After completing this week’s Practicum Experience, reflect on pattern recognition in diagnoses. Explain how pattern recognition of patient symptoms might help lead to a diagnosis.
Primary diagnosis this week is COPD exacerbation and allergic rhinitis.
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Pattern Recognition
As advanced practice nurses (APN’s) become proficient and knowledgeable in the disease process, it will become second nature to utilize pattern recognition in diagnosing patients and providing quality patient care. Pattern recognition is used to diagnose certain conditions that have very unique symptoms (Strzoda, 2010). The purpose of this paper is to reflect on the importance of pattern recognition in regards to patient diagnosis and explain how the use of pattern recognition may be helpful or potentially harmful in assisting the APN in correctly diagnosing patients.
Pattern Recognition in Healthcare
Many times in the healthcare field pattern recognition is used to diagnose and treat patients with a number of different conditions. Utilizing this style of diagnosis is very efficient and time saving in a fast paced healthcare setting. There are a number of conditions that present with certain symptoms in which the APN may diagnose a patient before walking into the exam room.
One diagnosis that has very distinct symptoms is a urinary tract infection (UTI). Symptoms that a patient who has a UTI may complain of include pain or burning upon urination, urinary urgency and frequency, dark-colored urine with a foul odor, suprapubic and low back pain, and costovertebral tenderness. Utilizing pattern recognition with symptoms such as these will allow the APN to make the likely diagnosis of UTI. Another method of diagnosing UTI utilizing pattern recognition and without the above symptoms is reviewing a urinalysis. At times there are patients who present to the clinic for other reasons such as a routine medication follow-up or lab work. Lab results from a complete blood count (CBC) may show elevated white blood cells (WBC’s) and urinalysis results may reveal elevated leukocytes, protein, and blood in the urine. While the patient is asymptomatic, he/she has very indicative lab results that suggest a UTI.
Pattern Recognition: Helpful or Harmful
Pattern recognition is a helpful tool that allows APN’s to recognize that certain signs and/or symptoms are directly associated with certain diseases or conditions. As mentioned earlier this method is very efficient and time saving. It allows APN’s who practice in busy settings to diagnose and even write prescriptions for patients based on their symptoms before walking in to the exam room.
While there are many positives in regards to pattern recognition, there are also negatives. A major problem with utilizing this method in the healthcare setting is misdiagnosing. At times APN’s may prematurely diagnose a patient without considering other options or conditions that may be of concern for the patient (“Basic Strategies for Diagnosis,” 2011). When diagnosing a patient with a UTI based on their presenting symptoms it is important to follow-up with the patient to assure the symptoms have subsided with the prescribed treatment and there is not a possibility of a urethral issue. Other diagnoses that may be misinterpreted with pattern recognition are as follows: Bell’s palsy being mistaken for a stroke or vice versa and Parkinson’s disease may be mistaken for essential hand tremors.
Conclusion
Pattern recognition is an efficient way to provide health care to patients in a fast paced setting. It can be conveniently utilized to diagnose and treat patients before walking into the exam room. While it is helpful in many ways, pattern recognition must be used sparingly and follow-up is required in order to rule out any underlying conditions that may be a result of the presenting symptoms. Proper follow-up will confirm that the APN made the correct diagnosis and assure the symptoms have been effectively treated with prescribed medications.
References
Strzoda, K. (2010). Evaluation of Macrocyosis. American Family Physician, 79(3), 203-214.
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Pattern Recognition in Healthcare
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