Discussion: NR 544 Data Collection and Risk Management

Discussion: NR 544 Data Collection and Risk Management

Discussion NR 544 Data Collection and Risk Management

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Saleema had total hip replacement in March 2015. One week later, the stitches started to bleed. She was concerned and went to the doctor’s office and was told it was a superficial hematoma. The bleeding continued on for three weeks and involved two doctor’s appointments and one trip to the emergency room. She was sent home each time with a diagnosis of a superficial hematoma.

Finally, Saleema’s visiting nurse saw her on a home care visit and called an ambulance, concerned about the amount of blood loss. Upon further investigation at the ER, a terrible infection was discovered that had spread into the bone. Saleema went in for emergency surgery and a PICC line was placed in order to administer the medication vancomycin. On this medication, she developed Steven’s Johnson’s syndrome, which was not diagnosed right away as the skin peeled off her hands. She ultimately went into acute renal failure and had to go back to the hospital. Two days post-admission, she developed C-diff and several vancomycin-resistant infections. She died in the hospital, two months after the original surgery. The cause of death was determined to be septicemia. Saleema lost her life over what was supposed to be a routine hip replacement.

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As a future risk management nurse, please discuss the following points and questions.

Discuss your interview plan with Saleema’s family to collect data around her incident.

Which method of interview do you prefer to use, and why?

The goal of the interview is to provide accurate answers to questions of interest. Please provide two relevant questions and discuss which measurement levels you would use with your question. Explain your choices.

Scientific data collections may face a range of risk factors that could hinder, constrain, or limit current or future data use. Identifying such risk factors to data use is a key step in preventing or minimizing data loss. This paper presents an analysis of data risk factors that scientific data collections may face, and a data risk assessment matrix to support data risk assessments to help ameliorate those risks. The goals of this work are to inform and enable effective data risk assessment by: a) individuals and organizations who manage data collections, and b) individuals and organizations who want to help to reduce the risks associated with data preservation and stewardship. The data risk assessment framework presented in this paper provides a platform from which risk assessments can begin, and a reference point for discussions of data stewardship resource allocations and priorities.

Data Collection Method

Using data is crucial in public health since it can be used in numerous ways and for various purposes. In public health, data is used to demonstrate and assess the effect of an intervention, track progress towards a goal, identify barriers to care, and drive public policy. Before identifying the data collection approaches, it is vital to develop the questions the evaluation will address (Badu et al., 2019). Quantitative and qualitative data are usually collected to answer questions in public health. The purpose of this paper is to describe how the PHN will collect primary data about an identified health need of a specific population.

Chosen Population and Identified Health Need

Mental health disorders among adolescents (10-19 years) are a significant public health problem. Depression, anxiety, and behavioral disorders are among the leading causes of illness and disability among adolescents. Approximately 14% of 10-19 year-olds experience mental health disorders worldwide (Gunnell et al., 2018). Besides, suicide is the fourth leading cause of mortality among 15-19 year-olds. High-stress levels are associated with mental disorders in adolescence. Factors attributed to adolescent stress include exposure to adversity, exploration of identity, peer pressure, quality of home life, relationships with peers, media influence, and gender norms (Gunnell et al., 2018). Adolescents with mental health disorders are mainly vulnerable to discrimination, social exclusion, stigma, educational difficulties, physical ill-health, risk-taking behaviors, and human rights violations.

Most Appropriate Data Collection Method for the Chosen Population

Focus groups are the most appropriate data collection method for the adolescent population since it is effective and cost-efficient when dealing with a large and diverse research population. A focus group should typically have 6-10 subjects with a moderator who regulates the tone of the conversation and guides the discussion. Focus groups would be most appropriate regarding adolescent mental health since they are open-ended, allowing the researcher to explore various opinions and ideas that may arise during the discourse (Adler et al., 2019). In addition, focus groups would help the PHN to discover other significant points that may not have been considered in the systematic investigation.

Adler et al. (2019) explain that focus group interviews allow the subjects to tell their stories, express opinions, and even draw pictures without adhering to a strict series of questions. The data collection method is suitable for collecting data from children, adolescents, youths, and adults. Furthermore, focus groups create a safe peer environment for adolescents and help to avoid power imbalances between researchers and participants. Therefore, the focus groups method can be used to ask adolescents about their causes of stress, mental health disorders they experience, mental health promotion and prevention practices, and access to mental health services.

Type of Data That Will Be Collected

Qualitative data will be collected with regard to mental health in adolescents to examine the experiences of adolescents with mental health issues. Badu et al. (2019) explain that qualitative methods are relevant in mental health research, particularly when we want to comprehend sensitive issues from consumers of mental health services. Therefore, qualitative data will be used to understand adolescents’ experiences with issues that make them vulnerable to mental health disorders. Besides, it will be used to understand how adolescents deal with mental health issues and the various challenges they encounter when accessing preventive and treatment services for mental health conditions. Qualitative methods will help in collecting subjective experiences of adolescents with mental health stigma (Badu et al., 2019). The experiences of adolescents identified from the qualitative data will be particularly significant in developing public health policy to improve mental health wellbeing and care for adolescents.

Health Indicators Specific to the Population

Depression is a health indicator for adolescents (10-19 years). Depression is an important measure of mental disorders, projected to be the largest contributor to Disability Adjusted Life in 10–19-year-olds (Marsh et al., 2022). The indicator entails the number of young persons aged 10–14 and 15–19 who report having been sad, discouraged, or bored almost every day for two weeks or more. According to Newby et al. (2021), experts recommend simultaneously considering anxiety and depressive disorders and acknowledging the overlap in symptoms and treatment. The indicators were proposed to evaluate the prevalence of depression and anxiety and the treatment-seeking behavior for these mental health conditions.

Example Questions to Be Used In Data Collection

  1. What factors often create stress in your life? This is to understand the factors that cause stress among adolescents. The anticipated data include socioeconomic, school, relationships, violence, and family stressors.
  2. How do you manage stress? This will identify stress management strategies employed by adolescents and their effectiveness. The expected data include adolescents’ experiences with stress management approaches.
  3. Which common mental health disorders have you seen among adolescents in your community? This will establish the mental disorders that adolescents have identified among their peers. The expected data include emotional, behavioral, eating, and risk-taking disorders.
  4. What is your experience with mental health preventive services in your community? The question will examine adolescents’ experiences with preventive services for mental healthcare and if they perceive them as beneficial. The expected data include positive and negative experiences with mental health preventive services.
  5. What challenges do adolescents with mental health conditions face in your community? The question will identify the challenges experienced by adolescents diagnosed with mental disorders. The expected data include challenges like access to treatment, stigma, and discrimination.


The leading causes of illness and disability among adolescents include depression, anxiety, and behavioral disorders. Focus groups will be the most appropriate data collection method since they can elicit the perspective of adolescents. Qualitative data will be used since it helps to understand consumers’ experiences in the process of preventive care, treatment, and their therapeutic relationship with mental health providers.




Adler, K., Salanterä, S., & Zumstein-Shaha, M. (2019). Focus Group Interviews in Child, Youth, and Parent Research: An Integrative Literature Review. International Journal of Qualitative Methods.

Badu, E., O’Brien, A. P., & Mitchell, R. (2019). An integrative review on methodological considerations in mental health research–design, sampling, data collection procedure, and quality assurance. Archives of Public Health77(1), 1-15.

Gunnell, D., Kidger, J., & Elvidge, H. (2018). Adolescent mental health in crisis. Bmj361.

Marsh, A. D., Moller, A. B., Saewyc, E., Adebayo, E., Akwara, E., Azzopardi, P., … & Guthold, R. (2022). Priority Indicators for Adolescent Health Measurement–Recommendations From the Global Action for Measurement of Adolescent Health (GAMA) Advisory Group. Journal of Adolescent Health.

Newby, H., Marsh, A. D., Moller, A. B., Adebayo, E., Azzopardi, P. S., Carvajal, L., … & Guthold, R. (2021). A scoping review of adolescent health indicators. Journal of Adolescent Health69(3), 365-374.