The Application of Data to Problem-Solving Nursing Essay
The Application of Data to Problem-Solving Nursing Essay
The Application of Data to Problem-solving
Healthcare Scenario
In a pediatric outpatient primary care clinic, one provider alone may see 15-20 children in a day, at the least. Some of those children may live in a home where food choices and physical activity may not be the healthiest. As healthcare providers, it is important to look at the whole child and family dynamic when assessing a child’s health status The Application of Data to Problem-Solving Nursing Essay. Therefore, gaining data on children’s health in the home could help prevent certain mental and physical illnesses.
Data to be Accessed
Some important data to be obtained could include the patient’s weight, blood pressure, a food diary for the patient, an activity diary, and a feelings/mood diary. Some other good ideas from Imoisili et al. (2021) would be to include hemoglobin A1c and liver markers such as ALT and lipids. Depending on the age, this could be done using a sort of game to help children be more motivated to document their daily choices. The patient could write it down in a notebook that the clinic can provide for them, or if they are younger, they can draw pictures in it. What might be useful for older children is documenting their food intake, activity level, or mood on a mobile device application that can be synced to the clinic’s medical record. The Application of Data to Problem-Solving Nursing Essay The only one who would have access to this would be the patient’s provider. If the patient is using a notebook to write or draw in, they would simply return it once a week to the clinic to be documented in the medical record system.
Knowledge Derived from Data
From this specific data, we can obtain a deeper knowledge of a patient’s life at home, of the food options the patient has available to choose from, their activity level, and their emotional state. All of these play a factor in a patient’s overall health. Each category of health affects the other. This knowledge can help us to target what needs to be focused on instead of simply telling the patient and his or her parents that they must eat healthier and be more physically active. Diving into what is really the issue behind the patient’s increased weight will provide more success rates for the patient and family. The underlying issue may not even be physical activity or food choices. It may be psychological stress on the child, in which case, resources would be provided for them to help resolve the psychological issue within the patient The Application of Data to Problem-Solving Nursing Essay.
Clinical Reasoning and Judgement
Clinical reasoning and judgement can be formed from the knowledge obtained from this specific data by observing the trends of certain ages and population groups in their physical activity and food choices. The Application of Data to Problem-Solving Nursing Essay The nurse leader can infer from this information the influences of each individual patient’s daily life and possibly be able to offer suggestions of lifestyle changes that the family and patient can implement in their daily choices.
Application of Data
With the application of this data obtained, we as healthcare providers must keep in mind that the “psychosocial concerns such as stress and dysfunction in the family, or a child’s experience with bullying can increase the chances of dropout” (Berry et al., 2021). So we must make sure that when we apply this new information to our patient’s lives, that we follow up with them and make sure we gave them the greatest chance of success for the future and for the rest of their lives. A study performed by Thompson et al. (2019) showed that regular checkups and teachings from nutrition specialists and behavioral specialists with the patient and family greatly increase the success rate in weight management over a two-year period.
Conclusion
Pediatric obesity is a prevalent issue in today’s world, and as we integrate data that we obtain from current patients, we can positively affect the outcome of their health now and in future years to come. We can obtain data from our patients electronically or written. That is the beauty of today’s technology and our increasing ability to help our patients in more than just the conventional method.
Resources
Berry, D. C., Rhodes, E. T., Hampl, S., Young, C. B., Cohen, G., Eneli, I., Fleischman, A., Ip, E., Sweeney, B., Houle, T. T., & Skelton, J. (2021). Stay in treatment: Predicting dropout from pediatric weight management study protocol. Contemporary Clinical Trials Communications, 22. https://doi-org.ezp.waldenulibrary.org/10.1016/j.conctc.2021.100799 The Application of Data to Problem-Solving Nursing Essay
Imoisili, O. E., Lundeen, E. A., Freedman, D. S., Womack, L. S., Wallace, J., Hambidge, S. J., Federico, S., Everhart, R., Harr, D., Vance, J., Kompaniyets, L., Dooyema, C., Park, S., Blanck, H. M., & Goodman, A. B. (2021). Body Mass Index and Blood Pressure Improvements With a Pediatric Weight Management Intervention at Federally Qualified Health Centers. Academic Pediatrics, 21(2), 312–320. https://doi-org.ezp.waldenulibrary.org/10.1016/j.acap.2020.11.026
Thompson, K. L., Chung, M., Handu, D., Gutschall, M., Jewell, S. T., Byham-Gray, L., & Parrott, J. S. (2019). The Effectiveness of Nutrition Specialists on Pediatric Weight Management Outcomes in Multicomponent Pediatric Weight Management Interventions: A Systematic Review and Exploratory Meta-Analysis. Journal of the Academy of Nutrition and Dietetics, 119(5), 799–817. https://doi-org.ezp.waldenulibrary.org/10.1016/j.jand.2018.12.008
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7 months ago
Tanaka Ruzvidzo
Week 1 – Peer Response #1
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7 months ago
Robin Moyers WALDEN INSTRUCTOR MANAGER
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7 months ago
Tiffany Turner
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7 months ago
Tanaka Ruzvidzo
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The Application of Data to Problem-Solving
Healthcare Scenario
The Healthcare scenario I have selected is a suicide risk assessment. Suicide has been on the rise, more so due to the Covid-19 pandemic The Application of Data to Problem-Solving Nursing Essay. Working in an in-patient setting I have seen this first-hand. It is important therefore to quickly and accurately assess the risk of suicide on all patients coming into the hospital. According to Saab et. Al (2021), risk assessment is key to effective self-harm and suicide prevention and management. This needs to be done immediately during ER triage, on admission to a unit and as needed during their hospital stay depending on behaviors assessed.
Data to be Accessed
A questionnaire can be developed to ask specific questions that will give guidance on how to proceed. Using informatics, an algorithm can be developed depending on the answers given that will direct course of action to be taken. Data that can be gathered include asking questions like suicide ideations, attempts, plan, depression etc. Data can also be gathered from others, like family members, friends, case workers, or anyone else.
Clinical Reasoning and Judgment
Depending on the algorithm the treating clinician then will put in a consultation for behavioral health to assess the patient. Behavioral health will then use the data gained from the assessment to decide if the patient is at high suicide risk and qualifies for their services or not. The Behavioral health clinician is trained to look at different things like nonverbal communication, body language as well as the patients’ responses to questions. This in addition to the data gained from the questionnaire can determine the next course of action.
Application of Data
Once all the data is put together, it is like the pieces of a jigsaw puzzle coming together. Information gathered from ER triage, through to patient admission and during their stay is integrated to give a wholistic picture. “Informatics are a set of tools, and that the important use of informatics has to do with how you use those tools strategically” (Paone & Shevchik, 2017). Using the data gained they can decide whether the patient needs to be admitted to the behavioral unit, whether they will need outpatient counseling, or if they are not at risk and can be discharged to go home. Strategic use of the data is important to determine the way forward.
Conclusion
Data analyzed regarding suicide risk can be one step in alleviating this by ensuring early identification and assessment. This will ensure aid is quickly given to those that are most vulnerable and help reduce the rate of suicide. “Enhanced delivery of care, improved health outcomes, and advanced patient education are just a few aspects that have improved” (Sweeney, 2017). Thanks to informatics this is doable and can improve not only patient outcomes, but also enhance the quality of healthcare provided.
References
Paone, S., & Shevchik, G. (2017). Trends in Population Health. YouTube. YouTube. Public Health Informatics: “translating” knowledge for health.
Saab, M. M., Murphy, M., Meehan, E., Dillon, C. B., O’Connell, S., Hegarty, J., Heffernan, S., Greaney, S., Kilty, C., Goodwin, J., Hartigan, I., O’Brien, M., Chambers, D., Twomey, U., & O’Donovan, A. (2021). Suicide and self-harm risk assessment: A systematic review of prospective research. Archives of Suicide Research. https://doi-org.ezp.waldenulibrary.org/10.1080/13811118.2021.1938321
Sweeney, J. (2017). Healthcare Informatics. Online Journal of Nursing Informatics, 21(1), 4–1.
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7 months ago
Tae Kim
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Thank you for a great post, Tanaka. It is not only critical to assess the suicidal risk on admission, each shift, and as needed but also to utilize coping skills to intervene suicidal thoughts and attempts The Application of Data to Problem-Solving Nursing Essay.
Suicide is a serious issue that seems to keep growing despite prevention efforts. Suicides have increased by 24 percent in the past 20 years and now suicide is one of the top ten causes of death in the US. Not only is the problem growing there has been little progress over the last 50 years in understanding suicide and improving outcomes in at-risk individuals (Coppersmith et al., 2018). Identifying high-risk patients is difficult. RNs are considered “front-line” in suicide prevention because of their contact with patients but RNs rarely identify at-risk patients. Yet most people who do commit suicide had visited a healthcare provider within the previous month. Part of the reason for failing to identify at-risk patients is that most RNs have little or no training on how to assess, treat, evaluate or refer a suicidal patient. RNs , therefore, feel ill-prepared and afraid to talk to patients about suicide (Bolster et al., 2015). Although PMHNPs are better trained and should be better able to identify at-risk patients, this may not necessarily be the case. One study in rural Kentucky indicated that nine of ten psychiatric nurses surveyed overestimated their ability to identify and treat persons with suicidal ideation (France, 2019).
Informatics offers significant opportunities in the effort to identify at-risk patients. One example is through the natural language processing of social media. Studies with natural language processing and machine learning have detected quantifiable signals around suicide attempts and how to design an automated system for estimating suicide risk among patients. The results could be used by those without specialized mental health training (e.g., primary care doctors) to identify at-risk patients. Although this is a potentially life-saving technology, there may be ethical and privacy implications. So far this technology has been used only for individuals who have “opted in” for analysis and intervention (Coppersmith et al., 2018) The Application of Data to Problem-Solving Nursing Essay.
References
Bolster, C., Holliday, C., O’Neal, G., & Shaw, M. (2015, January) Suicide assessment and nurses: What does the evidence show? The Online Journal of Issues in Nursing, 20(1). https://ojin.nursingworld.org/MainMenuCategories/ANAMarketplace/ANAPeriodicals/OJIN/TableofContents/Vol-20-2015/No1-Jan-2015/Suicide-Assessment-and-Nurses.html
Coppersmith, G., Leary, R., Crutchley, P., & Fine, A. (2018). Natural language processing of social media as screening for suicide risk. Biomedical Informatics Insights, 10, 1 – 11. https://journals.sagepub.com/doi/pdf/10.1177/1178222618792860
France, W. F. (2019). Psychiatric nurses’ knowledge of suicide prevention. [Dissertation, Walden University]. Walden Dissertation and Doctoral Studies Collection. https://scholarworks.waldenu.edu/cgi/viewcontent.cgi?article=8505&context=dissertations
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7 months ago
April Ward
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7 months ago
Tae Kim
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When a patient or member of their family is ill, injured, or suffering from any medical condition, they and their families rely on healthcare experts to help them recover. We may help, but we can also cause harm if we make key mistakes. As nurses, we must use whatever tools we have at our disposal to enhance our capacity to serve while reducing the possibility of making mistakes. This is a career that largely relies on information. That data must be valuable and meaningful. The characteristics of valuable and meaningful information include “accessibility, security, timeliness, accuracy, relevancy, completeness, flexibility, reliability, objectivity, utility, transparency, verifiability, and reproducibility” (McGonigle & Mastrian, 2017, p. 23).
We utilize informatics from the time a patient is admitted until they are discharged at the hospital where I am presently working. Patient identification mistake is one of the avoidable issues. If they have the same first or last name, they are emphasized with a distinct letter style. In a typical scenario we use Medical Record Numbers (MRNs), patient’s initials, picture identifications and Contact Serial Numbers (CSNs). Additionall
