Discussion: Big Data Risks and Rewards
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 Discussion: Big Data Risks and Rewards.
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.
10 months ago
Iyabo Osidele
RE: Discussion – Week 5
One potential benefit of using big data as part of a clinical system
What is big data? “Big data” refers to the massive amounts of data generated by the digitization of everything that can be consolidated and analyzed using certain technology. Electronic health records (EHRs), medical imaging, genomic sequencing, payment or records, pharmaceutical research, wearables, and medical gadgets are among the data sources. The use of health care data analytics offers a number of positive and even life-saving implications. Big Data spans all of these areas in the healthcare industry, as it is widely used by both the public and private sectors (Walter, 2019). It is also referred to as all the data generated as a result of interactions between stakeholders and health care systems. They’re data from medical devices, pharmaceutical research, municipal records, genomic sequencing, medical imaging, and electronic health records, to name a few sources. Public records, search engines, smart phones, government agencies, patient portals, and research initiatives are all sources of big data (Tavazzi, 2019). There is a lot of benefit in using big data as part of a clinician system, of which I will discuss one. Benefits include improved patient healthcare, error reduction and precise treatments, lower overall healthcare costs, more accurate diagnoses and treatment, system advancements, improved management and administration, and increased accessibility to healthcare services (Walter, 2019).The potential benefit is that it helps to improve patient healthcare. That is, big data provides higher clinical insights to a variety of healthcare practitioners. These cutting-edge analytics improve patient care in the healthcare system by allowing doctors to prescribe better treatments and make more precise clinical choices, removing any ambiguity from the treatment process. Big data analytics appears to be bringing about a shift in healthcare, with the data being utilized to determine which methods are most successful for patients, resulting in better patient outcomes.
One potential challenge or risk of using big data as part of a clinical system
Despite the benefits of big data in healthcare, its use is hampered by some challenges such as data breach, data security, size, aggregating, and updating data. One of the most serious drawbacks of big data is the absence of privacy, particularly when it comes to private medical records. Big data needs access to everything, including private documents and social media posts, to be productive and gain a complete picture of a patient. Many big data professionals believe that technology sacrifices individual privacy for the greater good. While big data allows doctors to keep track of a patient’s health from almost anywhere, it does not provide the patient any autonomy. Although there are rules protecting the privacy of medical records, some of them do not apply to the sharing of big data. Many academics and healthcare professionals believe that present privacy policies need to be overhauled in order to safeguard patients while also allowing analysts to do successful analysis (Young, 2016).
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One strategy you have experienced, observed, or researched that may effectively mitigate the challenges or risks of using big data you described.
There are many ways to prevent breaches of privacy in the healthcare system. Such ways are by conducting an annual security risk analysis, providing continuing education, monitoring devices and records, limiting access to patient information, restricting use of personal devices, updating the IT infrastructure, and lastly, investing in a good legal team. The one I will propose is to limit access to patient information, Users should only have access to patient healthcare data that is relevant to their role to limit access to patient information. Preventing a healthcare data breach necessitates restricting access and controlling user authorization, and also reminding staff not to leave electronic devices or paper records unattended is part of continual education for them. Another aspect is to ensure that every employee is trained on the right procedures for logging on and off devices, particularly shared devices (Walter, 2019).
References
Young, A (2016). Healthcare Technology. The Pros and cons of big data in the healthcare industry. Retrieved December 27, 2021, from https://www.healthtechzone.com/topics/healthcare/articles/2016/11/18/427248-pros-cons-big-data-the-healthcare-industry.htm
Walter, C. (2019). Top benefits of big data analytics in healthcare industry. Retrieved December 27, 2021, from https://www.drcatalyst.com/top-benefits-of-big-data-analytics-in-healthcare-industry
Tavazzi, L. (2019). Big data: Is clinical practice changing? European Heart Journal Supplements, 21(Supplement_B). https://doi.org/10.1093/eurheartj/suz034
10 months ago
Cheryl Wagner WALDEN INSTRUCTOR MANAGER
RE: Discussion – Week 5
Great informational post, Iyabo,
with some wonderful discussion points! I agree wholeheartedly that we are making big strides with getting health care data and we certainly have more and more of it, but I still feel that we need to have a universal nursing language, just as the physicians have their universal language that they use to communicate. We are missing so much data because we do not really chart in a uniform manner that allows us to research our charting and determine if our care is effective or not. If we could just all use the same language we could have a big data set that would have a LOT of useful information that we could analyze. Big data sets are awesome and can really help us to learn things that we might have had to wait FOREVER to discover.
For example, I was remembering a research study done at the University of Iowa by Dr. Marita Titler and colleagues, where she was interested in using their standardized nursing language system – they use North American Nursing Diagnoses Association (NANDA), Nursing Interventions Classification (NIC) and Nursing Outcomes Classification (NOC) – and she was able to gather that data from their electronic medical records. She data mined the records to see if there were any particular nursing interventions (the NIC) associated with fall prevention in the elderly. Lo and behold, she got much more than she was looking for!! And she did it with hundreds of patient records – so a LOT of data – which of course makes the findings super believable!
Not only did she find the answer to her question of which intervention nurses used effectively for fall prevention – which BTW was that there were less falls in the patients who had the Fall Prevention intervention documented – but she also found – mainly because of the large data set she was able to gather, that for every 20% decline of staffing below average, the cost of patient care increased by around $1100 (Titler et al, 2005). What a phenomenal finding!! Of course, management did not listen, but still it was great to know that nursing care was effect AND could be measured in a research study using standardized languages.
Then I think of all the information we could find out if we could JUST get nurses to agree on a language, teach it in the schools, and use it at the bedside. What wonders we could do!
Whoop Whoop!!
What do you think?
Nice work!
Dr. Cheryl
References
Titler, M., Dochterman, J., Picone, D., Everett, L., Xie, X., Kanak, M., & Fei, Q. (2005). Cost of hospital care for elderly at risk of falling. Nursing Economic$, 23(6), 290-306.
10 months ago
Iyabo Osidele
RE: Discussion – Week 5
Hi Dr. Cheryl , I agreed with you, it would have been a great opportunity for the nurses to have a universal nursing language, just as the physicians do, we need a standardized nurse language that will lead to the development of large databases. From these databases, evidence-based standards can be developed to validate the contribution of nurses to patient outcomes, and it would have been better to incorporate it in the big data in order to deliver evidence-based information that will improve efficiencies and help us better understand the best practices connected with any disease, accident, or illness throughout time. And i believes the direct care or bedside nurse benefits greatly from the usage of standardized nursing languages. Better communication between nurses and other health-care providers, increased visibility of nursing interventions, improved patient care, improved data collection to evaluate nursing care outcomes, increased adherence to standards of care, and facilitated assessment of nursing competency are just a few of the benefits (Rutherford, 2008). I believe making use of nursing language will have a significant impact on nursing care planning. The use of a single vocabulary that all nurses can understand will be a great benefit in nursing, now that we are making use of electronic documentation, and the use of electronic health record. In fact, it is impossible for medicine, nursing or any health care-related discipline to implement the use of ED without having a standardized language or vocabulary to describe the key components of the care process..
Reference
Rutherford, M (2008). Standardized nursing language: What does it mean for nursing practice?. Retrieved December 29, 2021, from https://ojin.nursingworld.org/MainMenuCategories/ThePracticeofProfessionalNursing/Health-IT/StandardizedNursingLanguage.html
10 months ago
Olga Tsoy
RE: Discussion – Week 5-reply 1
Good day colleagues Iyabo Osidele,
I completely agree with you on the risks and challenges of operating big data. In my main discussion post, I also raised concern over the security and privacy of healthcare records. I also believe that limiting employee access to patient medical records, updating systems frequently, and audit devices and digital documents can help secure the data; however, we need other multipoint approaches when looking at the bigger picture.
Cybersecurity has been a high-priority topic since the rapid surge of data growth in several decades. Many research articles concluded that conventional processes and human analysts are insufficient to keep data secure; instead, a big data analytics (BDA) tool can best resolve these issues (Rawat et al.,2021). Big data security focuses mainly on confidentiality, so access control and encryption techniques are used (Rawat et al.,2021).
Reference:
Rawat, D. B., Doku, R., & Garuba, M. (2021). Cybersecurity in Big Data Era: From Securing Big Data to Data-Driven Security. IEEE Transactions on Services
Computing, Services Computing, IEEE Transactions on, IEEE Trans. Serv. Comput, 14(6), 2055–2072. https://doi.org/10.1109/TSC.2019.2907247
10 months ago
Tinsae Berhe
RE: Discussion – Week 5
Hi Iyabo
I enjoyed reading your discussion and it contains very important points in it. One thing that I also think would be challenging for any organization would be unstructured data which can affect data patterns and quality of work as well exposing itself to opportunistic known as hackers. No need for me to go over the cybersecurity issues since you already laid it out perfectly in your discussion. Author Jeniffer Thew, mentioned that “The lack of data standardization can also make it challenging for a CNE to assess how the organization or a particular unit is performing and to make well-informed decisions about what to change. Having good data is key to making effective changes” (Thew, 2016). Therefore, having standardized data is critical for better patient outcomes, the safety of the organization, and all.
Reference
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse Execs. Health leaders. Retrieved December 14, 2021, from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
10 months ago
CHIOMA EDEH
RE: Discussion – Week 5
Hi Iyabo,
Nice post. I agree with you that big data provides higher clinical insights to a variety of healthcare professionals. Access through big data leads to high-quality patient care. Patient clinical data are well analyzed, processed, and help prevent harm to patients. Digital data are and will be a big source of information, and possibly of innovation (Bailly et al., 2021).
You made a point on ways to prevent breaches of privacy in the healthcare system through Conducting an annual security risk analysis. At my place of work, security risk analysis is usually conducted every three months. Staff is also required to do the online security/phishing class every six months to help educate staff on the importance of security breaches. Security refers to an individual’s right to expect that private information, once given in confidence for approved uses by third parties, will thereafter be maintained safely against unauthorized intrusion (Schulte, 1999).
Reference:
Bailly, S., Meyfroidt, G., & Timsit, J.-F. (2018). What’s new in ICU in 2050: big data and machine learning. Intensive Care Medicine, 44(9), 1524–1527. https://doi.org/10.1007/s00134-017-5034-3
Schulte Scott, J. (1999). Privacy, confidentiality, and security: protecting “personally identifiable information.” Healthcare Financial Management: Journal of the Healthcare Financial Management Association, 53(3), 26–27.
10 months ago
Stanley Asafor
RE: Discussion – Week 5
Great post, Iyabo,
I believe big data has brought in many positive changes in the health care system, as you mentioned in your posts, such as improved patient healthcare, error reduction, precise treatments, more accurate diagnoses, and treatment. Patients’ care has improved thanks to electronic data systems such as point click care, rtask, epic, which summarizes patients’ data in a mouse click and lets the nurses and providers know considerations that have not been done when patients fall below their baselines etc. Doctors/providers can keep track of a patient’s health from almost anywhere through extensive data systems. They can go to past visits in a mouse click and check a patient’s past medical records to assist the patient better. To do that, information about individual patients is extracted and compiled into flow sheets; vital signs and other physiologic measurements lend themselves nicely to flow sheets (Glassman, K. S. (2017).
We have the downside of big data, such as when the data system is down for maintenance during working hours. You cannot retrieve or get access to critical patient information. We also have data breaches that interrupt the data systems. It will be better to do the maintenance at night when traffic is less on the data system. Thew, J.(2016)
One of the ways to take care of the data breach is to change employee passwords constantly. Some techniques remain clunky, requiring the doctors to navigate through many screens making their work difficult.
Reference:
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.pd
Thew, J. (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
10 months ago
Tina Haslett
RE: Discussion – Week 5
Hello Iyabo!
Big data means big responsibilities. All healthcare workers in America are required to complete health information privacy training with each new employment opportunity. The Health Insurance Portability and Accountability Act (HIPAA) of 1996, and the Health Information Technology for Economic and Clinical Health Act (HITECH) of 2009 were both enacted to ensure health information was protected and only available to the patient and the healthcare professionals provided care unless consent is given by the patient (MCGonigle & Mastrian, 2017). For research purposes, data should not include any identifying information such as name, date of birth, address, social security numbers, etc. HIPAA also requires research studies to be approved by institutional review boards (Melnyk & Fineout-Overholt, 2019). The misuse of health information is a continuing issue and is a potential risk to big data being used to improve patient outcomes. You provided some excellent methods to keep health information protected. Thanks for the great post!
References
McGonigle, D., & Mastrian, K. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Jones & Bartlett Learning.
Melnyk, B., & Fineout-Overholt, E. (2019). Evidence-based practice in nursing and healthcare (4th ed.). Walters Kluwer.
10 months ago
Doreen Muller
RE: Discussion – Week 5
While working in a community clinic in the HIV department, our patients came into the clinic every three months for lab work to monitor the efficacy of their medication. Part of the lab work done included tests for sexually transmitted diseases (STDs), which included syphilis, chlamydia, and gonorrhea. According to Thew (2016) “…big data holds the potential to change healthcare delivery for the better.” For any of our patients that tested positive for any STD, we were required to report it to the public health department. Prior to submitting the information to the public health department, we offered our patients anonymity of notifying their partners and if they accepted, we included it in the information sent to the public health department. According to Jastania et al. (2019). “…big data is a collection of huge volume of trustworthy data, accumulating in high velocity, and coming from variety of sources, not only medical records. Veracity means the quality of data, and variability highlights the inconsistency of its format.”
The benefits of big data in our community clinic were to keep track of communicable diseases, it showed if there was a trend and an uptick in STDs and which communities were affected. With this data, the public health department could notify partners that may have been exposed to an STD. Additionally, the communities can be educated on risk reduction and treatment provided to those in the community who had been exposed to an STD and tested positive. According to Pastorino et al. (2019). “The use of Big Data in healthcare poses new ethical and legal challenges because of the personal nature of the information enclosed.” With the information we gathered from the positive STD tests, if the big data was hacked into that would expose very personal information and that could end up in a lawsuit.
References
JASTANIA, R., NAGEETI, T., AL-JUHANI, H., BASAHEL, A., ALJURAID, R., ALANAZI, A., ALDOSARI, H., & ALDOSARI, B. (2019). Utilizing Big Data in Healthcare, How to Maximize Its Value. Studies in Health Technology & Informatics, 262, 356–359. https://doi.org/10.3233/SHTI190092
Pastorino, R., Vito, C. D., 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, 23–27. https://doi.org/10.1093/eurpub/ckz168
Thew, J. (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
10 months ago
Iyabo Osidele
RE: Discussion – Week 5 Response #1
Hello Doreen, I agree with you, you mentioned in your post that ” big data holds the potential to change healthcare delivery for the better. This is very true because with the use of big data in healthcare nowadays has help in many way to improve patient health. Various healthcare providers benefit from big data analytics since it provides them with more clinical insights, by allowing doctors to prescribe better treatments and make more precise clinical choices, removing any ambiguity from the treatment process. Looking at it now, big data analytics appears to be bringing about a shift in healthcare, with the data being utilized to determine which methods are most successful for patients, resulting in better patient outcomes (TestingXperts, 2021). And also, it helps in early intervention before it get worse. The main purpose of big data in healthcare is to employ predictive analytics to identify and manage medical issues before they become more serious. Big data unquestionably improves the efficiency of the entire process. A patient who is seeing a doctor to reduce weight, for example, may be offered medication to treat high cholesterol. If the patient publishes on social media about stressful events in their lives, the big data algorithm may assess that information and identify the patient as having a heart attack risk. The doctor can then alter the treatment to reduce the chance of a heart attack, effectively resolving the issue before it becomes life threatening (Young, 2016).
References
TestingXperts. (2021, October 28). Significant benefits with big data analytics in Healthcare. Retrieved December 28, 2021, from https://www.testingxperts.com/blog/Big-Data-Analytics-Healthcare
Young, A (2016). Healthcare Technology. The Pros and cons of big data in the healthcare industry. Retrieved December 28, 2021, from https://www.healthtechzone.com/topics/healthcare/articles/2016/11/18/427248-pros-cons-big-data-the-healthcare-industry.htm
10 months ago
CHIOMA EDEH
RE: Discussion – Week 5
Hi Doreen,
Nice post. Big data helps with organizing data and tracking data in an organized pattern. What is big data exactly? It can be defined as data sets whose size or type is beyond the ability of the traditional relational databases to capture, manage and process the data with low latency (Joshi et al., 2021). I commend your clinic on the efficacy of taking care of patients with sexually transmitted diseases. Educating the community on the risk of disease and its treatment is an important way to reduce the transmission of sexually transmitted disease. The most common interventions identified for balancing health care professional education and patient care delivery were ward round teaching, protected learning time, and continuous professional development (Sholl et al., 2017).
Reference:
Joshi, S., Vibhute, G., Ayachit, A., & Ayachit, G. (2021). Big data and artificial intelligence – Tools to be future ready? Indian Journal of Ophthalmology, 69(7), 1652–1653. https://doi.org/10.4103/ijo.IJO_514_21
Sholl, S., Ajjawi, R., Allbutt, H., Butler, J., Jindal, S. D., Morrison, J., & Rees, C. (2017). Balancing health care education and patient care in the UK workplace: a realist synthesis. Medical Education, 51(8), 787–801. https://doi.org/10.1111/medu.13290
10 months ago
ISATU JOHNSON
Week 5 Discussion Response #1
10 months ago
Justina Oyiboke
RE: Discussion – Week 5
Hello Doreen,
I like your big data post. You stated that big data could improve the healthcare delivery system, which is correct, particularly with the advancements in technology and its enhancement of care delivery. Glassman (2017) states succinctly that data and quality care are inextricably linked. The use of data in nursing care has aided in the structure of patient care, the availability of histories, the improvement of treatment, teaching, follow-ups, and patient outcomes. As you mentioned, I agree that because big data can hold all of the information, nurses can use it effectively to teach and send loud messages to patients about sexually transmitted diseases. According to Wang et al. (2018), another critical use of big data in healthcare is the prediction of future trends and events, resulting in the information used as the basis of evidence-based interventions. Furthermore, at the point of care for patients, big data in conjunction with informatics assist nurses in communicating, mitigating error, and supporting decision-making (Glassman, 2017).
References
Glassman, K. S. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45–47. https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf
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. doi:10.1016/j.techfore.2015.12.019
10 months ago
Kealiiaumoku Klein
RE: Discussion – Week 5
10 months ago
Tina Haslett
RE: Discussion – Week 5
Hello Doreen!
This is a great topic to discuss. Health information such as sexual health is often shared and misused because it can involve other individuals other than the patient. The Health Insurance Portability and Accountability Act (HIPAA) signed President Clinton was designed to provide legal guidelines for protecting healthcare information (McGonigle & Mastrian, 2017). The clinic that I am employed in offers treatment of HIV and hepatitis in the Early Inverntion Program (EIP). The healthcare information charted by individual the EIP department are “locked” and only certain individuals that provide direct care to the patient can access the health information. This also applies to health information for behavioral health patients. Individuals can get STD testing in the family practice department. The results are usually discussed with the patient after identifying information is confirmed. Many time patients will ask to call a partner so sexual health status is provided to them, but this is a direct violation of HIPAA. The health department will contact the clinic for treatment follow up of STDs. According to the Wisconsin Department of Health Services (2021), chlamydia, gonorrhea, antibiotic resistant gonorrhea, syphilis, chancroid, and pelvic inflammatory disease are all reportable STDs. Thanks for the great post!
References
McGonigle, D., & Mastrian, K. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Jones & Bartlett Learning.
Wisconsin Department of Health Services. (2021). Sexually transmitted diseases (STD). Retrieved January 1, 2022, from https://www.dhs.wisconsin.gov/std/index.htm
10 months ago
CHIOMA EDEH
RE: Discussion – Week 5
Big data is applied in clinical systems to influence patient health outcomes positively. Health care providers utilize the acquired knowledge from the analysis of big data to make accurate and informed decisions in the treatment of patients (Glassman, 2017). One of the significant benefits of extensive data application is the reduction of medication errors in hospitals and other clinical facilities. In clinical systems, big data can be used to analyze medication prescription records of patients and flag items that do not match. This can be done by creating reminders, clinical flags, and medical alerts. This application of big data is capable of significantly reducing medication errors.
Although the application of big data in the clinical system has brought many benefits, it is associated with challenges. One of such challenges in using big data is inadequate knowledge of big data and applying it to clinical systems (Thew, 2016). Since big data is an emerging issue and is taught in medical colleges, many health care providers lack the technical know-how in analyzing big data and obtaining valuable information that can be applied in clinical systems. This aspect limits the application of big data in many clinical systems.
Insufficient knowledge and technical know-how in using big data by health care providers can be solved by developing education and training programs on big data (Thew, 2016; Mcgonigle & Mastrian, 2017). Health care providers who frequently interact with big data, such as hospital IT specialists, clinical leaders, and department heads, can be trained by an information technology expert specializing in big data. This will equip the health professionals with the required knowledge to navigate big data.
References
Glassman, K. S. (2017, November). Using data in nursing practice. American Nurse Today. Retrieved December 14, 2021, from https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf
Mcgonigle, D., & Mastrian, K. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Jones & Bartlett Learning.
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse Execs. Health leaders. Retrieved December 14, 2021, from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
10 months ago
Doreen Muller
RE: Discussion – Week 5
Hello Chioma,
Thank you for your post. I certainly agree with you, one of the benefits of big data is a reduction in medication errors. According to Campbell et al. (2021),” Medication errors (MEs) result in a minimum of 7,000 deaths yearly.” Having big data in place for analysis and to detect errors could prevent medication errors. Some of the clinical software I have utilized had flags to verity entries that had been captured as erroneous. This provides an opportunity to correct an entry prior to submitting a final entry.
Indeed, new technology can be challenging, I believe having a nurse informaticists on staff to train staff in the new technology to help them transition to new technology would help with knowledge deficit in big data and how to apply it to clinical systems. According to Wang et al. (2018). “A prerequisite for implementing big data analytics successfully is that the target healthcare organizations foster information sharing culture.”
References
Campbell, A. A., Harlan, T., Campbell, M., Mulekar, M. S., & Wang, B. (2021). Nurse’s
Achilles Heel: Using Big Data to Determine Workload Factors That Impact Near
Misses. Journal of Nursing Scholarship, 53(3), 333–342.
https://doi.org/10.1111/jnu.12652
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.
10 months ago
Tinsae Berhe
RE: Discussion – Week 5
Hello Chioma
Great discussion, and I agree with you that the significant benefit of extensive data application is the reduction of medication errors in hospitals and other clinical facilities. One example I can use here is the compatibility of IV antibiotics with isotonic fluids. The organization I work for uses the EPIC software system. The EPIC system flags to alert nurses about medication errors and one example is zosyn(piperacillin & tazobactam) and LR incompatibility. Using the flag system is critical for patient safety and reduces unnecessary organization costs. Nurses play a vital role in putting pertinent data in the charting system. Glassman, K., describes that “Nurses must partner with the vendors of EHR systems to improve this workflow so that the important narrative information can be captured to improve health for all patients” (Glassman, 2017).
Reference
Glassman, K. S. (2017, November). Using data in nursing practice. American Nurse Today. Retrieved December 14, 2021, from https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf
10 months ago
Hannah Brosnahan
Discussion Response 2- Week 5
Chioma Edeh: I enjoyed your post. I agree with you that “[o]ne of the significant benefits of extensive data application is the reduction of medication errors….” Big data analytics are being employed in a digital drug dose checking platform at the Phoenix Children’s Hospital (Cerrato 2017). The platform was designed to create alerts to warn prescribers about dosage problems before orders are written and has resulted in no overdosing incidents at the hospital since it was implemented in 2011 (Cerrato 2017). It has been reported that the “dosing alert system ‘triggers about 30 alerts every day or 3% of the drug orders at Phoenix Children’s Hospital,’” (Cerrato 2017). Further, “[o]f the 330 hard stops each month, 90% resulted in modified orders,” (Cerrato 2017). As you noted in your post, the issue of education or a lack thereof is a major one that will need to be addressed. The informatics competency helps nurses make informed decisions and mitigate errors (Glassman 2017).
References
Glassman, K.S (2017, November). 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.pdf
Cerrato, P. (2017, March). Will Big Data Reduce Medical Error? Medpage Today. Retrieved January 2, 2022, from https://www.medpagetoday.com/resource-centers/advances-in-dermatology/big-data-reduce-medical-errors/1553
10 months ago
Justina Oyiboke
RE: Discussion – Week 5
10 months ago
Cheryl Wagner WALDEN INSTRUCTOR MANAGER
RE: Discussion – Week 5
Great informational post, Justina,
And nice discussion points! I think we are making some strides in gathering data to inform nursing – especially the LARGE pools of data that are in the charts – imagine how cool it is to connect a nursing intervention with a positive patient outcome, as Titler et al. (2005) were able to do (they found that patients who received the nursing intervention of fall prevention had significant less falls and lower length of stay than those patients who did not) but I also think there are many other avenues to explore with Big Data.
As McCormick et al (2015) state:
Through the use of electronic health records (EHR), clinical documentation not only serves to record individual patient experiences but, if the data are collected and reported in a standardized fashion, they can also be aggregated to discern best practices in clinical care which will ultimately lead to improved care and outcomes. Aggregating these data for quality improvement is one form of reuse. To date, quality improvement activities have focused primarily on reuse of medical data. The use of standardized nursing terminology will significantly improve the reuse of nursing data by increasing the ability to share and compare quality data. The ability to share data will enable meaningful analysis of those data for all users who perform clinical care, quality audits, clinical research and other healthcare related operations.
This view is also shared by the Institute of Medicine. They noted that ultimately, the successful sharing of comparable evidence-based healthcare data, including nursing data, will foster improvements in the quality of care (IOM, 2012).
What do you think?
Nice work!
Dr. Cheryl
References
Institute of Medicine). (2012). Best care at lower cost: The path to continuously learning health care in America. National Academies of Science, Engineering and Medicine website. Retrieved from http://www.nap.edu/catalog.php?record%5Fid=13444
McCormick, K.A., Sensmeier, J., Dykes, P.C., Grace, E.N., Matney, S.A., Schwarz, K.M., Weston, M.J. (2015). Exemplars for advancing standardized terminology in nursing to achieve sharable, comparable quality data based upon evidence. Online Journal of Nursing Informatics, 19(2). https://www.himss.org/exemplars-advancing-standardized-terminology-nursing-achieve-sharable-comparable-quality-data-based
Titler, M., Dochterman, J., Picone, D., Everett, L., Xie, X., Kanak, M., & Fei, Q. (2005). Cost of hospital care for elderly at risk of falling. Nursing Economic$, 23(6), 290-306.
10 months ago
Justina Oyiboke
RE: Discussion – Week 5
Dr. Wagner,
It is true that utilizing EBP effectively results in improved patient outcomes, leading to a decrease in the demand for healthcare resources. As a result, healthcare organizations can cut costs. For instance, outdated practices may have included supplies, equipment, or products that are no longer required for specific procedures or techniques. No matter how it is diced, EBP is a critical component of providing safe, high-quality patient care, and nurses must be knowledgeable about current practices to provide patients with the best care (Eastern Illinois University, 2018). I also agree that if the data are collected and reported in a standardized fashion, they can lead to best practices in clinical care. Regardless of the industry, come to think of it, decisions should be based on facts and sound. The value of data collection and analysis using Big Data technologies has shown that the more accurate the data gathered, the more sound the decisions made, and the better the outcomes achieved. If I may add, Big data in healthcare is already providing solutions for improving patient care and helping to generate good value in healthcare organizations (Pastorino et al., 2019).
References
Eastern Illinois University. (2018). Why is evidence-based practice in nursing so important?
https://learnonline.eiu.edu/programs/rn-to-bsn/evidence-based-practice-important/
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(3), 23–27. https://doi.org/10.1093/eurpub/ckz168
10 months ago
Mariline Corvil
RE: Discussion – Week 5
Yes, Justina,
I agree that Big data helps lower healthcare costs and improve patient outcomes. The health system’s database must be tied and protected from data breaches such as hacking, cyber theft, or data phishing. Big data significantly improves the patient experience by cost savings, enhanced patient health, increased preventive services, and reduced errors—patient health, for example, through vital sign monitoring applications. We’ve observed diabetes patients track their insulin dosages and upcoming appointments using big data. Additionally, big data has identified cost-cutting opportunities in the clinical sector, lowering the overall cost of clinical interventions (Agrawal & Prabakaran,2020). Security concerns have been the primary impediment to utilizing big data in the clinical system. Big data is highly vulnerable to bogus data created and stored in the system by cybercriminals, which will degrade the original, accurate clinical data quality. They have gained access to the design and altered its results, resulting in false system results such as incorrect temperatures. Utilizing current technologies could resolve the security issue (Fox & Vaidyanathan,2016)
References
Agrawal, R., & Prabakaran, S. (2020). Big data in digital healthcare: lessons learnt and recommendations for general practice. Heredity, 124(4), 525–534. https://doi.org/10.1038/s41437-020-0303-2
Fox, M., & Vaidyanathan, G. (2016). Impacts of Healthcare Big Data: A Framework with Legal and Ethical Insights. Issues in Information Systems, 17(3), 1–10.
10 months ago
Perkaloah Queeglay-Tarpeh
RE: Discussion – Week 5
RESPONSE #1
Hello Justina,
Great informational post! As you mentioned, with technological advancement, data is increasingly becoming important in attaining optimum results through data collection, interpretation, and analysis to predict the present and future events. The latest technologies and the resulting growing scale of data being produced in the healthcare industry are compelling healthcare professionals to understand and link data for emerging growth opportunities (Au-Yong-Oliveira et al., 2021). Additionally, Big data is increasingly becoming more prevalent and it influences how nurses train, practice, develop policy, and conduct research. I also agree that the utilization of Big data aids in minimizing healthcare costs and advancing patient outcomes. In addition, consumer device development has significantly improved clinical data gathering, as it allows continuous collection of patient vitals and its real-time evaluation (Agrawal & Prabakaran, 2020). While opening the potential of clinical benefit, the utilization of health-linked big data generates significant challenges. Legal and Ethical challenges include the danger of compromising individual autonomy, privacy, and the solidarity-based method to healthcare funding (Ienca et al., 2018). I also agree that effective adoption of Big Data is empowered by the creation and utilization of machine learning (ML) approaches.
References
Agrawal, R., & Prabakaran, S. (2020). Big data in digital healthcare: Lessons learned and recommendations for general practice. Heredity, 124(4), 525-534. https://doi.org/10.1038/s41437-020-0303-2
Au-Yong-Oliveira, M., Pesqueira, A., Sousa, M. J., Dal Mas, F., & Soliman, M. (2021). The potential of big data research in healthcare for medical doctors’ learning. Journal of Medical Systems, 45(1). https://doi.org/10.1007/s10916-020-01691-7
Ienca, M., Ferretti, A., Hurst, S., Puhan, M., Lovis, C., & Vayena, E. (2018). Considerations for ethics review of big data health research: A scoping review. PLOS ONE, 13(10), e0204937. https://doi.org/10.1371/journal.pone.0204937
10 months ago
Stanley Asafor
RE: Discussion – Week 5
10 months ago
Tokunbo Allen
RE: Discussion – Week 5
10 months ago
Kayla Joyce
RE: Discussion – Week 5
Hi Tokunubo! Great post. I agree that having all the information in front of you (like past labs, imaging, and visits) when a patient is admitted improves patient care. This helps because you are able to see what brought them into the medical facility in previous times. Though this is helpful in some cases, having this power, to see a patient’s chart that far back, can be a HIPAA violation if that staff member isn’t supposed to be in their chart. Hospitals should give ongoing ethics training to staff members and develop more effective measures to improve EMR privacy protection (Sher et al., 2016). Staff members should continue to show awareness to the privacy of their patients and maintain ethical. Nurses are crucially responsible for care integration and patient safety since nurses do the majority of EHR documentation in hospitals (including plans of care, physiological parameters, assessments, interventions, and progress evaluations) (Glassman, 2017).
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.pdf
Sher, M.-L., Talley, P. C., Cheng, T.-J., & Kuo, K.-M. (2016). How can hospitals better protect the privacy of Electronic Medical Records? perspectives from staff members of Health Information Management Departments. Health Information Management Journal, 46(2), 87–95. https://doi.org/10.1177/1833358316671264
10 months ago
ISATU JOHNSON
Week 5 Discussion Response 2
Hello Tokunbo
I enjoyed reading ur post and certainly agreed about the challenges u mentioned on accessing pt data and how it it’s becoming the most challenging domain of big data and it vulnerability to breaking patients privacy considerations protected by HIPPA act.
The major risk to patients is the exposure of their personal health information. The combining of information into large data sets increases the potential for the data to be reidentified and used in ways patients never would have intended.
Big data can pose a serious threat to to patients privacy if care is not taken. Patients information such as addresses, pictures, names can be find easily which could lead to exploitation.
In most cases, clinical data are captured in various systems, even within an organization, each with a somewhat different intent and often not well integrated. For example, an EHR is primarily used for documenting patient care and was designed to facilitate insurance company billing and pharmacy records were designed for inventory management.
These systems were not developed to capture the temporal and process information which is indispensable for understanding disease progression, therapeutic effectiveness and patient outcomes.
Reference
Sewell, J. (2018). Informatics and Nursing. Lippincott Williams & Wilkins.
Sweeney, J. (2017). Healthcare informatics. On-Line Journal of Nursing Informatics, 21(1).
Gibson M (2002) Doing a doctorate using a participatory action research framework in the context of community health. Qualitative Health Research 12(4): 546–588.
10 months ago
Justina Oyiboke
RE: Discussion – Week 5
Hi Tokunbo,
You hit the nail on the head when you said that data is the driving force for organizational change and fuel for innovation, especially in the medical field. In Price & Cohen (2019), they argued that big data enables more powerful evaluations of health care quality and efficiency, which can then be used to improve care. Data analysis has been shown to provide clinical insight to health care providers, allowing them to prescribe, treat, and make clinical decisions with greater precision, reducing the amount of uncertainty associated with inpatient care (Catalyst, 2018). Information about patients can be distributed to other health management teams more efficiently using big data and informatics. The amount of data we collect has skyrocketed since the world went digital. It is possible to extract, manage, analyze, and interpret large datasets and turn them into hypotheses that can be put into action. The medical and health sector has gradually entered the era of big data as the advancement process has continued to accelerate. Many areas of nursing practice can benefit from new methods and ideas provided by large-scale, multi-channel, and diverse data sets, such as improving the level of practice, monitoring disease, and helping in care delivery (Zhua et al., 2019).
References
Catalyst, N. (2018). Healthcare big data and the promise of value-based care.
NEJM Catalyst/. https://catalyst.nejm.org/doi/full/10.1056/CAT.18.0290
Price, W. N., 2nd, & Cohen, I. G. (2019). Privacy in the age of medical big data. Nature
Medicine, 25(1), 37–43. https://doi.org/10.1038/s41591-018-0272-7
Zhua, R., Hana, S., Sub, Y., Zhangc, C., Yuc, Q., & Duan, Z. (2019). The application of big data
and the development of nursing science: A discussion paper. International Journal of Nursing Sciences, 6(2), 229-234. https://doi.org/10.1016/j.ijnss.2019.03.001
10 months ago
Hannah Brosnahan
Discussion Response 1 – Week 5
10 months ago
Mariline Corvil
RE: Discussion – Week 5
One potential benefit of using big data as part of a clinical system
One of the primary benefits of using big data as part of a clinical procedure is that it enables the early detection of diseases. When diseases are detected early on, they are straightforward to cure and effectively control. When conditions such as cancer are detected early, they can be treated entirely; however, when they are caught late, nothing can be done to rescue the patient, and the disease is usually fatal. Within the field of oncology, the objective of big data is to generate predictions for individuals with specific traits and the projected risks and advantages of particular cancer treatments (Naqa, Kosorok, JIn, Mierzwa, & Ten Haken, 2018). Big data would significantly enhance patient outcomes by allowing for more individualized therapy to be captured using data from a broader sample of the population. For instance, ovarian cancer is a common occurrence in women and, due to its high fatality rate, it ranks fourth among all cancers. The high mortality rate associated with ovarian cancer is attributed to the fact that most people were unaware of the disease until it progressed to Stage III or IV. The key to resolving this issue is early detection, which will help minimize the fatality rate of ovarian cancer. Yasodha, and Anathanarayanan 2015).
One potential challenge or risk of using big data as part of a clinical system and explain
The challenge surrounding big data is a significant impediment to the acceptance and application in the therapeutic system. The possibility of a conflict between privacy and personal liberty has surfaced as a critical issue impeding the use of big data. The utilization of vast data may reveal private information if unauthorized entities with malevolent intent gain access (Mehta and Pandit 2018).
Propose at least one strategy you have experienced, observed, or researched that may effectively mitigate the challenges
The challenge of big data usage can be addressed by introducing proper policy initiatives and frameworks. The policy measure will govern data use and access while addressing privacy concerns. Establishing policy initiatives is a necessary first step toward fully resolving Big Data-related privacy problems.
References:
Naqa,I., Kosorok, M., Jin, J., Mierzwa, M., & Ten Haken, R. (2018). Prospects and Challenges for clinical decision support in the era of big data. JCO Clinical Cancer Informatics. Retrieved from https://ascopubs.org/doi/full/10.1200/CCI.18.00002.
Mehta N. and Pandit A. (2018). Concurrence of big data analytics and healthcare: A systematic review. International journal of medical informatics, 114, 57-65. 2.
Yasodha P. and Anathanarayanan N. R. (2015). Analysing big data to build knowledge-based system for early detection of ovarian cancer. Indian journal of science and technology. 8(14), 1-7. 3. Murdoch, T. B., & Detsky, A. S. (2013). The inevitable application of big data to health care. Jama, 309(13), 1351-1352.
10 months ago
Mariline Corvil
RE: Discussion – Week 5
One potential benefit of using big data as part of a clinical system
One of the primary benefits of using big data as part of a clinical procedure is that it enables the early detection of diseases. When diseases are detected early on, they are straightforward to cure and effectively control. When conditions such as cancer are detected early, they can be treated entirely; however, when they are caught late, nothing can be done to rescue the patient, and the disease is usually fatal. Within the field of oncology, the objective of big data is to generate predictions for individuals with specific traits and the projected risks and advantages of particular cancer treatments (Naqa, Kosorok, JIn, Mierzwa, & Ten Haken, 2018). Big data would significantly enhance patient outcomes by allowing for more individualized therapy to be captured using data from a broader sample of the population. For instance, ovarian cancer is a common occurrence in women and, due to its high fatality rate, it ranks fourth among all cancers. The high mortality rate associated with ovarian cancer is attributed to the fact that most people were unaware of the disease until it progressed to Stage III or IV. The key to resolving this issue is early detection, which will help minimize the fatality rate of ovarian cancer (Yasodha. and Anathanarayanan 2015).
One potential challenge or risk of using big data as part of a clinical system and explain
The challenge surrounding big data is a significant impediment to the acceptance and application in the therapeutic system. The possibility of a conflict between privacy and personal liberty has surfaced as a critical issue impeding the use of big data. The utilization of vast data may reveal private information if unauthorized entities with malevolent intent gain access (Mehta and Pandit 2018).
Propose at least one strategy you have experienced, observed, or researched that may effectively mitigate the challenges.
The challenge of big data usage can be addressed by introducing proper policy initiatives and frameworks. The policy measure will govern data use and access while addressing privacy concerns. Establishing policy initiatives is a necessary first step toward fully resolving Big Data-related privacy problems.
References:
Mehta N. and Pandit A. (2018). Concurrence of big data analytics and healthcare: A systematic review. International journal of medical informatics, 114, 57-65. 2.
Naqa,I., Kosorok, M., Jin, J., Mierzwa, M., & Ten Haken, R. (2018). Prospects and Challenges for clinical decision support in the era of big data. JCO Clinical Cancer Informatics. Retrieved from https://ascopubs.org/doi/full/10.1200/CCI.18.00002.
Yasodha P. and Anathanarayanan N. R. (2015). Analysing big data to build knowledge-based system for early detection of ovarian cancer. Indian journal of science and technology. 8(14), 1-7. 3. Murdoch, T. B., & Detsky, A. S. (2013). The inevitable application of big data to health care. Jama, 309(13), 1351-1352.
10 months ago
Tokunbo Allen
RE: Discussion – Week 5
10 months ago
Cheryl Wagner WALDEN INSTRUCTOR MANAGER
RE: Discussion – Week 5
Great informational post Mariline,
And nice discussion points! I like the points made by Topaz and Pruinelli (2017) related to the need of Big Data in nursing, and their discussion of some of the reasons that nurses are not quite making use of the data as we should be. They noted
“Big data are becoming increasingly more prevalent and they affect the way nurses learn, practice, conduct research and develop policy. The discipline of nursing needs to maximize the benefits of big data to advance the vision of promoting human health and wellbeing. However, current practicing nurses, educators and nurse scientists often lack the required skills and competencies necessary for meaningful use of big data. Some of the key skills for further development include the ability to mine narrative and structured data for new care or outcome patterns, effective data visualization techniques, and further integration of nursing sensitive data into artificial intelligence systems for better clinical decision support. There are growth-path vision recommendations for big data competencies for practicing nurses, nurse educators, researchers, and policy makers to help prepare the next generation of nurses and improve patient outcomes trough better quality connected health” (Topaz & Pruinelli, 2017, p. 165).
I think that is a good place to start, as they recommend – with competencies designed along a growth path. Also, as I have been noting throughout the course – we do need to have one standardized language that nurses everywhere use to document their care. That in itself would make the harvesting of the data much easier and the data itself would be more useful.
What do you think?
Nice work!
Dr. Cheryl
References
Topaz, M., & Pruinelli, L. (2017). Big data and nursing: Implications for the future. Studies in Health Technology and Informatics, 232, 165-171.
10 months ago
Cynthia Kadiri
RE: Discussion – Week 5
Mariline
Potential benefit of big data is applying it for meaningful use of improved patient outcome and population (Glassman, 2017). You mentioned in your post that with big data use in your clinic of practice early detection of disease produces good end result , because if diseases are detected early the disease can be treated and save lives. in addition to saving lives nurses being the largest group of health care professionals use the knowledge and competency to mitigate errors.
References
Glassman, K.S (2017). Using data in nursing practice . American nurse today, 12(11)
10 months ago
Silvanus Manduku
RE: Discussion – Week 5
Hi Mariline.
This is very profound. Big data has become a pivotal element of the clinical system. It’s commendable of you to illustrate how nursing efficiencies have been impacted by big data. In your candid explanation, one thing stands out: Consideration of big data as a tool for improved nursing outcomes. Regardless of the region or facility, this is the way to go for the healthcare sector. However, there is still much to be done to propel big data in producing more benefits to the healthcare sector.
I can reaffirm that big data enables the early detection of disease. This has gone a long way in saving the lives of patients, not only in the United States but all over the world. Additionally, there are enough signs to show that big data enables personalized care (Rehman et al., 2021). Nonetheless, the existence of ‘Privacy conflicts’ as a great impediment to big data success cannot be overlooked. Furthermore, data utilization has caused a lot of worry among patients. This makes them reluctant to share information.
On top of the identified solution for the aforementioned challenge, embracing data encryption will wipe out privacy issues/conflicts. Data encryption allows for fine-grained access (Rehman et al., 2021). Although policy measures are reliable in this particular quest, I propose the adoption of ‘Anonymization of Data’ to solve privacy concerns.
As for big data as a whole, there are more opportunities ahead. For instance, decision making largely relies on data. Therefore, big data opens the door towards improved procedures, treatment strategies and management of population health. However, McGonigle & Mastrian (2017) points out that the healthcare sector must invest in human capital. Personnels in the clinical system should be trained on data collection, management and analysis. By doing so, generating more knowledge to streamline healthcare will be realized. Therefore, big data will determine the future of healthcare. If the challenges are addressed keenly, nothing can go wrong.
References
McGonigle, D. & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge
(4th edition.). Burlington, MA: Jones & Bartlett Learning.
Rehman, A., Naz, S., & Razzak, I. (2021). Leveraging big data analytics in healthcare
enhancement: trends, challenges and opportunities. Multimedia Systems, 1-33.
10 months ago
Olga Tsoy
RE: Discussion – Week 5
Big Data
Easy access to portable technological devices allows us to create content more freely. Daily, people produce 2.5 quintillion bytes of information; it only took two years to develop 90% of the existing data (McGonigle & Mastrian, 2017). By creating more data, humans gain ideas, facts, understanding, wisdom, and, more importantly, the opportunity to improve the area of interest (McGonigle & Mastrian, 2017). However, some challenges also exist. According to Wang et al. (2018) article, healthcare providers still do not understand the power of big data analytics; only 42% of clinicians utilize the analytics strategy in their decision-making, and only 16% have knowledge of operating analytics to its full potential (para.3). There are pros and cons of using big data for the healthcare system.
Potential benefit of using big data as part of a clinical system
The most significant impact big data can contribute to the healthcare system is it can improve the development of healthcare policies and practices; provide new insights on disease prevention, disease detection, and in-hospital deaths. Big data can be used on the administration side to capture fraudulent insurance claims (McGonigle & Mastrian, 2017). According to a Walden University website (2018) video, the data was produced based on collected information about diabetic patients. The gathered data provided clinicians with ample useful information; healthcare professionals could build knowledge and wisdom regarding diabetes based on this information. Today, chronic disease diabetes can be well managed due to detailed data syntheses and analysis into proper interventions and treatments ( file 2). The process used to gather data is called data mining; it is a rational method focusing on covered predictive prognosis that will eventually drive the future behavior, skills, policies, trends, actions. The knowledge derived from data mining is proactive; it will allow evidence/knowledge-driven decision-making (McGonigle & Mastrian, 2017).
Potential challenge or risk of using big data as part of a clinical system
Big data has many advantages; however, some challenges also exist. The risks of using big data as part of the healthcare system can be complex: from inferior digital information control, impaired integration of digital systems to the increased volume of the digital surge of data (Wang et al., 2018). Possible data loss/breach can be a significant concern for data containing healthcare information as well.
I have encountered a situation with my personal healthcare records being compromised by a data breach at one of the healthcare facilities. I had to monitor my credit and personal information closely. The organization provided each affected individual with a two-year Experian membership to easily access any credit information change. I can see how this can be a big issue for organizations and individuals; I believe a more secure system needs to be in place to prevent a data breach.
Strategy
The problem I have encountered at a solo physicians’ practice medical office is the problem with the reliable storage of medical records data and cost. The alternative that some small companies are using is cloud storage. The timely processing and lower cost are advantages of this network system; however, the concerns with using the shared network are privacy and protection of patients’ data. The solution can be to use a private cloud instead, which provides a more secure environment but increases overall expense for the company (Wang et al.,2018). The balance should be achieved between cost and safety of information.
References
Laureate Education (Producer). (2018). Health Informatics and Population Health: Analyzing Data for Clinical Success.
https://content.waldenu.edu/dfa28261dea73c5a625b5b2befc0e73f.html
McGonigle, D., & Mastrian, K. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Jones & Bartlett Learning.
Wang, Y., Kung, L., & Byrd, T. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological
Forecasting and Social Change, 126, 3–13. https://doi.org/10.1016/j.techfore.2015.12.019
10 months ago
Perkaloah Queeglay-Tarpeh
RE: Discussion – Week 5
10 months ago
ISATU JOHNSON
RE: Discussion – Week 5 Initial Post
10 months ago
Iyabo Osidele
RE: Discussion – Week 5 Response #2
Good job, Isatu, you are absolutely right with your post where you mentioned that ” one potential of big data is the contribution towards nursing initiatives in terms of improvement of patient outcomes, care quality, patient safety, and saving cost”. Big data has helped in early detection and treatment effectiveness, and also the quality is improved as a result of the discovery of early signals and disease intervention, as well as a lower risk of adverse effects. It also expands illness prevention options through the identification of disease risk factors, and improved drug safety and patient safety by the ability to make better medical decisions based on information supplied directly to patients with outcome prediction. (Pastoring et al, 2019). Like you said, big data also save cost because employs big data analytics to identify patients with several chronic conditions (comorbidity) as being more likely to benefit from early interventions in care homes, avoiding emergency room visits.Big data analysis provides healthcare providers with clinical insights that would not otherwise be available. It enables them to prescribe therapies and make clinical decisions with higher precision, removing the guesswork that is typically associated with treatment and resulting in cheaper costs and better patient care (Cataylist, 2018).
Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019, October 1). Benefits and challenges of Big Data in Healthcare: An overview of the European initiatives. European journal of public health. Retrieved December 29, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6859509/
Catalyst, N. E. J. M. (2018). Healthcare big data and the promise of value-based care. NEJM Catalyst. Retrieved December 29, 2021, from https://catalyst.nejm.org/doi/full/10.1056/CAT.18.0290
10 months ago
Charmagne Yokoyama
RE: Discussion – Week 5 Initial Post
10 months ago
Doreen Muller
RE: Discussion – Week 5 Initial Post
10 months ago
Charmagne Yokoyama
RE: Discussion – Week 5 MAIN QUESTION POST
One potential benefit of using big data as part of a clinical system
Big data is everywhere in healthcare, and it begins the moment you step inside a clinic lobby or a hospital. Medical facilities collect personal information such as your address and health insurance to receive care. This begins the process of collecting data on each and every patient. As the patient moves further inside doorways and down the hall, health care workers collect your vitals, your weight, your height, allergies, and what is the medical purpose of your visit. All this data is entered into a computer system, collecting it and categorizing it so the information will be available with a few clicks of a computer button.
One potential benefit of using big data as part of a clinical system is easy access to your medical records, such as lab results and current diagnosed health concerns. The patient portals for healthcare connect you to your personal medical records when you sign in and use your password. “Nurses have to keep the patient front and center in everything we do and our ability to advocate for patients can include educating and supporting them to enter their own data into secure patient portals” (Glassman, 2017, p. 46). Using the patient portal email, allows the patient to communicate directly with their provider at any time. This technology in a clinical setting has enormous benefits to the patient because direct communication and lab results provide a foundation for optimal health.
One potential challenge or risk of using big data as part of a clinical system
The computer is collecting data, thousands of pieces of information about our patients every single day. One potential challenge in using big data in a clinical system is not being able to access the data, having too much useless data, or not interpreting the data correctly. Thew (2016) explained the lack of data standardization can also make it challenging for a CNE to assess how the organization or a particular unit is performing and to make well-informed decisions about what to change. Having good data is key to making effective changes. Good data to me is useful data, easily understood, and with a few clicks of a button – easily available.
Another potential challenge is having enough nursing informatics leaders involved in the creation of healthcare programs. There is a shortage of nurses, and this specialty area of nursing informatics is no different. Big data requires skilled people to understand and incorporate the information, so it is useful to the front-line workers. If we don’t have those skilled employees, then we will fall short with assigned tasks. It can be frustrating when you do not know how to complete a function on the computer, or you don’t know how to find the information you need at that time. I am always thankful for my tech-savvy colleagues!
One strategy you have experienced, observed or researched that may effectively mitigate the challenges or risks of using big data
One strategy I have experienced that may effectively mitigate the challenges or risks of using big data happened while working at Aurora Medical Center in 2016. The hospital began a useful technique of creating “super users” for newly adopted computer programs and any technical data system issue. Super users are floor nurses who learn the new tech system the hospital wants to roll out, and they play an active role in the success of those first few weeks. “Super users train and support nurses to use EHRs; they also collaborate with the organizational information technology (IT) department to address issues with the EHRs their nurses use” (“Calling Nursing Informatics Leaders: Opportunities for Personal and Professional Growth,” 2021). When you have big data happening on the floor, collecting it, and accessing it when you need it is extremely important. The super users assisted in that process and became wonderful supporters of the floor nurse.
References
Calling Nursing Informatics Leaders: Opportunities for Personal and Professional Growth. (2021). Online Journal of Issues in Nursing, 26(3), N.PAG. https://doi.org/10.3912/OJIN.Vol26No03Man06
Glassman, K. S. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45–47. Retrieved from https://www.americannursetoday.com/wpcontent/uploads/2017/11/ant11-Data-1030.pdf
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-bigpotential-challenges-nurse-execs
10 months ago
Klara Handrock
RE: Discussion – Week 5 MAIN QUESTION POST
Charmagne-
Thank you for your post. I agree that nursing leaders need to be involved in informatics and big data collection and review.
Data mining of big data can be used to link relationships between information. These patterns can then be used to predict and thus develop protocols to help reduce potential negative outcomes and improve patient care. These relationships can be utilized for the financial protection or gain of a facility. Nursing is patient centered. It is important that as nursing leaders we are maximizing the information derived from data mining of big data, and utilizing the knowledge derived from this process to guide policy implementation, patient centered protocols, and nursing practices (McGonigle, 2017).
Data needs to be of high integrity to help drive nursing practice, and accurately predict patterns. Nurses need to have an understanding of big data, how it is collected, and how it is reviewed. Data collection needs to be free of errors and inaccuracies, as this not only has potential implications for that patient. Those inaccuracies can also create problems during data mining. Nurses need to understand the implications of collecting accurate data, and how standardization across facilities, and clinicians can have huge impacts on the value of the data being collected (Rambur & Fitzpatrick, 2018).
Reference
McGonigle, D., & Mastrian, K. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Jones & Bartlett Learning.
Rambur, B., & Fitzpatrick, T. (2018). A plea to nurse educators: Incorporate big data use as a foundational skill for undergraduate and graduate nurses. Journal of Professional Nursing, 34(3), 176–181. https://doi.org/10.1016/j.profnurs.2017.10.005
10 months ago
Kayla Joyce
RE: Discussion – Week 5
The usage of big data in health care has proven to be quite advantageous in terms of giving good patient outcomes and well-organized documentation. Due to record keeping, compliance and regulatory obligations, and patient care, the healthcare business has historically created huge amounts of data (Raghupathi & Raghupathi, 2014). Big data aids in the reduction of costs and the quick access to records that are required. At any time, staff can get patient information from a remote location. Because of real-time documentation, the information is current. This keeps employees informed, making it easier for them to offer safe and effective patient care. With the advancement of data mining, we have not only been able to browse our data in real time, but we have also advanced beyond retrospective data access with navigational improvements (McGonigle & Mastrian, 2017) Discussion: Big Data Risks and Rewards.
With so many people having access to the data system, one challenge is the potential for a violation of privacy. You hear about nurses and other hospital staff members breaking HIPAA laws for celebrities who are admitted to the hospital all the time on the news. This has also been influenced by social media. Users may reach a huge audience in a matter of seconds via social media, and with this convenience, users can transfer information, which has caused issues in the form of illegal disclosure of patient health information on social media sites (Parris, 2015).There are also other times where staff members, in a hospital, will see a person they know or another staff member admitted to the hospital and go into their chart to see why they are admitted.
Through my experiences at my facility, I believe that employees shouldn’t have access to patients on floors they are not working on.. At my facility we use epic. Through epic, you are able to go to each floor throughout the whole hospital and click on any patient’s chart admitted. I believe if you need to look up a patient on another floor, you should have to input their full name and date of birth. This would reduce the number of people who have access to patient information. Protecting the privacy of our patients and ensuring that their information is only in the hands of workers who are directly involved in their care.
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of
knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.
Parris, T. (2015). HIPAA violations on social media. Applied Research Projects. https://doi.org/10.21007/chp.hiim.0025
Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and potential. Health information science and systems, 2, 3. https://doi.org/10.1186/2047-2501-2-3
10 months ago
Sarah Simpson
RE: Discussion – Week 5-Kayla Joyce
Kayla- I find that interesting that you are able to look up any patient on any floor! My system uses Cerner, although not as efficient as Epic we can not look up other patients on our other unit unless we put in full name and birth date. I do know that our company does have a policy with looking up other patients that are not your own and this is not allowed. I am guessing your system has something like this in place as well. I think that a way to mitigate this issue is to place alerts or notifications in place if you are out of your unit and on another unit. The system could then send these notifications to leadership or IT indicating that the provider is not in a place that they should be.I think that something that could be implemented to stop providers from accessing chart they are not suppose to is a specific password for patients specific to them. This could apply to a all providers in contact with that patient, this could prevent others from accessing the chart when they are not taking care of that patient in particular(Shenoy & Appel, 2017). A way they need to do this is through constant education and awareness of working with someone’s patient information. I know that my health care system implements security and HIPAA training each year to make sure we understand the precautions we need to take when working with someone else’s patient information and if we are able to have access to their information (Fox, 2020).
Fox, G. (2020). “To protect my health or to protect my health privacy?” A mixed‐methods investigation of the privacy paradox. Journal of the Association for Information Science & Technology, 71(9), 1015–1029. https://doi.org/10.1002/asi.24369
SHENOY, A., & APPEL, J. M. (2017). Safeguarding Confidentiality in Electronic Health Records. Cambridge Quarterly of Healthcare Ethics, 26(2), 337–341. https://doi.org/10.1017/S0963180116000931
10 months ago
Ashley Brimhall
RE: Discussion – Week 5
Kayla,
I appreciate the information you provided regarding privacy and the risks involved with data accessibility. Without knowing your facility, I applied the information you applied to the jobs that I currently work. I believe removing access to patients charts is necessary for some organizations, but extremely difficult in others. At my home health job, only having access to my patients assists with HIPAA concerns, but also prevents me from getting overwhelmed with useless data. In my wound care job, I see patients all over the building, most staff float to other units frequently, and the patients move often enough to make lack of access a problem. Finally, in the prison system, I access patients’ reports from other facilities due to movement and follow through. According to Wang et al. (2018). “A prerequisite for implementing big data analytics successfully is that the target health care organizations foster information-sharing culture.” A balance between enough information, and too much should always be considered in technology utilization.
References
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.
10 months ago
Perkaloah Queeglay-Tarpeh
RE: Discussion – Week 5
Big Data and Its Benefits to The Clinical System
Big Data in clinics and medicine includes various forms and large amounts of data created from healthcare organizations, such as medical imaging and clinical data. There are various sources for big data in healthcare including wearable video devices, monitoring devices, and health-linked mobile phone applications (Mehta et al., 2019). Additionally, a broad amount of data is created in various areas of the healthcare industry such as healthcare providers, medical equipment, medical insurance, medical research, and life sciences. With technological progress, there is a huge prospect for healthcare transformation through the utilization of this data (Mehta et al., 2019). Big data has the capability and likelihood to advance the efficiency and quality of care. It also provides an opportunity to forecast outcomes based on present primary or historical data and offers proof of benefits that might change traditional, industry-wide care criteria (Kruse et al., 2016). Besides, leveraging on patient-focused technology could also improve medication adherence. This will undoubtedly play a crucial role in advancing outcomes and improving the health-linked quality of life.
Challenges of Big Data
According to Mcgonigle and Mastrian (2017), the difficulty of Big Data evaluation emerges from merging different forms of electronically captured information. The healthcare industry generates and collects data at incredible speeds, however, varying electronic health records (EHRs) gather data in varying structures. For instance, unstructured, semi-structured, and structured data. This type could pose challenges when finding quality assurance or veracity of the data (Kruse et al., 2016). In addition, the EHRs could offer a rich data source, suitable for analysis to advance the understanding of disease mechanisms, as well as personalized and better healthcare, but the data configurations create difficulty when making analysis using standard methods. Besides, the incorporation of data from several databases and calibration for laboratory values and protocols remain major concerns.
Strategy to Effectively Mitigate Dangers of Big Data
Big Data Analytics (BDA) is gradually emerging as a trending procedure that various organizations are utilizing to generate valuable information from Big Data (Sinha, 2020). Additionally, to allow evidence-based decision-making, healthcare organizations require effective techniques to converting large volumes of varied data into meaningful understandings. The veracity aspect examines the correctness of data and its likely usage for data analysis. For instance, every client’s opinion on varying social media platforms and the web is varied and uncertain in form due to human involvement (Mcgonigle & Mastrian, 2017). This could be handled using analytics and tools created for mining and management of unreliable data. Besides, the advancement of software tools that could effectively aid healthcare by advancing the quality of supplementary care can influence large adoption as well as studies on the competence and usefulness of artificial intelligence and big data analysis for healthcare.
References
Kruse, C. S., Goswamy, R., Raval, Y., & Marawi, S. (2016). Challenges and opportunities of big data in health care: A systematic review. JMIR Medical Informatics, 4(4), e38. https://doi.org/10.2196/medinform.5359
Mcgonigle, D., & Mastrian, K. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Jones & Bartlett Learning.
Mehta, N., Pandit, A., & Shukla, S. (2019). Transforming healthcare with big data analytics and artificial intelligence: A systematic mapping study. Journal of Biomedical Informatics, 100, 103311. https://doi.org/10.1016/j.jbi.2019.103311
Sinha, D. S. (2020). Big data analysis: Concepts, challenges, and opportunities. International Journal of Innovative Research in Computer Science & Technology, 8(3). https://doi.org/10.21276/ijircst.2020.8.3.29
10 months ago
Charmagne Yokoyama
RE: Discussion – Week 5
RESPONSE #2 YOKOYAMA C
Hi Perkaloah,
You mentioned several points that I agreed with and I appreciate your effort with this posting.
Big Data and Its Benefits to the Clinical System
When I read your initial posting, I remembered one of our video media course references and I can elaborate on your comments about a broad amount of data is created in various areas. It was a cool youtube video that went into great details about all the different ways consumers provide data. Vinay 2014 provided examples when we visit the MD and provide all our health history, vitals, and body statistics. Then Vinay 2014 continued to share examples of sociodemographic information, wearable technology that tracks our exercise and sleeping, pharmaceutical data, and lastly medical diagnostic data. Discussing big data has been eye opening for me and most of us because we don’t really think about all the information we share with technology apps or the amount of information that is generated when we visit our primary care provider.
Challenges of Big Data
I agree with your statements concerning there are too many forms of big data using too many ways to merge the information. According to Mcgonigle and Mastrian (2017), the difficulty of Big Data evaluation emerges from merging different forms of electronically captured information. It is hard to use the data or analyze the data if you can’t find the data because of poor technology to technology communication. Han et al., 2020 “Despite investing more than $30 billion dollars and an increase in EHR uptake by providers, the US has neither achieved a cohesive, standardized usage of EHRs nor built the data infrastructure to facilitate fluid EHR data exchanges”. The challenge we face is to have everyone choose the same type of technology communication so the different data configurations do not create difficulty when analyzing the information. Kind regards, Char
References
Han, A., Isaacson, A., & Muennig, P. (2020). The promise of big data for precision population health management in the US. Public Health, 185, 110–116. https://doi.org/10.1016/j.puhe.2020.04.040
Mcgonigle, D., & Mastrian, K. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Jones & Bartlett Learning.
Vinay Shanthagiri. (2014). Big Data in Health Informatics [Video file]. Retrieved from https://www.youtube.com/watch?v=4W6zGmH_pOw
10 months ago
Klara Handrock
RE: Discussion – Week 5
Big Data
Potential benefit of using big data as part of a clinical system
Nursing is science and evidenced based, and data mining is an important aspect of it. Nursing uses data to identify patterns or relationships. Then the information can be utilized to reduce costs, increase safety, and or decrease the potential of negative outcomes. Data is constantly being collected, and if effectively utilized it can drive policy, prevent negative outcomes, and increase safety and efficiency. Protocols based on evidenced based practice. In healthcare this all has financial implications as improved patient outcomes, and prevention of negative outcomes equates to decreased costs (McGonigle & Mastrian, 2017).
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Potential challenge or risk of using big data as part of a clinical system
Utilizing big data can improve clinical practice, and reduce risk of complications; however, there can also be challenges when attempting to utilize data. Getting different systems to synchronize, so that data can be utilized can be a challenge. It can also be a challenge to analyze data from various sites and/or systems as there may be little to no standardizations between facilities, units, EHRs, and individual clinicians. Data can be utilized to make evidence based changes; however there has to be quality data, and it has to be streamlined for effective analysis and dissemination. There has to be a standardization for analysis and utilization to be effective (Thew, 2016).
Experience
Our facility utilizes data on a daily basis. On a basic care level, our EHR tracks certain patient diagnosis (creating alerts), COVID positives, pregnant females, suicide histories, and man downs. This can be extremely beneficial when attempting to complete CQI, HIV reports, or track infectious diseases. That said, I have found that same challenge that are listed above in that at times there is not a standardization and or adherence to flow. This skews the data, and thus inhibits the ability to derive conclusions due to human error, improper storage, or processing error. These all limit the integrity of the data.
We use flow sheets to track blood glucose levels. Then the provider is able to make medication adjustments based on data. However, if the clinician fails to input the data, fails to adjust the time to coincide with when the accuchecks actually occurred, or the clinician documents a fasting when it was a random check this effects the clinical significance of the data. In order to appropriately manage diabetics, it is imperative that numbers are not viewed in isolation, but are related to that individual’s trends, and prior data – this gives the data significance (Laureate, 2018).
References
Laureate Education (Producer). (2018). Health Informatics and Population Health: Analyzing Data for Clinical Success [Video file]. Baltimore, MD: Author.
McGonigle, D., & Mastrian, K. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Jones & Bartlett Learning.
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. HealthLeaders Magazine. https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs?page=0%2C1
10 months ago
Sarah Simpson
RE: Discussion – Week 5- Sarah Simpson
Benefits of Big Data in Health care
One of the biggest benefits of using Big Data, it its ability to work through various different health documents and other clinical data in an electronic health record. Big data has the advantage of compiling a large assortment of data and organizing it into descriptive analytics and other statistics needed in health care (Wang et al., 2018). The information gathered from the Big Data used allows for quicker, more efficient decision making on the parts of a business or health care system. Big data has unreal capability to predict, which will allow companies to use past and present data to make predictions about future events. In health care’s case, disease processes (Wang et al., 2018).
Challenges or Risks of Use of Big Data
When it comes to Big Data, analyzing and standardization of all data can be time intensive. If data is not standardized, data is difficult to compile and assessing information from the data can be a challenge. This could be the case for a nurse educator on a unit when they are trying to assess the work flow of their unit. If the data is difficult to work with, data collection and assessment will be a challenge for the nurse educator (Glassman, 2017).
Strategies for Improvement
In the world of data and analyzing, staff need to be properly educated in the data in which they are working with. This training can be done through the use of data mining projects, where medical educators learn and educate through a four-step process of gathering and analyzing data. The four-steps including 1) problem identification 2)exploration of the data 3)pattern discovery and 4)knowledge deployment or taking the data and comparing it to previous data to make predictions on patterns (McGonigle & Mastrian, 2017). This process places everyone on the same page, thus leading to more efficient data collection and organization.
Glassman, K. S. (2017, November). Using data in nursing practice. American Nurse Today. Retrieved December 14, 2021, from https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf.
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.
Wang, Y., Kung, L. A., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13. https://doi.org/10.1016/j.techfore.2015.12.019
10 months ago
Olga Tsoy
RE: Discussion – Week 5- reply 2
10 months ago
Josephine Smith
RE: Discussion – Week 5
Big data is defined in terms of 3 V’S. Volume, velocity and variety. Between 2001-2008, there was a surge in big data due to the need for handling massive amount of information. The idea of big data was to store massive amount of data in such a way that will be easily accessible by organization. During this time, healthcare organizations started to digitize medical 90records to increase proficiency. (Wang, 2018).
Big data is usually used by advanced practitioners to improve patient outcomes. One of the challenges of big data is the large complex data that needs to be analyzed to improve outcomes. It can be very complex and labor intensive because organization of data does not mean the same thing across systems. (Thew, 2016). A solution to this problem will be to have nurses involved in new technology and provide ide feedback. Nurses should have an input because they know what and how patient outcomes can be improved. (Glassman, 2017).
References
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse Execs. Health leaders. Retrieved December 14, 2021, from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
Glassman, K. S. (2017, November). Using data in nursing practice. American Nurse Today. Retrieved December 27, 2021, from https://www.myamericannurse.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf
Wang, Y., Kung, L. A., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13. https://doi.org/10.1016/j.techfore.2015.12.019
10 months ago
Eucharia Okolo
RE: Discussion – Week 5
One Potential Benefit of Using BIg Data in a Clinical System
One of the potential of using big data s part of a Clinical system is big is use to influence outcome that are meaningful to the nursing professionals and executive (Thew. 2016). The effective ways of managing this data can facilitate precision medicine by enable diction of heterogeneity in patient response to treatment. The potential of big data in health care relies on th ability to dictate patterns and to turn high volumes of data into actionable knowledge for precision medicine and decision making (Delaney. 2016). In light of these opportunities and potential are big deal, which can Benefit both patient and health care system.
Potential challenge of using Big data
One of the potential challenges of using big data as part of a clinical system is data integration, and organization collect data from numerous sources with can makes it hard to monitor the effectiveness of the integration process. The smallest error may prove fatal to the overall success of the process.
strategies that may effectively minimize challenge
With advancements in coding and statistical analysis, one could formulate programs that can separate consistent data from outliers making process more effective. Another way is to organize the program to have preset categories, similar in format of the multiple choice options. With the correct medical Information one can easily look up answers to the patients’ question. With data integration that enable collaboration and utilization of data across different systems will provide a comprehensive overview of patient health.
Reference
Delaney, C. W. (2016). Urgent Call for Nursing Big Data. Studies in Health Technology and Informatics, 225, 753–755.
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. HealthLeaders Media. Retrieved December 30, 2021, from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
10 months ago
Cheryl Wagner WALDEN INSTRUCTOR MANAGER
RE: Discussion – Week 5
Great informational post, Eucharia,
And nice discussion points! I noted in an earlier post that I was at the Big Data Nursing Conference at the University of Minnesota College of Nursing about a year ago – and it is pretty exciting to see that nurses are actually forming groups to address some of the issues with the electronic health records (EHRs) and nursing documentation – specifically that nurses are pretty invisible in the EHR.
The common complaint that I heard at the conference over and over was that no one ever asked nurses what would be useful to them in the EHRs – and nurses did not care because they are always feeling like they are so busy and just trying to get through the day, that they never complained about the lack of important nursing information in the records, and just did what they were told/trained to do with the EHRs. Basically most nurses chart what they are required to chart per institutional policy – like vitals, physical assessments, blood sugars, insertion of devices like intravenous lines (IVs) and all of the screening information – like for fall risk, pressure sore risk, sepsis risk, etc. Most of the time nurses are checking boxes on the record.
The sad thing is that no one charts what is going on with the patient, any conversations with the patient, any interactions with family or even patient care needs. All of that is usually given in the bedside verbal report, and so much of it is missed if for some reason the nurse forgets what she heard from the last report, or has something new to say and starts to think the report is taking too long, so cuts out the really vital information. I remember once with my students, a patient had been admitted with a lactic acid of 8 – which is darn near terminal – and after a couple of shift reports, the nurses stopped thinking that was important to mention. Although it is a long story and I am giving you the cliff notes version, ultimately that patient coded and died – septic shock that was not reversible. I believe – while I could be wrong – that had there been narrative charting on that patient, someone would have connected the dots and noticed the septic shock pattern.
It is really a crying shame, and of course nurses are all ‘too busy’ to worry about it – they just seem to want to get their job done and not have to deal with any other issues. They don’t stop to think that legally, they are liable if some major issue with the patient is not documented – like home care needs or inability to communicate or understand healthcare needs.
But more to the point, the amount of information we could learn about nursing and what nurses do to make a difference is just amazing, if we could get what we need in the EHR. We could show that we save money, we could show that we need better staffing, we could show that we can keep patients from being readmitted or from falling or from developing pressure sores, etc. TONS of stuff, really.
But we aren’t interested in helping ourselves or even worrying about the stupidity of the current EHRs.
Why is that, do you think?
Nice work!
Dr. Cheryl
10 months ago
Stanley Asafor
RE: Discussion – Week 5
Using big data in a clinical setting is helpful in various ways, including providing the ability to monitor remotely (Ayers, 2020). Big data analytics presents a wealth of potential for remote monitoring of glucose levels, medicines, activity levels, blood pressure among clients through biometric sensors and mobile data gathering applications. Using these data streams, care professionals might better manage chronically sick patients and enhance their patient involvement and quality of care by using remote monitoring support to monitor clients at home or in the hospital (McGonigle & Mastrian, 2021).
As a result, the patient has 24/7 access to care.One of the potential challenges for using big data in the clinical setting is Cybersecurity. Cyberattacks threaten patient safety since the healthcare sector relies on internet-connected technology in everything from patient treatment to record storage. Most medical records are considered to be unsecured on the internet. Systems left unprotected are often the target of hacking and data theft. The hacker may disrupt the operations of an organization. These include cloud security, unprotected mobile devices, ransomware and IoT attacks, and inexperienced users (Bresnick, 2017).
I propose to help mitigate cyberattacks by conducting a risk assessment to determine vulnerabilities (Glassman, 2017). There are several ways to reduce the organization’s cybersecurity risk, but the first step is to undertake a cybersecurity risk assessment. Performing a risk assessment may assist the firm’s IT security staff in discovering areas of vulnerability that might be exploited and then prioritize which measures should be taken first so that your organization can better safeguard its assets. We may get an up-to-the-minute glimpse of the organization’s cybersecurity posture by using a cybersecurity rating service. I have found carrying out risk assessment essential. Our organization detected the vulnerable sector and used antivirus software to prevent hackers from malicious attacks.
References
Ayers R. (2020, December 17). 5 ways the healthcare industry could use big data—and why it’s not. Dataconomy. https://dataconomy.com/2017/08/5-ways-healthcare-big-data/
Bresnick, J. (2017). Top 10 Challenges of Big Data Analytics in Healthcare. Health IT Analytics.
Glassman, K. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45-47.
McGonigle, D., & Mastrian, K. (2021). Nursing informatics and the foundation of knowledge. Jones & Bartlett Publishers.
10 months ago
Josephine Smith
RE: Discussion – Week 5 Response 1
Hi Stanley, great post. The more technology evolves, health care devices and applications evolve. Providers have better patient outcome because patients are more involved in their care with the use of devices and shareability of their health information. For example, the use of fitness trackers and tele monitors that are wearable in the future (Glassman, 2017). With better technology comes the challenge of making sure the data is secure. According to Advances in cyber security book, one of the ways to ensure secured data is by setting up a “secure execution compartment” by creating security tailored to the application, the user and the environment. (Hsu, 2013). That together with running cybers security risk assessments will be beneficial to organizations.
References
Hsu, D.F., Marinucci D. (2013). Advances in cyber security: technology, operations, and experiences (first edition). Fordham university press
Glassman, K. S. (2017, November). Using data in nursing practice. American Nurse Today. Retrieved December 27, 2021, from https://www.myamericannurse.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf
10 months ago
Kayla Joyce
RE: Discussion – Week 5
10 months ago
Mariline Corvil
RE: Discussion – Week 5
Informative post that Cybersecurity is one of the potential challenges for using big data in the clinical setting. However, big health record data has the potential to provide more decadent profiles of health and disease from birth to death, as well as from the molecular to the societal scale; accelerated understanding of disease causation and progression, the discovery of new mechanisms, and treatment-relevant disease subphenotypes, understanding health and diseases in whole populations and whole health systems (Hemingway et al. 2016). Oncology professionals expect big data to predict cancer patients with particular traits and assess the risks and advantages of various cancer treatments shortly (Naqa, Kosorok, JIn, Mierzwa & Ten Haken, 2018). Text files, which account for around 75% of an organization’s data, include a significant amount of an organization’s big data (McGonigle & Mastrian, 2017). Due to the technology needed in the healthcare system to obtain information on a global scale, the potential of a security breach is considerably raised. With the introduction of the Health Insurance Portability and Accountability Act (HIPPA), the federal government has made protected health information (PHI) a mandatory requirement.
References
Hemingway,H., Asselbergs, F., Danesh, J., Dobson, R., Maniadakis, N., Maggioni, A., van Thiel, G., Cronin, M., Brobert, G., Vardas, P., Anker, S., Grobbee, D., Denaxas, Innovative Medicines Initiative 2nd programme, Big Data for Better Outcomes, BigData@Heart Consortium of 20 academic and industry partners including ESC. (2018). Big data from electronic health records for early and late translational cardiovascular research: challenges and potential, European Heart Journal. 39(16). Pages 1481–1495, https://doi.org/10.1093/eurheartj/ehx487
McGonigle, D., & Mastrian, K. G. (2018). Nursing informatics and the foundation of knowledge. In D. McGonigle & K.G. Mastrian (Eds.). Nursing informatics and the foundation of knowledge (4th ed., p. 477). Burlington, MA: Jones & Bartlett Learning.
Naqa,I., Kosorok, M., Jin, J., Mierzwa, M., & Ten Haken, R. (2018). Prospects and Challenges for clinical decision support in the era of big data. JCO Clinical Cancer Informatics. Retrieved from https://ascopubs.org/doi/full/10.1200/CCI.18.00002.
10 months ago
Cheryl Wagner WALDEN INSTRUCTOR MANAGER
RE: Discussion – Week 5
Great informational post Stanley,
And nice discussion points! I have been commenting quite a bit in other posts about nursing’s need to get our languages into the electronic health record so that we can ‘mine’ the Big Data and generate more knowledge about nursing care and what a difference it makes.
Our biggest hurdle – I think – is getting the vendors on board to make these documentation systems useful for nursing – but over and over again, they seem to be telling everyone that it is too hard to do and will cost too much – but much worse – they say that nurses should just use everyone else’s languages so that we can ‘collaborate’.
Well there is some research out there that disproves this notion – with a finding that nurses have very different concepts in the delivery of their care. Check this out, from a research study by Boyd et al (2018):
“Physicians and nurses have worked together for generations; however, their language and training are vastly different; comparing and contrasting their work and their joint impact on patient outcomes is difficult in light of this difference. At the same time, the EHR only includes the physician perspective via the physician-authored discharge summary, but not nurse documentation. Prior research in this area has focused on collaboration and the usage of similar terminology. The finding that physician’s and nurse’s practice domains are markedly different is supported by the preliminary, quantitative evidence we found. Leveraging our documentation network and algorithms, we compare and contrast nursing and physician care and can differentiate professional contributions to patient outcomes and related and divergent concepts by each profession as distinctly different” (p. 71).
That definitely reinforces that we need our own languages to be able to adequately describe our care – and that we cannot use another profession’s languages. But how to get the vendors on board? That is the dilemma!
What do you think? I wonder what might help us to overcome this hurdle?
Nice work!
Dr. Cheryl
References
Boyd, A.D., Dunn-Lopez, K., Lugaresi, C., Macieira, T., Sousa, V., Acharya, S., …….. Di Eugenio, B. (2018). Physician nurse care: A new use of UMLS to measure professional contribution: Are we talking about the same patient a new graph matching algorithm? International Journal of Medical Informatics, 113, 63-71.
10 months ago
Stanley Asafor
RE: Discussion – Week 5
10 months ago
Hannah Brosnahan
Initial Discussion – Week 5
10 months ago
Marco Paolo Delmonte
RE: Initial Discussion – Week 5
Thank you for your post, Hannah,
I agree with your post, there are several ways to safeguard the protected health information (PHI) of our patients. There are always risks, whether you are accessing paper charts or Electronic Health Records (EHR). Anyone accessing EHR should do the necessary steps to protect PHI. I believed EHR has an advantage in protecting PHI over paper charting. Some features that EHR provides are requiring a password to log in, giving reminders that you are accessing charts you are not supposed to be accessing, and alerts users when they are pasting information from one patient chart to another. There are more features out there. One of the main focuses of EHR is the privacy and security of patient information (Kruse, 2017).
Most facilities now use EHR and the main access is through a computer. It is our responsibility to protect PHI. Yes, passwords are very important, and they should not be shared with anyone. It needs to be individualized and is now suggested to include numbers and special characters. We can also make sure that our computers are not facing people who are not supposed to view them. Privacy screens are also very good and always make sure you log out when stepping away from your computer. Two major pillars of medical ethics are privacy and confidentiality, and the enactment of the Health Insurance Portability and Accountability Act (HIPAA) has been the guiding act to protect them (Kayaalp, 2018).
References:
Kayaalp, M. (2018). Patient Privacy in the Era of Big Data. Balkan Medical Journal, 35(1), 8–17. https://doi.org/10.4274/balkanmedj.2017.0966
Kruse, C. S., Smith, B., Vanderlinden, H., & Nealand, A. (2017). Security Techniques for the Electronic Health Records. Journal of Medical Systems, 41(8). https://doi.org/10.1007/s10916-017-0778-4
10 months ago
Eucharia Okolo
RE: Initial Discussion – Week 5
Hi, Hannah
Great post. Yes there are many reasons clinicians and scientists prefer big data sets. It also offers the knowledge required for health care providers to streamline customers service processes that customize health care and create best practices for communicating with client (Pal et, 2021) ) .Nearly every department in a company utilize findings from big data analysis but handling its clutter and noise can pose problem. However, there is a wide range of techniques currently available , ranging form intuitive exact match to very complex matching techniques with adjustable cost of errors.(Molinari & Nollo 2020)
Referencce
Pal, S. K., Mukherjee, S., Baral, M. M., & Aggarwal, S. (2021). Problems of Big Data Adoption in the Healthcare Industries. Asia Pacific Journal of Health Management, 16(4), 282–287. https://doi.org/10.24083/apjhm.v16i4.1359
Molinari, A., & Nollo, G. (2020). The quality concerns in health care Big Data. 2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON), Electrotechnical Conference ( MELECON), 2020 IEEE 20th Mediterranean, 302–305. https://doi.org/10.1109/MELECON48756.2020.9140534
10 months ago
Marco Paolo Delmonte
RE: Discussion – Week 5
10 months ago
Cheryl Wagner WALDEN INSTRUCTOR MANAGER
RE: Discussion – Week 5
Nice post, Marco,
And nice discussion points!! I was at the Big Data Conference at the University of Minnesota College of Nursing in June 2019 and hopefully will be at another one this coming June 2022 – unless cancelled by COVI19 ☹ – but it is pretty exciting to see that nurses are actually forming groups to address some of the issues with the electronic health records (EHRs) and nursing documentation – specifically that nurses are pretty invisible in the EHR. Basically most nurses chart what they are required to chart per institutional policy – like vitals, physical assessments, blood sugars, insertion of devices like intravenous lines (IVs) and all of the screening information – like for fall risk, pressure sore risk, sepsis risk, etc., but no one charts what is going on with the patient, any conversations with the patient, any interactions with family or even patient care needs. Most of the time nurses are checking boxes on the record. It is really a crying shame, and of course nurses are all ‘too busy’ to worry about it – they just seem to want to get their job done and not have to deal with any other issues. They don’t stop to think that legally, they are liable if some major issue with the patient is not documented – like home care needs or inability to communicate or understand healthcare needs.
But more to the point, the amount of information we could learn about nursing and what nurses do to make a difference is just amazing, if we could get what we need in the EHR. We could show that we save money, we could show that we need better staffing, we could show that we can keep patients from being readmitted or from falling or from developing pressure sores, etc. TONS of stuff, really.
But we aren’t interested in helping ourselves.
Why is that, do you think?
Nice work!
Dr. Cheryl
10 months ago
Kealiiaumoku Klein
RE: Discussion – Week 5
Hi Marco,
I think that it is very human to dislike something new; especially when you have grown accustomed to a certain way of doing things. We experienced similar push back from the nurses in my facility with a major overhaul to EPIC recently. The entire interface changed including where we would typically locate patient data such as demographics and to do lists. Many of the nurses either disliked the change entirely or were uncertain about it. Keeping in mind that not everyone would usher in this change with open arms, we were given the choice to flip between the old interface and the new one. It certainly seems that after several months many of the same nurses who were complaining about it have actually taken to it. In my opinion, change is something to be embraced. A few helpful tips for nurses who are transitioning from an old system to a new one include taking your time; playing with the new system; and remembering that the goal is improved communication and safe, efficient, quality care (Rosiak, 2012). Another way to help with these transitions might be to frame one’s thinking around nursing values. Specifically, the ethical value of individual and professional competency that was identified by Shahriari et al. (2013) in their literature review really comes to bear on the need for adaptive EHRs. By their definition, individual competency involves the nurse’s use of evidence-based practices and staying up to date. EHRs can tie clinical protocols/practices with the literature that supports their use which fosters the growth of a nurse knowledge worker.
References
Rosiak, NP, J. (2012). Tips for Transitioning to a New Electronic Health Record System. Journal of the Advanced Practitioner in Oncology, 3(5). https://doi.org/10.6004/jadpro.2012.3.5.6
Shahriari, M., Mohammadi, E., Abbaszadeh, A., & Bahrami, M. (2013). Nursing ethical values and definitions: A literature review. Iranian journal of nursing and midwifery research, 18(1), 1–8.
10 months ago
Eucharia Okolo
RE: Discussion – Week 5
10 months ago
Kealiiaumoku Klein
RE: Discussion – Week 5
10 months ago
Cynthia Kadiri
RE: Discussion – Week 5
One potential benefit of using big data in clinical system
Electronic health record is electronic version of paper documentation, the complexity of big data analysis from combining different types of information which are electronically captured, data can be collected from electronic health care records , patient summaries genomics and pharmaceutical data. Clinical trails , telemedicine , mobile aps , sensors . Benefits include constant monitoring of a patient’s vital signs, symptoms monitoring, quality can be achieved more efficiently with the use of big data, it can provide a clear audit trail of clinical data that was recorded over time this will then result in shorter wait time and a more accurate way of diagnosing and treatment and reduce errors. Big data analysis gives health care providers clinical insight which may be difficult to obtain on paper which may not be readily available, it reduces the wait time enables the provider to make accurate clinical decision where by eliminating guesswork .
Potential Challenges of big data
Some of the challenges include human error employees imputing data must be properly trained to input data, if data is not accurately put in data this can lead inconsistency and result in errors in care and management of the patient . Lack of security is another problem that can be encountered, the medical record can be viewed by various other vendors who may have access to the EMR .
Strategy to effectively manage dangers of big data
One strategy that can be utilized to manage dangers of big data is continuous staff education and ongoing in-service for competencies. regular monitoring and oversight to ensure data is entered correctly to avoid errors
References
Hopp W.J. Li J Wang G big data and the precision
Mcgonigle , D & Mastrian , K (2017)
Nursing informatics and the foundation of knowledge 4th ed.
10 months ago
Ashley Brimhall
RE: Discussion – Week 5
Cynthia,
I agree with your assertion that human error, or input, creates a challenge for analyzing big data. Nurses document vitals, assessments, medication administration, communication between caregivers, families, providers, and various departments. Inevitably there will be some errors in the massive amount of data being input. As knowledge workers, nurses assess all of a patient’s data to determine what is pertinent, and their determination has implications that can have on patient care (Thew, 2016). Errors in documentation can prevent a nurse from noticing abnormalities and concerning changes. Ensuring timely, accurate documentation of all pertinent data creates a more complete picture of individual and organizational trends that can facilitate changes in policy or plan of care.
Refereces
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse Execs. Health leaders. Retrieved December 14, 2021, from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
10 months ago
Eucharia Okolo
RE: Discussion – Week 5
10 months ago
Cheryl Wagner WALDEN INSTRUCTOR MANAGER
RE: Discussion – Week 5
Great informational post Cyntha,
And nice discussion points! – although your post is a little brief. I have been commenting quite a bit in other posts about nursing’s need to get our languages into the electronic health record so that we can ‘mine’ the Big Data and generate more knowledge about nursing care and what a difference it makes. Our biggest hurdle – I think – is getting the vendors on board to make these documentation systems useful for nursing – but over and over again, they seem to be telling everyone that it is too hard to do and will cost too much – and worse – that nurses should just use everyone else’s languages so that we can ‘collaborate’.
Well there is some research out there that disproves this notion – with a finding that nurses have very different concepts in the delivery of their care. Check this out, from a research study by Boyd et al (2018):
“We found that only 26% of patients had synonyms (identical Unified Medical Language System [UMLS] or Concept Unique Identifiers [CUIs]) between the two professions’ documentation. On average, physicians’ discharge summaries contain 27 terms and nurses’ documentation, 18. We found an average of 4 terms related (distance less than 2) between the professions, leaving most concepts as unrelated between nurse and physician care. Our hypothesis that physician’s and nurse’s practice domains are markedly different is supported by the preliminary, quantitative evidence we found….. to compare and contrast nursing and physician care on a single patient, enabling a more complete picture of patient care. We can differentiate professional contributions to patient outcomes and related and divergent concepts by each profession” (p. 71).
That definitely reinforces that we need our own languages to be able to adequately describe our care – and that we cannot use another profession’s languages. But how to get the vendors on board? That is the dilemma!
What do you think? I wonder what might help us to overcome this hurdle?
Nice work!
Dr. Cheryl
References
Boyd, A.D., Dunn-Lopez, K., Lugaresi, C., Macieira, T., Sousa, V., Acharya, S., …….. Di Eugenio, B. (2018). Physician nurse care: A new use of UMLS to measure professional contribution: Are we talking about the same patient a new graph matching algorithm? International Journal of Medical Informatics, 113, 63-71.
10 months ago
Cynthia Kadiri
RE: Discussion – Week 5
10 months ago
Tinsae Berhe
RE: Discussion – Week 5
Discussion: Big Data Risks and Rewards
one potential benefit of using big data as part of a clinical system
As technology rapidly changes, the volume of data has increased in many settings. The application of big data in the clinical system has brought many benefits such as healthcare quality improvement, reducing medical errors, lowering cost, diagnosing diseases quickly and accurately, saving time, and more. According to Thew, “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 is not integrated” (Thew, 2016). The use of big data expands the clinician’s knowledge, gives greater insight and ideas that can benefit both the patient, clinicians, and the organization. Per Mcgonigle, D., and Mastrian, K., the evolution of data mining methods made it possible to navigate data in real-time. Using data mining tools allowed them to scan databases and identify previously hidden patterns Mcgonigle, D., & Mastrian, K. (2017).
one potential challenge or risk of using big data as part of a clinical system
One of the challenges of using big data would be having insufficient knowledge using technology appropriately. Due to that, datasets can get lost, medical and medication errors can happen. According to Wang et al.’s ( 2018) article, Evidence shows that only 42% of healthcare organizations surveyed are adopting rigorous analytics approaches to support their decision-making process; only 16% of them have substantial experience using analytics across a broad range of functions. As vultures circle in the sky looking for a dead animal, so do hackers waiting to raid on unsecured data. Having secured data protects the organization and patients, and professional workers. Doing so will reduce another challenge.
the strategy that may effectively mitigate the challenges or risks of using big data
Not having adequate knowledge of computers or data storage is one of the challenges I have encountered at the organization I work for. One strategy I have experienced that may effectively mitigate the challenges or risks of using big data is providing proper training by a skilled professional such as a nurse informaticist. Implementing a user-friendly computer system will benefit both the clinician and patient.
References
Mcgonigle, D., & Mastrian, K. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Jones & Bartlett Learning.
Thew, J. (2016, April 19). Big data means considerable potential, challenges for nurse Execs. Health leaders. Retrieved December 14, 2021, 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. Technological Forecasting and Social Change, 126, 3–13. https://doi.org/10.1016/j.techfore.2015.12.019
10 months ago
Cynthia Kadiri
RE: Discussion – Week 5
Hi Tinsae
nice post Nurses are the most important member of the health care , they are the largest group of health care , nurses must be well informed to be able to make good and informed practice decision, nurses need access to aggregate data about their patients and the impact of their care , they need to know how to interpret that data( Classman. K.S) Nurses do most of the documentation like assessment , Vital signs , care plan and other pertinent information needed for successful patient outcome.
It is imperative that nurses get properly trained to be able to use good critical thinking and skills for making an appropriate interpretation of the result (wang et al) this will help to prevent errors relevant. Key players like the managers who in turn will support the nurses should be adequately trained.
References
Glassman , K.S. (2017) using data in nursing practice . American Nurse Today
Wang, Y., King, L. & Byrd,, TA. (2018)
10 months ago
Eucharia Okolo
RE: Discussion – Week 5
Hi, Tinsae
Nice post , I think big data has many benefits , but there are some challenges of big data , these include data quality, Storage and lack of data science Professionals validating data, and accumulating data from different sources(Lv,et al 2020) As these data sets grow exponentially with time , it gets extremely difficult to handle. And that is why i think they should have a data Professionals who are experience in working with tools and making sense out of huge data sets because the future of health care practice will depend upon the leverage of big data analytics to analyze and handle massive amounts of disparate, unstructured and structured data sources.(Wang & Jones 2019)
References
Wang, L., & Jones, R. (2019). Big Data, Cybersecurity, and Challenges in Healthcare. 2019 SoutheastCon, SoutheastCon, 2019, 1–6. https://doi.org/10.1109/SoutheastCon42311.2019.9020632
Lv, Z., & Qiao, L. (2020). Analysis of healthcare big data. Future Generation Computer Systems, 109, 103–110. https://doi.org/10.1016/j.future.2020.03.039
10 months ago
Sarah Simpson
RE: Discussion – Week 5-Tinsae Berhe
Tinsae- I couldn’t agree more with you on this post.
I think one of the biggest issues we have today with our electronic health records(EHR) is the lack of education on learning the EHR properly. Many nurses that I have come across, especially of the older generation choose to get by with their knowledge of the systems leading to poor documentation and inefficient charting. At my hospital, we are required to complete “training” when we first start, but that is all of the knowledge we get before we start on the floor. We will get the occasional emails with changes to the system. This all needs to be changed. Due to poor implementation of technology on behalf of a hospital can continue the wave of not seeing the benefits of using the EHR correctly and overall negative perception of using technology (Adedejie, et al.,2018). Discussion: Big Data Risks and Rewards Constant, continued education on a health care system’s technology is needed for reinforcement of the features used in a system. EHRs are constantly changing, health care systems need to keep their staff in check and using their system properly. Poor charting leads to poor data to use for analyzing trends of a hospital or inpatient unit. Preventative analytics is often used by inpatient unit managers to show trending information for readmissions or preventative care on there unit (Wang et al., 2018). Proper documentation needs to be implemented by the nursing staff for this data to be helpful for the nurse manager.
Adedeji, P., Irinoye, O., Ikono, R., & Komolafe, A. (2018). Factors influencing the use of electronic health records among nurses in a teaching hospital in Nigeria. Journal of Health Informatics in Developing Countries, 12(2), 1–20.
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.
10 months ago
Marco Paolo Delmonte
RE: Discussion – Week 5
Thank you for your post, Tinsae,
I was just talking to a family friend who was a nurse for at least 25 years, and yes, she worked for the same skilled nurse facility since getting her license. About 5 years ago, they received a memo from their management informing them that they are switching to EHR from paper charting. She did not quit right away, she tried to get trained. She was so used to paper charting she was not comfortable with EHR. She was having a hard time with technology, she said. She was willing to learn, and she agrees that there are advantages in transitioning to EHR but claims their management did not give them proper training and support. She was scared she might make an error, affect the patient’s care, and lose her license. The prudent application of EHR system can improve the quality of care but can risk the patient if applied incorrectly (Zandieh et. al, 2008). She tried to find another job, but most facilities were already using EHR. She then decided to just retire.
I agree with you, proper training is very important. It is also very important to make sure that there is support available after the training. At the facility where I used to work, we had superusers on almost every shift to support nurses, especially new employees who are new to the EHR system we are using. An appropriate approach like adequate training is detrimental in increasing healthcare workers’ satisfaction and highly decreases errors (Aguirre et. al, 2018).
References:
Aguirre, R. R., Suarez, O., Fuentes, M., & Sanchez-Gonzalez, M. A. (2019). Electronic Health Record Implementation: A Review of Resources and Tools. Cureus. https://doi.org/10.7759/cureus.5649
Zandieh, S. O., Yoon-Flannery, K., Kuperman, G. J., Langsam, D. J., Hyman, D., & Kaushal, R. (2008). Challenges to EHR Implementation in Electronic- Versus Paper-based Office Practices. Journal of General Internal Medicine, 23(6), 755–761. https://doi.org/10.1007/s11606-008-0573-5
10 months ago
Ashley Brimhall
RE: Discussion – Week 5
Benefit
Big data allows leadership to view trends. These might be in clinical assessment, patient outcomes, workforce productivity, or other business objectives. According to Wang, Kung, and Byrd this process has, “evolved from business intelligence and decision support systems 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” (2018). Tools that analyze large data, with sophisticated functionalities, allow for clinical information integration and improvement in organizational insights. From this, businesses foresee patients’ needs and market trends to improve both quality of care and financial performance (Jiang et al., 2016)
Challenge
One of the biggest challenges of big data is the ability to analyze information efficiently. “When a CNE is analyzing and synthesizing data, it’s typically done manually and is a very time- and labor-intensive process…” (Thew, 2016). I have experienced this in one of my current nursing roles. The process for triaging health needs requests, or HNRs, requires the patient to submit a form on a tablet, where it is transmitted to a J-pay program. From there it is manually triaged by a nurse and entered into the emar. After that, a nurse must see the patient and appropriately refer the patient to mental health. A mental health clerk then reviews these referrals and schedules patients within the required timeframes. Finally, a mental health clinician goes to see the patient in person. These are just the steps for the patient to be seen initially. Later in the process, greater quantities of data are generated and handled by providers, nurses, techs, and records clerks. As expected human error makes analysis of the data fallible.
Strategy
In an attempt to rectify this challenge, several excel spreadsheets are generated for mental health nurse auditing. These sheets include pertinent information that allows the nurse to quickly review all HNRs for key mental health terms that may have been mis-triaged or referred incorrectly.
References:
Jiang, P., Winkley, J., Zhao, C., Munnoch, R., Min, G., & Yang, L. T. (2016). An intelligent information forwarder for healthcare big data systems with distributed wearable sensors. IEEE Systems Journal, 10(3), 1147–1159. Retrieved December 28, 2021, from https://doi.org/10.1109/jsyst.2014.2308324
Thew, J. (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. A. (2018). Big data analytics: Understanding its capabilities and
potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126(1), 3–13.
10 months ago
Silvanus Manduku
RE: Discussion – Week 5
Such an insightful yet profound argument from a colleague hints at the in-depth understanding of the topic. It’s commendable to mention and incorporate a leadership perspective. In no question, organizational insights, as well as trends, are better traced from data. I lean on the opinion that big data has turned out to be a determinant of how nurses operate in terms of practice, learning and conducting research. All these nursing elements present implications for the future – Both benefits and challenges.
As you have clarified in the discussion, an efficient way to analyze information is unavailable. According to Thew (2016), figuring out how to synthesize data is challenging for nurses. Although backup excel sheets are a great way to enhance data analysis, nurses and data personnel need to learn ‘effective’ data visualization techniques. Furthermore, embracing artificial intelligence in data systems will yield data competencies. By doing so, the nurses of the future will find an effective data system. The same will also contribute to improved outcomes alongside quality health.
Additionally, still on matters big data opportunities and risks, the healthcare fraternity have already witnessed how far data can go in impacting the nurses, patients, researchers and doctors. Behind big data, there is patient satisfaction (Adibuzzaman et al., 2017). However, approaches to big data need regular evaluation to keep up with the trends.
To a larger extent, big data requires data-survey nurses. The challenges being experienced in matters of data in healthcare can be dealt with by having the nurses familiarize themselves with devices and systems used to handle data (Adibuzzaman et al., 2017). Perceptively, all nurses need to be well-aware of the data processing procedures. Notably, the systems put in place should be capable of discovering relevant trends, warnings and structured patterns. Collectively, all these measures add up to sound risk mitigation strategies. Ultimately, big data will be promoted by far.
References
Adibuzzaman, M., DeLaurentis, P., Hill, J., & Benneyworth, B. D. (2017). Big data in
healthcare–the promises, challenges and opportunities from a research perspective: A case study with a model database. In AMIA Annual Symposium Proceedings (Vol. 2017, p. 384). American Medical Informatics Association.
Thew, J. (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
10 months ago
Cheryl Wagner WALDEN INSTRUCTOR MANAGER
RE: Discussion – Week 5
Nice post, Ashley,
And nice discussion points!! I was at the Big Data Conference at the University of Minnesota College of Nursing in June 2019 and hopefully will be at the another one this coming June 2022 – unless cancelled by COVI19 ☹ – but it is pretty exciting to see that nurses are actually forming groups to address some of the issues with the electronic health records (EHRs) and nursing documentation – specifically that nurses are pretty invisible in the EHR. Basically most nurses chart what they are required to chart per institutional policy – like vitals, physical assessments, blood sugars, insertion of devices like intravenous lines (IVs) and all of the screening information – like for fall risk, pressure sore risk, sepsis risk, etc., but no one charts what is going on with the patient, any conversations with the patient, any interactions with family or even patient care needs. Most of the time nurses are checking boxes on the record. It is really a crying shame, and of course nurses are all ‘too busy’ to worry about it – they just seem to want to get their job done and not have to deal with any other issues. They don’t stop to think that legally, they are liable if some major issue with the patient is not documented – like home care needs or inability to communicate or understand healthcare needs.
Plus, it is pretty appalling that nurses do not chart their nursing care – pretty much, nurses have all decided that they are too busy – or whatever excuse they use – to use the gold standard of nursing care – the care plan! Can you imagine? Nurses do not want to let anyone know that they are in charge of the care of that patient. I find that amazing – well actually astounding is a better word. Most of the nurses – including quite a few in my graduate level nursing classes – want to document everything and anything EXCEPT what kinds of nursing care they have delivered to the patient. Go figure.
But more to the point, the amount of information we could learn about nursing and what nurses do to make a difference is just amazing, if we could get what we need in the EHR – meaning nursing care plans – and then get nurses to use them to document their care. We could show that we save money, we could show that we need better staffing, we could show that we can keep patients from being readmitted or from falling or from developing pressure sores, etc. TONS of stuff, really.
But we aren’t interested in helping ourselves.
Why is that, do you think?
Nice work!
Dr. Cheryl
10 months ago
Klara Handrock
RE: Discussion – Week 5
Ashley-
Big data has huge implications for the future of healthcare and patient outcomes. As you mentioned, efficiency can be a challenging component of big data. The quality and thus the integrity of the data can also prove to be challenging. What information is being reviewed? Nurses are the primary healthcare individuals that are entering information, or data points into the EHR (Glassman, 2017). That said, are they consistently documenting matters such as medication compliance, availability of support system, or comprehension level? When looking at big data it is imperative that nursing is knowledgeable about what is and what is not in the data, and the implications that can have on patient care (Thew, 2016).
Nurses need to continually become more informed as technology and big data continues to drive patient care plans. The nursing profession needs to have a voice in what smart phrases, workflows, and data is being used. They need to be aware what data points are being pulled to determine efficacy and plan of care (Glassman, 2017). Nurses are advocates for patient care and being well versed in informatics, and being actively involved in big data is going to be instrumental in patient outcomes.
References
Glassman, K. (2017, November). Using data in nursing practice. American Nurse Today.
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. HealthLeaders Magazine. https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs?page=0%2C1
10 months ago
Silvanus Manduku
RE: Discussion – Week 5
Big Data Risks and Rewards
Regardless of the setting, loads of data are collected each day to facilitate the smooth flow of activities. The adoption of such massive information is made possible by the presence of digital technologies. Today, the healthcare sector is among the leading sectors in embracing big data – Complex data sets containing a variety of information. In a bid to ensure effective management of the performances in a hospital, big data is considered the solution towards influencing outcomes (McGonigle & Mastrian, 2017). Failure to use big data makes healthcare organizations stick to traditional technologies, which are not reliable in handling voluminous data. Nevertheless, big data has far-reaching risks and rewards.
Of the many benefits emanating from big data in nursing, big data leads to improved health outcomes (Shilo et al., 2020). Precisely, the massive data stored in the databases serve as a source of useful information for nursing professions. With the accessible data, nurses rely on big data for decision making – Clinical Decision Support. Healthcare professionals can make quick decisions on the spot (Thew, 2016). Furthermore, prescriptive decisions become easier to make. Consequently, this hints at the crucial functionality of big data and analytics. It’s already a trend in care facilities. From experience and observation, I was able to modify treatment for mentally ill patients, thanks to big data. In yet another instance, a patient’s blood pressure had increased alarmingly. However, a real-time alert was delivered to help administer treatment. This is enough evidence that big data has come to facilitate better treatment approaches.
As confirmed by Shilo et al. (2020), the benefits of big data in nursing override the challenges, some risks associated with big data have proved to persist. Even with the many years of reliance on big data, there still lacks clarity of data interaction in the system. It’s hard for nurses to figure out the much-needed standardization of data across all data centres and departments. For this reason, it becomes a nightmare to make informed treatment decisions while relying on big data. An excellent example is when I had to prescribe for a drug addict. Across the shared database, substantial prescription information was substandard. The same shows that not all nurses are committed to double accountability. Thus, it’s a hustle to have errorless information in matters of big data. In such a case, the existence of inaccurate data turns out to be a health hazard. According to Thew (2016), nurses and nurse leaders drown in data when variable information is left out in the data. This attracts the dire need to register improvements in big data.
The challenges and risks linked to big data in the clinical systems can be wiped off through infrastructural development; Tools and personnel to collect data. The tools or rather systems used to collect and store information must be modern and updated regularly (Shilo et al., 2020). Also, utilizing electronic health records (EHRs) is a must-do. As for data collection personnel, it’s the nurses who should prioritize quality data; Health history, personal information, ethnicity, age and other critical parameters. A great way to realize this quest is to embrace more nursing informaticists. For instance, nurses should be trained on flow, attention, analysis and syncing of data. While working at Gateway PAC Rehabilitation, integration of data was done for all collection points. This reduced redundancy and at the same time improved efficiency. As such, getting much from big data takes the collaboration of all health care staff.
References
McGonigle, D. & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge
(4th edition.). Burlington, MA: Jones & Bartlett Learning.
Shilo, S., Rossman, H., & Segal, E. (2020). Axes of a revolution: challenges and promises of big
data in healthcare. Nature medicine, 26(1), 29-38.
Thew, J. (2016). Big data means big potential, challenges for nurse execs. HealthLeaders Media.
Retrieved December 29, 2021, from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
10 months ago
Tokunbo Allen
RE: Discussion – Week 5
Response # 2
hello Silvanus
i agree with your concept of data collection ,
Big data within the context of health care refers to all the data generated from interactions between stakeholders and health care systems. In fact, they are information collected from medical devices, pharmaceutical research, mayor records, genomic sequencing, medical imaging, and electronic health records. Other sources of big data include public records, search engines, smart phones, government agencies, patient portals, and research studies (Tavazzi, 2019). Big data is useful for the health care industry. In this case, appropriate software and data analysis tools can be leveraged to determine trends and themes in the big data, which would then act as actionable information that informs advancements such as cost reduction, improved safety, better care outcomes, and value-based health care.
Reference
Adibuzzaman, M., DeLaurentis, P., Hill, J. & Benneyworth, B. (2017). Big data in healthcare – the promises, challenges and opportunities from a research perspective: A case study with a model database. AMIA Annual Symposium Proceedings Archive, 2017, 384-392. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977694/pdf/2731403.pdf NURS 6051C Discussion: Big Data Risks and Rewards Essay
Dash, S., Shakyawar, S. K., Sharma, M. & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6, Article number 54. DOI: 10.1186/s40537-019-0217-0. Retrieved from https://journalofbigdata.springeropen.com/articles/10.1186/s40537-019-0217-0
10 months ago
Tina Haslett
RE: Discussion – Week 5
Big data in healthcare can be described as information amassed from all recorded interactions with technology. Big data is a source of invaluable medical information in healthcare. This unstructured massive volume of data is organized by software designed to handle large amounts of data and then analyzed and transformed into data used for managing patient care (Wang et. al, 2018). One potential benefit of big data is applying it for meaningful use to improve patient outcomes and population health (Glassman, 2017). According to Wang et. al. (2018), nursing staff provide a large amount of big data in healthcare by charting all aspects of patient care in electronic health records (EHR). One risk of utilizing big data as part of a clinical system is that the majority of data is in the form of text files and useful information may be difficult to recognize (McGonigle & Mastrian, 2017). Useful trends can be identified in unstructured data by utilizing data mining. These trends identified by data mining can then be used for research purposes (MCGonigle & Mastrian, 2017). Nursing informaticists have the perfect skill set to excel with big data.
References
Glassman, K. S. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45-47. Retrieved from://www.americannursetoday.com/wp-content/uploads/2017/11/and11-Data-1030.pdf
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: 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.
10 months ago
Cheryl Wagner WALDEN INSTRUCTOR MANAGER
RE: Discussion – Week 5
Wow, Tina,
This is a pretty short post – although some nice discussion points! You may want to update it and add quite a bit more – largely because most of what you have posted is cited statements – nothing of what you think. And of course remember you have to have 76% or more of submitted work – including discussion posts – in your own words.
Anyway, I have been noting in other posts that nursing really can benefit from Big Data; however, we have a few hurdles to overcome, and they are pretty large. According to Westra et al (2015) “There is wide recognition that, with the rapid implementation of electronic health records (EHRs), large data sets are available for research. However, essential standardized nursing data are seldom integrated into EHRs and clinical data repositories. There are many diverse activities that exist to implement standardized nursing languages in EHRs; however, these activities are not coordinated, resulting in duplicate efforts rather than building a shared learning environment and resources” (p. 600).
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That is a BIG problem for us, and I think that we need to coordinate our efforts, as Westra et al (2015) note, and try to build that needed language. I was at the Big Data conference in Minneapolis – in June of 2019 [the 2020 meeting was cancelled due to COVID ☹] but there are plans for a June 2022 – and there are efforts being made, but very slowly. I think at the rate that the electronic health record (EHR) is being changed and advanced and morphed, we might never be able to catch up if we don’t do something soon. It might get to the point that the vendors will say, nope, we don’t have a need to change anything for nurses – just make due with what is there.
I was thinking maybe if we could somehow coordinate all the efforts of the nurse informaticists and have them sit down with the existing languages and just go with one, that might help. Or as my husband is prone to say – pretty soon the government will step in and demand that the records all be identical – as many of the European countries do now – for ease of billing, reading and using. And guess what languages those countries use – North American Nursing Diagnosis Association International (NANDA-I), Nursing Outcomes Classification (NOC) and Nursing Interventions Classification (NIC). For many of the European countries, Japan, Brazil, and others, their governments just mandate that standardization be used, with some even going so far as to name the languages they want in the health record.
Anyway, what do you think? What kinds of things can we do to help solve this mess?
Nice work!
Dr. Cheryl
References
Westra, B.L., Latimer, G.E., Matney, S.A., Park, J., Sensmeier, J., Simpson, R.L., ……. Delaney, C.W. (2015). A national action plan for sharable and comparable nursing data to support practice and translational research for transforming health care. Journal of the American Medical Informatics Association, 22(3), 600–607.