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Critically Ill Patient Analysis Framework

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1.2 PROBLEM STATEMENT Care of critically ill patient in the ward is a challenging process especially in the low resource countries. This is due to deficiency/ inadequate specialized or competent skilled personnels and absence of monitoring of patients closely. As the nurses are in constant contact with patients, they are in prime position to identifying problems at an early stage with the use of systematic patient assessment According to the standard of care, systematic assessment framework is used to assess critically ill patient for rapid assessment of the patient who is deteriorating. and also use early warning tools (EWS) as an observation monitoring tool that alert nurses to normal and abnormal physiological parameters. The ABCDE framework is used in conjunction with the Early Warning Score tool for assessing critically ill patient (Lees & Hughes, 2009). In Mnazi Mmoja Hospital setting nurse always keep seriously ill patient near to nurses station for the purpose of close observation and monitoring of vital signs. However nurses sorting the …show more content…

Dependent variable is care of critically ill patient while indipended variables are knowledge, practice of nurses and challenges of nurses on care critically ill patient in the ward. But here the researcher can base more on looking on knowledge and practice of nurses , if nurses is competent on assess by using ABCDE ie assess patient air way, breathing and circulation, and identify problem and able to intervene so these is help on maintain patient safety and lead quality care of critically ill patients. Also if nurses have knowledge of interpreting vital signs these can help nurses to identify patient who is deteriorating and intervene earlier, literatures show that nurses not only know to measure vital signs but also must interpret vital signs and act on

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It is JFK model risk assessment tool which includes every risk factors of the DVT. The JFK model risk assessment tool evolved through an evidence-based research and it proved that this model is working better than other models to assess the risk factors. Providing a valid and reliable tool for measuring the risk for DVT or PE in hospitalized patients will enable nurses to intervene early in patients at risk. Basing DVT risk assessment on the evidence provided in this study will assist nurses in becoming more confident in recognizing the necessity for interventions in hospitalized patients and decreasing risk (McCaffrey, R.,et.al. 2007). The table below is the DVT risk assessment tool made by this author based on the JFK model for the proposed

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The following scenario will best reflect my practice and use of informatics.   The scenario is not representative of a particular patient but is a combination of daily events in my position so that no patient rights are violated.             I am three hours into my shift as the assistant nurse manager (charge nurse) of a busy emergency department (ED) with my responsibilities in the department being to manage the flow of a shift that will see roughly 100 new patients during the 12 hours but also oversee the care of the 5-20 long term patient who are listed as observation or inpatient holds.   We can expand to 60 beds with the use of hall beds.   I have a bank of monitors to my left which display the EKG and vital signs of over 48 patients.

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In critically ill patients, several scoring systems have been developed. The Acute Physiology and Chronic Health Evaluation (APACHE) and the Simplified Acute Physiology Score (SAPS) are the most common scoring systems used in the intensive care unit (ICU).[1] They are used for risk stratification and prediction of mortality.[2] The scoring systems should be easy, quick,cheap and predict something clinically important over a wide range of clinical situations.[3] While it seems that scores using a larger number of data inputs are the best scoring systems, simpler scores are better than complex scores. The more the score complexity, the more the barrier to calculation, as it increases the probability that some data inputs may not be available.

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