Potential benefit of Big Data
The nursing industry continues to advance with the proper use of research and data. By advancing patient care, we can improve patient outcomes by reviewing and analyzing statistical data. Numerous data in ample information necessitate careful analysis due to their frequently complex content. Thanks to big data, nurses can review large amounts of data in an organized manner. Nurses can evaluate the efficacy of their patient interventions through extensive data analysis and then make the necessary adjustments to improve patient outcomes. Analytical capabilities in healthcare can find treatment patterns and extract links from vast amounts of medical data, providing a broader perspective for evidence-based clinical practice (Wang, Kung, and Byrd, 2018). Using big data daily can help nurses improve patient care interventions and outcomes. To monitor and assess patient risk and restraint behaviors, the psychiatric hospital where I work conducts extensive data analysis. We utilize electronic clinical record information to finish calculation sheet data sets on month-to-month, quarterly, and yearly premises. After that, additional care analysis is performed using these databases.
Additionally, we compare our facility’s data to our affiliated local hospital and sister programs. Access to this data makes it possible to plan future interventions and modify patient care using big data. In our program, integrated documentation includes all patient risk assessments, including self-harm, suicidal, and homicidal ideation. We can monitor a patient’s safety as well as the program’s overall safety standards while they are enrolled in our program. We then compare these levels across all residential programs and the inpatient units at our affiliated psychiatric hospital to evaluate policy and make any necessary adjustments.
BUY PLAGIARISM-FREE WORK HERE
Potential Challenge of Using Big Data
One of the biggest obstacles to using big data in a therapeutic system would be the possibility of human error. The technology we use to analyze and document clinical data was designed to work well with the data we input. When entering our data, we must adhere to the correct procedures to avoid making mistakes in the future. In the data review I previously described, the risk is currently only recorded by personnel in the nursing department. We supervise the inclusion of patient risk assessments in the subsequent data reviews. Our monthly assessments do not automatically include restraints and risk assessments that a nurse records in her shift documentation. We review each chart, and this information is passed on to the following link in our review chain. When transferring this documentation to a spreadsheet, a nurse could easily overlook it or enter it incorrectly. Every piece of documentation needs to be clear and precise. Although incorporating big data into nursing practice may result in positive outcomes, we must ensure that the available technologies are utilized appropriately.
Plan to deal with This Challenge
There are several ways to reduce the likelihood of human error when working with big data. To ensure the accuracy of the data we are analyzing, we have enhanced our facility’s data research method with several additional features. There is a possibility of human error beginning with the entry of each shift note and continuing throughout the entire review process. The best option would be a database that automatically populates with information from each recorded shift note. Although that might be a solution in the future, we must be careful to avoid mistakes now. When working with a lot of data, it is essential to ensure that it is entered correctly and consistently. The nurses are manually entering our risk data in our designated areas. In these facilities, each nurse receives ongoing instructions on accurately recording risk information and entering it into patient safety databases. We have incorporated evidence-based risk evaluations into the selected paperwork to guarantee that the risk conditions meet standard hospital requirements. McGonigle and Mastrian (2017) claim that by creating a single, comprehensive database, healthcare organizations can enhance interprofessional relationships while still adhering to privacy regulations. In all nurse meetings and communications, we emphasize the significance of accurate nursing record-keeping. Additionally, we have discussed and implemented strategies to lessen the likelihood of errors occurring at that time. By providing nurses with quiet areas to record their notes and then review the data, we have been able to evaluate and implement these data review strategies in our practice.
References
McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning.
Thew, J. (2016). Big data means significant potential challenges for nurse execs. Health Leaders Media. Retrieved https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execsLinks to an external site.
Wang, Y., Kung, L., & Byrd, T.A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13.
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.
-
BIG DATA RISKS AND REWARD
“Big data” refers to the enormous data sets that produce substantial facts as compared to smaller groups of the same data output that are not integrated. An individual’s first activity upon waking up is often data entry. They’ve finished reading updates from friends and relatives on social media and turned off their phone’s alarm. Today, data entry is essential to almost every aspect of our lives. These things—shopping, social media, and smart devices—create data and statistics. The gathered information will be used to advance healthcare technologies and delivery systems. It is vital to improve and grow the use of big data in healthcare because it changes how doctors and other multidisciplinary teams care for patients. The application of big data in the medical field has proven revolutionary. According to Thew (2016, April l9), the forms of data analytics that have been proposed have been constrained by an inability to grasp how this data interacts throughout the system.
BENEFITS OF BIG DATA IN CLINICAL SYSTEM
Some doctors are known to have unreadable handwriting. Due to the widespread use of cutting-edge technology in the medical field, medication errors have gone down. As one way that big data has made the clinical system better, the number of wrong prescriptions has gone down. According to the Center for Pharmaceutical Evaluation and Research (n.d.), the FDA receives more than 100,000 reports annually connected with a suspected medication error; reducing these errors improves results and saves lives. Every year, approximately 7 million people in the United States are affected by these errors. As a result, 7,000 people lose their lives, according to the Center for Drug Evaluation and Research (n.d.).
STRATEGIES TO EFFECTIVELY ALLEVIATE CHALLENGE.
The greatest worry is a breach in security. Around 25 million patient records may have been compromised in the first half of 2019 (Davis, 2019). Because of help from outside sources. A possible tactic is restricting patient access to the organization’s in-house interdisciplinary team. No outdoor group should be privy to a patient’s medical records because of the sensitive nature of their information. Personal information misuse can have serious repercussions. It would seem harmless to give experts access to patient’s records, but what about giving the entire group of specialists working in practice that kind of access? That would cause trouble on the inside. If you want to get this fixed, you need to hire a big data computing business that knows what they’re doing and has the security measures in place to protect your data. Employees should be reminded to take safety measures like changing their passwords often and only at their workstations, deleting any suspicious emails they get, and constantly logging out when they’re done.
References
Bates, D. W., Saria, S., Ohno-Machado, L., Shah, A., & Escobar, G. (2014). Big data in health care: using analytics to identify and manage high-risk and high-cost patients. Health Affairs, 33(7), 1123-1131.
Thew, J. (2016, April 19) Big Data Means Big Potential, Challenges for Nurse Execs. Health Leaders. Retrieved from: https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execsLinks to an external site..
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13
-
Collapse SubdiscussionRoberto Monroy Hello Odion!
Thanks for the interesting read; I agree that big data can solve many problems, including preventing medication errors. Illegible writing can lead to unnecessary tests,
diagnostics, and incorrect medication doses, leading to patient harm and even death (Sokol & Hettige, 2006). In my facility, we rely on paper charting, and
illegible handwriting is a significant issue. Nurses constantly have to track down doctors and clarify orders leading to delays in care. Programs/algorithms that detect and
prevent this from occurring will definitely improve patient outcomes. Big data will continue to shape and revolutionize healthcare; data can be used to improve the efficiency
of healthcare and facilitate informed decision-making, treatment, and prevention of diseases (Batko & Ślęzak, 2022). Technology progresses at an expectational rate; its full
benefit to healthcare has yet to be seen, but we are on the right track.
References
Batko, K., & Ślęzak, A. (2022). The use of Big Data Analytics in healthcare. Journal of big data, 9(1), 3. https://doi.org/10.1186/s40537-021-00553-4
Sokol, D. K., & Hettige, S. (2006). Poor handwriting remains a significant problem in medicine. Journal of the Royal Society of Medicine, 99(12), 645–646. https://doi.org/10.1177/014107680609901219
-
-
Collapse SubdiscussionAndrea M Allen Main Post
Big Data
Big data is continuing to grow exponentially. It is aggregated by the internet and social networks, text messages media files and web searches, transactions processing systems, customer databases, documents etc. In the clinical setting Big Data is associated with digitalizing medical records, improving care by allowing data tracking, and lowering cost. With Big Data, patients who visits the hospital on a regular basis can be identified quickly and easily classified based on their health condition which saves time and money because they can be treated rather quickly and discharged.
One Challenge of Big Data is lack of effective data governance procedures. The biggest obstacle for healthcare organizations is capturing data. Data requires specifics measures to be used efficient such as precision, formatted correctly, must be clean to be used across various healthcare system. Implementation costs is also another challenge. Costs of rise in use of ancillary services such as laboratory tests and x-rays, clinical chemistry tests and other little-ticket technology, cost of computers for units and departments, IT personnel/s, training, and education programs for healthcare professionals.
One strategy to streamline cutting costs while improving health is to have all the relevant stakeholders collaborate and adapt the design and performance of their systems by building the technological infrastructure to house and converge the massive volume of healthcare data and invest in the human capital to guide citizens into their new frontier of human health and well-being.
Reference
Pastorino, R., De Vito, C., […], & Boccia, S. (2019) Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. Eur J Public Health. (Suppl 3): 23-27 doi:10.1093/eurpub/ckz168
McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of
knowledge (5th ed.). Jones & Bartlett Learning.
Glassman, K. S. (2017). Using data in nursing practice Links to an external site.Links to an external site.. American Nurse Today, 12(11), 45–47. Retrieved from https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizationsLinks to an external site.Links to an external site.. Technological Forecasting and Social Change, 126(1), 3–13.
Vinay Shanthagiri. (2014). Big Data in Health Informatics Links to an external site.Links to an external site.
[Video file]. Retrieved from https://www.youtube.com/watch?v=4W6zGmH_pOw-
Collapse SubdiscussionJodian Walford Hi Andrea, you make a valid point. Big data is making significant strides in the healthcare system. According to Adibuzzaman et al., (2018), big data systems have shown potential for making fundamental changes in care delivery. Unfortunately, we will encounter challenges or disadvantages with every benefit. However, as McGonigle & Mastrian (2022) reminds us, the future depends on a prepared workforce ready to meet the challenges of tomorrow. Sensitive and confidential data is collected within the health industry from patients and their families. They are stored within the different networks on servers, making them accessible to provide the optimum care for our patients. Seh et al., (2020) highlight that “every blessing has a curse.” The use of electronic health recording has become a source of privacy breaches. Privacy becomes a challenge associated with analyzing big data because the generation and sharing of personal information are not protected (Ann Alexander & Wang, 2018).
Nevertheless, as you reasonably said, investing is a good strategy. Especially when training human resources. Data encryption is a great way to mitigate this challenge that comes with using big data. Abouelmehdi et al., (2018) explain data encryption as an efficient means of preventing unauthorized access to sensitive data. Only Authorized users can access the encrypted data with a secret code or password. Encryption can be successful in protecting data and maintaining data integrity.
References
Abouelmehdi, K., Beni-Hessane, A. & Khaloufi, H. Big healthcare data: preserving security and privacy. J Big Data 5, 1 (2018).
https://doi.org/10.1186/s40537-017-0110-7Links to an external site.
Adibuzzaman M, DeLaurentis P, Hill J, Benneyworth BD. Big data in Healthcare – the promises, challenges, and opportunities from a research perspective: A case study with a model database. AMIA Annu Symp Proc. 2018 Apr 16;2017:384-392.
Ann Alexander, C., & Wang, L. (2018). Big Data and Data-Driven Healthcare Systems. Journal of Business and Management Sciences, 6(3), 104–111.
https://doi.org/10.12691/jbms-6-3-7
McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning.
Seh, A.H. et al., (2020). “Healthcare data breaches: Insights and implications,” Healthcare, 8(2), p. 133.
https://doi.org/10.3390/healthcare8020133.
-
Collapse SubdiscussionBenedicta Kwevie Response 2
Hello Andrea
I agree big data can be used to store patient information like health records and patient admittance history. Since patient data is stored if they are ever readmitted, they can be easily identified and treated faster. It can help in understanding medications and progression in healthcare execution and delivery (Big Data for Patients | Big Data for Patients, n.d.). As data governance procedures are how you utilize data, a lack of them can cause disorganization in the organization and patient care. Without it, the quality of the data collected could decrease over time, causing less trust in the system (Liu, 2021).
References
Big Data for Patients | Big Data For Patients. (n.d.).
https://bigdataforpatients.reaganudall.org/Links to an external site.
Liu, T. (2021, July 28). What Happens When You Have No Data Governance? Association Analytics.
-
Collapse SubdiscussionColleen Lewis Hi Andrea,
It definitely seems that Big data could help to streamline the care for patients who are “frequent flyers” in the Emergency Department. One of the possible outcomes and hopes for big data is reduction of readmission rates. The use of big data to follow patient trends can be used in application to preventative care to help keep patients out of the hospital (Wang et al 2018). We know that many patients use the ED as their source of primary care. Data collected over time on a patients reason for visit, vital signs, diagnostic tests, and diagnoses at each visit could help inform certain interventions. Data collected on patients over time can help providers predict future behavior and assist them in providing better care through awareness of patient patterns, thus supporting provision of improved treatment plans and can also help to cut costs (Ghaleb et al 2022).
Ghaleb, E. A. A., Dominic, P. D., Muneer, A., & Almohammedi, A. A. (2022). Big Data in healthcare transformation: A short review. 2022 International Conference on Decision Aid Sciences and Applications (DASA). https://doi.org/10.1109/dasa54658.2022.9764966
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
-
-
Collapse SubdiscussionBarkisu Fortenberry Healthcare is increasingly adopting technology to make its processes more effective and save costs, resources, and time. The adoption of technology has seen healthcare collect a large amount of patient data and use it to provide real-time care that is well-tailored to patients’ needs (Dash et al., 2019). The vast data is the big data in healthcare available through electronic health records, which contain patient health information among other healthcare resources. The ability of big data has become more advanced, and healthcare professionals are exploiting every bit to meet patient needs effectively.
One of the most significant benefits of using big data in healthcare is the reduced cost. There are many ways that healthcare can reduce costs using big data. For instance, the hospital I work with uses predictive analytics to help it with staffing. The predictive analytics predict admissions rate over a given time, say a month or two weeks. So it helps the hospital to know which units need or will need the highest and low staff. With this, the hospital can allocate staff based on need, reducing overstaffing, increasing efficiency, and reducing patient waiting time associated with inadequate staffing.
Besides, I read an article on how big data are helping hospitals and physicians to follow up on patients, which I found exciting yet very helpful in monitoring patients’ adherence to medication and medical advice (Shilo et al., 2020). The article discussed how hospitals are using data to track patient locations. Specifically, the article talked about GPS-enabled inhalers for people with asthma. This inhaler enables physicians to track when asthmatic patient takes their medication. It could be crucial for healthcare professionals to better follow up on patients or develop more personalized treatment plans while effectively preventing diseases, complications and injuries.
Even with the many benefits, exploiting big data still faces challenges. Most healthcare organizations need more effective data governance procedures to capture data. As a person who has had the first experience using big data, I understand that people’s data must be clean, precise, and formatted appropriately to be used more efficiently (Shilo et al., 2020). However, while electronic health records with patient-protected healthcare information are kept in easy-to-retrieve and shared centralized databases, healthcare professionals still need help sharing the patient-protected information of the healthcare organization with outsiders who are not healthcare professionals involved in the patient care journey (Dash et al., 2019). This has led to much fear about data security as there have been many hacking and security violations that healthcare organizations and professionals have to handle daily.
To better address the named challenge, the healthcare organization and personnel must be cautious by using data appropriately. Healthcare organizations must give their healthcare professionals the resources they need to access the data, use it well, and only share it with the authorized person while strictly observing the policy concerning sharing protected patient health information (Shilo et al., 2020). This necessitates that healthcare organizations constantly educate their staff on protected health information security and how they make a data-driven decision independently using the data without making it vulnerable to hackers. In other words, big data are generally effective, but their optimal exploitation needs people with experience to use it appropriately behind the control wheel.References
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. 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.
Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6(1), 1-25.https://link.springer.com/article/10.1186/s40537-019-0217-0
-
Collapse SubdiscussionKatrina Brooks Technology affects almost every aspect of our daily lives from exchanging information
though text messages, using GPS on a mobile phone, doing household chores, etc. Technology is
important in healthcare for several reason including faster and easier access to patient’s records,
helps prevent adverse drug reactions, improved access to care such as telehealth and portable
diagnostic tools.
Multiple benefits can be obtained from using big data as part of a clinical system. “Big
data is a field that deals with ways to examine, analyze, and systemically extract data and
information from datasets that are too large or complexed to be processed using conventional
data and processing application software” (McGonigle & Mastrian, 2022). Big data can be used
to suggest interventions about a predicted complication based on the data in a patient’s EHR
such as vital signs, lab values and test results. “Using big data in this way will be a boon to
population health, in that it will help make inform decisions about how to manage risk and
disease states across the continuum” (Thew, 2016).
Barcode Medication Administration (BCMA) is another benefit, it is a system that uses a
handheld scanner to scan both the patient’s armband and medication to ensure it matches the
MAR. BCMA is the technology version of the five rights of medication. The five rights include
right patient, right drug, right dose, right route, and right time.
Patient privacy is a risk associated with using big data in clinical systems. The rise in
cyber-attacks is concerning for healthcare, businesses, and individuals. Hackers are attracted to
big data storage. “Optimizing cybersecurity should be high up on the priority list of any business
in the digital age, as not having the correct tools could possibly spell catastrophe” (Challenges of
Big Data in cybersecurity, 2019). Cybersecurity defends computers, servers, electronic systems,
mobile devices, network, and data from malicious attacks.
References
Challenges of Big Data in cybersecurity. Big Data LDN. (2019, August 29). Retrieved from
https://bigdataldn.com/news/challenges-of-big-data-in-cybersecurity/
McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of
knowledge (5th ed.). Jones & Bartlett Learning.
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Retrieved from
https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
-
Collapse SubdiscussionChristiana Nuworsoo Initial Post – Big Data Risk and Rewards
Big data is large and complex data that is so much so that it is difficult to process using traditional data processing
methods (McGonigle & Mastrain, 2022). In healthcare, for instance, the amount of data collected from patients even in one
day is enormous. This data comes from multiple sources such as physicians, nurses, laboratories, radiology, other clinicians,
and other facilities. Unfortunately, over 75% of the data collected in most organizations are unstructured and mostly
overlooked because they are usually in text files rather than databases (McGonigle & Mastrain, 2022).
The ability to sort through such files requires good data mining software. Data mining is a process that uses a specific
type of software to sort data for patterns and determine relationships. Six Sigma and Lean are data mining tools that can
eliminate defects, avoid waste, or assess quality control issues. The big data revolution challenged healthcare professionals to
assess datasets using advanced technology for seamless collection and analysis of information from numerous sources
(McGonigle & Mastrain, 2022).
Potential Benefit of Using Big Data
There are many potential benefits of using big data. There are managerial, strategic, operational/clinical, and IT benefits.
Clinical systems benefits include improvement in the quality and accuracy of clinical decisions; the ability to process large
numbers of health records in seconds; immediate access to clinical data for analysis; decrease in the time of the diagnostic
test; reduction in surgery-related hospitalizations; and exploration of new research avenues (Wang et al., 2019). Big data
allows clinicians to view patient trends and make decisions accordingly. Also, the information to make the decision is easily
accessible.
Potential Challenge or Risk Using Big Data and Possible Solution
A potential challenge of using big data in clinical systems is processing information without human supervision, which
might lead to inaccurate conclusions and lead to a patient being wrongly diagnosed and subsequently treated for the wrong
diagnosis, which could be detrimental and fatal if the error is not recognized early. A possible solution or strategy would be to
create a big data analytics system that is simple, convenient, and transparent enough to be applied to actual patient cases
(Mehta & Pandit, 2018). It should be a simple, relatively straightforward system that is easy to assimilate. A system that is too
complicated to understand and use in the long run becomes obsolete and not cost-effective.
References
Mehta, N., & Pandit, A. (2018). Concurrence of big data analytics and healthcare: A systematic review. International Journal of
medical informatics, 114, 57-65.
McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett
Learning.
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare
organizations. Technological forecasting and social change, 126, 3-13.
-
Collapse SubdiscussionBarkisu Fortenberry Response 2
Hello Christiana,
That was a great post with great insights. Indeed, the data sets in hospitals are huge and sometimes hard to process. Imagine having data from all the units in the hospital. First, sorting out and reading big data could be challenging, especially if a healthcare professional wants to assess a patient’s health information quickly (Rehman et al., 2022). You provided a suggestion that could make big data processing effective and easier. Data processing software is crucial in the hospital because they help sort the data making it easy to retrieve and process. In addition to the data processing software, it could be crucial to train healthcare professionals on data processing and how to use various unit technologies to help ease data processing. Lehane et al. (2018) noted that a lack of knowledge and skills hinders data mining and processing. Nurses who need to know what data they need to collect and how to document or retrieve stored data would delay the care they provide to patients or may make the whole data vulnerable to fraudsters. Therefore, the study stressed that equipping nurses with basic knowledge about data mining and processing is helpful in providing timely care to patients and processing or using data in safer ways. Otherwise, you provided great insights about how challenges healthcare professionals face in processing data could be overcome.
References
Lehane, E., Leahy-Warren, P., O’Riordan, C., Savage, E., Drennan, J., O’Tuathaigh, C., … & Hegarty, J. (2018). Evidence-based practice education for healthcare professions: an expert view. BMJ evidence-based medicine. https://ebm.bmj.com/content/early/2018/11/15/bmjebm-2018-111019.responses?versioned=true
Rehman, A., Naz, S., & Razzak, I. (2022). Leveraging big data analytics in healthcare enhancement: trends, challenges, and opportunities. Multimedia Systems, 28(4), 1339-1371. https://link.springer.com/article/10.1007/s00530-020-00736-8
-
-
Collapse SubdiscussionJodian Walford Big Data is a field of study that involves data management and analytics—defined as high volume, high velocity, and a great variety of information assets requiring new processing forms to enable enhanced decision-making (Tech America,2022). Big data’s increase in healthcare has developed meaningful benefits for clients and medical professionals. It refers to vast and complex data sets generated by various sources, such as electronic medical records, wearable devices, and social media (Abouelmehdi, Beni-Hessane & Khaloufi, 2018). The health field, especially in a clinical setting, is not immune to growth and has quickly embraced the use of big data. We see the evidence with that our EHR system. Thew (2016), reminds us to ensure big data is used to influence outcomes that are meaningful to the nursing profession.
One potential benefit of using big data as part of a clinical system is that it has created more accessibility. Telemedicine and using big data technology intelligent devices have led to remodeling and revolutionizing the entire healthcare industry. Clinical services can be delivered by way of technology, increasing patient outcomes, and reducing unnecessary ER visits by education on diagnosis, facilitating consultations to provide personalized treatment plans, or even monitoring patients remotely. According to Tulane University (2021), Big data allows doctors to serve patients in rural areas and other locations where a robust medical infrastructure may not exist. For example, patients can use smart home devices to communicate with medical providers. Big data approach is essential in improving evidenced-based healthcare decisions and patient outcomes. (Wang et al., 2018).
Despite the great benefits, we can still identify the cons. One potential challenge or risk of using big data as part of a clinical system is a breach of privacy through poor data security. There is a high risk of unauthorized users like hackers, cybercriminals, or persons outside of one’s treatment team accessing confidential information from electronic health recording system.
One strategy that may effectively mitigate these challenges is cloud Data protection agency. Cloud data protection is securing a company’s data in a cloud environment, wherever that data is, whether at rest or in motion, and whether it is managed internally by the company or externally by a third party (PrismaCloud, n.d). Using cloud data can continuously and actively work to identify and block security breaches, suspicious user behavior, cybercriminals, or hackers.
References
Abouelmehdi, K., Beni-Hessane, A., & Khaloufi, H. (2018). Big healthcare data: preserving security and privacy.
https://journalofbigdata.springeropen.com/articles/10.1186/s40537-017-0110-7
PrismaCloud, (n.d) What is Cloud Data Protection? Palo Alto Networks.
https://www.paloaltonetworks.com/cyberpedia/what-is-cloud-data-protection#:~:text=Cloud%20data%20protection%20is%20the%20practice%20of%20securing,the%20company%20or%20externally%20by%20a%20third%20party.
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs Links to an external site.
https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
Tech America (2022). What is Big Data and why is it important?, Tech America.
https://www.techamerica.org/what-is-big-data-and-why-is-it-important/#:~:text=Big%20Data%20is%20a%20term%20that%20has%20gained,requiring%20new%20processing%20forms%20to%20enable%20enhanced%20decision-making.
Tulane University, (2021). Big data in health care and patient outcomes, School of Public Health.
https://publichealth.tulane.edu/blog/big-data-in-healthcare/
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations Links to an external site.. Technological Forecasting and Social Change, 126(1), 3–13.
-
Collapse SubdiscussionKatrina Brooks Hi Jodian,
Adding virtual technology in healthcare has had a huge positive impact. Telemedicine makes it easy to connect to a physician or nurse practitioner. According to Johns Hopkins Medicine, some of the benefits include comfort and convenience, control of infectious illness, better assessment, family connections and primary care and chronic condition management. Telehealth became very popular during COVID-19 to prevent the spread of infection. Care that can received via telehealth include “treatment and follow up for ADD and ADHD, prescription management, mental health treatment, lab test or x-ray results, post-surgical follow up, physical and occupational therapy, skin conditions, etc.” (What is telehealth, n.d.).
Reference
Benefits of telemedicine. Benefits of Telemedicine | Johns Hopkins Medicine. (2022, January 18). Retrieved from https://www.hopkinsmedicine.org/health/treatment-tests-and-therapies/benefits-of-telemedicineLinks to an external site.
What is telehealth? Telehealth.HHS.gov. (n.d.). Retrieved from https://telehealth.hhs.gov/patients/understanding-telehealth/Links to an external site.
-
Collapse SubdiscussionRaminder Kaur Hi Jodian, Thanks for sharing your post.
Telemedicine technology intelligent devices have led to remodeling and revolutionizing the entire healthcare industry. Technology has unquestionably changed healthcare. Telemedicine is one of the technological milestones in the healthcare industry. A large number of healthcare facilities have accepted telehealth because it is beneficial to both patients and providers. Telehealth has assisted with extending and further developing admittance to a large portion of the medical care administrations. The ease of access to on-demand care offered by telehealth services is its most significant benefit. Because telehealth services have brought rural communities quite close, patients no longer need to drive for hours to reach the nearest hospital or specialists. The ecosystem of healthcare is benefiting greatly from telehealth. When their jobs changed and they had to move from one location to another, many patients received much help. They can continue their treatment with the same provider or specialist from anywhere, so they do not have to worry about switching providers. Telehealth allows providers to conduct more frequent follow-ups, making it easier for their patients. As such, it permits patients to join the tele-visit ( I Patient Care, 2018). It involves a patient receiving the services of a doctor from a distance, even though the two are in different locations. Technology has made it easier to set up telemedicine health plans by utilizing tools like video conferencing. The beneficial effects that it has had cannot be understated. For instance, it has reduced costs, made healthcare more accessible, and increased patient engagement with physicians. Telemedicine health plans have revolutionized healthcare at a crucial time for young people and the elderly. Today, seniors can age peacefully and enjoy their golden years without stress. The use of telehealth has made it easier for members to work together. As a result, improved coordination has made it even simpler for local providers to collaborate harmoniously to provide client care. The ascent in the quantity of care suppliers has allowed individuals to get to mind from assorted quarters. According to Coastal Telehealth Specialists, providers lose market share and suffer from market fragmentation due to members seeking services from multiple providers ( Coastal Telehealth Specialists).
References:
4 positive impacts of telemedicine health plans in Healthcare. Coastal Telehealth Specialists. (n.d.). Retrieved from https://coastaltelehealth.com/4-positive-impacts-of-telemedicine-health-plans-in-healthcare/#:Links to an external site.
Telemedicine – creating positive impact in healthcare. I Patient Care. (2018, August 24). Retrieved from https://ipatientcare.com/blog/telemedicine-positive-impact-in-healthcare/Links to an external site.
-
-
Collapse SubdiscussionBenedicta Kwevie Main Post
The definition of “big data” is data that has different variations of information collected and grouped, with three sections: volume or amount, velocity, and variety (What Is Big Data? | Oracle, n.d.). Big data can help organize and coordinate incoming data, regardless of type or difference. Three types of big data are structured, unstructured, and semi-structured. (Daniels, 2022). Structured is making the data organized and easier to understand, unstructured is out of order, and semi-structured is a mix of both, sometimes organized and sometimes uncoordinated.
Potential benefit of using big data as part of a clinical system
A clinical system is a technology system that helps healthcare providers with patient data and patient care (eHealth Network, 2019), and its users could benefit from using big data because it can help with the accumulation of patient data, all the variations, types and the speed or rate that is entered into any system or database. The data can be calculated and sorted using big data in a clinical system. Big data can help push and assist an organization in moving forward faster than sitting around and waiting for things to happen and risking being left using outdated things (Thew, 2016). In the clinical setting, big data can be used to obtain data for research purposes (Olivera et al., 2019). When conducting research, big data can help organize and maintain data collected no matter the state it is in or the speed it is submitted. Researchers can use big data to insert their findings from all over the world, in different varieties and speeds, to be stored indefinitely (Scientific Research and Big Data (Stanford Encyclopedia of Philosophy), 2020).
Potential challenge or risk of using big data as part of a clinical system
One potential challenge of using big data could be not having the right capacity to manage or maintain the information added to systems using big data. With big data, the name almost immediately tells you the main part of it; it accumulates patient data together. With this, you would need a system with a large amount of storage or capacity to hold patient data for an indefinite amount of time. You would also need a way to ensure that confidentiality is maintained, keeping all patient data and research private from public usage or viewing (Bruno, 2019). Another potential risk is breaches of data. There could be data leakage or break-ins that can cause patient data to be exposed to those who are not permitted (Daniels, 2022). Let’s say an important patient comes to a facility, and their health records and data need to stay confidential. Big data can help with this, but it runs the risk of the system getting hacked and the information getting stolen, exposing all the conditions the person has to the public.
Strategy you have experienced, observed, or researched that may effectively mitigate the challenges or risks of using big data you described
The addition of cloud computing to physical servers would address both issues of storage and security. Most current cloud computing services (such as Google Cloud and Microsoft Azure) have 24/7 accessibility and are governed by privacy regulations. They also give the end user the option of public, private, or even hybrid cloud services. (indeed.com – n.d.).
References
Bruno, R. (2019, April 4). Big Data Storage Challenges. Big Data HPC | Raid Incorporated.
https://www.raidinc.com/2015/07/big-data- storage-challenges/Links to an external site.
Daniels, N. (2022, December 25). Big Data and Privacy: What is it and What are the Risks? VPNoverview.com.
https://vpnoverview.com/privacy/anonymous-browsing/big-data-and-privacy/Links to an external site.
eHealth Network. (2019, July 2). Clinical Information Systems: An Overview – Elets eHealth. eHealth Magazine.
Indeed Editorial Team. (2021). 9 Types of Cloud Computing (With Definition and Tips).
Olivera, P., Danese, S., Jay, N., Natoli, G., & Peyrin-Biroulet, L. (2019). Big data in IBD: a look into the future. Nature Reviews Gastroenterology and
Hepatology
Oracle. (2022). What Is Big Data? | Oracle. Oracle | Cloud Applications and Cloud Platform. (n.d.).
Retrieved from https://www.oracle.com/big-data/what-is-big-data/Links to an external site..
Stanford Encyclopedia of Philosophy – Scientific Research and Big Data – (2020, May 29).
Retrieved from https://plato.stanford.edu/entries/science-big-data/Links to an external site.
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Links to an external site
Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execsLinks to an external site.
-
Collapse SubdiscussionSheila Ankrah Response #1
Hi Benedicta,
This is an excellent post. Using data to identify and analyze trends is a vital aspect of the provision of care to patients. There are several different ways in which data can be collected and used in a clinical system. Ahed et al. (2019) wrote that identifying actionable big data correlations can be used by hospital administration to identify and eliminate waste in departments, including billing and pharmacy. Healthcare organizations can use data to help them become more profitable and improve the quality of care they provide to patients.
With the collection of data, the issue of data security has become a significant issue for many healthcare organizations. Every data breach which occurs in healthcare is detrimental not only to the patient but to the organization as well. Zandona and Thompson (2017) wrote that data breaches jeopardize the patient’s identity and financial safety and the organization’s brand and reputation. Healthcare organizations cannot afford to have their reputations tainted by security risks and must use all available resources to protect their patients’ information.
References
Ahed Abugabah, Ahmad Al Smadi, & Alaa Abuqabbeh. (2019). Data Mining in Health Care Sector : Literature Notes. Computational Intelligence and Intelligent Systems, 63–68. https://doi-org.ezp.waldenulibrary.org/10.1145/3372422.3372451Links to an external site.
Zandona, D. J., & Thompson, J. M. (2017). Going Beyond Compliance: A Strategic Framework for Promoting Information Security in Hospitals. Health Care Manager, 36(4), 364–371.
-
Collapse SubdiscussionAndrea M Allen Hi Benedicta,
Mitigating the challenges or risks in using Big Data by Cloud Computing can be daunting. Cloud Computing has numerous downside such as Downtime as one of the biggest disadvantages. There is also Internet-based service outages s, vulnerability to attacks, network connectivity dependence, vendor lock-in, limited control, bandwidth issues, lack of support and numerous other issues. As in many other technological possible solutions to mitigate risks, shopping for the best possible outcome might seem promising but not the best solution.
Kuo M
Opportunities and Challenges of Cloud Computing to Improve Health Care Services
J Med Internet Res 2011;13(3):e67
URL: https://www.jmir.org/2011/3/e67
DOI: 10.2196/jmir.1867Zhang, Q., Cheng, L. & Boutaba, R. Cloud computing: state-of-the-art and research challenges. J Internet Serv Appl 1, 7–18 (2010). https://doi.org/10.1007/s13174-010-0007-6
-
Collapse SubdiscussionIrvin Michael Jones Hi, Benedicta,
Big data certainly can help organize immense amounts of information that many healthcare organizations have to manage, and one of the primary benefits is that it can specifically assist in managing patient data. As you mentioned, the accumulation of patient data can be overwhelming but due to big data systems such as electronic health records, organizing this data has become easier than ever. Witjas-Paalberends et al. (2018) states understanding how to properly organize big data that is both structured and unstructured can lead to better diagnosis and treatment of patient populations. Ideally, as technology continues to evolve, I hope to see more ways that healthcare organizations can utilize structured data which includes data in electronic formats. Unstructured data includes data that is typically collected on paper which can sometimes cause a lack of efficiency. According to Nasir et al. (2022) big data analyzation is a key factor of importance for healthcare organizations to focus on as the ability to successfully translate data can lead to performance improvements and a decrease in healthcare costs. As you mentioned, big data usage still carries potential risks and challenges such as lack of capacity. Lack of capacity can lead to concerns with not being able to successfully store important patient information which can lead to worsened patient outcomes and a decrease in efficiency for healthcare providers.
References
Nasir, W. M. H. M., Jusoh, Y. Y., Abdullah, R., & Abdullah, S. (2022). Towards Healthcare Organizational Performance
Deriving by Big Data Analytics Quality Factors: A Systematic Literature Review. 2022 Applied Informatics
International Conference (AiIC), Applied Informatics International Conference (AiIC), 2022, 1–6.
https://doi.org/10.1109/AiIC54368.2022.9914026
Witjas-Paalberends, E. R., van Laarhoven, L. P. M., van de Burgwal, L. H. M., Feilzer, J., de Swart, J., Claassen, E., &
Jansen, W. T. M. (2018). Challenges and best practices for big data-driven healthcare innovations conducted by
profit-non-profit partnerships – a quantitative prioritization. International Journal of Healthcare
Management, 11(3), 171–181. https://doi.org/10.1080/20479700.2017.1371367
Edited by Irvin Michael Jones on Dec 30, 2022 at 8:19pm
-
-
Collapse SubdiscussionRemi Oluremi Ojo Module 3 Week 5 Discussion:
Potential benefits and risks associated with the use of big data in the healthcare system.
In healthcare, big data can be described as a large set of electronic health data sets that is complex and too large to manage with traditional hardware and software. The data set cannot be easily managed with common data or traditional management methods and tools (Keenan, 2014).
Potential Benefits of using Big Data
In the healthcare system, there are various benefits of big data, such as the ability to keep patients safe and healthy, reduce hospital costs and expand diagnostic services (Adibuzzaman, et al., 2018). An example of how big data enables healthcare professionals to observe, analyze, and interpret trends that influence patient outcome, is the electronic health record (EHR) documentation of the blood sugars of diabetic patients. The EHR organizes the blood glucose numbers, and patterns with which the provider can observe if the patient blood glucose is controlled or not controlled and implement appropriate measures to normalize the patient’s blood sugar in a timely manner. The incorporation of this data is beneficial to the interdisciplinary team involved in the care of the patient, the physician, the nurse, the dietician, the endocrinologist, and the patient. Patients can also communicate with the healthcare professional using an app on their phone which allows easy access to the healthcare system. Big data, allows healthcare professionals to monitor patients closely and intervene timely, which thereby reduces frequent re-admissions hospital stays, and healthcare
Big Data Risks
There are great benefits in using big data to improve patient outcomes in the healthcare system, but there are also risks. One of the risks observed in big data usage is the compromise of patient confidentiality, and possible health insurance portability and accountability act (HIPAA) violations. Gaining access to patient information is getting easier, due to the ever-increase in advanced technology. Though clinicians access this information, with a protected password, and other safety measures, there are still cases of patient information getting compromised.
Possible Strategy
A possible strategy to prevent the risk of compromising patient information and HIPAA violations is the deidentification of protected health information for secondary use. This can be done by removing features that identify patients such as photos, names, zip codes, telephone numbers, social security numbers, and addresses before sharing the healthcare data with researchers and other secondary personnel (Kayalp, 2018). This is an essential process that can maintain patient privacy, though the process is tedious and time-consuming.
References
Adibuzzaman, M., DeLaurentis, P., Hill, J., & Benneyworth, B. D. (2018). Big data in healthcare – the promises, challenges, and opportunities from a research perspective: A case study with a model database. AMIA … Annual Symposium proceedings. AMIA Symposium, 2017, 384–392.
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
Keenan G. M. (2014). Big data in health care: An urgent mandate to change nursing EHRs!. On-line journal of nursing informatics, 18(1), http://www.himss.org/ResourceLibrary/GenResourceDetail.aspx?ItemNumber=28968.
-
Collapse SubdiscussionErica Schulte Response #2 – Erica Schulte – Remi Oluremi Ojo
Hello Remi, I enjoyed reading your post. Patient confidentiality and securing patient data are certainly a major challenge for healthcare facilities to maintain in the world of big data. In reading (panelZhihanLvPersonEnvelopeLiangQiao et al., 2020), there are many options including block chain and cloud technologies that could help in this scenario. However, there remains a lack of full investigation to prove if these are viable solutions. This will continue to be a challenge that healthcare facilities will face in this age of big data.
References
McGonigle, D., & Mastrian, K. G. (2022). Chapter 22: Data Mining as a Research Tool . In Nursing Informatics and the foundation of knowledge (pp. 537–561). essay, Jones & Bartlett Learning.
panelZhihanLvPersonEnvelopeLiangQiao, A. links open overlay, ZhihanLvPersonEnvelope, LiangQiao, AbstractIn order to explore the development of healthcare in China and the privacy and security risk factors in medical data under the background of big data, LeeY.T., StankovicJ.A., RizwanA., MahmoudM.M.E., EmaraK., CenaF., EnayetA., VilleneuveE., ChenM., JuddooS., KraemerF.A., IyengarA., DanielsM., HeZ., BhuiyanM.Z.A., … KaramoozianA. (2020, March 25). Analysis of Healthcare Big Data. Future Generation Computer Systems. Retrieved January 4, 2023, from https://www.sciencedirect.com/science/article/pii/S0167739X20304829
-
-
Collapse SubdiscussionSimranjeet Brar Big Data Risks and Rewards – Initial Post
Cost savings, enhanced preventative services, mistake minimization, and health promotion are just some of the ways in which big data enhances the patient experience (McGonigle, & Mastrian, 2022). The use of monitoring apps and gadgets to keep tabs on a patient’s vitals has been greatly improved by the availability of big data. For instance, diabetics can use specific apps to keep tabs on things like their insulin intake and scheduled checkups with their healthcare providers. With the use of big data analysis, doctors may pinpoint areas where they might save money, such as in the diagnostic and treatment phases. By collecting and analyzing data thoroughly, medical practitioners may provide patients with effective care.
The clinical system relies heavily on big data technology since it provides vast information on risk factors and illnesses that doctors may use to plan and administer therapy. Big data is a vital resource for reducing health-related mortality and comorbidities. In healthcare settings, the technology enhances productivity. Big data is used by healthcare providers to analyze patterns inpatient admissions and discharges, as well as the frequency with which patients return for additional treatment. To provide better treatment at lower costs, for instance, physicians can utilize predictive analytics to determine the optimal number of staff members to employ. The usage of electronic medical records is bolstered by big data, which also facilitates the collection and analysis of demographic and health information for better decision-making by healthcare practitioners. In addition to enhancing administrative and financial efficiency, big data also helps prevent medical mistakes by providing complete and precise data.
Ineffective data governance processes are one of the obstacles that must be overcome when using big data in the clinical system. Challenges in collecting complete and reliable data are commonplace in the healthcare industry. Data should be correct, clear, and properly prepared to ensure it is relevant across healthcare systems before it can be used efficiently. Security flaws in big data are likely to jeopardize the privacy and confidentiality of patient records. As an example, the system may provide fictitious data, which might result in mistakes and subpar medical treatment. Since fraudsters intentionally insert and fabricate fake data into clinical systems, reducing data quality, this issue is likely to arise. Lack of security audits, unreliable mappers, and issues with granular access control are some additional obstacles brought on by big data (Oussous et al., 2018).
Current technologies, such as access control, authentication, data masking, and encryption, may successfully alleviate the dangers and problems associated with the usage of big data. To protect private information, data masking replaces it with random numbers or other meaningless values. Identity information, such as a patient’s name, date of birth, and social security number, can be concealed from hackers in this way. This prevents them from pinpointing the information they can fake (Wang et al., 2018). To successfully restrict the use or sharing of patient information in a healthcare environment, access control requires users to get permission or approval from the patient.
References
McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning. pp 537-558.
Oussous, A., Benjelloun, F., Ait Lahcen, A., & Belfkih, S. (2018). Big data technologies: A survey. Journal of King Saud University – Computer and Information Sciences, 30(4), 431-448. https://doi.org/10.1016/j.jksuci.2017.06.001Links to an external site.Links to an external site.
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizationsLinks to an external site.Links to an external site.. Technological Forecasting and Social Change, 126(1), 3–13.
Edited by Simranjeet Brar on Dec 28, 2022 at 10:14pm -
Collapse SubdiscussionMleh Porter Big data is a term used to describe large and complex datasets that are difficult to process using traditional methods. It is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications (Elhoseny et al., 2018). Big data enables businesses to identify trends and correlations in their data, allowing them to make better decisions, optimize operations, and gain a competitive advantage. Big data is used to power predictive analytics, machine learning, artificial intelligence, and more. By leveraging the power of big data, organizations can improve their efficiency, increase their profitability, and gain a competitive edge.
The Benefit of Big Data
One potential benefit of using big data as part of a clinical system is the potential to improve patient outcomes. By collecting and analyzing data from a wide range of sources, such as electronic health records, research studies, and patient surveys, healthcare providers identify patterns in patient health and develop personalized treatments tailored to individual patient needs (Dash et al., 2019). This leads to improved diagnostic accuracy and better overall patient care. Glassman (2017) has pointed out that using big data helps reduce healthcare costs by detecting potential problems early and providing more efficient treatments. The use of big data also has the benefit of reducing medical errors and increasing the accuracy of medical research. Thew (2016) has explained that by harnessing the power of big data, healthcare providers gain insights that help them provide better patient care.
Risk of Using Big Data
A potential challenge or risk of using big data that researchers in healthcare have pointed out is the potential for privacy and security breaches (Thew, 2016). As data is collected from different sources, it is vital to ensure that it is secure and that patient information is kept confidential. It is essential to consider the data’s accuracy and its potential implications for clinical decision-making. If the data is not correctly managed and monitored, it could lead to inaccurate results and incorrect decisions. Furthermore, using big data can lead to algorithmic bias, which, in effect, could lead to unfair treatment of specific patient groups (Glassman, 2017). From this, healthcare providers need to ensure the privacy and security of the data and consider the potential implications of using big data for clinical decision-making.
Mitigation Strategy
Several strategies could be used to mitigate the identified risks of big data use. One strategy that effectively mitigates the challenges or risks of using big data is using secure data management systems (Dash et al., 2019). A secure data management system enables healthcare providers to ensure that patient data is kept confidential and secure. What is more, data management systems are used to monitor the data’s accuracy and ensure that it is used appropriately. Furthermore, data management systems are used to detect algorithmic bias and identify potential data patterns that could lead to unfair treatment of specific patient groups. For example, organizations such as the Mayo Clinic have implemented secure data management systems to ensure the privacy and accuracy of their data. The Mayo Clinic has implemented a secure data management system to ensure the privacy and accuracy of its data. This system monitors the data’s accuracy and helps detect any algorithmic bias. In short, the secure data management system helps ensure that patient data is kept confidential while preventing potential algorithmic bias problems.
In conclusion, big data has the potential to improve patient outcomes and reduce healthcare costs. However, there are challenges and risks associated with using big data, such as privacy and security breaches and algorithmic bias. To mitigate these challenges, healthcare providers must implement secure data management systems and algorithms for detecting and mitigating algorithmic bias.
References
Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6(1), 1-25. https://doi.org/10.1186/s40537-019-0217-0Links to an external site.
Elhoseny, M., Abdelaziz, A., Salama, A. S., Riad, A. M., Muhammad, K., & Sangaiah, A. K. (2018). A hybrid model of internet of things and cloud computing to manage big data in health services applications. Future Generation Computer Systems, 86, 1383-1394. https://doi.org/10.1016/j.future.2018.03.005Links to an external site.
Glassman, K. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45-47. https://www.myamericannurse.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf
Thew, J. (2016). Big data means big potential, challenges for nurse execs. https://www.healthleadersmedia.com/nursing/big-data-means-big-Links to an external site. potential-challenges-nurse-execs
-
Collapse SubdiscussionMansong Ntekim Hello Mleh,
Thanks for your well-written discussion post. Advances in technology has enabled us to generate massive amount of data to the extent that the data are unmanageable with the available technology. Like any other sector of our society, the healthcare industry is generating data at a large rate that presents significant advantages and challenges at the same time (Dash, et al, 2019). We cannot underscore the advantage of “predictive capability” of big data in healthcare. This is when information from big data is deciphered and used to predict future trends. Predictive capability allows managers to analyze current and historical data and use such data in predicting future events and trends (Wang, et al, 2018). With big data, there is still the threat of privacy and security breach. Hackers and other criminal minded individual are always in search of people’s data to use in their criminal exploits. It is therefore vital for organizations to beef-up their information security to protect patients’ data from any form of compromise.
References
Dash, S., Shakyawar, S.K., Sharma, M., Kaushik, S. (2019). Big Data in Healthcare: Management, Analysis and Future Prospects. Journal of Big Data 6, 54 (2019). https://doi.org/10.1186/s40537-019-0217-0Links to an external site.
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations Links to an external site.Links to an external site.. Technological Forecasting and Social Change, 126(1), 3–13.
-
-
Collapse SubdiscussionGuoming Feng Main Post
Potential benefit of using big data as part of a clinical system
Although broadly used, there is no unique definition for big data, but generally, big data is describing a volume of data that beyond human being’s comprehension and it is impossible managed by standard computing systems. Beside extremely high volume, big data also has the other characters: 1. velocity, data are generated or collected in very rapid rate; 2. variety, data are collected from multiple places or points simultaneously, and when the data are retrieved, they can be retrieved in different forms. 3. veracity, data’s completeness is uncertain; and 4. Value, data collection should be guided by certain purpose and should always be considered with any data-related project (Carter-Templeton, et al., 2021).
Big data can be used for analysis and provide objective support facilitating informed decision-making about the diagnosis and treatment of patients, prevention of diseases (Batco & Slezak, 2022). But more important application of big data is that they can be used in the healthcare sector to predict the trends and provide relative intervention options (Wang et al., 2018), which is essential for healthcare plans in a big scale. For example, big data collective from different sources stored a massive amount of information about people infected COVID-19 virus around the world, scientists then analyzed the data to understand the nature of the COVID-19 virus. This big data analytics on one hand supported the rapid development of COVID-19 vaccines and advanced medications to treat patients, and on other hand predicted the spread of COVID-19 virus (Hallem et al., 2020). Big data sharing will allow healthcare information to be processed much more rapidly than in the past during other pandemics such as Spanish flu in 1918. In the hospital system I’m working in, the management used the big data to predict the trend of COVID-19 infection and distributed resources to dealing effectively with the tread.
Potential challenges or risks of using big data as part of a clinical system
One of the biggest potential challenges or risks of using big data is that the data do not fully capture temporal and process information. Most of the time, clinical data are collected and captured in different systems, for example, even in a same facility. Each of system collects clinic data with own specific purpose and at times not well integrated (Adibuzzama, et al., 2018). For example, when a COVID-19 patient is care in our hospital, an EHR is purposefully designed for documenting patient care and facilitating insurance company billing for this patient, while the pharmacy records are designed for managing inventory. The systems together are not designed to capture the temporal and process information which is essential for understanding COVID-19 progression, severeness, the therapeutic effectiveness, and patient result (Adibuzzama, et al., 2018).
Proposed strategies to mitigate the challenges or risks of using the big data
As the analysis above, too much not reverent information, too much data collection sources are a big challenge for application of big data. The best proposed strategy to mitigate the challenge or risk of using the big data is to scale down their data when the organization accessing them (Adibuzzama, et al., 2018). Which means that the organization should identify what data are important and relevant to the purpose of the usage of the data and get rid of the not relevant data. Through this process, quantitative of stored data reduced but quality of data achieved, healthcare quality improved.
References
Adibuzzaman, M., DeLaurentis, P., Hill, J., & Benneyworth, B. D. (2018). Big data in healthcare – the promises, challenges and opportunities from a research perspective: A case study with a model database. AMIA … Annual Symposium proceedings. AMIA Symposium, 2017, 384–392.
Batko, K., & Ślęzak, A. (2022). The use of Big Data Analytics in healthcare. Journal of big data, 9(1), 3. https://doi.org/10.1186/s40537-021-00553-4
Carter-Templeton, H., Nicoll, L.H., Wrigley, J., Wyatt, T.H., (September 30, 2021) “Big Data in Nursing: A Bibliometric Analysis” OJIN: The Online Journal of Issues in Nursing Vol. 26, No. 3, Manuscript 2.
Haleem, A., Javaid, M., Khan, I. H., & Vaishya, R. (2020). Significant Applications of Big Data in COVID-19 Pandemic. Indian journal of orthopaedics, 54(4), 526–528. https://doi.org/10.1007/s43465-020-00129-z
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
-
Collapse SubdiscussionRemi Oluremi Ojo Response #2
Hi Guoming,
Thanks for your excellent post. I agree with you on the relevance of big data technology to the COVID-19 pandemic. The COVID-19 epidemic caused a lot of disasters and deaths in the health, economic, societal, and social systems globally. For such an epidemic to be controlled, its behavior and characteristics require a thorough understanding and this can be achieved by collecting and analyzing the big data related to the epidemic (Alsunaidi, et al., 2021). Big data is an innovative technology that allows a large amount of data of patients to be stored digitally as in the case of the COVID-19 (Coronavirus) pandemic. It helped to reveal trends, patterns, associations, and insights into the control and spread of the virus. Big data can be used to decrease the risk of spreading the virus using a comprehensive data-capturing ability. It can store an enormous amount of information about the people infected with the COVID-19 virus and help with understanding the detailed nature of the virus. The data acquired can further be utilized to develop future prophylactic methods over again. Data on all types of COVID-19 cases such as those that currently have the infection, recovered, and are deceased can be stored, used to identify cases, and help to apportion the resources to protect the health of the public. In general, big data gives a huge amount of information to epidemiologists, scientists, and health workers to enable them to make an informed decision to attack the COVID-19 virus (Haleem et al., 2020).
References
Haleem, A., Javaid, M., Khan, I. H., & Vaishya, R. (2020). Significant applications of big data in the COVID-19 pandemic. Indian journal of orthopedics, 54(4), 526–528. https://doi.org/10.1007/s43465-020-00129-z
Alsunaidi, S. J., Almuhaideb, A. M., Ibrahim, N. M., Shaikh, F. S., Alqudaihi, K. S., Alhaidari, F. A., Khan, I. U., Aslam, N., & Alshahrani, M. S. (2021). Applications of big data analytics to control COVID-19 pandemic. Sensors (Basel, Switzerland), 21(7), 2282. https://doi.org/10.3390/s21072282
-
-
Collapse SubdiscussionMansong Ntekim Week 5 Discussion.
Information is fundamental to a better organization and new developments. The more information available, the better we can organize and deliver the best outcomes. That is why data collection is a crucial part for every organization. Data can be used to predict current trends of certain criterion and future events. Individuals and organizations daily activities are inundated with tons of data generated from social activities, science, work, health, etc. The present situation can be compared to a data flooding. Technological advances have helped us in generating more and more data, even to a level where it has become unmanageable with the current available technologies. This has led to the creation of the term ‘big data’ to describe data that is large and unmanageable. Like every other industry, healthcare organizations are producing data at a tremendous rate that presents many advantages and challenges at the same time. (Dash, et al, 2019).
One potential benefit of using big data as part of a clinical system
At this time, the health care industry is yet to appreciate the immense benefits that can be amassed from the analytic of big data. One of the benefits of big data is its use in predictive capability. “Predictive Capability” uses a set of sophisticated statistical data to build patterns and forecast future events. Predictive capability highlights future trends and investigation of new perceptions through distilling of information from large store of data. This system assists managers to reference current and historical data to generate context-aware recommendations that enable them to accurately predict future events and trends (Wang, et al., 2018). Being able to use data to predict future outcomes is beneficial as it will help in the quick treatment for a patient that presents with the same ailment where there is data of successful treatment with the model.
One potential challenge or risk of using big data as part of a clinical system
One major challenge in the EHRs the lack of standardization of the systems. All of a patient’s record can only be seen when all the systems used interface. The lack of standardization of data is challenging as the analytic person has difficulty assessing the performance of the organization or a certain unit in order to make an informed decision (thew, 2016).
Data security presents another problem for big data. Health systems must improve their information security to protect their database from breach. Hacking, cybertheft, or data phishing can result in patients’ data stolen and used for criminal activities. The risk of data compromise can be limited by using cloud technology for storing data. Cloud storages are often highly protected by healthcare organizations and the cloud service provider (Wang et al., 2018).
To safeguard the risk of big data, institutions must safeguard their data. During my time working at a county jail facility, there were multiple attempts by hackers to get into the system and change the release dates of some of the people locked up in the jail. The attempt was discovered, and the department decided to contract their record security to an outside cyber security firm.
References
Dash, S., Shakyawar, S., Sharna, M., Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. J Big Data 6, 54 (2019). https://doi.org/10.1186/s40537-019-0217-0Links to an external site.. https://link.springer.com/article/10.1186/s40537-019-0217-0#citeasLinks to an external site.
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs Links to an external site.Links to an external site.. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
-
Collapse SubdiscussionMansong Ntekim References
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations Links to an external site.Links to an external site.. Technological Forecasting and Social Change, 126(1), 3–13.
-
Collapse SubdiscussionSimranjeet Brar Mansong,
I enjoyed reading your detailed post. As you’ve mentioned, the health care industry is yet to appreciate the benefits of using big data along with the potential risks. When it comes to the benefits, the utilization of big data is advantageous since it allows for effective follow-up, which in turn reduces hospital costs and shortens patients’ stays. This is fundamental for providing care that is coordinated across disciplines and individualized to each patient’s needs. Big data has a number of advantages, but its application is complicated by a dearth of management expertise in areas like data governance (Awrahman et al., 2022). Implementing effective techniques to manage and control big data is one approach that may be used to address this issue (Pesqueira et al., 2020).
References
Awrahman, B. J., Aziz Fatah, C., & Hamaamin, M. Y. (2022). A Review of the Role and Challenges of Big Data in Healthcare Informatics and Analytics. Computational Intelligence and Neuroscience, 2022. doi: 10.1155/2022/5317760Links to an external site.Links to an external site.
Pesqueira, A., Sousa, M. J., & Rocha, Á. (2020). Big data skills sustainable development in healthcare and pharmaceuticals. Journal of Medical Systems, 44(11), 1-15. https://doi.org/10.1007/s10916-020-01665-9
-
-
Collapse SubdiscussionRoberto Monroy Data is collected worldwide in every profession/industry; in the medical field, this collection of data can be analyzed to discover trends and other meaningful data to improve healthcare (McGonigle & Mastrian, 2022). One potential benefit of using big data is the ability to use applications or mobile devices to monitor patients and detect risk factors for disease; this data can be analyzed in real-time and prompt users to make changes to reduce health risk, thus improving health outcomes (Pastorino et al., 2019).
One potential challenge of using big data in the clinical setting is privacy; big data is said to have access to almost everything, including private health information, private recordings, and even social media (Awrahman et al., 2022). This is concerning as, time and time again, we have seen cyber-attacks on information systems leading to personal information being stolen or leaked to the public. If this were to occur in a clinical setting, it could have devasting effects on a patient’s well-being.
I would propose increased monitoring and surveilling of this data to prevent such incidences from occurring; in addition, I would push for the development of systems that only collect pertinent information regarding our personal health history and avoid using social media platforms or similar as a means to collect data as they can be inaccurate.
References
Awrahman, B. J., Aziz Fatah, C., & Hamaamin, M. Y. (2022). A Review of the Role and Challenges of Big Data in Healthcare Informatics and Analytics. Computational Intelligence and Neuroscience, 2022, 5317760. https://doi.org/10.1155/2022/5317760Links to an external site.
McGonigle, D. & Mastrian, K. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning.
Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019). Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. European journal of public health, 29(Supplement_3), 23–27. https://doi.org/10.1093/eurpub/ckz168Links to an external site.
-
Collapse SubdiscussionBarkisu Fortenberry Response 1
Hello Roberto,
I agree that privacy which entails how the data is used, including the people authorized to access it, is one of the most significant challenges that big data in healthcare faces. The patient journey in the hospital brings together different team players, each performing their role aiming at one specific goal: meeting the patient’s needs. However, how these players use the big data safeguards it or could let it into unsafe hands, such as cyber thefts; this leads to the question of how healthcare team players could use the big data safely without giving fraudsters a chance (Senthilkumar et al., 2018). I am happy that you proposed monitoring and surveillance of the use of big data, which I support that is crucial in ensuring new ways that cybertheft develops to steal patient health information are discovered and protective measures put in place. Still, healthcare workers must be continuously educated and updated about the new tricks that cybertheft use and how to overcome them because they are the primary portal of entry that the cybertheft will use to steal patient health information (Ristevski & Chen, 2018). A healthcare worker who does not know how to safeguard patient information could easily engage in activities that make the data vulnerable to fraudsters. As a result, healthcare organizations must frequently assess the staff’s knowledge of the privacy and safety of protected patient information and educate them based on the result of such evaluations. The organization should also share with staff the result of the monitoring and surveillance to ensure they are updated about the new ways of protecting patient-protected health information (Lv & Qiao, 2020).
References
Lv, Z., & Qiao, L. (2020). Analysis of healthcare big data. Future Generation Computer Systems, 109, 103-110. https://doi.org/10.1016/j.future.2020.03.039Links to an external site.
Ristevski, B., & Chen, M. (2018). Big data analytics in medicine and healthcare. Journal of integrative bioinformatics, 15(3). https://www.degruyter.com/document/doi/10.1515/jib-2017-0030/html?lang=de
Senthilkumar, S. A., Rai, B. K., Meshram, A. A., Gunasekaran, A., & Chandrakumarmangalam, S. (2018). Big data in healthcare management: a review of literature. American Journal of Theoretical and Applied Business, 4(2), 57-69. http://www.sciencepublishinggroup.com/j/ajtab
-
Collapse SubdiscussionBertina Boma Soh Hey Roberto, big data has become capital. Think of some of the world’s biggest tech companies. A large part of the value they offer comes from their data, which they’re constantly analyzing to produce more efficiency and develop new products.
Recent technological breakthroughs have exponentially reduced the cost of data storage and compute, making it easier and less expensive to store more data than ever before. With an increased volume of big data now cheaper and more accessible, you can make more accurate and precise business decisions.
-
Collapse SubdiscussionOdion Iseki Hello Roberto
Great post ,I find your post very insightful as you touched all relevant issues regarding this. Data security at work can make it less likely that a former worker will steal or otherwise misuse sensitive information about the company. One way to achieve this objective is to have all potential workers sign a nondisclosure agreement and undergo background checks. By signing this NDA, employees agree not to disclose proprietary information to other parties. No matter what method you use, keeping sensitive information safe at work requires keeping it secret.
References
Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
-
Collapse SubdiscussionChristiana Nuworsoo Roberto,
Cyber attacks and/or cyber breaches in healthcare are becoming more prevalent because of the large amount of sensitive
information that can be found. As we become more reliant and dependent on technology for efficient patient care, Information
like patient social security numbers, credit cards, birth dates, and other health records are compromised because it makes the
institutions vulnerable to cyber attackers (Ghafur et al., 2019). Also, users of these systems must be conscious of how they use
them. Globally, healthcare is the industry where the most threat (about 46%) of data breaches comes from inside
the institution due to employee negligence and abuse of access to data (Ghafur et al., 2019). Cyber attacks in the healthcare of
any institution are costly and detrimental to patients.
One significant issue is that most healthcare institutions purchase their information systems from commercial vendors and
need more institutional experts to maintain them(Gopinath & Olmsted, 2022). Without experts researching possible threats and
dangers, the institution and its patients are left unguarded. The time has come for institutions to employ experts with the
systems they decide to purchase for their organizations so that more stringent security protocols can be created to ensure cyber
attacks and/or breaches do not occur.
References
Ghafur, S., Grass, E., Jennings, N. R., & Darzi, A. (2019). The challenges of cybersecurity in health care: the UK National Health
Service as a case study. The Lancet Digital Health, 1(1), e10-e12.
Gopinath, S., & Olmsted, A. (2022). Mitigating the Effects of Ransomware Attacks on Healthcare Systems. arXiv preprint
arXiv:2202.06108.
-
-
Collapse SubdiscussionErica Schulte Main Post – Erica Schulte
Benefits of Using Big Data
Utilizing big data as part of a clinical system has many benefits. These can include the use of Electronic Health Records and other tools for patient monitoring as well as communication. In a video communication focusing on the benefits of big data in diabetes management, practicing physician Grant Shevchik, (Walden University, 2018) discusses some of the tools that are being used in his field. Collecting the progression of data from a patient is the one area in particular that can be extremely beneficial. While an initial view of a patient’s status could be deemed negative, understanding that patient’s progression up to that point may change the viewpoint of a provider. This progression is most easily understood through the data collected within an Electronic Health Record. In addition, the ability to communicate through available technology, specifically smart phones, with the patients has hallowed for the ability to quickly contact individual patients and also efficiently distribute mass information to multiple patients.
Challenges of Using Big Data
While the future of big data within healthcare and clinical systems is extremely bright, there are also challenges that need to be considered. These challenges include security, ownership, storage, and even what data should be used (Shanthagiri, 2014). To focus on one of these challenges in particular, the decision of the data to focus can be a critical element. There is such a vast amount of data and information that is produced in today’s world, the term ‘drowning in data’ can be a real issue (Thew, 2016). This creates an issue of nurses and nurse leaders abandoning certain data and instead relying on topics that they feel most strongly about.
Strategies to Overcome the Challenges of Big Data
For myself, currently working in the healthcare insurance field, utilizing informatics and big data is necessary to all aspects of my work. When I look at the ‘Big Data Checklist’ discussed in Jennifer Thew’s article, (Thew, 2016), the steps really identify and are apparent within the culture that has been established. The elements that are described within the checklist includes creating a culture that thrives on data. This is necessary in my current field as the data collected is what we rely on to make an educated decision. The next step to the checklist includes creating big data competencies which is necessary to maintain efficiencies, this is a requirement within my position. Finally, creating an infrastructure with the ability to support big data is necessary for many reasons. Ultimately, if the tools are not available to support the big data efforts, then the efforts will not be successful.
References
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs Links to an external site.Links to an external site.. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
Walden University, LLC. (Producer). (2018). Health Informatics and Population Health: Analyzing Data for Clinical Success [Video file]. Baltimore, MD: Author
Vinay Shanthagiri. (2014). Big Data in Health Informatics Links to an external site.Links to an external site.
[Video file]. from https://www.youtube.com/watch?v=4W6zGmH_pOw-
Collapse SubdiscussionAdrienne Aasand Response #2:
Erica,
Thank you for your discussion post. It is interesting reading about your perspective as a nurse working in healthcare insurance and how using big data impacts this field. I agree with your comment that creating infrastructure to support big data is an important strategy when using big data (Threw, 2016). An existing infrastructure supporting big data is the Unified Medical Language System (UMLS). UMLS integrates various terminologies and coding systems and brings together health and biomedical vocabularies so that different computer systems can work together while compiling data (Austin et al., 2021). One initiative that advances healthcare and knowledge discovery by using UMLS is the Nursing Knowledge Big Data Science Initiative. The goal of this initiative is to develop an action plan to shape health policy and nursing informatics based on sharable, comparable nursing data. It provides structure for nurses to use big data in healthcare research, to ultimately improve patient outcomes. It guides nurses on data collection practices and provides education for nurses in research and documentation (Delaney & Weaver, 2018). Using a system such as UMLS is an important strategy to using big data to advance nursing practice and healthcare.
References
Austin, R., Chi, C., Delaney, C., Kirk, L., Michalowski, M., Pruinelli, L., Rajamani, S., Monsen, K. (2021). COVID-19 response empowered through
nursing knowledge generated through existing IT infrastructure. Online Journal of Nursing Informatics, 25(1), 3-1.
Delaney, C. & Weaver, C. (2018). 2018 nursing knowledge big data science initiative. CIN: Computers, Informatics, Nursing, 36(10), 473-474.
doi: 10.1097/CIN.00000000000000486.
Threw, 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
-
-
Collapse SubdiscussionBertina Boma Soh The potential benefit of using big data as part of a clinical system
Big data has revolutionized the world of healthcare and medical research. By exploiting the potential of big data, clinicians have gained insight into diagnosing and treating diseases in unprecedented ways. One of the major advantages of using big data in a clinical system is that it allows doctors to review vast amounts of historical information quickly and accurately. This can enable greater accuracy when making diagnoses or prescribing medications for patients, as patterns can be identified across many individuals and circumstances(Wang et al., 2018).
Additionally, using big data can help reduce the amount of time spent researching various treatments and allow doctors to understand better how certain treatments might affect different demographics or conditions. Additionally, by utilizing machine learning algorithms, clinicians can compare new information against historical trends and identify any correlations that may result in improved care delivery practices.
Potential challenge or risk of using big data as part of a clinical system
Big data is increasingly being used in clinical systems to improve the accuracy of diagnoses and provide better patient care. However, its use comes with several potential challenges and risks. To begin with, data privacy is an important issue to consider when using big data due to the sensitivity of clinical information. If proper safeguards are not implemented, medical records could be exposed or stolen, leading to serious implications for patients and their providers. Personal health information (PHI) must be kept secure, as a data breach could put patients at serious risk. Large volumes of PHI can be collected and stored with big data, increasing the risk of a data breach. It is also important to consider how data is collected, stored, and shared. If data is not properly managed, it can fall into the wrong hands, causing a breach of sensitive information.
Additionally, as large amounts of data are collected from an ever-growing range of sources, and it can be difficult to ensure that the information is accurate and reliable. Inaccurate or incomplete datasets can lead to incorrect patient treatment decisions, which could seriously affect their health (Dash et al., 2019).
Mitigation Strategy
Implementing strong security measures is one strategy for mitigating the risks and challenges associated with using big data in a clinical system. It is essential that all medical data is encrypted and stored securely using methods such as tokenization and authentication. Additionally, access to the data should be limited to those with the appropriate credentials. Doctors should also be trained in data security best practices, such as avoiding the use of weak passwords or storing patient data on unsecured devices. Furthermore, organizations should consider implementing a data breach response plan, which outlines the steps to be taken if a breach is detected. This should include informing the appropriate authorities and supporting affected patients. Finally, organizations should ensure that their data is collected and stored in a way that complies with all relevant regulations, such as HIPAA (Thompson, 2018). This will ensure that patient data remains protected and that organizations remain compliant.
References
Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6(1), 1-25.
Thompson, E. C. (2018). Cybersecurity incident response: How to contain, eradicate, and recover from incidents. Apress.
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological forecasting and social change, 126, 3-13.
-
Collapse SubdiscussionAdrienne Aasand Response #1
Bertina,
Thank you for your discussion post about the challenges and opportunities of using big data in healthcare. In your post you mentioned that as large amounts of data are collected from many sources, a challenge is to ensure information is accurate and reliable. To ensure accuracy of data, healthcare organizations need to provide data collection guidelines for data availability, criticality, authenticity, sharing and retention. In addition, healthcare organizations will need to define the value of their data to determine which data should be used (Wang et al., 2018). Audits can also be conducted to verify accuracy of data. Accuracy of data is essential because it will ultimately lead to information that will guide the development of new patient treatments or care models, and will lead to better patient outcomes (McGonigle & Mastrian, 2022).
References
McGonigle, D. & Mastrian, K. (2022). Nursing informatics and the foundation of knowledge (5th 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(1), 3-13.
-
Collapse SubdiscussionSimranjeet Brar Bertina,
I enjoyed reading your thorough post regarding big data and its potential risks and benefits. It’s fantastic to be able to broaden our horizons and learn new things beyond the realm of direct patient care that most of us has been exposed during majority of our careers. Big data is a huge component of how corporate and top-level management teams obtain insight to address challenges related to patient outcomes, which has always been a curiosity to me. Big data refers to an ever-expanding store of information that may be mined for insights into previously unseen connections and trends (McGonigle & Short, 2022). The incorporation of smartphones into medical practice is a major step forward. Most large-scale medical networks offer patient applications where patients may save their medical records, prescriptions, and test results for easy access. Keeping track of patient medical histories, laboratory results, and spotting trends requires a vast data collection, but this is how physicians and organizations handle it. Integrating individual data from mobile health applications or linked devices is another advantage of big data since it might provide novel insights into disease risk factors (Pastorino, 2019) I’m curious to find out more about the state of the art in data collecting and how we can utilize it to improve our understanding of the world and the lives of its populations.
References
McGonigle, D., & Mastrian, K.G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning.
Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019, October). Benefits and challenges of big data in healthcare: an overview of the european initiatives. European Journal of Public Health. 29(Suppl 3), 23-27. https://doi.org/10.1093%2Feurpub%2Fckz168Links to an external site.
-
Collapse SubdiscussionKatrina Brooks Hi Bertina,
There are some safety measures built into EHR systems to protect personal health information (PHI) such as access control tools like passwords and PIN numbers to control access to patient information to authorized individuals and encrypting stored information, meaning health information cannot be read without using a special key to decrypt it made available to authorized individuals. Privacy and security concerns has been the biggest barrier with using EHR systems. Firewall which is software or hardware that prevents unpermitted network traffic is another way to protect PHI and maintain HIPPA compliance. “Firewalls are essential to healthcare organizations because they are the first blockade in protecting EHR systems and other technologies from cyber-attacks” (Firewall, n.d.). The chances of a network getting hacked without firewall protection is much higher.
References
Firewall. Definitive Healthcare. (n.d.). Retrieved from https://www.definitivehc.com/resources/glossary/firewallLinks to an external site.What security safeguards are designed to prevent electronic health records from being “hacked?” | HealthIT.gov. (2013, January 15). Retrieved from
-
-
Collapse SubdiscussionColleen Lewis Main post, Discussion week 5: Benefits and risks of big data
One potential benefit of big data is improvement of clinical care using patient data to inform evidence-based practice. Big data analytics systems have the unique ability to analyze both semi structured and unstructured data that wasn’t possible with traditional forms of data management (Wang et al 2018). With analytical capabilities, users can identify patterns of care and associate massive amounts of information from healthcare records. For example, analysis of big data can identify patterns of patient readmission to the hospital that had previously gone unrecognized (Wang et al 2018). Patients’ lab results and clinical imaging are examples of semi or unstructured data that can now be analyzed and used to inform future care for those patients. Recognition of patterns, such as readmission, along with patterns in labs or imaging can inform decisions in care for patients and has the potential to improve outcomes.
The predictive capability of big data analytics has the potential to be extremely helpful in recognition of patterns and predicting future trends. By using sophisticated statistical tools, models of future environmental trends can be created and used to inform managers decisions (Wang et al 2018). By analyzing patients’ lifestyle and habits, along with the information gathered throughout their hospital stay, predictions can be made regarding future needs in disease management. That information can inform preventative care for patients. In an analysis by Thew (2016), Casper states the promise of prescriptive capabilities of big data is it “will give us knowledge and suggest interventions, or the capability to do something about a predicted upcoming event”.
However, with knowledge of potential future direction of disease and guidelines for disease management based on big data, providers of healthcare must be careful to not lose sight of the importance of personalized patient care. Personalized medicine involves taking individual variability into account when planning care for treatment and prevention strategies for a patient (Balthazar et al 2018). It’s important that providers do not move away from honoring individual variability in their patient care approach as big data predicts certain trends and needs in disease management.
The use of big data to track patient trends, use information to inform care and predict patterns raises some other ethical concerns involving consent. The use of patient information from electronic health records for research requires informed consent. There are regulatory frameworks that guide use of patient data for purposes of research. While the potential to improve patient care with use of big data serves to benefit, some patients have concerns regarding the sale of their information to others. “Patients have significant concerns about sharing their anonymized personal health records when they might be divulged or sold to other organizations to be used for profit” (Balthazar et al 2018).
Some methods to avoid the unethical use of patient data are ensuring there are mechanisms for blanket or individual consent for development, validation, and use of big data analytics for research (Balthazar et al 2018). Also, its necessary to examine what mechanisms are in place to ensure data of patients who have opted out are excluded. Balthazar et al (2018) suggest that patients should be informed of what their information can and cannot be used for and what their rights are, regarding use of their personal health information for research (p 584).
While the use of big data has promising potential to improve patient outcomes through analysis of unstructured data and massive amounts of patient data across health records, researchers must be extremely careful to ensure consent has been obtained from patients whose records are used. Further, as clinicians use analyses of future trends in disease management to shape their approach to patient care, they should remain sensitive to individual patient needs and focus on maintaining the patient-centered care approach.
References
Balthazar, P., Harri, P., Prater, A., & Safdar, N. M. (2018). Protecting your patients’ interests in the era of big data, artificial intelligence, and Predictive Analytics. Journal of the American College of Radiology, 15(3), 580–586. https://doi.org/10.1016/j.jacr.2017.11.035
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Health Leaders Media. Retrieved December 28, 2022, from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs?page=0%2C1
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
-
Collapse SubdiscussionJamee Renee Linnenbrink First Response
Colleen,
Your post is well put together and I agreed with what you were trying to get across. One of the more commonly forgotten about issues with big data collection is the ethical implications of collecting data. This includes and is not limited to potential misuse of personal information, well-publicized privacy breaches, and ongoing profiling of individuals for commercial purposes (Garattini et al, 2017). These often can be described as “unintended” risks but are still large risks for our patients. One of the other downplayed ethical issues of big data is the environmental waste that big data machines produce. Yes, this is arguably less than paper waste, but it still needs to be kept in mind. Computers, batteries, and wires, all still have to be disposed of somehow and the waste of these products can also have an environmental impact (Lucivero, 2020).
Jamee
References
Garattini, C., Raffle, J., Aisyah, D. N., Sartain, F., & Kozlakidis, Z. (2019). Big data analytics, infectious diseases and associated ethical
impacts. Philosophy & technology, 32(1), 69-85.
Lucivero, F. (2020). Big data, big waste? A reflection on the environmental sustainability of big data initiatives. Science and engineering
ethics, 26(2), 1009-1030.
-
-
Collapse SubdiscussionMansong Ntekim Week 5 Discussion
There have been great innovations in health technology over many years of practice of medicine, but scantly has any impacted the practice of medicine than digital technology. Dramatic improvements in networking and computers have not only expanded options for medical treatments but have also transformed how clinicians perform their jobs. From massive diagnostic imaging scanners to tiny wearable sensors, technology is an integral part of modern healthcare (IBM, n. d.). Using technology to measure and capture data across the whole system of patient care gives health organizations a big-picture view of how they’re performing. Technology also helps to automate that measurement so organizations can continuously review their results, spot issues that need to be fixed and uncover ways to enhance care and the patient experience (IBM, n. d.).
The use of Vocera badge was introduced into our facility in 2015 due to complaints of staff lack-luster attitude towards their duties, to keep track of staff whereabouts, to improve on-time communications (voice or text) between staff members, or secure texting to contact a physician or other care team members, alert on the location of staff and patient, and to reduce the noise of frequent over-heard paging of staff in the facility. The use of Vocera badge has improved on-time contact and communication between staff, the alert/panic button helps to summon immediate assistance for staff or patients’ that need immediate assistance. The device has greatly reduced the incidence of staff disappearance from their duty post or remaining out of contact. In a mental health unit like ours, the safety of the staff and patients are crucial, and the Vocera badge is a needed technological innovation.
The efficacy of any technological innovation is as good as the commitment of its users. Despite the benefits of the Vocera system, there are still challenges with the commitments of some of the users. There are instances where the nurse or the mental health tech (MHT) leave the Vocera badge at the nursing station or elsewhere and walk away. There was a situation where a MHT could not account for his Vocera badge at the end of the shift and search of the unit ensued. The badge was found under a patient’s mattress. The misplacement of the Vocera device by staff could place patients sensitive information in the wrong hands, a HIPPA violation.
There is the risk of data safety if the receiver of the message does not have a headset. Users of Vocera are trained to interrupt the sender of the message or use the pause button, then move to a secured location before relaying any patient related information (Vocera Communications, n. d.). The use over improves patients’ outcomes. A nurse mentioned a situation when she was with a patient in the lab and the patient went into respiratory distress, The nurse didn’t have to leave her patient to find a phone, nor take her focus from what she was doing. She just pressed the alert button and help arrived timely.
The Vocera technology has a promising potential in the future of nursing practice, according to Halifax Health (2017), “One of the most interesting new alerts connects the Vocera Communication System to a new point-of-care decision-support application from Lippincott Solutions. The software monitors patient data gathered from the EHR system, looking for early signs of a developing infection. When it sees trouble, the system automatically sends an alarm to the appropriate nurse’s Vocera Badge. With this early warning, the hospital staff can act immediately to accelerate treatment and ensure a patient’s speedy recovery.”
Reference
Hallfax health (2017). Halifax Health Ensures Communication Security, Ends Up Reducing Patient Stress and Wait Times. https://www.vocera.com/sites/default/files/VC-3032%20Halifax%20Health%20Case%20Study.pdf
IBM (N. D.) How technology has changed Healthcare. https://www.ibm.com/ph-en/topics/healthcare-technologyLinks to an external site..
Vocera Communications (n. d.). HIPPA Data Security and Privacy Standards for Voice Communications Over a Wireless LAN. https://www.vocera.com/sites/default/files/resources/wp_hipaa_0108_v1.pdf
-
Collapse SubdiscussionJamee Renee Linnenbrink Second Response
Mansong,
I have an interesting story that involves tracking badges. Ours does not have a name, but by what you described they do all the same functions. The father of the hospital’s CEO was being taken care of after some significant illness. He reported to his daughter the CEO the night after his admission that he was left to lay all night without being checked on, changed, or assisted in any way after he pressed that call light several times. Before any of the staff could even explain their side of the story they were called to the nurse manager’s office the next day. Most of them had to come back to work that night and had been sleeping. They were questioned by a very upset CEO as to why her dad was not being given top-notch care. Luckily the nurse manager before the meeting was able to defend her employees as she pulled from the system how many times each employee entered the room, how long they stayed in the room, and how many times the patient pressed his call light. This could have potentially saved them their job in a worse-case scenario. Your post sparked the question as to how often big data is used in court cases involving healthcare.
Data misuse and ethical complications are a concern when it comes to big data and the clinical setting. What are the ethical complications of using big data collection against the employee? The firing of an employee after data collection of misuse of narcotics can be beneficial to the employer, and is an obvious problem for the employee but how ethical is it to track an employee through an entire shift (Cohen and Mello, 2019). Also, in cases like those stated in the story, it was beneficial to the employee. In cases like malpractice, there may be so much data produced that it may be intimidating and difficult to know where to start (Steward and Cavasos, 2019). Either way, the ethical implication for the patient and the employee are at stake.
Jamee
References
Cohen, I. G., & Mello, M. M. (2019). Big data, big tech, and protecting patient privacy. Jama, 322(12), 1141-1142.
Steward, D., & Cavazos, R. (2019). Big data analytics in US courts: uses, challenges, and implications. Springer Nature.
-
-
Collapse SubdiscussionJamee Renee Linnenbrink Initial Post
Big Data Used every day
Today I am sitting in the library with my computer on, my phone beside me, the coffee that I picked up at the grocery store, and my Spotify list playing music. All after I registered and signed in to a workout class this morning. I have already generated a large amount of data for the day and it is not even close to noon yet. Technology has vastly grown in the last 10 years and is continually growing. Big data in healthcare has had a considerable influence across healthcare functions, including clinical decision support, disease surveillance, and health management, among others (Khanra et al, 2020).
Big Data Potential Benefits
Not only has big data changed the hospital flow and nursing. It has also significantly changed research and education in healthcare benefiting the clinical system. Exploiting new tools to extract meaning from a large volume of information has the potential to drive real change in clinical practice (Hulsen et al, 2019). The production of big data learning is limitless as far as sharing information and producing healthcare workers that have access to a large amount of information and answers to complex clinical studies that can be put into place while practicing. This can/has improved the clinical system as far as the outcomes of the patients.
Big Data Complications
Complications can occur with big data compilation. One of the biggest complications that we can deal with in health care is to effectively use machine big data tools in health care, limitations of data collection must be addressed (Ngiam and Khor, 2019). When electronic healthcare systems and other data-collection tools are used there are certain limitations to the data that can be collected and then need to use judgment and clinical thinking tools to implement and evaluate data may be needed.
References
Ngiam, K. Y., & Khor, W. (2019). Big data and machine learning algorithms for health-care delivery. The Lancet Oncology, 20(5), e262-e273.
Hulsen, T., Jamuar, S. S., Moody, A. R., Karnes, J. H., Varga, O., Hedensted, S., … & McKinney, E. F. (2019). From big data to precision medicine. Frontiers in medicine, 34.
Khanra, S., Dhir, A., Islam, A. N., & Mäntymäki, M. (2020). Big data analytics in healthcare: a systematic literature review. Enterprise Information Systems, 14(7), 878-912.