Secondary Analysis of Archived Data (SAAD) in Public Health Research

In public health research, accessing appropriate data sets is often crucial for addressing pressing issues like maternal mortality. While some researchers conduct original research, others rely on secondary analysis of archived data (SAAD) to explore existing information and draw conclusions. This approach is beneficial in contexts where original research may be time-consuming or financially prohibitive. The SAAD process involves the retrospective analysis of pre-existing data to answer new research questions, often using quantitative methods.

Relevance of the Data Set to Public Health Research

Our project focuses on the critical issue of maternal mortality in underserved communities, particularly among Black and Hispanic women. The data set being analyzed for the Final Project contains information related to maternal health outcomes, Medicaid policies, and racial disparities in healthcare access. This data is critical for answering the research question: How can extending Medicaid postpartum care coverage in underserved communities reduce maternal mortality and improve health equity for Black and Hispanic women?

The data sets relevance lies in its inclusion of variables related to Medicaid coverage, maternal health outcomes, and demographic data, essential for examining disparities in maternal mortality. Given that Medicaid covers a significant portion of births in the U.S., the dataset provides a valuable resource for analyzing how expanding postpartum care can affect health outcomes. Additionally, the inclusion of racial and ethnic data allows for a focused analysis of disparities affecting Black and Hispanic women, who experience higher maternal mortality rates due to systemic inequities in healthcare access and quality.

Evaluating Data Validity and Integrity

Before initiating an SAAD, evaluating the validity...

Validity refers to whether the data measures what it claims to measure, while integrity involves ensuring the data is accurate and complete. In this case, the data set includes variables such as postpartum care access, Medicaid coverage periods, and maternal mortality rates, directly relevant to the research question. These variables have been collected by reputable public health organizations and government bodies, suggesting that the data is likely valid and reliable.

However, one must also consider potential limitations,...

…it readily available for analysis.

Determining the integrity of the data involves assessing its source, collection methods, and completeness (Haley et al., 2022). Since reputable health organizations collected this dataset, it will likely be accurate and reliable. However, as noted earlier, potential inconsistencies between states Medicaid policies or gaps in capturing social determinants of health could affect the datas overall integrity. To mitigate these risks, the researcher should review the data collection process, cross-reference with other data sources, and perform sensitivity analyses as needed.

Conclusion

Using secondary analysis of archived data (SAAD) allows public health researchers to explore existing data sets to answer new research questions, such as the impact of Medicaid expansion on maternal mortality disparities. While the data set being analyzed for the Final Project includes many relevant variables, such as Medicaid coverage and maternal health outcomes, it is essential to evaluate its validity and integrity. Researchers must also be prepared to overcome the limitations inherent in secondary data by employing triangulation, qualitative supplementation, and sensitivity analyses. Through this rigorous approach, SAAD can provide valuable insights into addressing…