Data response 2 | Nursing homework help

A hypothetical scenario based on my organization that would benefit from collecting and analyzing data to gain knowledge is a rise in the cesarean section rate. Rates of cesarean deliveries have risen in high-income countries over the last decade (Wong et al., 2019). I have noticed that labor-management techniques and cesarean section rates vary between nurses and providers. Evidence suggests that different provider attitudes and practices can lead to variation in cesarean birth rates (Wong et al., 2019). Many nurses are proactive managing position changes with laboring mothers under epidural anesthesia; however, there are many variations in frequency and types of positioning. According to Borges et al. (2021), changes in positioning lead to changes in the pelvic space, and certain positions may prevent labor obstruction. Also, I have noticed that some physicians have a higher Cesarean Section rate than others. I hypothesize that this may be due to low tolerance for varying situations, including fetal heart rate decelerations and slow labor progression. Some physicians expect labor progression at a rate of a centimeter per hour. However, this is unrealistic and inaccurate for a labor diagnosis of failure to progress (World Health Organization, 2018). Similarly, labor may not progressively change until a laboring woman reaches 5 centimeters; therefore, augmentation should not occur before this time (World Health Organization, 2018). I think data would be beneficial in identification of an underlying reason for an increased cesarean section rate. 
 Due to the rise in cesarean section rate, I would assess data from a panel of full-term laboring women. I would be interested in determining if changes in nurse, provider, or labor management techniques altered the cesarean section rate. It would be helpful to gather information about cervical dilatation, position changes, frequency of position changes, providers caring for the patient, length of labor, and medication used to augment labor. Data would be collected through nurse input and documentation into the electronic health record and accessed through Epic’s data information system. Data processing would then occur to analyze the data. It would be beneficial to gather this information to determine the impact of different labor management techniques and providers on the cesarean section rate. 
This data may help derive knowledge about staff with an increased cesarean section rate and identify those that require additional education. As data is collected and knowledge is acquired, clinical algorithms could process the data and send alerts to the nurse when data indicates a slowing in labor progression or when a laboring mother is falling off the typical labor curve. According to McGonigle and Mastrian (2022), an alert offers users the information necessary to interact with the system. This algorithm could assist staff in implementing techniques to augment or assist labor progression. The data also may assist with evidence regarding best practice techniques that I could share with colleagues.  According to Nagle et al. (2017), this knowledge could generate algorithms for decision-making that could be automatically integrated into electronic health records worldwide. 
As a nurse leader, I would use clinical reasoning and judgment in the formation of knowledge to help improve the cesarean section rate. Knowledge is understanding information and applying this information to arrive at a decision or support tasks (McGonigle

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