Data Integration to Improve Real-world Health Outcomes Research for Non-Small Cell Lung Cancer in the United States: Descriptive and Qualitative Exploration

Exploring Oral Cavity Cancer in the United Arab Emirates (UAE)

Background This study delves into the demographics and clinical characteristics of oral cavity tumors in the context of the United Arab Emirates. It further investigates the efficacy of four different treatment modalities in impacting patient survival rates. It aims to understand if any treatments significantly improve survival compared to others. Methodology To assess the survival outcomes across the different treatment groups, the study employed the log-rank test, a non-parametric statistical test widely used in survival analysis. The sample consisted of patients from the electronic medical records assigned to one of the following four treatment groups: radiotherapy only (RT), radiotherapy with surgery and chemotherapy (RT+S+C), radiotherapy with surgery (RT+S), and, finally, radiotherapy with chemotherapy including immunotherapy (RT+C). Data collection involved tracking survival times from the initiation of treatment until the last follow-up period or the occurrence of an event (e.g., death). The statistical analysis was conducted using the chi-squared statistic to determine the distribution of survival times across the groups, providing a quantitative measure of the difference between the observed and expected survival. The Kaplan-Meier curve was plotted for the cohort divided into four groups. Results The log-rank test yielded a p-value of 0.321019, suggesting no statistically significant difference in survival among the treatment groups at the 5% significance level. The chi-squared statistic was 3.498018, within the 95% acceptance region, further corroborating the null hypothesis of no significant survival difference across the groups. Despite this, an observed medium effect size of 0.59 indicates a moderate difference in survival between the groups. Conclusions The findings illustrate that while there is no statistically significant difference in survival rates among the four treatment groups, the medium effect size observed suggests a moderate difference in survival. This emphasizes the need to consider the statistical significance and effect size in clinical research, as they provide different insights into treatment efficacy.

Real-World Data for Interdisciplinary Health Care Research: A Case Example

Real-word data (RWD) refer to data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources, including electronic health records, medical claims data, and patient-generated data. Data sets that combine personal health data stored in different sources can provide a more complete picture of an individual's health and can be used to improve population health through research and practice. The 2-tiered aim of this article is to provide a brief introduction to using RWD in health care research and to present a case study that demonstrates data curation and data merge from different sources while highlighting the benefits and limitations of using RWD. The current digital health ecosystem and value-based care approach highlight the need to use RWD to catalyze the advancement of health care research and practice. This is an excellent field that nurse researchers can lead, as they have an innate understanding of such data and data sources.