Discussion - Week 5
Big Data Risks and Rewards
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.
To Prepare:
- Review the Resources and reflect on the web article Big Data Means Big Potential, Challenges for Nurse Execs.
- Reflect on your own experience with complex health information access and management and consider potential challenges and risks you may have experienced or observed.
By Day 3 of Week 5
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.
By Day 6 of Week 5
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.
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5 months ago
Robin Moyers WALDEN INSTRUCTOR MANAGER
RE: Discussion - Week 5
Class:
Welcome to week 5 Module 3. Don't forget to submit your main post by 11:59 pm MT Wednesday and respond to two posts on two more dates by Saturday night. Make sure to post three separate days (dates) out of the week. If you don't know how to see the date of your post, hover over the time stamp and the date and time will appear. Remember, post on three different dates out of the week---regardless of your individual time zone.
Also, make sure to include at least three references in your main post and at least two references in each participation post.
Dr. Moyers
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5 months ago
Kirsi Hoselton
RE: Discussion - Week 5
Week 5 Discussion
Transforming Nursing and Healthcare Through Technology
Initial Post
Data is essential to implementing clinical decisions to configure critical objective information. After reviewing the article “ Using data in nursing practice,” the author referred that the implementation of practice decisions influenced patient care (Glassman, 2017). Therefore, as a nurse, it is essential to have the knowledge to access specific data and understand how to interpret the data (Glassman, 2017). Increased amounts of data stored and collected regularly are known as “ Big Data” ( McGonigle & Mastrian, 2022).
Benefits of using Big Data
One beneficial aspect of implementing data into everyday practice as a health professional can reduce healthcare costs. Implementing big data systems is exhibited through various ways by making essential changes with identifying and discovering new treatments and incorporating changes to delivery care (Adibuzzaman et al., 2018). These changes can be identified by preventing medical and medication errors, triaging patients, implementing interventions to reduce emergency room visits, practicing preventative care to reduce hospital readmissions, and reducing health care costs (Adibuzzaman et al., 2018). Extensive data analysis can provide clinical insight to healthcare professionals to increase positive clinical decisions by enhancing patient care, lowering costs, and eliminating unnecessary treatment.
Potential Risks of using Big Data
Electronic health records (EHR) include pertinent and private information about the patient, such as; identification data, past and current medical conditions or diagnosis, and healthcare professional documentation. EHR provides sensitive healthcare data, which provides concerns related to privacy and security due to the potential of data leaking. Therefore, there may be consequences related to discrimination or the injury of others (Peters & Buntrock, 2014). For example, insurance companies may deny healthcare coverage due to a patient’s specific diagnosis. Most concerning is that data may leak, and information could fall into the wrong hands.
Strategy to mitigate challenges of using Big Data
One strategy that could efficiently mitigate the security and privacy risks of implementing big data is the Health Insurance Portability and Accountability Act (HIPPA). HIPPA was a law created in 1996 (Claiff & Muhlbaier, 2003). The purpose of HIPPA is to protect personal health information, which is a federal law (Claiff & Mahlbaier, 2003). The security and privacy laws protect patient information. Therefore, as healthcare professionals, it is essential to practice to protect data from being leaked.
Conclusion
Big data is essential for healthcare professionals to provide safe patient care. However, when using data can provide challenges and risks that can become threatening towards patients. Therefore, as healthcare professionals, it is crucial to know what big data is, how to implement it, interpret data and make sure it remains protective.
References
Adibuzzaman, M., Delaurentis, P., Hill, J., & Benneyworth, B. (2018, April 16). Big data in healthcare– the promises, challenges and https://scholarworks.iupui.edu/handle/1805/17886.
Califf, R. M., Muhlbaier, H. (2003, August 26). Health insurance portability and accountability act (HIPAA). Circulation. https://www.ahajournals.org/doi/full/10.1161/01.cir.0000085720.65685.90.
Glassman, K. S. (2017, November). Using data in nursing practice. https://www.myamericannurse.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf.
Peters, S., & Buntrock, J. (2014, September). Big data and the electronic health record: The Journal of ambulatory care management. Big Data and the Electronic Health Record. Retrieved September 28, 2021, from https://journals.lww.com/ambulatorycaremanagement/Abstract/2014/07000/Big_Data_and_the_Electronic_Health_Record.4.aspx.
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5 months ago
Robin Moyers WALDEN INSTRUCTOR MANAGER
RE: Discussion - Week 5
5 months ago
Kirsi Hoselton
RE: Discussion - Week 5
5 months ago
Tina Alino
RE: Discussion - Week 5
5 months ago
Tiffany Turner
RE: Discussion - Week 5
5 months ago
Chaquita Nichols
RE: Discussion - Week 5
I agree with you. If healthcare facilities want to reap the benefits completely, they would need to employ a data analyst or informatics nurse. Informatic nurses are gaining the knowledge to assist in coming up with a system that would be beneficial to these healthcare facilities. “Today, nurses have the option to pursue specialization and credentials at a variety of levels including graduate specialization and specialty certification. Nurses have pursued these opportunities recognizing the necessity of informatics knowledge and skills now and particularly into the future, as face an increasingly connected world of digital healthcare. To a large extent, the core competencies of the nursing informatics specialist have become essential for all nurses and expectations of the specialist role will continue to evolve even further” (Nagle & Junger, 2017). “In today’s high-tech world, expectations of the healthcare industry are that nurses will have informatics competencies including project management skills which are crucial for improved quality outcomes and safety for patients. NI supports nurses, consumers, patients, the interprofessional healthcare team, and other stakeholders in their decision-making in all roles and settings to achieve the desired outcome” (Sipes, C., 2016).
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5 months ago
salome ugwu
RE: Discussion - Week 5
Kirsi
Incredible post including all the details of big data and the data analytics. As you mentioned, there are several benefits on using big data, it allows the health care organizations to turn raw data into relevant trends, predictions, and projections with unprecedented accuracy. Some of the big data analytics include; identifying the root causes of failures and issues in real time, fully understanding the potential of data driven that helps for patient support, improving collaboration and increase quality of patient services. Big data analysis helps to improve the effectiveness of patient report, assessment which in turn improves the whole hospital setting.
References
Lee, C. H., & Yoon, H. J. (2017). Medical big data: promise and challenges. Kidney research and clinical practice, 36(1), 3–11. doi:10.23876/j.krcp.2017.36.1.3
Vayena, E., Dzenowagis, J., Brownstein, J. S., & Sheikh, A. (2018). Policy implications of big data in the health sector. Bulletin of the World Health Organization, 96(1), 66–68. doi:10.2471/BLT.17.197426
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5 months ago
Ivo Ngosong
RE: Discussion - Week 5
5 months ago
Kene Fall
RE: Discussion - Week 5
Hello Kirsi, great post! I agree that “one beneficial aspect of implementing data into everyday practice as a health professional can reduce healthcare costs” (Hoselton, K., 2021). Data scientists use software and analytical tools to analyze and predict patterns in massive amounts of data to improve the quality of care (Glassman, K. S.2017). According to Adibuzzaman et al., 2018, Big data systems improve the efficiency and effectiveness of healthcare delivery. Therefore, accurately understanding and interpreting data can help nurses make informed decisions regarding patient care to improve the quality of care.
References
Adibuzzaman, M., Delaurentis, P., Hill, J., & Benneyworth, B. (2018, April 16). Big data in healthcare– the promises, challenges and https://scholarworks.iupui.edu/handle/1805/17886.
Glassman, K. S. (2017, November). Using data in nursing practice. https://www.myamericannurse.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf.
Hoselton, K. (2021, September 29). Discussion-Week 5. Big Data Risks and Rewards. Retrieve from: https://class.waldenu.edu/webapps/discussionboard/do/message?action=list_messages&course_id=_16878521_1&nav=discussion_board_entry&conf_id=_4070104_1&forum_id=_9382264_1&message_id=_120375874_1
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5 months ago
Sophie Enjema Ndumbe
RE: Discussion - Week 5
Hello Krisi,
Great post, I agree with you that nurses should know how to access and interpret data. When nurses have knowledge in technology and know how to interpret data, it will be very easily for them especially when they have a critical situation at work. We encounter a lot of challenges when we work with big data especially when we work with people who are incompetent, they make the job very difficult for us. Warm et al. (2009) States “all healthcare professionals should be offered a health informatics curriculum as part of their continuing professional development” (p.72). Big data makes it easy for us to solve complex problems since we meet with people who have knowledge in specific area of technology. Through Information technology we use specific data, software, knowledge and evidence based practice to solve problems and provide care to patients (Laureate Education, 2012).
References
Laureate Education (Executive producer). (2012). Data, information, knowledge, and Wisdom continuum [ Multimedia file] Baltimore, MD: Author. Retrieved http://mym.cdn.laureatemedia.com/2dett4d/Walden/NURS/6051/03/mm/continuum/index.html
Warm DL, Thomas SE, Heard VR, Jones VJ, & Hawkins-Brown TM. (2009). Benefits of information technology training to National Health Service staff in Wales. Learning in Health & Social Care, 8(1), 70–80.
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5 months ago
Amy Birkenstamm
RE: Discussion - Week 5
Hi Kirsi,
I think that big data is essential for health care professionals to remain organized, systematic and well equipped within an organization. As organizations grow, thinking outside of the box to better improve communication in a central location, such as in a database, can be beneficial. The application of Big Data in health care is already providing solutions for bettering patient care and generating value in health care companies (Pastorino et al., 2019). Proper staffing management and oversight of the system is also imperative in order to protect patient confidentiality. This leads into adequate ongoing training opportunities to keep all systems cohesive and working properly.
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.
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5 months ago
Miguel Rodrigo Estrera
RE: Discussion - Week 5: Initial Post
Big Data Risks and Rewards
Benefits of using Big Data
Big Data is an interdisciplinary field that necessitates the collaboration of researchers from various disciplines and the participation of researchers with a variety of skills to carry out initiatives that fully exploit the methodological innovations that Big Data is bringing to the academic setting. By using a predictive model and real-time analytics, big data analytics can improve the efficiency of the decision-making process in healthcare organizations by improving the collection, management, and integration of data (M, Favaretto, De Clercq, Schneble, & Elger, 2020).
Potential challenge or risk of using Big Data
However, despite the advancements in information technology, there were still difficulties. A variety of issues, including poorly designed information systems and workflow, compatibility across interfaces with the electronic health record (EHR), and a lack of standardized vocabulary used in nursing documentation, contribute to this situation (Thomas & Reed, Laura , 2016).
Strategy to mitigate challenges of using Big Data
To achieve this goal, one method is to draw on the knowledge of nurse informaticists to engage with clinical nurses, information systems professionals, and electronic health record (EHR) suppliers to construct data models that depict the influence of nursing on quality improvement. (Thomas & Reed, Laura , 2016) Another strategy is for the organization to further educate and develop Informatics competency among nurses to improve Informatics skills. Nursing leaders must learn and apply informatics competencies to be empowered and make meaningful contributions toward a future healthcare vision. They must also mitigate current challenges related to digital health solutions and advocate for and advance digital health that promotes the quadruple aim of healthcare (Lo, Bryan, et al., 2021).
References
Lo, Bryan, Nagle, Lynn, White, Peggy, Kleib, Manal, Kennedy, Margaret, & Strudwick, Gillian. (2021, May). Digital and informatics competencies: Requirements for nursing leaders in Canada. SAGE Premier. doi:https://doi-org.ezp.waldenulibrary.org/10.1177/08404704211015428
M, F., Favaretto, M., De Clercq, E., Schneble, C., & Elger, B. (2020, February). What is your definition of Big Data? Researchers’ understanding of the phenomenon of the decade. PloS One, 15(2). doi:https://doi-org.ezp.waldenulibrary.org/10.1371/journal.pone.0228987
Thomas, C., & Reed, Laura . (2016). Big Data, Big Challenges: Implications for Chief Nurse Executives. JONA, 46(3), 113-115. doi:DOI: 10.1097/NNA.0000000000000307
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5 months ago
Robin Moyers WALDEN INSTRUCTOR MANAGER
RE: Discussion - Week 5: Initial Post
Thank you Miguel. Your post leads me to a question...
Class:
If given the opportunity, how would you standardized big data in health care?
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5 months ago
Miguel Rodrigo Estrera
RE: Discussion - Week 5: Initial Post
Hello Dr. Moyer, Thank you for responding to my post. Data standardization in electronic health records (EHRs) is critical for clinical practice and retrospective research in clinical and research settings. However, due to nonidentical duplication, typographical errors, and variations in EHR data, it is still challenging to standardize this information. The goal of standardization is to eliminate these disadvantages by collecting information in a standard format and curating the information held in electronic health records (EHRs), among other things (Kim, Shin, Soo-Yong, Kang, Mira, Yi, Byoung-Kee, & Chang, Dong Kyung, 2019). Communication of nursing data across organizations and electronic health records is critical for enhancing care coordination and achieving higher quality results. Nursing can assist clinical users and improve patient care by providing information models that reflect the best evidence and clinical expertise related to national terminology standards (Chow, Marilyn, et al., 2015).
To standardize data, I would assemble a project team comprised of several stakeholders, including the Nursing Department, Nursing Informatics, Information Technology, Medical Doctors, and Quality Management. The team will create a standardized nursing information model for a nursing-sensitive quality indicator, record the process as a repeatable technique, and show an interoperability strategy for data sharing between sizeable integrated health delivery networks (Chow, Marilyn, et al., 2015).
References
Chow, Marilyn, Beene, Murielle, O'Brien, Ann, Greim, Patricia, Cromwell, Tim, DuLong, Donna, & Bedecarre, Diane. (2015, March). A nursing information model process for interoperability. Journal of the American Medical Informatics Association, 22(3), 608-614. doi:https://doi-org.ezp.waldenulibrary.org/10.1093/jamia/ocu026
Kim, M., Shin, Soo-Yong, Kang, Mira, Yi, Byoung-Kee, & Chang, Dong Kyung. (2019). Developing a Standardization Algorithm for Categorical Laboratory Tests for Clinical Big Data Research: Retrospective Study. Journal of Medical Internet Research, 21(8). doi:10.2196/14083
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5 months ago
Dorothy Chudi-Agbaku
RE: Discussion - Week 5: Initial Post
Hi Miguel,
Good post. In addition to other challenges facing the use of big data as part of a clinical system, I would like to add one. Nursing is one profession that stay with patients more and generate more data than any other profession and as a result, should have access and ability to interpret data concerning patients and their care in order to be able to make informed decisions in practice (Glassman, 2017). As beneficial as the use of big data may be in the clinical settings, it is unfortunate that data entered into the electronic health records (EHRs) by the nurses are not standardized and as a result cannot be analyzed and are not interoperable across organizations and EHRs (Keenan, 2014). Keenan stated that many organizations assemble and tailor their EHRs to meet their unique needs and this has made the data not to be defined, measurable, and retrievable in the same format. This compromises the ability to compare data collected across organizations which is necessary for creating big data that can be used for research. Vendors often tell customers of their ability to build systems that will create interoperable nursing data but always failed to do so. Therefore, in order to mitigate this challenge, the nursing leaders must ensure that the vendors clearly show that there is interoperability of nursing data and that the data can be merged and analyzed with the same nursing data across organizations and EHRs (Keenan, 2014).
Dorothy.
References
Glassman, K. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45-57. https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf
Keenan, G. (2014). Big Data in healthcare: An urgent mandate to change nursing EHRs! Online Journal of Nursing Informatics, 18(1). https://doi.org/ojni.org/issues/?p=3081
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5 months ago
Tanaka Ruzvidzo
RE: Discussion - Week 5: Response # 2
Dear Miguel, I enjoyed reading your discussion post. I would like to add that one of the challenges of managing big data is that communication amongst stakeholders is key and should be done on a constant basis in order to maximize the benefits of big data. Pastorino et al., (2019) reported that “Achieving effective and proportionate governance of health-related data will be essential for the future healthcare systems, and it requires that stakeholders collaborate and adapt the design and performance of their systems to reach the maximum innovative potential of information and innovation technology on health” (Pastorino et al., 2019, p. 26).
Big data adds value to any organization, but challenges are to be expected. You mentioned several challenges and the strategies to mitigate them in your discussion post. It is important for organizations to overcome these so that they can realize the benefits of big data which may be exponential. “Considering the huge benefits of big data, it is imperative to identify the challenges and resolve them accurately. It is expected that with modern technologies, all the barriers can be removed in near future and big data analytics tools, utilizing artificial intelligence, will be able to offer the best possible strategies based on social and individual conditions” (Ayani et al., 2019, p. 60).
References
Ayani, S., Moulaei, K., Darwish Khanehsari, S., Jahanbakhsh, M., & Sadeghi, F. (2019). A Systematic Review of Big Data Potential to Make Synergies between Sciences for Achieving Sustainable Health: Challenges and Solutions. Applied Medical Informatics, 41(2), 53–64.
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
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5 months ago
Sophie Enjema Ndumbe
RE: Discussion - Week 5: Initial Post
Hello Miguel,
Great post, in big data there is collaboration among different people to achieve a common goal. Big data is very complex and thus people who work with big data need to be experts in their various areas of specialization. When people cannot perform their jobs well then, they start having failures and the company will start losing customers in the end the company might fail for not functioning properly. Managing big data is very challenging especially when people lack knowledge and understanding of the system, it become difficult to hire individuals. The shortage of big data scientists makes it very difficult for institutions or healthcare facilities which uses big data to meet their needs (Dolezal, & McLeod, 2019).
I agree with you that when the program is not designed well then it poses a risk to the company. This will be a big challenge; people might start using fraud or scamming the system. According to Collins (2016) another challenge in big data, is that it cost a lot of money to run the system which is extremely broad.
References
Collins, B. (2016). Big Data and health economics: Strengths, weaknesses, opportunities, and threats. Pharmacoeconomics, 34(2), 101–106. https://doi-org/ 10.1007/s40273-015-0306-7
Dolezel, D., & McLeod, A. (2019). Dolezel, D., & McLeod, A. (2019). Big Data Analytics in Healthcare: Investigating the Diffusion of Innovation. Perspectives in Health Information Management, 1–19.
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5 months ago
salome ugwu
RE: Discussion - Week 5: Initial Post
Hi Miguel
Very informative post. There are some challenges when it comes to Big Data and health-care. In addition to the ones you listed, a challenge is data security (Chandra, Ray, Goswami, 2017). Even when a facility has security practices in place to protect patient information, when sharing of patient information via the cloud with other facilities where those practices are not in place puts patient information at risk. A solution is that HIPPA regulations can catch up to the current trend in health-care and produce data safety guidelines Big Data and for all organizations that contributing and sharing patient information (Chandra, Ray, Goswami, 2017).
The general purpose of Big Data in the healthcare domain is to analyze, identify and solve medical problems before they come to represent serious problems (Alexandru, Radu, Bizon, 2018). Big Data makes the healthcare more efficient (Alexandru, Radu, Bizon, 2018). . In health care large amounts of data is produced daily which can ultimately lead to many great things, but can also expose many points of failure (Alexandru, Radu, Bizon, 2018). When we get to a point when we can reach the full or even a more optimal potential with big Data while providing data security, we can some cool and life saving things on a grand scale.
I was intrigued when you mentioned the patient portals for providers to see patients. This will lead to less people unnecessarily hospitalized and those saved costs of occupying a hospital bed can lead to resources available for the community, especially the under-served.
References
Chandra, S., Ray, S., Goswami, R.T. (2017). Big Data Security in Healthcare: Survey on Frameworks and Algorithms. IEEE. https://ieeexplore-ieee-org.ezp.waldenulibrary.org/document/7976767?arnumber=7976767&SID=EBSCO:edseee
Alexandru, A.G., Radu, I.M., Bizon, M.L. (2018).Big Data in Healthcare - Opportunities and Challenges. Informatica Economică 22(2) . Retrieved from https://eds-b-ebscohost-com.ezp.waldenulibrary.org/eds/pdfviewer/pdfviewer?vid=6&sid=b2ec24d5-3d2a-48ed-9b65-09a218e2d9d1%40pdc-v-sessmgr01
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5 months ago
Mercy Ambe Mbu
RE: Discussion - Week 5: Initial Post
Hi Miguel,
Great and insightful post. I enjoyed reading your discussion. I agree with you that one of the challenges with the use of data is standardization. The advancement of technology has allowed the availability of increasing scale, scope, variety, and complexity of digitalized health data. According to De Groot, De Veer, Paans, and Francke (2020), standardized terminologies facilitate the nursing process, promote accurately formulation of patients' care needs, and plan concrete interventions. Analyzing these data might become challenging due to extensive variation. Consolidating data requires characteristics of the data to resemble each other.
Organizations like the American Nurses Association (ANA), through its Committee for Nursing Practice Information Infrastructure (NPII), have formulated terminologies that provided a framework for the uniform collection and management of nursing data (McGonile & Mastrian, 2017). These terminologies provide opportunities for consistency and easy recognition of nursing data, facilitate communication, easy measurement of outcomes, and better interpretation of outcomes. Examples of recognized terminologies to support nursing practice are the North American Nursing Diagnosis Association (NANDA), Omaha system, Nursing Management minimum data set (NMMDS), ABC codes 2000, etc. Utilization of existing terminology systems and continuous improvement of these systems will enhance data analyses and easy use for decision-making.
References
De Groot, K., De Veer, A. J. E., Paans, W., & Francke, A. L. (2020). Use of electronic health records and standardized terminologies: A nationwide survey of nursing staff experiences. International Journal of Nursing Studies, 104. https://www-sciencedirect-com.ezp.waldenulibrary.org/science/article/pii/S0020748920300080
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Jones & Bartlett Learning.
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5 months ago
Ivo Ngosong
RE: Discussion - Week 5: Initial Post
Miguel, thank you for your input. I agree that nurse informaticists' ability to communicate with clinical nurses, information systems experts, and electronic health records (EHR) is beneficial (Thomas & Reed, Laura , 2016). Patients may use informatics to give important information to their clinicians and to share that knowledge with family, friends, and other patients. Patients may be able to exercise more influence over their medical treatment with this knowledge. This is a critical job in the healthcare industry. While this is a behind-the-scenes job, these healthcare workers help patients by organizing, storing, and managing health data via electronic health records (EHR). Healthcare systems and people who deal with them have grown even more essential in today's age of big data. Healthcare professionals have simpler access to patient information when they use these systems, which may assist physicians and nurses arrive at faster solutions and results. These healthcare experts also interact with politicians and IT professionals, serving as a link between the two sectors. Overall, their understanding of people, medicine, and health information technology makes them a valuable asset in hospitals (M, Favaretto, De Clercq, Schneble, & Elger, 2020).
M, F., Favaretto, M., De Clercq, E., Schneble, C., & Elger, B. (2020, February). What is your definition of Big Data? Researchers’ understanding of the phenomenon of the decade. PloS One, 15(2). doi:https://doi-org.ezp.waldenulibrary.org/10.1371/journal.pone.0228987
Thomas, C., & Reed, Laura . (2016). Big Data, Big Challenges: Implications for Chief Nurse Executives. JONA, 46(3), 113-115. doi:DOI: 10.1097/NNA.0000000000000307
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5 months ago
Amy Birkenstamm
RE: Discussion - Week 5: Initial Post
Miguel,
Great post and enjoyed seeing your direct approach and discussion on both the risks and rewards of utilizing big data technology within medical practices. Big data "typically 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," according to the Online Journal of Nursing Informatics (Thew, 2016). Since nursing led the charge in the effort to connect quality and safety in their practices, evidence-based practice, informatics, and quality improvement became essential. Nurses were the pillar of development of the Quality and Safety Education for Nurses (QSEN) Institute, which has defined the essential knowledge, skills, and attitudes that ensure all new RN's and APRN's are prepared to participate in healthcare teams to improve quality and patient safety (Glassman, 2017). In my opinion, if all team members of the organization/practice is on board with all the required standards, the use of nursing data and technology can be extremely efficient without sacrificing quality and safety of patient care.
References
Big Data Means Big Potential, Challenges for Nurse Execs. (2016, April 19). HealthLeaders. https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
Glassman, K. (2017, November). Using data in nursing practice. Practice Matters. https://www.myamericannurse.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf
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5 months ago
Kene Fall
RE: Discussion - Week 5: Initial Post
Hello Miguel. Great post! Big Data refers to the vast volume of data generated by various sources. Its rapid growth and complexity make it an attractive opportunity for developers (Thomas, C. et al., 2016). However, some challenges arise when it comes to using Big Data. One of the fundamental challenges of using Big Data is to utilize electronic health record data (EHR) correctly. According to the article of Glassman (2017), HITECH is a program that aims to enable providers to use electronic health record data to improve the care of their patients.
Glassman, K. S. (2017, November). Using data in nursing practice. https://www.myamericannurse.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf.
Thomas, C., & Reed, Laura . (2016). Big Data, Big Challenges: Implications for Chief Nurse Executives. JONA, 46(3), 113-115. doi:DOI: 10.1097/NNA.0000000000000307
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5 months ago
Jessica Ferrin
RE: Discussion - Week 5
Healthcare organizations can make evidence-based decisions by analyzing big data (Wang et al., 2018). Sorting through data to make patient-centered decisions can be overwhelming for healthcare leaders. However, using the information to support change improves patient care.
Thew (2016) interviewed chief nursing executive (CNE) Jane Englebright. Englebright states it can be frustrating looking at data whose missing variables are the ones we care most about (Thew, 2016). For example, as a nursing leader, I was held accountable to remain productive in staffing my department. The company had set staffing grids we were instructed to stay compliant with to keep our productivity within an acceptable percentage. Open position requisitions would get denied if we did not meet our targets whether we needed the position filled or not. One missing variable from a staffing grid is the acuity of the patient load. As a manager and even a bedside nurse, acuity and ratio were the two factors I care most about. The unit is a surgical step-down unit, also considered an intermediate intensive care unit (IICU), and we care for post-open heart surgical patients and various other cardiovascular patients. Unfortunately, patients who remained on the unit past midnight, considered "under observation" or "outpatient in a bed," did not count into our productivity numbers. We could have six patients out of 14 with either bed status; therefore, the data suggested we should only have two nurses on shift. The acuity level was never taken into consideration of the productivity percentage, and I constantly had to justify my need for three nurses on shift for a census of 14.
In an article by O’Keeffe (2016), an acuity tool was implemented to optimize nursing care. The acuity tool could be used at my facility as data collection over a period of time to have valuable information to dispute set nursing grids. Nursing documentation in the electronic health record (EHR) is sent automatically to the acuity tool (O’Keeffe, 2016). Having the ability to advocate for safe patient ratios using big data will promote a safe working environment for nurses.
References
O'Keeffe, M. (2016, April 7). Acuity-adjusted staffing: A proven strategy to optimize patient care. American Nurse. Retrieved from https://www.myamericannurse.com/acuity-adjusted-staffing-proven-strategy-optimize-patient-care/
Thew, K. (2016, April 19). Big data means big potential, challenges for nurse execs. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
Wang, Y., Kung, L., & Byrd , T. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technology Forecasting and Social Change, 126(1), 3-13.
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5 months ago
Robin Moyers WALDEN INSTRUCTOR MANAGER
RE: Discussion - Week 5
Good insights Jessica. Big data can be used beyond clinical use.
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5 months ago
Kirsi Hoselton
RE: Discussion - Week 5
Jessica,
Thank you for sharing. I enjoyed reading your post about the acuity tool. It sounds like a great tool to implement into nursing practice to assist with data collection.
Data is essential to implementing clinical decisions to configure critical objective information. After reviewing the article “ Using data in nursing practice,” the author referred that the implementation of practice decisions influenced patient care (Glassman, 2017). Therefore, as a nurse, it is essential to have the knowledge to access specific data and understand how to interpret the data (Glassman, 2017). Increased amounts of data stored and collected regularly are known as “ Big Data” ( McGonigle & Mastrian, 2022).
One strategy that could efficiently mitigate the security and privacy risks of implementing big data is the Health Insurance Portability and Accountability Act (HIPPA). HIPPA was a law created in 1996 (Claiff & Muhlbaier, 2003). The purpose of HIPPA is to protect personal health information, which is a federal law (Claiff & Mahlbaier, 2003). The security and privacy laws protect patient information. Therefore, as healthcare professionals, it is essential to practice to protect data from being leaked. Big data is essential for healthcare professionals to provide safe patient care. However, when using data can provide challenges and risks that can become threatening towards patients.
References
Califf, R. M., Muhlbaier, H. (2003, August 26). Health insurance portability and accountability act (HIPAA). Circulation. https://www.ahajournals.org/doi/full/10.1161/01.cir.0000085720.65685.90.
Glassman, K. S. (2017, November). Using data in nursing practice. https://www.myamericannurse.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf.
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5 months ago
Tanaka Ruzvidzo
RE: Discussion - Week 5 - 1st Response
Dear Jessica, thank you for your post that has led me to do further research on big data. I found it interesting to note that artificial intelligence is being used in many sectors daily, thanks to big data and this has improved the quality of people's lives all over the world. According to Yang et al. (2021), “Artificial intelligence approaches are commonly presented in many applications using big data, which consists of all relevant data about the medical health and diseases which a model can access at the time of execution or diagnosis of diseases” (Yang et al., 2021, p. 1). This has resulted in added value and provision of quality health care.
There are still barriers to the use of big data and the healthcare industry seems to be lagging compared to other industries. Since the use of big data has the potential to improve patient care and at the same time lower costs, it is a win-win situation. To help overcome some of the challenges it is recommended that “to truly transform care so that it is delivered in a way that is sustainable, responsible, and patient-centered, health systems need to act on these opportunities, invest in big data, and routinely use these data in the delivery of care” (Jones et al., 2018, p. 435).
Without a sense of urgency, responsibility, or vision to recognize missed opportunities, healthcare organizations will continue to fall behind other industries and ultimately become obsolete.
References
Jones, L. K., Pulk, R., Gionfriddo, M. R., Evans, M. A., & Parry, D. (2018). Utilizing big data to provide better health at lower cost. American Journal of Health-System Pharmacy, 75(7), 427-435. https://doi.org/10.2146/ajhp170350
Yang, Y. C., Islam, S. U., Noor, A., Khan, S., Afsar, W., & Nazir, S. (2021). Influential usage of big data and artificial intelligence in healthcare. Computational and Mathematical Methods in Medicine, 2021, 1-13. https://doi.org/10.1155/2021/5812499
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5 months ago
salome ugwu
RE: Discussion - Week 5
Thanks for the informative post. I do agree with you that big data is highly useful in healthcare as it can be analyzed to develop critical insights that can be used to inform and improve healthcare. Dimitro (2016) explains that organizations today are surrounded by large external and internal datasets that can be computationally analyzed to outset any associations, trends, and patterns relevant to a healthcare problem in question. Various technologies have been developed over the decades, with the aim to obtain relevant knowledge. These technologies often rely on various algorithms (Wang, Kung & Byrd, 2018). A negative drawback of big data is that it requires high computational knowledge, which in turn necessitates the understanding of the full potential of the system may offer. This can potentially result in increased healthcare costs, which are directly or indirectly passed to the patients.
References
Dimitrov, D. V. (2016). Medical internet of things and big data in healthcare. Healthcare informatics research, 22(3), 156-163.
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, 3-13.
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5 months ago
April Ward
RE: Discussion - Week 5
Discussion Response #2
Hello Jessica,
Your discussion post seemed similar to mine, in that we both are focused on data to show our productivity in our patient-centered work. Maintaining productivity can be challenging at times, no matter which area of health care we work in. According to Wang, Kung & Byrd (2018), increasing productivity can be achieved by using big data.
We must all identify the problems that interfere with our productivity in health care. McGonigle & Mastrian (2018) say that data mining is a logical process of using data to predict trends. By predicting trends, we may be able to better define the problem, which will aid us in better caring for our patients.
References
McGonigle, D., & Mastrian, K. G. (2018). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.
Wang, Y., Kung, L., & Byrd, T. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technology Forecasting and Social Change, 126(1), 3-13.
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5 months ago
Tiffany Turner
RE: Discussion - Week 5
Hi Jessica, I agree with your statement regarding healthcare facilities leaders being overwhelmed by the data surrounding patient centered care. It is my belief that the healthcare leaders would be less overwhelmed and would better utilize their data if they would hire Informatics nurses and data analyst. Hiring said personnel would better utilize their data and improve patient outcomes for the facilities who has not specifically hired said personnel (Schoenbaum, 2020). Studies have shown that there is a significant improvement in patient care when informatics nurses are involved (Brennan, et al., 2013). Thanks for your post it was quite interesting.
References
Brennan, C. W., Daly, B. J., & Jones, K. R. (2013). State of the science. Western Journal of Nursing Research, 35(6), 760–794. https://doi.org/10.1177/0193945913476577
Schoenbaum, A. E. (2020, September 30). Nursing informatics key role in defining clinical workflow, increasing efficiency and improving quality. HIMSS. https://www.himss.org/resources/nursing-informatics-key-role-defining-clinical-workflow-increasing-efficiency-and
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