Understanding Statistical Measurements

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Understanding Statistical Measurements

Introduction

When data analytics are properly used in healthcare environments, it significantly helps to improve patient care. Validity refers to the scope or length at which an instrument, including survey or test is used to measure what it is required to measure, while reliability tend to evaluate how stable and consistent a measurement is. In health-related study, validity and reliability help to demonstrate the qualities in a measuring instrument. Utilizing tests or survey tools in research to measure validity and reliability provides important concepts known as theoretical constructs, which a crucial component of research quality in healthcare (University of the West of England, 2020). This project discusses an application of data analysis, reliability and validity, and assorted statistical tests used in health-related research (GCU, 2020)Understanding Statistical Measurements.

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Data Analysis

Types of Study Used in Each Article

The first article is entitled “Patients’ experience and perception of hospital-treated Clostridium difficile diseases” and implements the qualitative research methods. According to the article, Clostridium difficile could be the leading cause of diarrhea not related to any antibiotics. This could be the foundation of nosocomial illness. The article uses the qualitative research design to establish the results of facility-treated Clostridium illnesses on the patient’s lives. Different people are interviewed, and the responses are examined to draw a conclusion from them (Guillemin.et.al, 2014).

The second article is called “Facilitators and barriers to implementing antimicrobial stewardship plans” and uses the quantitative approach. From the article, ASPs encounter different barriers or even facilitators when using the antimicrobial stewardship plans. For this reason, they carried out a quantitative research as 16 pharmacists who were members of the program and 6 experts to represent the 22 expert medical facilities in the region. They experimented with the plan to determine the effect of using the plan on the medical results, the safety of the patients, application of the plan, resistance, charges as well as the metrics of the procedure.

In the third article, which is the “Effectiveness of post prescription antibiotic stewardship to reduce carbapenem consumption” and implements the mixed research method. The article emphasizes the need to increase monitoring of instructions, especially with the increased ESBL-PE prevalence outcomes with the high application of carbapenems. Furthermore, the study implements both qualitative and quantitative research methods Understanding Statistical Measurements.

Types of Statistical Tests

The first article used the non-parametric tests in the research while the second article used the parametrical statistical test (Pakyz.et.al, 2014). Also, in the third article, both types were used for the statistical test. The choice of the test type is dependent on the nature of research and the types of data involved.

Applicability of the Statistical Tests

The non-parametrical statistical test was applicable for the first article, especially for the reason that it was a qualitative research. This implies that the data used was not in numerical form. Rather, the data was in the form of opinions and perceptions of people regarding the study topic. For this study, spearman’s rank was used to analyze the results of the study. The second article used the parametric statistical test especially for the reason that it involved numerical data. Pearson’s correlation was used to test the outcomes since it involved numbers in establishing the relationship. The third article used mixed research methods. Each of the statistical tests was used depending on the kind of data that was being handled at any point during the study, whether numerical or non-numerical. Whenever qualitative research was done, the non-parametric test was used, and vice-versa Understanding Statistical Measurements.

Parametric and Non-Parametric Tests

A parametric test is a statistical test that involves numerical assumptions of a particular population parameter. It differs from the non-parametric test in that the non-parametric test involves non-metric independent variables. The parametric test involves measurements which give rise to ratios and intervals while the non-parametric test considers the ordinal and nominal measurement levels. For the parametric test, the researcher has full information about the phenomenon under study, while for the non-parametric test, the researcher is not informed about the study phenomenon. The parametric statistical test is applicable for the variables only unlike for the non-parametric test which is applicable in scenarios involving both variables and attributes. The Pearson’s coefficient is best to use with the parametric statistical test to establish the correlation between two variables, whether dependent and independent or between an independent and another independent variable. Meanwhile, the Spearman’s rank of correlation is used with the non-parametric statistical test.

Reliability and Validity

The validity and reliability levels of results for any research is aimed at testing the applicability of the results to another scenario. They also determine the accuracy and hence dependency levels of the research outcomes. In all the three articles, the authors founded their research on some assumptions. During the researches, they considered the administration period, and they gave clear directions on what ought to be done during the research. They also take into account the shortcomings of previously carried out researches to ensure further accuracy levels. The involved persons during the study also met the criteria of selection. The cognitive interviewing process or sessions add pretests in a bid to identify any issues within the questionnaire also aims at ensuring that the procedures of study are efficient. Based on these considerations, it would be imperative to state that the approaches increased the reliability and validity levels of the collected data and hence makes the study reliable even in the future.

Summary

The first article aims at establishing the perceptions of patients and the community at large based on the hospital-treated Clostridium difficile diseases. The research is responsible for triggering the report of the patient’s complaining of uncontrollable and persistent diarrhea. The disease affected the physical and psychological health of the patients in a very adverse way. They also got emotionally distressed as the affected persons kept by themselves most of the time. The patients could also not take up their daily roles as usual and the disease had also collapsed the social lives of most of the patients. Increased cases of the disease made the community get more conscious of hygiene to avoid further infections.

In the second article, it explains the program that different health facilities applied to test their robustness and decrease the implementation of antibiotics. The main one was the antimicrobial stewardship plans — the study aimed at establishing the barriers and facilitators of the plan implementation.

The third article is oriented towards learning the best strategies that the ASPs could implement to ensure the best communication and interrelationships with each other. It also emphasizes the need for medical practitioners to use the available resources in the most effective manner to ensure the best medical results (Kallel.et.al, 2017)Understanding Statistical Measurements.

References

Guillemin, I., Marrel, A., Lambert, J., Beriot-Mathiot, A., Doucet, C., Kazoglou, O., … Arnould, B. (2014). Patients’ Experience and Perception of Hospital-Treated Clostridium difficile Infections: A Qualitative Study. The Patient – Patient-Centered Outcomes Research, 7(1), 97-105. doi:10.1007/s40271-013-0043-y

Kallel, H., Abboud, P., Nkouka, S., Mahamat, A., Moreau, B., Nkont Cho, F., … Djossou, F. (2017). Effectiveness of post prescription antibiotic stewardship to reduce carbapenem consumption: a quantitative study. Journal of Hospital Infection, 97(3), 294-295. doi: 10.1016/j.jhin.2017.08.007

Pakyz, A. L., Moczygemba, L. R., VanderWielen, L. M., Edmond, M. B., Stevens, M. P., & Kuzel, A. J. (2014). Facilitators and barriers to implementing antimicrobial stewardship strategies: Results from a qualitative study. American Journal of Infection Control, 42(10), S257-S263. doi: 10.1016/j.ajic.2014.04.023

Raheja, K., Dubey, A. & Chawda, R. (2017). Data Analysis and its Importance in Health Care. Retrieved from https://www.ijcttjournal.org/2017/Volume48/number-4/IJCTT-V48P132.pdf

University of the West of England, (2020). Data Analysis: Validity and Reliability. Retrieved from http://learntech.uwe.ac.uk/da/Default.aspx?pageid=1429 Understanding Statistical Measurements

 

 

Appendix

Comparison Table

Type of Article Title of Article Type of Analysis and Rationale Applicability of Test Reliability and Validity
Qualitative “Patients’ experience and perception of hospital-treated Clostridium difficile diseases.” · Formative evaluation

· Impact evaluation

 Spearman’s rank of correlation Cognitive interview
Quantitative “Facilitators and barriers to implementing antimicrobial stewardship plans” · Outcome evaluation

· Process evaluation

 Pearson’s correlation coefficient Pretests on questionnaire.
Mixed Methods “Effectiveness of post prescription antibiotic stewardship to reduce carbapenem consumption” · Process evaluation

· Outcome evaluation

 Pearson’s correlation tests and Spearman rank of correlation Conventional pretests

I, (Bola Odusola-Stephen), verify that I have completed (10) clock hours in association with the goals and objectives for this assignment. I have also tracked said practice hours in the Typhon Student Tracking System for verification purposes and will be sure that all approvals are in place from my faculty and practice mentor Understanding Statistical Measurements.