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Introduction
My position as a hospice admission nurse has equipped me with adequate data management skills. Some of the activities undertaken include identification of target populations, data collection, coordination, and analysis. This discussion gives a personal reflection of my experience with various aspects of data management.
Personal Reflection
I have been evaluating patients to see if they meet the criteria for hospice. We have been using various hospice items such as QUAPI to manage crucial patient data. The process begins by identifying the target population and relevant measures. Data sources are considered to capture appropriate information to ensure patients receive quality hospice care (Sensmeier, 2015). Individuals work together to collect and coordinate data. The analysis is also done to come up with the best practices and models for delivering quality care.
Skilled Areas
My practice as a hospice admission nurse has equipped me with sufficient skills in areas such as identification of target populations, data entry coordination, and collection. For instance, I understand how to engage in continuous learning to identify specific populations for hospice care. The use of questionnaires and other tools of data collection guide me to identify populations and come up with appropriate patient support models. My skills in data entry coordination have improved over the years.
Throughout the data management process, I collaborate with different nurses and physicians to record collected data. This can be done using spreadsheets and data analysis tools. My team uses different data analysis programs and software applications depending on the nature of the collected information. I am also capable of improving data quality. This is achieved using a concept known as data cleansing. The skill empowers me to produce appropriate data for planning and decision-making processes. These skills have led to better health outcomes for my patients.
Areas for Improvement
However, some areas require more skill improvement. For example, my data analysis proficiency is not fully developed. This is the case because I have mainly been evaluating patients to see if they meet the criteria for hospice. The other area is the ability to interpret analyzed data and communicate the information to different stakeholders (Sensmeier, 2015). These gaps explain why I have been unable to work in different units.
Activities to Increase my Competencies in Data Management
Several activities can be accomplished in my current practice setting to increase my data management competencies. To begin with, I will undertake a number of researches focusing on individuals in need of hospice care. These studies will be completed using quantitative methods. This move will result in improved data analysis and implementation skills (Sensmeier, 2015). The second activity is that of lifelong learning. The practice will be combined with activities such as data analysis and interpretation. The approach will equip me with new skills in the area. The third sphere of action is to establish new teams in my workplace. The team will identify new data management tools and apply them in the hospice setting. This activity will empower me to use modern tools to manage data and analyze the acquired information to maximize patient outcomes.
Conclusion
Although my roles as a hospice admission nurse are limited to evaluating patients for hospice, I have acquired numerous skills in data management. Some of these competencies include data collection, entry, and identification of target populations. I will embrace approaches such as lifelong learning, and teamwork, and research to improve my data management skills. The acquired abilities will guide me to support the needs of every patient in need of hospice support.
Reference
Sensmeier, J. (2015). Big data and the future of nursing knowledge. Nursing Management, 46(4), 22-27. Web.
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