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Nurse informatics can help to collect data on a topic of interest and to help to evolve practices and improve outcomes. This is particularly helpful within the realm of nursing because there is grave importance in evolving policies and procedures used to reflect the most current research. Nurse informatics is described by the ANA as, “a specialty that integrates nursing, science, computer science, and information science to manage and communicate data, information, and knowledge in nursing practice” (ANA, 2001, Pg.17). Without nursing informatics, there would be little to no evolution of healthcare.
A common scenario within the hospital is the high risk for readmission of patients shortly after discharge. Often times there are several unforeseen factors at play that can contribute to the patient being readmitted to the hospital within a 30-day window. This can lead to excess stress for patients and families with excess money and time spent. This can also negatively affect a hospital system by causing a shortage of beds within the hospital, profit penalizations, and poor reputation. As described by Silverstein et al., (2008) readmissions can be for a variable of reasons such as recurrence of the same chronic disease exacerbation, a complication from the last admission, an adverse drug reaction, an injury from health care, or premature discharge to a location or facility that cannot provide adequate services (p. 363). Elderly make up the largest population at risk for readmission, hence this is the population that research focuses on.
Within this scenario, data could be collected from a large sample of the patient population over the age of 65 and those patients who were alive at discharge. The electronic health record can prove essential in the collection of this data by alerting those patients who have been readmitted within a 30-day time period following discharge. This data is reliable and gathered from an authoritative and credible source, as the EHR provides us with only objective, non-biased, impartial information (McGonigle & Mastrian, 2022). Data that may be of importance would be things such as age, sex, race, insurance, discharge location, medical or surgical services provided, and comorbidities (Silverstein et al., 2008). From the population sample these data points would be retrieved for future analysis and synthesis to find a common trend or pattern in data that could be linking the patient to their high readmission risk.
From this data, knowledge can be derived that could give valuable insight to the variables that lead to readmission. For example, a patient could have a higher chance of readmission if they are an elderly patient sent to a long term nursing facility that is not equipped to manage the patients medication regimen or enteral nutrition. This would suggest that better discharge coordination could have prevented this readmission if more time were taken to match the patient to a facility who is better equip to care for their specific needs.
A nurse leader could use clinical reasoning and judgement by taking the synthesis of this information and applying it to practice. Dissemination of information would produce interventions that could be applied to practice and even lead to new policy implication (Sweeney, 2017). For example, the data may outline that the highest risk for readmission is poor discharge planning. This could lead to an improvement in the case management screening process for facility placement. It could also lead to the implementation of a program who closely follow the patients who are deemed to be at higher risk with more assistance with discharge planning and more frequent primary care or telehealth visits provided. This information could be mutually beneficial across all healthcare systems in helping to keep patients out of the hospital with the best health outcomes.
References
American Nurses Association. (2001). Scope and Standards of Nursing Informatics Practice. Washington, DC: American Nurses Publishing.
McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning.
Silverstein, M. D., Qin, H., Mercer, S. Q., Fong, J., & Haydar, Z. (2008). Risk factors for 30-day hospital readmission in patients ≥65 years of age. Proceedings (Baylor University. Medical Center), 21(4), 363–372. https://doi.org/10.1080/08998280.2008.11928429
Sweeney, J. (2017). Healthcare Informatics. Online Journal of Nursing Informatics, 21(1), 4-1.
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Struggling with where to start this assignment? Follow this guide to tackle your assignment easily!

Step 1: Understanding the Assignment

The topic of this post is about nursing informatics and its role in reducing hospital readmissions. The goal is to discuss how nurse informatics can be used to collect data, analyze it, and then apply this data to improve healthcare outcomes. The post focuses on the elderly population (patients over 65) who are at high risk for hospital readmissions within 30 days of discharge. You will need to discuss how data can be collected, how clinical reasoning is applied, and how this leads to policy change or better practices.

Step 2: Organizing Your Response

Introduction:

• Start with a brief introduction about the role of nurse informatics in improving healthcare outcomes.
• Use the quote from the ANA (2001) to define nursing informatics. Make sure to mention how it integrates science, computer science, and information science.
• Establish the importance of improving healthcare policies through evolving practices based on research.

Discuss the Issue of Hospital Readmissions:

• Describe the challenges hospitals face due to readmissions.
  • Mention the negative consequences: stress for patients, financial burden, and pressure on hospital resources.
  • Use Silverstein et al. (2008) to explain the possible causes of readmission.
• Target Population: Highlight the elderly population as the primary group at risk.

Data Collection Using Nurse Informatics:

• Explain how data can be collected: Introduce the role of the Electronic Health Record (EHR) as an essential tool in monitoring and tracking readmission rates.
  • Mention how data points like age, sex, race, insurance, discharge location, medical services, and comorbidities can be collected and analyzed.
  • Emphasize that EHR data is objective and reliable (McGonigle & Mastrian, 2022).

Deriving Knowledge and Application to Practice:

• Discuss how patterns or trends could be identified from this data.
  • Example: Elderly patients sent to under-equipped facilities are at a higher risk for readmission.
  • Show how this knowledge can guide better discharge planning.
  • Highlight the role of clinical reasoning and judgment in utilizing this data to improve patient outcomes.

Nurse Leadership in Policy Implementation:

• Explain how a nurse leader can use this data to make changes.
  • For example, improving case management or implementing telehealth to prevent readmissions.
  • Discuss how interventions can reduce hospital readmissions by improving the discharge process and post-discharge care.

Conclusion:

• Summarize key points: how nurse informatics can improve hospital outcomes, specifically reducing readmissions.
• End by discussing how these practices can have a positive impact across healthcare systems.

References:

• Include the references from the post in APA format:
  • American Nurses Association. (2001). Scope and Standards of Nursing Informatics Practice.
  • McGonigle, D., & Mastrian, K. G. (2022). Nursing Informatics and the Foundation of Knowledge.
  • Silverstein, M. D., et al. (2008). Risk Factors for 30-Day Hospital Readmission in Patients ≥65 Years of Age.
  • Sweeney, J. (2017). Healthcare Informatics.

Step 3: Citation and Research Tips

• In-text citations: Ensure that each piece of information taken from a source is properly cited within the text.
  • Example: (McGonigle & Mastrian, 2022).
• Use scholarly sources: For any further research, ensure your sources are peer-reviewed and from reliable journals.
• Follow APA guidelines: Be mindful of proper formatting for in-text citations and references.

Step 4: Final Review

• Check word count: Ensure that the post meets the minimum length requirement.
• Proofread: Ensure grammar, punctuation, and APA formatting are correct.
• Review the structure: Make sure each section transitions smoothly into the next.

By following these steps, you will be able to write a well-organized, researched, and insightful post on the role of nursing informatics in improving healthcare outcomes, specifically in reducing hospital readmissions.

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