As a healthcare manager, using variations is critical to achieving a variety of results which help develop holistically stable and effective care processes over time. Based on the fact that patients are most concerned with the quality of individual care given while healthcare providers generalize this factor, the choice of analytical tools such as mean differences is vital (Cox, 2018). This essay aims at identifying the most appropriate situations under which a healthcare manager can use mean differences between two or more groups. Additionally, most experiments and investigations conducted by healthcare managers are aimed at studying the reasons and overall impact of changes observed from healthcare outcomes over time. These questions are answered by hypothetical tests which are then analyzed using different tools and hence the purpose of this text. A healthcare manager might thus incorporate the use of mean differences between two groups if their goal is to understand the difference between variables (Cox, 2018).
For instance, when investigating whether the current quality of healthcare has improved over time and which measures will ensure it remains better in the future, the manager may evaluate two types of variations; common cause variations and special cause variations from two or more groups. This would be an appropriate situation in which applying mean differences will result in changing healthcare practices as required. The analysis and comprehensive understanding of the difference of the averages of the experimental group and the control group facilitate the real-time decision-making processes required to improve the quality of healthcare by stakeholders. In conclusion, this essay finds that a healthcare manager may use mean differences between two groups or more to determine the difference between two experiments conducted which help better evaluate the current state and quality of healthcare provided.
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References
Cox, D. R. (2018). Analysis of binary data . Routledge.
