paired data. Unlike the paired t-test, which compares two related groups, ANOVA evaluates the variance among multiple groups, so it is not similar to the paired t-test.

Correct Answer

C. To analyze data to forecast future outcomes and effects

Explanation

The main purpose of a predictive study in healthcare research is to use data and statistical methods to forecast future outcomes, trends, or behaviors. Predictive studies typically analyze existing data to identify patterns and relationships that can help anticipate future health events, such as disease outbreaks, patient readmissions, or the effectiveness of treatments over time. This is crucial in healthcare for planning, resource allocation, and improving patient care.

Why other options are wrong

A. To describe the characteristics of a population

Descriptive studies focus on summarizing the characteristics of a population rather than predicting future outcomes. Predictive studies go beyond description and are designed to forecast future events based on data.

B. To explore new areas of research without specific hypotheses

Exploratory studies are aimed at identifying new areas of research without predefined hypotheses, whereas predictive studies are focused on forecasting specific outcomes based on data analysis.

D. To conduct experiments to determine cause-and-effect relationships

Experimental studies are typically used to determine cause-and-effect relationships through controlled experiments. Predictive studies do not focus on causality but instead on forecasting future events based on existing data.

Correct Answer

B. It ensures that the physician has a valid medical license and no history of malpractice.

Explanation

The National Practitioner Data Bank (NPDB) is a critical resource for hospitals to ensure that physicians being onboarded meet all necessary professional standards. It contains information about any malpractice claims, adverse actions taken against the physician's license, or other disciplinary actions. By utilizing the NPDB, hospitals can verify that the physician has a valid medical license, is free from serious ethical or legal issues, and is fit to provide care to patients. This helps maintain patient safety and ensures that healthcare providers adhere to high standards of practice.

Why other options are wrong

A. It helps in determining the salary of the new physician.

The NPDB does not provide any information related to salary determination. Salary negotiations are typically based on other factors such as experience, qualifications, and hospital policies, not the NPDB.

C. It provides information on the physician's research contributions.

The NPDB does not focus on a physician's research activities or academic achievements. Its purpose is to track licensure, disciplinary actions, and malpractice history, not research contributions.

D. It allows hospitals to compare the physician's performance with others in the state.

While the NPDB provides important information regarding a physician’s history, it does not offer direct comparisons of performance with other physicians. Hospitals might rely on other metrics or performance reviews to evaluate and compare physician performance.

Correct Answer

B. Regression analysis

Explanation

Regression analysis is the statistical method used to assess the relationship between variables. In healthcare research, it is commonly used to understand how different factors (such as treatments, demographics, and health conditions) impact outcomes. Regression models can be used to predict future outcomes and evaluate the strength and nature of these relationships between variables.

Why other options are wrong

A. Descriptive statistics

Descriptive statistics is used to summarize and describe the features of a dataset, such as means, medians, and standard deviations, but it does not analyze relationships between variables. It focuses on presenting data rather than making predictions or assessing relationships.

C. Predictive modeling

While predictive modeling uses regression and other techniques to predict future outcomes, it is broader in scope. Predictive modeling often involves machine learning and other advanced methods, whereas regression analysis specifically looks at the relationship between variables.

D. ANOVA

ANOVA (Analysis of Variance) is used to compare means across three or more groups, not to assess relationships between variables. It evaluates the differences in means between groups rather than exploring how one variable impacts another.

Correct Answer

B. It allows for the analysis of variance among multiple groups simultaneously.

Explanation

ANOVA (Analysis of Variance) is used to compare the means of three or more groups to determine if there are statistically significant differences between them. In healthcare research, ANOVA is particularly useful when researchers want to compare various treatments, patient groups, or other variables across multiple categories. It is preferred over other tests, such as the t-test, when comparing multiple groups because it can handle multiple comparisons in a single analysis, reducing the risk of Type I errors.

Why other options are wrong

A. It provides a simple comparison of two groups.

ANOVA is specifically designed for comparing more than two groups. For comparing two groups, a t-test would be more appropriate.

C. It is easier to compute than regression analysis.

While ANOVA and regression analysis are both statistical techniques, the ease of computation depends on the complexity of the data and the model. ANOVA is not necessarily easier to compute than regression analysis, as both have their own computational challenges.

D. It focuses solely on descriptive statistics.

ANOVA is an inferential statistical method, not just descriptive. It is used to test hypotheses about the differences in group means, which goes beyond descriptive statistics and involves making inferences about population parameters.

Correct Answer

C. To facilitate early diagnosis and treatment of health issues

Explanation

The primary purpose of medical screening in employee health programs is to detect potential health issues early, which allows for timely intervention, diagnosis, and treatment. This proactive approach helps in reducing the risk of serious health conditions and contributes to improving the overall well-being of employees. It is a key part of promoting a healthy workplace and reducing long-term health costs by addressing issues early.

Why other options are wrong

A. To provide comprehensive health education

While health education is an important aspect of employee health programs, it is not the primary purpose of medical screening. Medical screening focuses on identifying existing health problems rather than educating employees about health topics.

B. To ensure compliance with health regulations

Medical screenings may be required by certain regulations in specific industries (e.g., for workplace safety), but the primary purpose is not simply to ensure regulatory compliance. It’s about early identification of health risks and addressing them before they lead to more severe issues.

D. To monitor employee productivity

While employee health may indirectly impact productivity, medical screening is not intended to monitor or assess productivity. Its focus is on detecting health issues and providing the necessary medical care to employees.

Correct Answer

A. It leads to a false conclusion that a treatment is effective when it is not.

Explanation

A Type I error occurs when a researcher incorrectly rejects the null hypothesis, concluding that there is a significant effect or relationship when there is actually none. In healthcare research, this could lead to the adoption of ineffective treatments, potentially exposing patients to unnecessary risks or side effects. False positive results can divert resources, cause inappropriate treatment decisions, and ultimately harm patient outcomes.

Why other options are wrong

B. It results in the acceptance of a null hypothesis that should be rejected.

This describes a Type II error, not a Type I error. A Type II error occurs when a researcher fails to reject a false null hypothesis, which means an actual effect is missed.

C. It indicates that the sample size was too large.

Sample size issues may influence the likelihood of both Type I and Type II errors, but a Type I error is not inherently related to the sample size being too large. A Type I error is about rejecting a true null hypothesis, regardless of sample size.

D. It has no significant impact on research outcomes.

This is incorrect because a Type I error can have significant consequences, especially in healthcare research. It may lead to harmful treatment decisions or misdirect resources, making it a critical concern in research outcomes.

Correct Answer

B. The differences in the incidence, prevalence, mortality, and burden of disease that exist among specific populations.

Explanation

Health disparities refer to the unequal burden of disease, illness, and death that different populations face. These disparities can be related to factors such as race, ethnicity, socioeconomic status, geography, and access to care. By focusing on the differences in incidence, prevalence, and mortality, this definition captures the essence of health disparities, which are a key concern in public health and healthcare equity efforts.

Why other options are wrong

A. The differences in health status among racial-ethnic characteristics

While racial and ethnic factors can contribute to health disparities, this definition is too narrow. Health disparities involve broader factors, including socioeconomic status, access to healthcare, and other determinants of health, not just racial-ethnic differences.

C. The similarities between two or more ethnic-racial or age groups

This option describes homogeneity rather than disparities. Health disparities focus on differences, not similarities, in health outcomes across various population groups.

D. The differences that exist among income and education

Income and education are factors that contribute to health disparities, but health disparities encompass a broader range of issues, including healthcare access, disease outcomes, and other social determinants of health. This option does not fully capture the full scope of what health disparities are.

Correct Answer

C. F-test

Explanation

The F-test is used to compare the variances of two populations by calculating the ratio of the two variances. It is commonly used in the context of ANOVA and other statistical analyses to determine if there is a significant difference between the variances of two or more groups.

Why other options are wrong

A. T-test

The T-test is used to compare the means of two groups, not variances. It does not provide information about the ratio of variances.

B. Z-test

The Z-test is typically used to compare population means when the sample size is large or the population variance is known. It is not designed to compare variances.

D. Chi-square test

The Chi-square test is used to examine the relationship between categorical variables, not to compare variances. It is often used in tests of independence and goodness of fit but does not assess variances.