Knowledge tranfer among workers
Research suggests that organizations that embrace and encourage knowledge transfer among workers not only sustain and build professional competence and organizational engagement, but also enhance the quality of the work life for professionals (McGonigle, D & Mastrian, K.G.). One benefit of the big data the user-friendly systems called computers that we use to enter data. When you go to the ER with your phone number, they will be able to pull up your medical history and making your process a little faster. While a large part of the data and analytics can directly impact patient care, healthcare systems also have an opportunity to use data to increase their own operational efficiency which also impacts patients (Strachan, M. 2018). But one of the potential risks of using the big data is when the computers are down, and you cant do anything for a couple of hours. You must acquire nurse notes and write down orders and take it to the pharmacy if needed. It can be very frustrating until the computers are rebooted. Whether information is manually entered back into the system or scanned once systems are back online depends on the length of the outage. The difference in the amount of patient information after an outage lasting an hour and one lasting 12 hours is significant and entering large volumes of data can increase the likelihood of human errors. (McKinney, M. 2007). One strategy I have observed is the frustration that we often have as nurse leaders in looking at this data, is [that] some of the variables we care about the most, aren’t even in the data,” Englebright says. “We don’t have something that measures nursing competence, for example. We don’t have something that measures how committed the nurses are. We don’t have something that measures if the patient really [is] going to do the stuff we just invested all this time in teaching them to do. Because of this, CNEs end up having to advocate for the things they care about in a person-on-person debate, then being able to make a persuasive business case based on data (Thew, J. 2016, April 19).
