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.
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.
DESCRIPTION
According to the American Nurses Association, nursing informatics is the specialty that integrates nursing science with multiple information and analytical sciences to identify, define, manage, and communicate data, information, knowledge, and wisdom in nursing practice. The contribution of nurse informaticists in developing and improving technology, such as electronic medical records (EMRs) and clinical decision support (CDS), is essential for reducing medical errors, patient care delays, and healthcare costs (McGonigle & Mastrian, 2022). Nursing informatics and hemodialysis intersect in several impactful ways, enhancing patient care and outcomes. The use of the Crit-Line provides real-time data that can be used to help clinicians and nurses make decisions about a patient’s treatment. The Crit-Line is a monitor that measures a patient’s blood volume, hematocrit, and oxygen saturation during dialysis treatment.
DATA COLLECTION
The Crit-Line system is primarily used in hemodialysis to monitor and manage a patient’s blood volume during dialysis, helping to prevent complications such as hypotension by adjusting fluid removal rates. By providing detailed data on fluid removal and blood volume changes, the Crit-Line helps healthcare providers determine the patient’s ideal dry weight. Informatics tools can analyze the data collected by the Crit-Line system to identify trends and patterns. This helps in predicting potential complications and adjusting treatment plans accordingly (critlineresources.com).
SCENARIO OVERVIEW
It’s a Monday morning after a holiday weekend. One of your patients, MJ, arrives for his scheduled dialysis treatment. MJ is a little SOB today, requiring 2L NC, but otherwise stable. He is normally hypotensive (SBP90’s). However, today he is also 4kg above his dry weight. Removing such a large volume of fluid could lead to worsening hypotension in any dialysis patient. MJ chronic hypotension could not only make this challenging, but it could also be dangerous. The Crit-Line is ideal for this situation. It will help the healthcare provider adjust the amount for fluid removal while minimizing the risk of symptoms, thereby maximizing the treatment.
ROLE OF NURSE LEADERS
Nurse leaders play a crucial role in leveraging knowledge gained from nursing informatics to enhance patient care and improve healthcare outcomes. By identifying potential errors and implementing evidence-based practices, nurse leaders can enhance patient safety and reduce the risk of adverse events. Also, with continuous monitoring and evaluation of patient outcomes, nurse leaders can identify areas of improvement and implement strategies to enhance the quality of care.
Reference
American Nurses Association. Nursing Informatics: Scope and Standards of Practice. 2nd ed. Silver Spring, MD: American Nurses Association; 2015.
CRIT-LINE Where Therapy and Diagnostics Meet. https://www.critlineresources.com/Koppelingen naar een externe site.
McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning.
DB Response 2:
Maternal Morbidity and Mortality
The United States has rising maternal morbidity and mortality rates, particularly for minority populations. As one of the most technologically robust nations, we are well-positioned to utilize a shared system of health records to analyze data to improve maternal outcomes. As a public health nurse and postpartum nurse, I propose a scenario focusing on reducing maternal mortality rates.
Qualifying Data Collection and Access
Data collection should be comprehensive and include patient medical history, demographics, and social determinants of health. Additionally, data on the patient’s maternal medical history is crucial—for example, patient history of pregnancies, lab results, and history of prenatal care. Childbirth complications and postpartum complications should also be included, such as the types of interventions performed and the duration of intervention. This comprehensive data is obtained through electronic health records (EHRs), patient monitoring systems, and patient-reported outcomes surveys (McGonigle & Mastrian, 2022). This data should be accessible through a centralized EHR system so that nurse leaders and healthcare professionals can analyze trends and outcomes (Healthcare Informatics, 2017).
Knowledge Derived from Data
Healthcare professionals can gain valuable knowledge by analyzing the comprehensive data. Specific risk factors for maternal morbidity and mortality can be identified, such as advanced maternal age or pre-existing conditions like hypertension or diabetes. This understanding can lead to developing targeted interventions to mitigate these risks. Additionally, the data informs what patients are at higher risk for complications by associating trends and patterns with outcomes. Further, data on the interventions applied can inform what methods reduced maternal risk factors. For example, optimizing postpartum care protocols and ensuring timely follow-up appointments for high-risk patients can significantly reduce complications and improve outcomes (McGonigle & Mastrian, 2022).
Clinical Reasoning and Judgment
A nurse leader would use clinical reasoning and judgment to analyze and translate the data into actionable strategies and implement targeted solutions. For instance, if data reveals that specific patient demographics are at a more increased risk for postpartum complications, the nurse leader may advocate for expanded monitoring and targeted care plans for these patients. Additionally, considering existing hospital protocols, the nurse leader can work towards revising clinical guidelines, increasing staff training, or implementing new postpartum care procedures. Knowledge gained from data analysis must be effectively applied to improve patient care and outcomes (Nagle et al., 2017).
Conclusion
Collecting a large dataset is necessary to address the maternal morbidity and mortality rates in the United States. While the amount of data collected will indeed be immense, the knowledge obtained from the synthesis can inform new healthcare practices. Healthcare professionals could forge strategies to solve issues and contribute to the broader body of nursing knowledge, ultimately enhancing the quality of care provided to postpartum patients.
References
Healthcare Informatics: @ Walden University Library. (2017). Ebscohost.com. https://eds.p.ebscohost.com/eds/detail/detail?vid=1&sid=a84e5ce4-c61e-49ba-af82-d1d541bffabe%40redis&bdata=JkF1dGhUeXBlPXNoaWImc2l0ZT1lZHMtbGl2ZSZzY29wZT1zaXRl#AN=128848047&db=rzh
McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning.
Nagle, L., Sermeus, W., & Junger, A. (2017). Forecasting informatics competencies for nurses in the future of connected health. Evolving Role of the Nursing Informatics Specialist, 212–221. https://doi.org/10.3233/978-1-61499-738-2-212