NURS 8310 Week 2 Discussion: Descriptive Epidemiology, Data Sources, and Data Collection

NURS 8310 Week 2 Discussion: Descriptive Epidemiology, Data Sources, and Data Collection

Descriptive epidemiologic model describes how disease patterns are identified and categorized by variables including person, place, and time for monitoring (Friis, & Steelers, 2021). Data that is sourced from epidemiological studies is foundational for developing policies and clinical guidelines, community preparedness to managing population health, and promoting further investigations of health factors that may impact population wellness. Advanced practice nurses (APNs) are in unique health professional roles to use descriptive epidemiology studies for tracking how patients are impacted by diseases, which further informs clinical delivery of care and community-based preventative interventions. The purpose of this discussion is to describe a population health issue within vulnerable groups and review primary and secondary methods of data sourcing for case identification and diagnostic measures.

Suicide Rates and Vulnerable Populations

As a psychiatric mental health nurse practitioner (PMHNP), suicide is a predominant health concern impacting patients across the lifespan. The National Institute of Mental Health (NIMH) (n.d.) emphasizes that suicide is one of the top leading cause of deaths in the U.S and provides ongoing surveillance of suicide rates, methods of completion, and additional sources for monitoring trends. According to the Centers for Disease and Control Prevention (CDC) (2024), Native Americans and Hispanic individuals are among the highest ranking populations for completed suicide rates in the U.S. in 2022 compared to their counterparts. Healthcare inequity has disproportionately impacted vulnerable populations and epidemiology data-driven initiatives are crucial for reducing the rates of suicide among non-white individuals (U.S. Department of Health and Human Services [HHS], 2024). By utilizing information from databases to track suicide rates and contributing factors, healthcare clinicians are able to determine assessments to administer and life-saving interventions needed to mitigate suicidal symptoms and behaviors.

Data Collection Methods

Statistical records from public health surveillance databases, such as the CDC, are valuable for collecting primary data for describing and studying the prevalence of suicide among people of color (CDC, 2024; NIMH, n.d.). Health-related organizations and government-affiliated databases, including the NIMH and HHS, are valuable secondary source for data mining in determining factors related to risks of suicide. Vital statistics registration systems are highly reliable databases for reviewing mortality statistics for suicide-related deaths in the U.S, as cause of death and causative factors are recorded for individuals (Friis, & Steelers, 2021). Accuracy of data findings are important for observation of exposures and rates for suicide to further inform policy initiatives for prevention and standardizing national clinical guidelines. Although, caution is advised when interpreting primary and secondary data sources regarding race-related suicides, given the known inaccuracies as reported by U.S. Census Bureau surveys, leading to underestimations for suicide rates pertaining to specific racial groups (NIMH, n.d.). Leveraging database records are helpful for determining contributing factors for completed suicide, such as individuals that endorse thoughts of contemplating suicide, planning behaviors, and actions towards attempting suicide. In summary, descriptive epidemiology and available data sources are impactful for informing clinicians, health organizations, and the public of the detrimental consequences of suicide. Advocacy for suicide awareness is necessary for determining initiatives to preventing