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The Application of Data to Problem Solving

The Application of Data to Problem Solving

In the modern era, there are few professions that do not to some extent rely on data. Stockbrokers rely on market data to advise clients on financial matters. Meteorologists rely on weather data to forecast weather conditions, while realtors rely on data to advise on the purchase and sale of property. In these and other cases, data not only helps solve problems, but adds to the practitioners and the disciplines body of knowledge.
Of course, the nursing profession also relies heavily on data. The field of nursing informatics aims to make sure nurses have access to the appropriate date to solve healthcare problems, make decisions in the interest of patients, and add to knowledge.
In this Discussion, you will consider a scenario that would benefit from access to data and how such access could facilitate both problem-solving and knowledge formation.
To Prepare:

Reflect on the concepts of informatics and knowledge work as presented in the Resources.
Consider a hypothetical scenario based on your own healthcare practice or organization that would require or benefit from the access/collection and application of data. Your scenario may involve a patient, staff, or management problem or gap.

By Day 3 of Week 1
Post a description of the focus of your scenario. Describe the data that could be used and how the data might be collected and accessed. What knowledge might be derived from that data? How would a nurse leader use clinical reasoning and judgment in the formation of knowledge from this experience?

example:Problem Solving skills are the most important skills used in determining, practicing, and evaluating nursing care for sick or healthy individuals (Wang, Lo, Chi-Hui, & Ya Lie, 2004; Lee & Brysiewicz, 2009). The nursing process, which is called a Problem-Solving process, is an organized, systematic approach composed of collecting data, defining problems, determining interventions toward patient care, intervening, and evaluating outcomes. It is possible to provide effective, objective, and professional care by using the nursing process written by Ancel, G. (2016). Data are needed and collected for problem-solving. EMR workflow assists and facilitates the caregivers for the continuity of the patients care.
Hypothetical patient scenario: 
A moderately obese man, recently extubated after a left-sided thoracotomy, continues to be sedated and occasionally has desaturations of oxygen saturation levels despite stimulation and encouragement to cough and deep breathe. The patient is wearing a simple face mask with a flow of 8L/min. An arterial blood gas is drawn, with the following values: pH 7.32, PaCO2 50mmHg, HCO3 25meq/L, and PaO2 65mmHg. 
The use of the nursing process to collect data will be relevant in this situation. Pre-op nurses admit patients, read the history and physical, assess the patients condition, check vital signs, and obtain medication reconciliation. This information is disseminated to the anesthesia team, surgeon, and intraoperative nurse and then relayed to the PACU nurses by the anesthesia team during the patients phase one recovery. Accessed on all the documentation is through EPIC, which our institution used.
We know from the data collected that the patient has respiratory acidosis, a common acid-based imbalance encountered in the post-op setting. An important consideration is that the patients health history, condition, and surgery placed him at risk for hypoxia. Obesity is often linked with obstructive sleep apnea, which is strongly suggested in the scenario. Any type of thoracic or abdominal surgery can interfere with normal respiratory functioning because of pain, bleeding, or compromise respiratory anatomy and physiology, Putrycus, B. & Ross, J. (2013).
The use of data and information, technology, previous learning, experiences, nursing theory, McGonigle, D. & Mastrian, K.G. (2017) were utilized.
References:
Ancel, G. (2016). Problem-Solving Training: Effects on the Problem-Solving Skills and Self-Efficacy of Nursing Students. Eurasian Journal of Educational Research, 64, 231“246.
McGonigle, D., & Mastrian, K.G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.
Putrycus, B. & Ross, J. (2013). Certification review for perianesthesia nursing: 3rd ed. p.; cm.
Wang, J.J., Lo, Chi-Hui, K., Ya, Lie, K. (2004). Problem solving strategies integrated into nursing process to promote clinical problem-solving abilities of RN- BSN students. Nurse Education Today, 24 (8), 589-95.

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