Utilizing conjoint analysis to explicate health care decision making by emergency department nurses
Goals and purpose of the study
The pilot study aimed at testing the applicability of conjoint analysis in making decisions by nurses in emergency sections in hospitals. The study also aimed at learning the individual nurse’s experiences when dealing with patients with intellectual disability (ID). Decisions made at the emergency departments in hospitals determine whether a patient will be admitted or not. Conjoint analysis test was used to assess the essential factors in decision making process. Decision makers wittingly assembled the factors to arrive at a final decision (Fisher, Orkin & Frazer, 2010).
Nonparametric tests in the study and their results
Chi square test and the Fisher’s test were the two nonparametric tests used in the study. The Chi square test compared rankings observed in the experiment to those expected before the start of the experiment. Fisher’s test was used to manipulate data in the contingency tables used in the study. The correlation between the expected and the observed rankings was high (Pearson’s r ≥ 0.928). Fisher’s test was used to align the importance of making decisions with the nurse’s needs and rights (Fisher et al., 2010).
Why the t-test and ANOVA were not appropriate
The ANOVA test and the t-test are parametric tests that are used to compare means between groups. They could not fit in the study because ordinal data were used and the assumption that the data did not follow normal distribution was made.
Strengths and weaknesses of the study and recommendations
The study used an excellent design and statistical tests to find out the factors associated with making critical decisions in emergency department in hospitals. The study findings are essential in the healthcare industry because they associate nurses’ decisions to several factors.
Development and pilot testing of guidelines to monitor high-risk medications in the ambulatory setting
Goals and purpose of the study
The study aimed at developing guidelines for regulating high-risk drugs in outpatient settings. The study also aimed at completing the recommended testing for drugs given to patients in outpatient settings. High-risk drugs could cause much harm to patients when they are not carefully dispensed to the patient population. The study envisaged to improve the situation in the future by understanding the dynamics involved in emergency departments and developing appropriate recommendations (Tjia et al., 2010).
Nonparametric tests used and their results
The study used a nonparametric test that examined the trend among the ordered groups. The study ordered groups were categorised in time, i.e. 30 days, 42 days, 180 days and 365 days.
Why the t-test and ANOVA were not appropriate
The ANOVA test and the t-test could not fit in the study because ordinal data were used and the assumption that the data did not follow the normal distribution was made.
Strengths and weaknesses of the study and recommendations
The study used an excellent design and statistical tests to find out the prevalence of risks caused by high-risk drugs dispensed to patient population. The study results are essential in the healthcare industry because they categorized the high-risk drugs on the basis that they could cause harm when not carefully dispensed to patients (Tjia et al., 2010).
Frequently used statistical analysis
Nonparametric test analyses are the most frequently used tests in nursing research. The analyses have fewer assumptions than the parametric analyses. The tests do not assume that data are normally distributed and they are applied to analyze quantitative ordinal data.
References
Fisher, K., Orkin, F., & Frazer, C. (2010). Utilizing conjoint analysis to explicate health care decision making by emergency department nurses: a feasibility study. Applied Nursing Research, 23(1), 30-35.
Tjia, J., Field, T. S., Garber, L. D., Donovan, J. L., Kanaan, A. O., Raebel, M. A.,… & Gurwitz, J. H. (2010). Development and pilot testing of guidelines to monitor high-risk medications in the ambulatory setting. The American journal of managed.