NURS-6051N Transforming Nursing & HC Full Class

INTERACTION BETWEEN NURSE INFORMATICISTS AND OTHER SPECIALISTS

Nature offers many examples of specialization and collaboration. Ant colonies and bee hives are but two examples of nature’s sophisticated organizations. Each thrives because their members specialize by tasks, divide labor, and collaborate to ensure food, safety, and general well-being of the colony or hive.

Of course, humans don’t fare too badly in this regard either. And healthcare is a great example. As specialists in the collection, access, and application of data, nurse informaticists collaborate with specialists on a regular basis to ensure that appropriate data is available to make decisions and take actions to ensure the general well-being of patients.

In this Discussion, you will reflect on your own observations of and/or experiences with informaticist collaboration. You will also propose strategies for how these collaborative experiences might be improved.

To Prepare:

• Review the Resources and reflect on the evolution of nursing informatics from a science to a nursing specialty.
• Consider your experiences with nurse Informaticists or technology specialists within your healthcare organization.

BY DAY 3 OF WEEK 3

Post a description of experiences or observations about how nurse informaticists and/or data or technology specialists interact with other professionals within your healthcare organization. Suggest at least one strategy on how these interactions might be improved. Be specific and provide examples. Then, explain the impact you believe the continued evolution of nursing informatics as a specialty and/or the continued emergence of new technologies might have on professional interactions.

BY DAY 6 OF WEEK 3

Respond to at least two of your colleagues* on two different days, offering one or more additional interaction strategies in support of the examples/observations shared or by offering further insight to the thoughts shared about the future of these interactions.

 Interactions between Nurse Informaticists and other Professionals

When working in a hospital setting, nurse informaticists must collaborate with a variety of professionals to ensure the patients are getting the appropriate care “Informaticists must be willing to share, communicate, and deliberate with other professionals caring for the same patient to achieve the best outcomes for the patient” (McGonigle & Mastrian, 2022, p. 348).

One example that I have recently experienced a nurse informaticist working with other professionals is when I attended a new employee orientation at a local hospital. The orientation to Epic lasted 4 hours; we were shown the basics. How to view and put in orders, add medications, and discontinue them. It was a lot of information to try to remember in 4 hours. Those who attended the training were mostly nurses, doctors, and nurse practitioners. Once the training was completed, we were given a survey to fill out about the training. This allowed employees to provide their feedback and recommendations.

Another example that I have observed nurse informaticists working with other professionals is when a physician wanted to incorporate new criteria for placing a foley catheter in patients. The physician wanted to add if the patient has had any recent UTIs and indications for catheter use. The nurse informaticist spoke to the physician, gathered all the information she needed, and communicated with other physicians on that floor to add additional criteria.

Suggestions for Improvement

I have a few suggestions to improve the new employee orientation. The first suggestion is to incorporate another day of training. If another training day is added, it will not feel as overwhelming. There was a lot of information to try to remember. The second suggestion would be giving the employees a fake patient to enter information on for training. Being able to enter data from the beginning of a patient’s hospitalization to the end would allow employees to understand the admission and discharge process better.

One thing I suggest with adjusting criteria for foley catheter placement is having a committee that reviews and communicates with all the physicians and nurse managers on all the criteria and bundles and adjusts accordingly. I would have this committee meet at least every three months. Staying up to date with best practices is essential so the patients can have the best outcomes.

 Continued Professional Interactions

The healthcare field is ever-changing, and with that comes technological changes. Nursing informaticists are essential for this change; having them interact with other healthcare professionals is just as important. Nurse informaticists and nurse managers are developing new ways to provide the best patient care and policies (Mosier et al., 2019). With the advancement of video technology, healthcare professionals can better interact with each other. This allows nurse informaticists and other health care professionals to communicate even when not on-site. With the changing technology, informatics competencies are necessary to keep up with the changes so patients will have better outcomes (Sipes, 2016).

References

McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning.

Mosier, S. , Roberts, W. & Englebright, J. (2019). A Systems-Level Method for Developing Nursing Informatics Solutions. JONA: The Journal of Nursing Administration, 49 (11), 543-548. doi: 10.1097/NNA.0000000000000815.

Sipes, C. (2016). Project management: Essential skill of nurse informaticists. Studies in Health Technology and Informatics, 225, 252-256.

• Main Question Post:

   

  Big data is the accumulation of large data sets that can be studied to reveal patterns, trends, and associations. Big data is considered big, since it cannot be processed quickly enough by older data analysis tools (Coursera, 2022). As technology evolves in healthcare, the use of big data will be able to have a major impact on patient outcomes.

   

  One of the benefits of using big data in healthcare would be being able to find common symptoms of a disease. The Covid-19 pandemic provided an opportunity for the CDC to formulate a Coronavirus self-checker. With the self- checker people can view Covid-19 symptoms ranging from mild to severe illness (CDC, 2022). The use of the self-checker enabled many users to view symptoms and determine if they needed to be tested. Also, the development of the Covid-19 vaccines was another way big data was able to be used. Again, the CDC formulated a safety monitoring system called V-safe that allows you to share how you feel after getting a Covid-19 vaccination. V-safe then sends automated message to ask how you are feeling after a period of time. V-safe check ins helps the CDC (2022) monitor the safety of vaccines.

   

  One challenges of using big data in the clinical system would be having technical difficulties and users not being able to analyze the data presented. McGonigle and Mastrian (2022) mention that there are fewer than 15, 000 formally trained medical informaticist in the U.S. In turn this creates a huge talent gap and healthcare organizations do not have the expertise necessary to make data effective. For big data to be effective appropriate data governance must be maintained. A strong data governance should provide clear guidelines for data availability, criticality, authenticity, sharing, and retention that allows healthcare organization to utilize data effectively (Wang et al., 2018).

   

   

  Centers for Disease Control and Prevention (2022). Symptoms of Covid-19. Retrieved from, https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.htmlLinks to an external site.

   

  Centers for Disease Control and Prevention (2022). What is V-safe? Retrieved from, https://www.cdc.gov/coronavirus/2019-ncov/vaccines/safety/vsafe.htmlLinks to an external site.

   

  Coursera (2022). What Is Big Data? A Layperson’s Guide. Retrieved December 27, 2022, from https://www.coursera.org/articles/what-is-big-data-a-laypersons-guideLinks to an external site.

  McGonigle, D., Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5^th ed.). Jones & Bartlett Learning

   

  Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126(1), 3-13

   

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  • Collapse SubdiscussionConor Westerman

    Conor Westerman

    Dec 30, 2022Dec 30, 2022 at 9:29pm

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    Hi Georgette,

     

    I appreciated reading your post on big data. I also wrote about COVID-19 being an example of big data being put to work in healthcare. The idea that big data will have a major impact on patient outcomes is essential to getting more informaticists to work utilizing data to drive healthcare forward.

    The vaccine side-effect reporting system was very useful and showed the COVID-19 vaccine overall represented a minimal risk to most individuals (CDC, 2022). You touched on a big drawback from the text in that there are not enough medical informaticists who can help to synthesize data and put it to use.

     

     

    References

     

    Centers for Disease Control and Prevention (2022). What is V-safe? Retrieved from, https://www.cdc.gov/coronavirus/2019-ncov/vaccines/safety/vsafe.htmlLinks to an external site.

     

    McGonigle, D., Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5^th ed.). Jones & Bartlett Learning

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• Collapse SubdiscussionFlorah Deann Tackett

  Florah Deann Tackett

  Dec 27, 2022Dec 27, 2022 at 6:36pm

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  Main Post

  Big Data

  Big Data is an extensive collection of data that is being generated quickly that is too difficult to manage in the traditional way (Thew, 2016). Big Data is needed in healthcare organizations to help manage electronic medical records. Big Data improves the quality of services that the healthcare organization provides.

  Benefits of Using Big Data

              A benefit of using Big Data in healthcare is that healthcare providers can use the information collected to identify diseases early on. A healthcare provider can access information quickly to diagnose diseases. For example, providers can determine diabetes early or help prevent a patient from getting diabetes by using Big Data. Another example would be to help providers better understand how to care for many patients. Information about each patient can be made into flow sheets (Glassman, 2017). This leads to better outcomes, care for patients, and decreases healthcare costs.

  Potential Challenge

              A potential challenge with using Big Data in healthcare is security. Healthcare organizations are at risk of security breaches and getting hacked. In 2020 one in three healthcare organizations reported that their system was hit by ransomware (Weiner & Writer, 2021). Hospitals often are at risk for cyber-attacks because they have tons of patient information that is of value. Often hospitals do not have the funds to get the extra security.

  Strategy to Mitigate Challenges

  There are a few things that could help decrease cyber-attacks on healthcare organizations. The first and most important way is to have the latest security software for electronic medical records and stay up to date on the software. Another way is to incorporate a multifactor authentication for employees when they log into the system. The last way is to educate staff on cyber-attacks and suspicious emails. Educating staff to report suspicious emails and not to open them is essential. Doing all these things can help decrease the chances of cyber-attacks.

   

  References

  Glassman, K. S. (2017). Using data in nursing practice. Links to an external site.American Nurse Today, 12(11), 45–47. Retrieved from https://www.americannursetoday.com/wp- content/uploads/2017/11/ant11-Data-1030.pdfLinks to an external site.

  Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-Links to an external site.means-big-potential-challenges-nurse-execs

  Weiner, S., & Writer, S. S. (2021, July 20). The growing threat of ransomware attacks on

  Hospitals. AAMC. Retrieved December 26, 2022, from https://www.aamc.org/news-Links to an external site.

  insights/growing-threat-ransomware-attacks-hospitals

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  • Collapse SubdiscussionLaura Mcbee

    Laura Mcbee

    Dec 29, 2022Dec 29, 2022 at 5:35am

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    Hi Florah,

    Nice post.  I like how you highlighted the need for big data and how its uses can promote more timely diagnosis and treatment of patients.  Big data can be a big head start for not only providers but also for medical scientists and researchers as the information can more importantly bring to light trends in medicine and the reaction and or responses to medication. The combination of predictive analytics and the increased development of innovative therapies could allow data scientists to observe trends in prescription medications, the outcomes of these treatments and the patient’s genetic profile which can subsequently allow physicians to be capable of understanding a head of time the gene variants suggesting the existence of the disorder, with the particular health history of the patient, and allow use of a more precise medication with is more successful in care (Kaustubh, et al., 2021). It is vital that organizations commit to promoting the use of big data by supporting its existence to better serve patients.  A strategy suggested is for organizations to generate new business ideas from big data predictive analytic tools because these tools can provide detailed reporting and identify market trends that allow companies to accelerate new business ideas and generate creative thinking (Wang, et al., 2018).   Innovation is important in the changing healthcare for the better and big data can help solve and promote better decision making and spawn new ideas and research that could unveil pivotal medical treatment and care for patients.

    References

    Kaustubh A., K., P., J. S., S., K. S., Hindavi C., D., & L., P. P. (2021). Big Data and Electronic Health Record in Pharmacy: A systematic Review. Journal of Advanced Scientific Research, 12, 39-45

    Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126(1), 3-13.

     

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• Collapse SubdiscussionPatrick R King

  Patrick R King

  Dec 27, 2022Dec 27, 2022 at 6:58pm

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  Main Post

   

  Big Data is becoming the future for nearly every aspect of life. Starting first in business analytics, the healthcare system has begun to adopt Big Data for data collecting and interpretation. As described by Wang et al., Big Data assists healthcare organizations in receiving, interpreting, and disseminating massive amounts of data across a wide range of other healthcare networks to provide better patient outcomes (2016). This allows for a vast amount of information to be readily collected and sought for. Big Data is a “large complex data set that yields substantially more information when analyzed as a fully integrated data set” compared to using unintegrated data sets of the same data (Thew, 2016). Big Data can be perceived as both a blessing and a curse to healthcare users.

  A major benefit Big Data offers to the healthcare industry is a library of information that is readily accessible. Healthcare is all data gathering through medical assessments and examinations. Big Data allows for the input of this data and healthcare organizations to quickly analyze the “immense volume, variety, and velocity of data” then utilize the data in supporting and developing evidence-based practices (Wang et al., 2016). Big Data can grant access to hundreds of thousands of data at the click of a button, but it is not perfect in its system.

  Despite the many uses Big Data presents, the implementation of this system has not been without errors. Does the name Google Flu Trends sound familiar? This system is an example of Big Data being used with big promises but crashing results. Google created a system to track and predict influenza sickness with the intention of preventing the general population from contracting influenza. Ultimately, the algorithms Google uses were changed, and the system misinterpreted each time a search of “Influenza” was made, the search was made by someone that is sick with the flu and looking for further information. This increased visits to physicians and costed consumers more than driving down healthcare costs as intended. The program was scrapped after a short two years of operation (Househ et al., 2017). This is called “false discovery,” and artificial intelligence analysis was interpreted as hard evidence.

  To prevent these “false discoveries” made by Big Data, the healthcare community must collaborate with Big Data instead of relying on the data presented. Much like the Google Flu Trends, researchers placed too much trust in Big Data. Combining traditional data collection and analysis with the data presented by Big Data is the best way to prevent mistakes like the Flu Trend (Househ et al., 2017). This will ensure that the data collected is reliable and accurate for researchers and informaticists. Taking this precaution and correcting the mistakes of Big Data offers the healthcare industry multitudes of promising and essential services.

  References:

  Househ, M. S., Aldosari, B., Alanazi, A., Kushniruk, A. W., & Borycki, E. M. (2017). Big Data, Big Problems: A Healthcare Perspective. Studies in Health Technology and Informatics, 238, 36–39.

  Thew, J. (2016, April 19). Big data means big potential, challenges for nurse exec. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs

  Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126(1), 3–13.

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• Collapse SubdiscussionLaura Mcbee

  Laura Mcbee

  Dec 27, 2022Dec 27, 2022 at 7:02pm

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  Module 3 Discussion Post MAIN

   

  Benefit of Using Big Data

  The healthcare arena continues to advance forward with increased capabilities of technology and the use of data to help drive change and support decision making.  Big data is a collection of data so vast and complex that traditional methods and data management tools are not able to store, process or interpret the data efficiently (McGonigle & Mastrian, 2022).  My organization is able to use big data to drive important decisions for the pharmacy and support the antimicrobial stewardship program which can largely improve patient outcomes.  A way our organization is able to utilize this complex big data is through data mining software that sorts through data to discover patterns and ascertain relationships (McGonigle & Mastrian, 2022).  Our pharmacists utilize our electronic medical record system to collect data about a patient’s medication history, medication allergies, and current medication lists which helps assist in providing safe, efficient, and timely care to patients.  Our organization also utilizes Sentri 7 software that mines data within the EMR to assist in the assessment of increase antibiotic usage, ordering trends, physician specific trends in antibiotic ordering, and the correlation between antibiotic usage and specific infections such as Clostridium Difficile infections.  This information, otherwise may not be identified or interpreted in a timely enough manner to make important decisions on patient care.  This information largely supports our antimicrobial stewardship and drives conversations and enhances learning and clinical inquiry.  Big data provides the healthcare industry with the potential of massive EMR data study on results, patterns, temporary trends and associations (Kaustubh, et al., 2021).

  Challenge or Risk of Using Big Data

  Big data is vital to decision making for organizations and leadership rely heavily on big data. The analysis of massive amounts of data in the hospital pharmacy has great potential for unlocking novel research questions and insights into patient management and drug safety, but challenges of privacy and security in regards to data sharing can be a concern (Del Rio-Bermudez, et al. 2020).  Human limitations can also yield additional challenges such as lack of big data and analytical knowledge and lack of trained data scientists to make use of big data and the primary skills of big data technology and platforms (Kaustubh, et al., 2021).

  Strategy to Mitigate the Challenge or Risk

              Big data can improve patient outcomes and it is key that organizations who rely heavily on the big data foster an information sharing culture because this is critical for reducing resistance to new information management systems from physicians and nurses (Wang, et al., 2018).  In order to combat barriers to big data and analytical knowledge, organization leadership must support growth and competency by equipping the employees in a critical role in the new information-rich work environment with regular analytical training courses in areas such as basic statistics, data mining and business intelligence (Wang, et al., 2018).  Staying current and up to date is key to success.

   

  References

  Del Rio-Bermudez, C., Medrano, I.H., Yebes, L. et al. Towards a symbiotic relationship between big data, artificial intelligence, and hospital pharmacy. J of Pharm Policy and Pract 13, 75 (2020). https://doi.org/10.1186/s40545-020-00276-6Links to an external site.

  Kaustubh A., K., P., J. S., S., K. S., Hindavi C., D., & L., P. P. (2021). Big Data and Electronic Health Record in Pharmacy: A systematic Review. Journal of Advanced Scientific Research, 12, 39-45.

  McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of 

       knowledge (5th ed.). Jones & Bartlett Learning.

  Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126(1), 3-13.

   

   

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  • Collapse SubdiscussionCassandra Lynn Johnson

    Cassandra Lynn Johnson

    Dec 28, 2022Dec 28, 2022 at 6:36pm

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    Laura,

    Thank you for sharing information regarding your hospital’s use of Sentri 7 software to trend and track big data within your EHR. This is a software system I needed to familiarize myself with; as such, I took the opportunity to research this technology further and see the benefits associated with this technology. I reviewed a research study that conducted a retrospective analysis of pharmaceutical interventions based on the use of the said product (Huber et al., 2016). The research demonstrated significant value associated with clinical surveillance software as a tool adding clinical value to patient care when evaluating interventions such as antimicrobial therapies (Huber et al., 2016).

    The example you shared in your post demonstrates how big data, when appropriately analyzed, improves patient outcomes. Good data produce good decisions, which allow great providers to provide excellent care (Thew, 2016). It is vital to ensure adequate knowledge of both why the data is essential and how to utilize the data to obtain it from the healthcare team. Reducing the resistance that inevitably comes with changes and new operations is imperative to developing a sharing culture (Wang et al., 2018). Thank you for your time and the information you shared during your post.

     

    References

    Huber, S. et al. (2016, October 21). Retrospective evaluation of pharmacist interventions of use of antimicrobials using a clinical surveillance software in a small community hospital. Retrieved December 28, 2022, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5419378/

    Thew, J.  (2016, April 19). Big data means considerable potential challenges for nurse execs. Retrieved December 27, 2022, from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execsLinks to an external site.

    Wang, Y., Kung, L., Byrd, T.  (2018, January). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technology Forecasting and Social Change, 126(1), 3–13. Retrieved December 27, 2022, from https://www.sciencedirect.com/science/article/pii/S0040162516000500?via=ihubLinks to an external site.

     

     

     

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• Collapse SubdiscussionCassandra Lynn Johnson

  Cassandra Lynn Johnson

  Dec 27, 2022Dec 27, 2022 at 8:38pm

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  We are amidst a world driven by computer information technology. As we prepare for this discussion post, we sit with, at a minimum, a computer and a phone either in our lap, on our bedside, etc., all of which are connected to the internet, generating information and tracking keystrokes and contributing to the collection of big data. Big data, coined in the late 1990s, refers to expansive amounts of information generated with each interaction with a computer information system (Wang et al., 2018). Big data is further defined as consistently growing knowledge in three dimensions: volume of data, velocity or speed at which the information is collected, and the variety of organized and unorganized data a system can collect (Dash et al., 2019). Every day each of us generates extensive amounts of information that can be stored and analyzed to provide trending data and research to predict the next steps in practically every area of business, technology, healthcare, etc. Nurses represent the largest group of healthcare professionals and, as such, have the potential to make the most significant impact in ensuring the quality and safety of patient interventions and outcomes (Glassman, 2017). As nurses, we must begin to run towards technology, not away, and utilize the information that is gathered to help us to inform our next steps.

  This week’s discussion asks us to review and reflect on big data and its risks and rewards in healthcare. The article Big Data Means Big Potential, Challenges for Nurse Execs sets the stage for the potential that lies within the concepts and practices of big data but, in turn, requires the reader to reflect on their experiences using data to guide decisions (Thew, 2016). Nursing leadership and executives are in a position every day that requires them to make decisions. Good data produces good decisions (Thew, 2016). When data points are expansive and do not automatically connect with a one-to-one ratio, it can be challenging to process the data that has been gathered to make the necessary decisions (Threw, 2016). This can lead to ill-informed, poorly guided decisions.

  The electronic health record is a complex system actively collecting, tracking, and trending personal health data about the individual patients we serve. This information, for example, can be used to make evidence-based care decisions regarding interventions providing the best outcomes for patients across large data sets. We can ensure the best outcomes for those we treat by utilizing the data points to generate best practices. On the contrary, this information can be used to inflict harm. Even the most protected systems are open to the potential risk of being hacked. This places the confidential information of everyone within the system at risk of being compromised. I, just like many others, have had my information included in a data breach. This invasion of privacy makes you question a system’s integrity and challenging ways to improve privacy.

   

  Resources

  Dash, S. et al. (2019, June 19). Big data in healthcare: Management, analysis, and

  prospects. Journal of Big Data. Retrieved December 27, 2022, from https://link.springer.com/article/10.1186/s40537-019-0217-0Links to an external site.

  Glassman, K. S. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45–47.

  Retrieved from https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdfLinks to an external site.

  Thew, J.  (2016, April 19). Big data means considerable potential challenges for nurse execs.

  Retrieved December 27, 2022, from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execsLinks to an external site.

  Wang, Y., Kung, L., Byrd, T.  (2018, January). Big data analytics: Understanding its capabilities

  and potential benefits for healthcare organizations. Technology Forecasting and Social Change, 126(1), 3–13. Retrieved December 27, 2022, from https://www.sciencedirect.com/science/article/pii/S0040162516000500?via=ihubLinks to an external site.

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• Collapse SubdiscussionSopheap Ly

  Sopheap Ly

  Dec 27, 2022Dec 27, 2022 at 9:17pm

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            Big data is “ in-field shorthand that refers to the sheer mass of data produced daily by and within global computer networks at a pace that far exceeds the capacity of current databases and software programs to organize and process. Virtually any organization that gathers information—government, businesses, retail stores, services, hospitals, social media outlets—faces an enormous challenge in gathering information that is generated at massive rates every minute, reading that data into meaningful and coherent information, and then storing it efficiently and effectively,” (Dewey, 2022).

  There are many risks and benefits to using big data, one benefit would be the easy access to patient information on patients who come in and out of the hospitals, healthcare providers would have access with the touch of a button when patients arrive for appointments or emergency visits.  This allows their information to be stored in one place.  Big data use is a place where everything is stored, in hospitals, everything concerning a patient is documented in the system, this includes medications that has been administered to a patient, any allergies or medication reactions that the patient may have acquired, any falls they have sustained, and falls.  With this consolidated storage of information, the healthcare system is able gather any statistics about falls and medication reactions, and many more information to improve any evidence-based practice experiments the hospitals may be evaluating.  “Storing the data is, of course, just part of the story. For the data to be of use it must be analyzed, and for this a whole new range of sophisticated techniques is required, including machine learning, natural language processing, predictive modelling, neural networks, and social network mapping. Sitting alongside these techniques are a complementary range of data visualization tools,” (Gordon, 2014).

  A potential challenge of using big data as part of the clinical system is that there is so much information on how to use the program that it does get confusing and difficult. “In this sense, the ‘social’ in social data is a construct that problematizes any simple measurement of what people are doing, before we even consider why they are doing it or what it means to them or indeed us,” (Hand, 2014).  With the advancement of technology, as a society we rely heavily on technology.  We use it in the hospital system for documentation, technology is used to demonstrate to patients exercise routines and even food preparation ideas.  Technology has become a part of our lives.  With this advancement, society tends to believe everything on the internet, at times it can provide false information.  When it comes to documenting information about patients in the computer system, if one is not paying attention, an error in documentation can occur by documenting on the wrong patient.

  Hospital staff taking time for documentation will decrease the error risk when documenting.  Educating patients and staff on how to use technology appropriately would be beneficial for all. “In terms of techniques, this centers on application programming interface (API) integration, for example identifying customer affinity based on sentiments gleaned from Facebook ‘likes’, positive tweets and Yelp reviews. To be properly processed, these call for an understanding of multiple APIs and data integration tools,” (Gordon, 2014).

   

  Dewey, J., PhD. (2022). Big data. Salem Press Encyclopedia.

   

  Gordon, K. (2014). Big data : Opportunities and challenges. BCS Learning & Development Limited.

   

  Hand, M., & Hillyard, S. (Eds.). (2014). Big data? : Qualitative approaches to digital research. Emerald Publishing Limited.

   

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• Collapse SubdiscussionMarie Lo

  Marie Lo

  Dec 27, 2022Dec 27, 2022 at 10:43pm

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  The informatics competency teaches nurses how to use information and technology at the point of care to communicate, manage knowledge, reduce error, and support decision-making. Nurses must have access to aggregate data about their patients and the effects of their care, as well as be knowledgeable about how to interpret that data, in order to make wise practice decisions (Glassman, 2017). By switching from paper-based systems to electronic health record (EHR) systems, the healthcare sector has benefited from advancements in information and communication technology, enabling it to offer its clients better and more affordable services. Big healthcare data holds great promise for enhancing patient outcomes, forecasting epidemic outbreaks, gaining insightful information, preventing diseases, lowering healthcare delivery costs, and enhancing general quality of life (Abouelmehdi et al., 2018). Physicians’ handwriting is notoriously bad. Medication errors have been reduced as a result of the use of modern technology in healthcare. One of the advantages of big data in the clinical system has been the reduction in the number of prescription errors. Prescription error reduction improves outcomes and saves lives.

  A growing concern in the field of big data analytics is the invasion of patient privacy as a result of the emergence of advanced persistent threats and targeted attacks against information systems. Choosing the permissible uses of data while protecting patient security and privacy is a difficult task. Big data, no matter how beneficial to medical science and critical to the success of all healthcare organizations, should only be utilized if security and privacy concerns are addressed (Abouelmehdi et al., 2018). Internal and external breaches of privacy are both possible. They include unauthorized access/disclosure, improper disposal of unnecessary but sensitive data, loss or theft of confidential data, or the unintentional sharing of confidential data with an unauthorized party, any hacking/IT incident such as a malware attack, ransomware attack, phishing, spyware, or fraud in the form of stolen cards (Seh et al., 2020). As a nurse, I am extremely cautious when a patient’s family or friends call about obtaining personal information about the patient. To avoid oversharing and HIPPA violations, I always encourage my patients to share their own personal information. Data breaches involving healthcare are significantly more expensive than typical data breaches. Therefore, security professionals, healthcare organizations, and researchers need to give preventive measures top priority (Seh et al., 2020). Big data privacy and security are important issues. In the healthcare industry, it is crucial to protect sensitive data about personally identifiable health information. Healthcare organizations must implement security measures and approaches to safeguard their big data, associated hardware and software, and clinical and administrative data from internal and external threats (Abouelmehdi et al., 2018).

   

  Abouelmehdi, K., Beni-Hessane, A., & Khaloufi, H. (2018, January 9). Big Healthcare data: Preserving Security and Privacy – Journal of Big Data. SpringerOpen. Retrieved December 27, 2022, from https://journalofbigdata.springeropen.com/articles/10.1186/s40537-017-0110-7

  Glassman, K. S. (2017). Using data in nursing practice Links to an external site.Links to an external site.. American Nurse Today, 12(11), 45–47. Retrieved from https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdfLinks to an external site.

  Seh, A. H., Zarour, M., Alenezi, M., Sarkar, A. K., Agrawal, A., Kumar, R., & Khan, R. A. (2020, May 13). Healthcare data breaches: Insights and implications. Healthcare (Basel, Switzerland). Retrieved December 27, 2022, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349636/

   

   

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  • Collapse SubdiscussionDawn Cahill

    Dawn Cahill

    Dec 28, 2022Dec 28, 2022 at 9:10am

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    Response 2

    Marie Lo

    As you have mentioned big healthcare data includes a lot of information. I think another issue with this much information and in relation to big data is the aspect of being “large and unmanageable” (Dash et al, 2019, p.2). Healthcare leaders are more likely to suffer from data overload with the amounts of information becoming available. According to Wang et al (2018) it would be highly beneficial for organizations to understand the potential of big data analytics and it is suggested to implement an IT governance. This governance is stated to assist organizations with clearly defining goals, procedures, metrics, and measures with big data available (Wang et al, 2018).

    References:

    Wang, Y., Kung, L., Byrd, T.  (2018, January). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technology Forecasting and Social Change, 126(1), 3-13. 

    https://www.sciencedirect.com/science/article/pii/S0040162516000500?via=ihubLinks to an external site.

     

    Dash, S., Shakyawar, S.K., Sharma, M. (2019). Big data in healthcare: management, analysis and future prospects. J Big Data 6, 54. https://doi.org/10.1186/s40537-019-0217-0

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  • Collapse SubdiscussionDamacrine Morangi Anyuga

    Damacrine Morangi Anyuga

    Dec 29, 2022Dec 29, 2022 at 12:09am

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    Response #2

    Hi Marie,

    It is true that the health sector has been one of the major beneficiary of advancement in technology and use of big data. The use of electronic Health Records has led to favorable outcomes in healthcare as there is ability to analyze different data types such as laboratory findings, imaging data ,doctors notes  and information gathered from the patient. This analysis are used to determine the prognoses, diagnose and plan treatment leading to better management and outcomes for patients (Ngiam & Khor, 2019).Clinical data Integration can also be useful in disease surveillance and reduction of healthcare costs . It is therefore important that the healthcare sector invests on user friendly and, transparent big data systems and  training clinical analysts as there is a notable non availability in skilled and trained clinical analysts (Merendino et al., 2018). This could help overcome the challenges by decreasing issues such a breach of privacy and bias which comes with use of this big data in the clinical setting.

    References

    Merendino, A., Dibb, S., Meadows, M., Quinn, L., Wilson, D., Simkin, L., & Canhoto, A. (2018). Big data, big decisions: The impact of big data on board level decision-making. Journal of Business Research, 93, 67-78.

    Ngiam, K. Y., & Khor, W. (2019). Big data and machine learning algorithms for health-care delivery. The Lancet Oncology, 20(5), e262-e273.

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• Collapse SubdiscussionFlavin Akande

  Flavin Akande

  Dec 28, 2022Dec 28, 2022 at 10:09am

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  Main Post

  Big Data Risks and Rewards

  In the past decades, healthcare facilities kept patient information on printed records. However, with the advanced technology and incorporation of information technology in the healthcare industry, patient information is computerized for easy storage and retrieval. Other than saving space that was originally used to store huge files and a lot of information, the use of electronic health records increases security, safety, and confidentiality of patient information. Furthermore, it improves the quality of care, efficiency in history taking, and patient experience. Therefore, most healthcare organizations reap many benefits when they integrate bid data into their clinical systems.

  Benefits of Big Data

  Bid data application in healthcare improves patient outcome, experience, and overall health due to reduced medical errors that are usually associated with manual paper-work. For example, electronic health records promote efficiency and saves time (Bora, 2019). Before, patients sued to que for long hours since the nursing and care process involved manual paper-work, which wasted a lot of time since files had to be moved manually between departments including the laboratory, pharmacy, physician room, and finance. Besides, history taking and recording of vital signs took longer since the nurses had to record everything manually. However, with the introduction of electronic health records, history taking, recording of vital signs, and moving of patient information across departments became easier, which saves time and energy (Dhaya et al, 2019). Hence, patients are served within the shortest time possible. Additionally, electronic health records have reduced medical errors that usually occur due to errors in recording patient information, which consequently reduces healthcare costs (Dash et al., 2019). Due to the numerous benefits, big data should be adopted by all healthcare organizations.

   

  Challenges of Big Data

  Though bug data has been shown to improve care and patient outcomes, most healthcare organizations have challenges maintaining safety and confidentiality of patient information. This is attributed to the fact that systems can be hacked and patient data obtained, which not only compromises their confidentiality but also poses safety risks since the information can be used to blackmail them (Olaronke & Oluwaseun, 2016). Furthermore, data loss can be detrimental to the organization and some have faced legal implications due to information lost in cybercrime. Sometimes, the systems are complex and without adequate training, most employees might not be able to use the systems properly, which leads to incomplete information (Kumar et al.,2020). Besides, some systems may not be synched together for various departments, which might create confusion.

  Mitigations of Challenges

  One of the ways to address challenges posed by big data is to ensure sufficient data management. Since big data plays a critical role in the decision-making process, including managerial and clinical decisions, it is important to properly manage data to ensure and appropriate use of data. Security measures should be put in place to prevent hacking and related cybercrime activities. For example, institutions can put up a firewall, update systems, schedule back-up, educate employees on proper use of the system, and designate experts that would immediately resolve system anomalies. (Olaronke & Oluwaseun, 2016). Therefore, data management will reduce incidences of hacking, data loss, and virus attacks.

  Conclusion

  Bid data plays a critical role in healthcare since it improves patient care, patient outcomes, and experiences. It promotes easy, safe, and fast storage and retrieval of information. However, it faces challenges like hacking and other cybersecurity crimes, which has impact on the organization and patient. Therefore, proper mitigation should be put in place to ensure safety and confidentiality of patient information by reducing incidences of hacking.

  References

  Bora, D. J. (2019). Big data analytics in healthcare: A critical analysis. Big Data Analytics for Intelligent Healthcare Management, 43-57. https://doi.org/10.1016/b978-0-12-818146-1.00003-9Links to an external site.

  Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: Management, analysis and future prospects. Journal of Big Data, 6(1). https://doi.org/10.1186/s40537-019-0217-0Links to an external site.

  Dhaya, R., Devi, M., Kanthavel, R., & AlGarni, F. (2019). Big data analysis and management in healthcare. Data Science, 127-157. https://doi.org/10.1201/9780429263798-6Links to an external site.

  Kumar, A., Singh, K. K., Singh, K. K., Kumari, C., & Chakraborty, S. (2020). An analysis on future prospects of big data in healthcare. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3611503Links to an external site.

  Olaronke, I., & Oluwaseun, O. (2016). Big data in healthcare: Prospects, challenges and resolutions. 2016 Future Technologies Conference (FTC). https://doi.org/10.1109/ftc.2016.7821747Links to an external site.

   

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• Collapse SubdiscussionJames Mangrum

  James Mangrum

  Dec 28, 2022Dec 28, 2022 at 1:52pm

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  Big Data

  Big data and the Internet of Things (IOT) are two technological concepts that have revolutionized nearly every industry. In healthcare health information networking has streamlined sharing of healthcare information between providers increasing continuity of care. It has simplified the codification of diagnostic testing into the patient Electronic Health Record (EHR), and improved collaboration between department. All this information collected however is not structured and that which is not structured exists in an amalgamation of data that cannot be segregated or stored conventionally. This is referred to as Big Data (Batko & Ślęzak, 2022).

  Big Data offers a unique landscape for information collection whether for benefit or nefarious purposes. Healthcare is one of the areas of data generation where the generation of such data is incidental in the care of patients. Healthcare providers generate significant data and connect protected health information (PHI), but their primary concern is the care of the patient. This creates a risky model, where providers must be reminded to remain vigilant in the protection of PHI. State and federal laws protect patients from the release of PHI, but with Big Data, PHI can be created from data aggregation.

  Big data is also being touted as the forefront of medical research. The massive collection of healthcare data lends itself to medical research well. Increased sample size is often believed to increase the validity of research (Faber & Fonseca, 2014). However, over sized samples can be excessive and complicate and offer unforeseen variable. Studies also show that small data techniques may be more precise with improved health outcomes (Househ et al., 2017).

  One concept being discovered in the development of protection for Big Data is the Actor – Network Theory (ANT). The ANT postulates a all networks must not only consider the technological data that is being transferred but the operators of that system to adequately attempt to protect such data (Stachel & DeLaHaye, 2015).  This method of protection can be seen in intradepartmental trainings at the operator level. HIPAA in services and PHI trainings can help reorient the healthcare professional to consider the risks they pose by indiscriminately disposing or aggregating data.

   

   

  References:

  Batko, K., & Ślęzak, A. (2022). The use of Big Data Analytics in healthcare. Journal of big data, 9(1), 3. https://doi.org/10.1186/s40537-021-00553-4Links to an external site.

   

  Faber, J., & Fonseca, L. M. (2014). How sample size influences research outcomes. Dental press journal of orthodontics, 19(4), 27–29.

  https://doi.org/10.1590/2176-9451.19.4.027-029.eboLinks to an external site.

   

  Househ, M. S., Aldosari, B., Alanazi, A., Kushniruk, A. W., & Borycki, E. M. (2017). Big Data, Big Problems: A Healthcare Perspective. Studies in health

  technology and informatics, 238, 36–39.

   

  Stachel, R., & DeLaHaye, M. (2015). Security breaches in healthcare data: an application of the actor-network theory. Issues in Information Systems.

  16(2), 185-194.

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  • Collapse SubdiscussionAlicia Brooke Richardson

    Alicia Brooke Richardson

    Dec 29, 2022Dec 29, 2022 at 11:34am

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    James,

    Electronic health records have helped provide efficient and quality care to patients, thereby reducing medical errors and cost of care and improving patient outcomes (McGonigle & Mastrian, 2022). Electronic health records have made a big change in the way that healthcare is delivered. I can still remember when paper charting was the only way and EHRs were not even thought about. This is where big data came into play. There were so many errors in paper charts, and it was hard to find information quickly. This can be a barrier to assessing organizational performance and making a well-informed decision (Thews, 2016). Big data has many advantages but also a few downfalls but nothing like paper charting. One advantage paper charting did have was the protection of PHI. Where EHR with big data has the ability to be accessed by many and potentially hacked.  One of the ways to address challenges posed by big data is to ensure sufficient data management. Since big data plays a critical role in the decision-making process, including managerial and clinical decisions, it is important to properly manage data to ensure appropriate data use. This is something that was not thought of with paper charting. Big data has made so many changes to the ways one chart. Hopefully with big data and technology growth in the field of charting who knows what patient charts will look like in twenty years.

     

     

    McGonigle, D., & Mastrian, K.G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning.

    Thew, J. (2016). Big data means big potential, and challenges for nurse execs. Retrieved from https://www.healthleadermedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs

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    • Collapse SubdiscussionJames Mangrum

      James Mangrum

      Dec 30, 2022Dec 30, 2022 at 1:15am

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      Alicia,

      I cant agree with this more. The transition from paper charting to EHR has got to be one of the single biggest changes in the healthcare industry for a long time. I remember my early days of charting on carbon copy and bubble sheet. The ability to quickly access patient information via EHR and charting software is almost too easy. The ease of which this information could be incidentally spilled, and is, is a genuine problem that we are all both victim and perpetrator. Incidental exposure is amplified due to the massive amount of data that is collected (Veliz, 2019).

      I was also struck by the challenges of aggregation and deciphering of such data. Did you see the 5 V’s of Big Data. Veracity was the one I thought about when I think of all the loose information that cannot be reproduced and thus seems rather subjective. There is an ongoing discussion of whether EHR data is good enough for clinical practice decisions in broader scope (Reimerm & Madigan, 2019).

      References:

       

      Véliz C. (2019). Medical privacy and big data: A further reason in favour of public universal healthcare coverage. Philosophical Foundations of Medical Law. Oxford (UK): Oxford University Press,  https://www.ncbi.nlm.nih.gov/books/NBK550264/Links to an external site.

       

      Reimer, A., & Madigan, E. (2019). Veracity in big data: How good is good enough. Health Informatics Journal. 25(4). 1290-1298. https://10.1177/1460458217744369.

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  • Collapse SubdiscussionDeanna Linn Howe

    Deanna Linn Howe

    Dec 31, 2022Dec 31, 2022 at 11:03am

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    Hi James and all, 

    I appreciate your comments to this discussion. Healthcare facilities are faced with remarkable challenges when it comes to security, privacy, confidentiality and so on, therefore, patients as well as all employees must know that such information should not be shared. Many organizations require employees to attest to corporate compliance yearly, and the descriptions of fraudulent actions are described along with the penalties for committing these acts. However, employees still engage in such behaviors. How can nursing administrators encourage corporate security compliance? Thanks, Dr. Howe 

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• Collapse SubdiscussionYetunde Adeola Adewoyin

  Yetunde Adeola Adewoyin

  Dec 28, 2022Dec 28, 2022 at 6:05pm

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  MAIN POST

                                   Big Data Risk and Reward in Clinical Practice

  Big Data is a sensitive issue for the clinical system, for its availability can benefit medical and healthcare operations. Big data refers to a large complex data set that yields substantially more information when analyzed as a fully integrated data set as compared to the outputs achieved with smaller sets of the same data that are not integrated (Thew, 2016). The availability of healthcare data is growing exponentially as electronic health records, the use of wearable devices, social media and internet, and genomic information continue to expand (Gleason & Dennison, 2017). Electronic health records have helped in providing efficient and quality care to patients, thereby reducing medical errors as well as cost of care, and improving patient outcomes (McGonigle & Mastrian, 2022).

                         

                                   Benefits of Big Data

  Big data in the healthcare system improves operational efficiency. One promising breakthrough is the application of big data analytics. Big data analytics that is evolved from business intelligence and decision support system enable healthcare organizations to analyze an immense volume, variety and velocity of data across a wide range of healthcare networks to support evidence-based decision making and action taking (Wang, et al., 2018). Health care industry usually faces multiple challenges, ranging from management of new disease outbreaks to maintaining an optimal operational efficiency.

  The big data approach is essential in improving evidence-based healthcare decisions and patient’s outcomes (Wang et al., 2018). News database management systems such as MongoDB, MarkLogic and Apache Cassandra for data integration and retrieval, allow data being transferred between traditional and new operating systems. These big data analytics tools with sophisticated functionalities facilitate clinical information integration and provide fresh business insights to help healthcare organizations meet patient’s needs, and thus improve quality of care and financial performance. Big data contributes to healthcare processes by improving diagnosis, quality, and effectiveness of treatments, predicting the patient outcome, and improving pharmaco-vigilance and patient safety. Also, big data have a potential benefit of helping in identification and promptly intervening the effective ways of managing the high risk and high-cost data of patient responses (Bates et al., 2014).

                                     Challenges/Risks of Big Data

  Information integration is the key to success in big data analytics implementation. The challenges involved in the integration of information across systems and data sources within the healthcare system remain problematic in many instances.  Most healthcare organizations encounter difficulties in integrating data from legacy systems into big data analytics frameworks (Wang et al., 2018). The challenges of big data include time consumption, and lack of standard especially for the Nurse Executives. This can be a barrier to assessing organizational performance, and to make a well-informed decision (Thews, 2016). Nurses encounter a lot of pressure in processing data to provide evidence-based care, and to improve patient outcomes. In this vein, this leads to unmanageable and exhausting workflow (Clancy & Reed, n.d.)

                            Strategies to mitigate the Challenges/Risk of Big Data

                  It is important for nurses to be part of the decision-making process in developing new technology in every healthcare organization and give a well-informed decision and feedback on data processing and utilization (Thew, 2016). To create a strong data environment, there must be an established data governance for managing the availability, usability, integrity, and security of the organization’s data. The data governance support group is composed of technology, process improvement and clinical experts.

  These strategies include ;

  • Developing an information sharing culture: This is critical for reducing any resistance to new information management systems from physicians and nurses. Without an information sharing culture, data collection and delivery will be limited.
  • Training key personnel to use big data analytics: The key to utilize the outputs from big data analytics effectively is to equip managers and employees with relevant professional competencies, such critical thinking, and the skills of making appropriate interpretation of the results (Wang et al., 2018).

   

               References

  Bates, D.W., Saria, S., Ohno-Machado, L., Shah., A., & Escobar, G. (2014). Big data in health care: using analytics to identify and manage high risk and high-cost patients. Health Affairs, 33(7), 1123-1131.

  Clancy, T.R., & Reed, L. (n.d.). Big Data, Big Challenges Implications for Chief Nurse Executives. Journal of Nursing Administration, 46(3), 113-115, https://doi-org.ezp.waldenulibrary.org/10.1097/NNA.0000000000000307Links to an external site.

  Gleason, T., & Dennision, C.R. (2017). Big Data: Contributions, Limitations, and Implications for Cardiovascular Nurses. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5393269/Links to an external site.

  McGonigle, D., & Mastrian, K.G. (2022). Nursing informatics and the foundation of knowledge (5^th ed.). Jones & Bartlett Learning.

  Thew, J. (2016). Big data means big potential, challenges for nurse execs. Retrieved from https://www.healthleadermedia.com/nursing/big-data-means-big-potential-challenges-nurse-execsLinks to an external site.

  Wang, Y., Kung, L., & Byrd, T.A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting & Social Change, 126, 3-13. https://doi-org.ezp.waldenulibrary.org/10.1016/j.techfore.2015.12.019Links to an external site.

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  • Collapse SubdiscussionAlicia Brooke Richardson

    Alicia Brooke Richardson

    Dec 30, 2022Dec 30, 2022 at 9:12am

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    Yetunde Adeola Adewoyin,

    Big data is mainly collected from various healthcare systems and fields, such as medical devices, electronic health records (EHR), flowsheets, pharmaceutical research, and clinical trials (Dash et al., 2019). As part of healthcare organizations, nurses may also obtain big data from the internet, patient portals, public records, and other relevant healthcare fields. The major challenge of data fragmentation and lack of digitization uniformity is obstructed efficiency; the data fragmentation results in many small data being overlooked either because personnel did not record the data into the EHR or they were lost (Liang et al., 2018). This results in the unavailability of accurate data on many records impeding their credibility; hence challenging to apply such data in clinical stages. For example, in the US, the decentralization of various health facilities makes it difficult to obtain all the required data assuming facilities still operate manually. The data can easily get lost, or the machines to record them might not be available. Increasing the levels of digitization and data sharing in such areas by installing computers, new sharing systems, and training personnel will aid in curbing such challenges (Liang et al., 2018).

     

    References

    Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis, and future prospects. Journal of Big Data,6(1), 1-25.

    Liang, H., Luo, M., Wang, R., Lu, P., Lu, W., & Long, L. (2018). Big Data in health care: Applications and challenges. Data and Information Management,2(3), 175-197.http://dx.doi.org/10.2478/dim-2018-0014

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• Collapse SubdiscussionKyle Hickman

  Kyle Hickman

  Dec 28, 2022Dec 28, 2022 at 6:09pm

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  Big Data Benefits

  In healthcare, there are numerous areas where data is needed from xray, labs, primary care, and billing. One benefit to big data is that it can ensure continuity of care. Without aggregated data, or the different pieces of healthcare communicating with each other well, errors in billing can occur and continuity of care is interrupted (McGonigle & Mastrian, 2022). Continuity of care can be improved because patient information such as medication lists, medical history, and allergies can be updated just once for all pieces of healthcare. This can ensure that if there is an emergency and a patient is unable to communicate effectively, doctors and medical staff are able to treat the patient quickly (Tulane, 2021). It can also help different doctors and specialists prescribe medications or treatments that do not contraindicate one another. If a patients healthcare data was collected and centralized across the nation, no matter where they were to go, the medical staff could have access to necessary medical records.

  Risk of Big Data

  In Europe, there are various studies occurring about big data in healthcare. In general, it has been found to be helpful in improving performance and outcomes in healthcare (Pastorino, 2019). However, there are certain disadvantages to big data. One example is that the accuracy will remain in the patient updating information in a timely matter. If the patient does not desire to work with the system, they would not be added to it and could not receive the extra benefits. Another problem is that having big data requires cooperation with many different parties and interests (Pastorino, 2019). These conflicting parties could cause problems with having an effective aggregation of the data and what to do with it. Some parts could want to sell the information to marketing companies for example. Aggregating the data could cause problems with storage and obtaining that information also.

  Big Data Solution

  One solution to the multiple parties competing for differing interests could be to have multiple companies encouraged to compete and also cooperate and share information. This would keep costs for healthcare companies lower and also encourage companies to create better and better products. As these products are continually improving, the next step would be to share the data with each other to help with continuity of care for the patients. In my rural area, we just switched to EPIC and ended up “piggy backing” from the EPIC version of a larger hospital group in the state. Through our EHR system we are able to access the records from the larger hospital group which helps to see the results and data from the specialist groups patients are referred to. This has helped us to improve our patient care and to help with continuity of care for our patients.

  References

  McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning

  Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019). Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. European journal of public health, 29(Supplement_3), 23–27. https://doi.org/10.1093/eurpub/ckz168

  Tulane University. (2021, July 7). How Big Data in Health Care Influences Patient Outcomes. Retrieved December 28, 2022, from https://publichealth.tulane.edu/blog/big-data-in-healthcare/

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