D9 last milestone

The IHP 525 Milestone Four Assignment

Precious Teasley

Southern New Hampshire University

IHP-525-Q3469 Biostatistics 24TW3

Professor Cecilia Younger

April 15, 2024

The IHP 525 Milestone Four Assignment

Health Question

The question asks if age has an impact on the survival chances of MI patients. MI stands for Myocardial Infarction which is commonly referred to as heart attack (Institute of Medicine, 2010). When people grow older, their body organs become weaker, and their functionality drops. This implies that an older patient's heart is not as strong as a young person's and in case of a heart attack, the mortality rate for older people is higher. The long-term survival of patients aged 65 and above with acute myocardial infarction is 65% (Kappagoda & Greenwood, 2012). Age affects the survival of MI patients. Younger patients have greater survival rates than older ones. The younger population is generally healthier and stronger; therefore, they have better chances. Their immunity is also higher and this generally boosts their health (Morrow, 2016). On the contrary, the older population is weaker and has minimal chances of surviving a heart attack.

Tables

Parameter estimates

Variance Table for Regression Model

Graphs Generated from The Data in The Tables

Graph 1

Graph 2

Graph 1 and 2 represent the Health Question: To what extent does gender influence length of hospital stay for MI patients? The presented data indicates that gender does not correlate with a prolonged hospital stay for patients diagnosed with a myocardial infarction (MI). The analysis involved a sample of 100 individuals, comprising 65 men and 35 women diagnosed with MI. However, the data did not account for other potential factors, such as additional comorbidities, that might influence the length of hospital stay for either gender, such as a history of coronary artery bypass following an MI. With a higher representation of men in the sample, it suggests a higher incidence of MI among men. Nevertheless, upon admission for an MI, there was no significant difference observed in the length of hospital stay between men and women.

Statistical Tests Table 1

Best Choice

As illustrated in Table 1, the t-test is employed to examine the association between gender and length of stay (LOS). This statistical method enables the comparison of mean values between two groups. A substantial difference between averages suggests a meaningful divergence. Notably, the sizable sample size, coupled with responses clustering closely around the mean and exhibiting low variability, as indicated by the low standard deviation, enhances the reliability of the analysis. The calculated t-statistic registers at -1.1928541, yielding a p-value of 0.2358. In graph 1 and 2 illustrates the distribution of samples, with the green line denoting the mean for each group.

Biostatistical Examination

Analysis of the graph 1 suggests that gender 0 displays a broader range for LOS compared to gender 1. Although the means for both genders exhibit relative proximity, the visual representation does not portray significant variance. Similarly, examination of the graph 2 reveals comparable means between the groups. However, gender 1 appears to have fewer data points than gender 0. The pivotal insights derived from the t-test (Table 1) furnish the foundational data necessary for drawing informed conclusions. Notably, the hypotheses, H0 and Ha, along with the outcomes of the hypothesis test, are delineated within Table 1. The significance level set at 0.05 guides the interpretation of the p-value, aiding in discerning the statistical significance of observed differences in LOS between genders.

Research Conclusions

Findings from this study offer preliminary insights into the potential influence of gender on the duration of hospital stays for MI patients. While our results suggest minimal disparity between male and female LOS, graphical representations hint at a higher prevalence of hospital stays among gender 0 individuals. This underscores the importance of statistical analysis in informing decision-making processes.

Recommendations

This research raises pertinent questions regarding the role of gender in LOS for MI patients, warranting further investigation. Future studies should strive for balanced representation across gender groups to mitigate biases stemming from uneven sample sizes. Additionally, delving into the demographic and medical backgrounds of MI patients could shed light on factors contributing to prolonged LOS. Exploring variables such as age, ethnicity, socioeconomic status, and quality of care could provide valuable insights and necessitate revisions to sample size and research methodologies. Furthermore, considering the evolving landscape of gender identity, future research could explore LOS disparities pre- and post-transition, offering a more comprehensive understanding of healthcare outcomes.

References

Institute of Medicine (2010). Cardiovascular disability: Updating the social security listings. The National Academies Press.

Kappagoda, C. & Greenwood, P. (2012). Long-term management of patients after myocardial infarction. Springer.

Morrow, D. (2016). Myocardial infarction: A companion to Braunwald’s heart disease. Elsevier Health Sciences.