When you wake in the morning, you may reach for your cell phone to reply to a few text or email messages that you missed overnight. On your drive to work, you may stop to refuel your car. Upon your arrival, you might swipe a key card at the door to gain entrance to the facility. And before finally reaching your workstation, you may stop by the cafeteria to purchase a coffee.
From the moment you wake, you are in fact a data-generation machine. Each use of your phone, every transaction you make using a debit or credit card, even your entrance to your place of work, creates data. It begs the question: How much data do you generate each day? Many studies have been conducted on this, and the numbers are staggering: Estimates suggest that nearly 1 million bytes of data are generated every second for every person on earth.
As the volume of data increases, information professionals have looked for ways to use big data—large, complex sets of data that require specialized approaches to use effectively. Big data has the potential for significant rewards—and significant risks—to healthcare. In this Discussion, you will consider these risks and rewards.
Post a description of at least one potential benefit of using big data as part of a clinical system and explain why. Then, describe at least one potential challenge or risk of using big data as part of a clinical system and explain why. Propose at least one strategy you have experienced, observed, or researched that may effectively mitigate the challenges or risks of using big data you described. Be specific and provide examples.
Respond to at least two of your colleagues* on two different days, by offering one or more additional mitigation strategies or further insight into your colleagues’ assessment of big data opportunities and risks.
Click on the Reply button below to reveal the textbox for entering your message. Then click on the Submit button to post your message.
*Note: Throughout this program, your fellow students are referred to as colleagues.
Michea Discussion ( in APA 7 format and at least 2-3 references)
With the fast growing pace of technological advancement in the health care sector, daily operations of the institution helps generate millions of data that over time needs proper channels of transmission, storage, processing, assimilation and utilization. Following from the vast amount of data generated, some of its benefits includes but is not limited to functioning as a pattern discovery aid with relation to the amount of variance or similarity in the cases seen by a particular health care organization, the data bank develops a pattern memory which helps the facility better prepare based on the statistical evidence derived from their previous encounter with a surge of disease only relative to the hospitals geographical location. “Pattern discovery entails much more than simply retrieving data to answer an end user’s query. Data mining tools scan databases and identify previously hidden patterns. The predicative, proactive information resulting from data mining analytics then assists with development of business intelligence, especially in relation to how we can improve.” (McGonigle, 2017, p477)
Another benefit of using big data is its ability to enhance continuity, stemming from when a patient checks into the hospital till the moment they are discharged, the vast amount of data generated from laboratory testing, imaging or other specialized test makes for continuity in care since every department and or axillary health care support system can access such data and proceed with their plan of care without having to reduplicate efforts of redoing labs and imaging studies before attempting to care for the patient, hence this serves a dual purpose of efficiency in the delivery of care while also providing the patient with a cost saving approach. “Eliminating duplication of effort will go a long way to simplifying and streamlining nursing workflow within EHRs. Patient care devices (such as cardiac monitors, vital sign monitors, and I.V. infusion pumps) can be linked with the EHR. Many of them are essentially mini-computers that store and send their discrete data to the EHR.” (Glassman, 2017, p46)
Given the leaps and bounds in the advent of health care technological advancements, other issues that need immediate attention is the risk and challenges associated with its use. Unplanned power outages during inclement weather conditions presents as a great risk factor to the use of the big data warehouse since the resourcefulness and operability of the system hinges on uninterrupted power supply. Another challenge with the use of the big data system is how to keep the system running during moments of downtime or system upgrades, cooperation on the part of the patient to embrace new development and the changes made to enhance their care also presents with a risk factor to the overall functioning of the parameters implemented in place. “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.” (Thew, 2016)
Some of the strategy I have experienced and or observed that will effectively mitigate the challenges associated with big data includes but is not limited to utilizing the following solutions; The use of back up generators have proven to be a more efficient way of managing unplanned power outages while delivering uninterrupted care to our clients. Planning of down time and or system upgrades should be slated for when the hospital anticipates low census like during the holidays when a skeleton crew could manage operations within the hospital. The concept of having a back up data storage in the cloud, will also serve for the purpose of accessibility and easy retrieval of data should the institutions primary system and data bank experience a crash.
Jams Discussion ( in APA 7 format and at least 2-3 references)
Big data refers to a large amount of information gathered through technology which we use to generate meaning in the world (McGonigle & Mastrian, 2018). There are many benefits of using big data as part of a clinical system such as quick easy access to a plethora of patient information to use by the healthcare professionals and the patients. Glassman (2017) states that patients being able to view their own health information and results through patient portals keep them up to date on labs, medications, and upcoming appointments.
The challenge of using big data as part of a clinical system is seen when there are large amounts of data coming through, but each set has its own language that needs to be manually translated as seen with HCA (Thew, 2016). McGonigle and Mastrian (2018) states that a strategy for sorting through the large amounts of information coming through is to invest in data mining techniques. There are many “data mining techniques,” one of them uses algorithms, these techniques place similar information into categories which makes it easier to analyze (McGonigle & Mastrian, 2018).
Glassman, K. S. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45–47. Retrieved from https://www.americannursetoday.com/wpcontent/uploads/2017/11/ant11-Data-1030.pdf
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-bigpotential-challenges-nurse-execs
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