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Application of Data to Problem Solving Discussion

Application of Data to Problem Solving Discussion

Application of Data to Problem Solving Discussion


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 practitioner’s and the discipline’s 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.
  • Module 1

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?

By Day 6 of Week 1

Respond to at least two of your colleagues* on two different days, asking questions to help clarify the scenario and application of data, or offering additional/alternative ideas for the application of nursing informatics principles.

*Note: Throughout this program, your fellow students are referred to as colleagues.

Learning Resources

Required Readings

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.

Required Media

Laureate Education (Producer). (2018). Health Informatics and Population Health: Trends in Population Health [Video file]. Baltimore, MD: Author.

Application of Data to Problem Solving Discussion Sample Essay

Having the best result is the main objective when treating patients as a healthcare professional. A community of professionals can regularly improve upon the superior knowledge from the past thanks to the ongoing evolution of medical practice. This can be done by developing policies and procedures based on research-supported practices. The data gathered to support the change in healthcare practice serves as the basis for evidence-based practice. Because they “increase patient outcomes, cut costs, and streamline care for many healthcare disciplines,” data-driven evidence-based practices are crucial to achieving the aim for healthcare professionals (Card et al., 2020).

A scenario where data collection would be useful in my current health system would be for decreasing exposure risk of COVID-19 in post-partum and neonate couplets on the mother baby unit. Though mother/baby units are typically “clean” units without contagious patients, multiple opportunities can be presented for improvement to decrease risk.

Data Collection and Access

The current situation allows for hospital personnel that have potentially been exposed during the workday to care for patients on the mother/baby unit. Because the Center for Disease Control has provided information that “exposures while performing physical examinations or during nebulizer treatments were more common” (Heinzerling et al., 2020), and that more data needs to be collected regarding the risk of exposure in the healthcare setting, it is important to determine the risk to this vulnerable population relating to potentially exposed healthcare workers. Data collection for staff that work in potentially infections environments as well as clean units would include but not be limited to phlebotomists, respiratory therapists, imaging technicians, and housekeeping. Potentially infectious staff would then be labeled “dirty” after exposure. The data that would be collected would be contact and date tracing of care for “dirty” staff, rate of infection of “dirty” staff, infection rate of “clean” staff and contact tracing to “dirty” staff, and post exposure tracing of patients. Comparison to cross floor contamination rates can also be compared. The data could be stored and accessed in a shared and editable document on the hospital intranet.

Informatics Clinical Application

Based on the collected data, policy changes that can occur to decrease data of patient exposure could be developed. The intended knowledge to be gained would be regarding the risk of exposure to “clean” patients from “dirty” staff.

If the data were to show risk, policy could then be implemented and assessed to see if risk could be mediated. This could include completing necessary testing on clean patients prior to dirty patients, designating clean staff members for testing and care of clean patients, and decreasing exposure of potentially exposed staff members by having nursing staff collect routine lab draws. Data could then be collected to determine if interventions led to better outcomes.

Nursing Judgement and Reasoning

In this scenario, the leadership team can justify policy and procedure change through use of evidence-based practice. By developing changes based on data that has been collected and evaluates and then presenting the data with the change in policy, the reasoning behind change can be justified as necessary for improving patient outcomes by nursing staff. The ability to create this link between the data and procedure change leading to improved patient care is vital to the success of the evidence-based practice. The support from management is crucial in creating change because “attitudes, beliefs and knowledge by health care professionals found that although many saw the benefits, they did not believe that they had the skills, knowledge, and abilities needed to incorporate them into clinical practice” (Rahmayanti & Saleh, 2020). By presenting the data, rationalizing change, and showing through data how the change was positive for patients will allow data to create positive outcomes.


Through using data to create evidence-based practice, the best possible patient outcomes can be achieved. The data is the foundation for this change. The analysis provides justification for new policies and procedures. The validation of these policies and procedures creates buy in and culture changes for the nurse. The support from management allows the data to create successful change. In this scenario specifically, policies and procedures created based on need that would be supported by data will keep a vulnerable population from unnecessary exposure to a potentially deadly virus at a minimum.


Card, E., Wells, N., Abbu, S., Myers, J., Denton, T., & Dubree, M. (2020). Empowering Nurses: Creation of a Peer-Reviewed Journal as a Catalyst for Innovative Nursing Research and Enhancing Evidence-Based Nursing Practice, 50, 402–406.

Heinzerling, A., Stuckey, M., Scheuer, T., Xu, K., Perkins, K., Resseger, H., … Epson, E. (2020, August 4). Transmission of COVID-19 to Health Care Personnel During Exposures to a Hospitalized

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