NURS-6051C Module 1: Week 1: Discussion

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 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.

Resources

Be sure to review the Learning Resources before completing this activity.
Click the weekly resources link to access the resources.

WEEKLY RESOURCES

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?

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.

 

Solution

In the hospital, a significant issue is rehospitalization after discharge. Which in return reflects complications in patient care and discharges. This can be a dangerous and costly risk for the initial admitting hospital. Below is my scenario regarding hospital re-admission.

A scenario is a nurse working with a patient that was recently discharged after having a heart attack. This patient has had a past diagnosis of high blood pressure and currently takes several medications. After reviewing the medical record, including data on past hospitalizations, and the current medication reconciliation, lifestyle factors, and lab results, the nurse identify certain risk factors that would make the patient a high candidate for rehospitalization. Data can help identify patients at higher risk of rehospitalization and guide interventions that can prevent unnecessary readmissions (Bleich, Ozaltin, & Murray, 2009).

By having access to data analytics tools the nurse can evaluate the patient’s history and patterns and issues with past medications or follow up appointments. Also, data from devices that a patient can wear such as a halter monitor, or blood pressure monitors data can be integrated into patients’ health record comma which will allow for real time monitoring and intervention. This will allow for further adjustments to their treatment and lifestyle changes.

By having access to this comprehensive data can target problem solving for rehospitalizations. Nurses can work collaboratively with other health care professionals to tailor interactions that address the underlying issues behind the rehospitalization. These might include refining discharge plans, scheduling more frequent follow-ups, offering patient education on medication adherence, or connecting patients to community support services (Kohl & Dorr, 2016).

The integration of data helps us solve problems and take care of issues immediately which contribute to a broader knowledge in the nursing field. By tracking patterns of rehospitalization over time and analyzing patient outcomes, nurses and healthcare organizations can contribute to research on best practices for preventing readmissions (Hines, Barrett, Jiang, & Steiner, 2014). In summary data is critical for problem solving and advancement of solving complex problems. Nurses with access to detailed and real-time information can make better decisions and therefore have better patient outcomes.

References

Bleich, S. N., Ozaltin, E., & Murray, C. J. (2009). How does satisfaction with the healthcare system affect patient outcomes? British Medical Journal, 337, a1561. https://doi.org/10.1136/bmj.a1561

Hines, A. L., Barrett, M. L., Jiang, H. J., & Steiner, C. A. (2014). Conditions associated with hospital readmissions among Medicare beneficiaries. Preventing Chronic Disease, 11, E99. https://doi.org/10.5888/pcd11.140205

Kohl, R. M., & Dorr, D. A. (2016). The role of data analytics in reducing hospital readmissions. Journal of Nursing Administration, 46(3), 164-170. https://doi.org/10.1097/NNA.0000000000000321

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