Direction:
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.
Allison P.
Post.
Simply put using big data gives us big numbers and access to greater amounts of information (Thew, 2016). Being able to better manage the information that we are given will in theory lead to better patient outcomes over time. An interesting piece of the study done and referenced in Technological forecasting and social change speaks to the literal innumerable amounts of data that have been collected in the healthcare industry (Yang et al). Through greater use of the already collected big data would be able to give us better real time information, again leading to better patient outcomes (Wang et al, 2018). Real time information instead of reports being given or run at certain time intervals they could be populated at any time for real numbers (Yang et al, 2018). The possibilities for this data are endless but some other benefits could be cost reduction, better patient practices/treatment, streamlining of treatments and policies, etc.
A risk that seems to already be happening and would continue to happen with an increase of putting all this patient information and data out there is data breaches. According to a peer reviewed article written in 2020 from 2014-2019 it is estimated that at least 154 million people had their personal health records involved in some sort of breach (Seh, et al, 2020). The average breach is about 2600 records and in the United States has the average cost of about 15 million dollars (Seh, et al, 2020). As the breaches have proven there is a strong desire for hackers to gain patients protected health information for the value of the contained information. Aside from breaches there is also patient information that is being accessed without permission (not a breach), people looking at medical information that they should not have access to. These two issues combined make it harder for the general public to trust that their personal information will be kept safe.
On a quick side note Amazon now offers access to health care visits for members. Amazon asks patients to sign away their rights to HIPPA, and disclose patients complete health file (Fowler, 2023). Amazon has gotten around this by saying that patients are voluntarily making this choice but this is how they can be seen (Fowler, 2023). Many patients are not educated as to what HIPPA truly is or how important it is to keep your health information yours. Amazon of course is denying anything nefarious but is this direction we are going to go in with so much more of our data being online?
Data collection and use when monitored and stored properly is a resource that we need to improve patient outcomes. But, with the current rate of data breaches increasing and no clear way to stop them it is scary to think that my personal information could be viewed by anyone. Ill use the example of where I work, we are only allowed to be in charts that we are supposed to be in. In the morning when I am assigned patients I make my list of patients and I have to say I am going in their charts as their nurse. If I need to go in another chart to pass a medication for a fellow nurse that is all closely monitored, if I am somewhere I am not supposed to be I have to answer to it. As a society we have gotten to comfortable with all of our information being out there instead I hope that we can get back to a place where information is used as needed but kept out of the hands of people with ill intent.
Reference
Fowler, G. A. (2023, May 2). Analysis | To become an Amazon Clinic patient, first you sign away some privacy. Washington Post. https://www.washingtonpost.com/technology/2023/05/01/amazon-clinic-hipaa-privacy/
Glassman, K. S. (2017). Using data in nursing practiceLinks to an external site.Links to an external site.. American Nurse Today, 12(11), 45–47. Retrieved from https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdfLinks to an external site.
Seh, A. H., Zarour, M., Alenezi, M., Sarkar, A. K., Agrawal, A., Kumar, R., & Khan, R. A. (2020). Healthcare data breaches: Insights and implications. Healthcare, 8(2), 133. NCBI. https://doi.org/10.3390/healthcare8020133
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execsLinks to an external site.Links to an external site.. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizationsLinks to an external site.Links to an external site.. Technological Forecasting and Social Change, 126(1), 3–13.
Samanthan H
Post:
In simple terms, big data is described by its extensive volume, variety, and complexity, which requires the development of new methods, processes, and computerized identification tools to report significant patterns and hidden information (Rolla, 2023). Using big data analysis can improve patient care. One benefit of using big data is being able to analyze data of complex patients to reduce the chance of hospitalization. Venna et al. (2023) explain how the reduction of hospitalization by 25% due to the big data analysis of medical records for patients at an increased risk of complications due to their chronic diseases. Being able to identify patterns of patients who have complex chronic diseases can offer clinicians the opportunity to provide specific care tailored to the patient’s needs. Venna et al. (2023) identified that providers who were able to use big data information had better patient results, reduced costs, decreased death rates, and fewer unfavorable drug reactions.
Technology has many great uses and has come along way within the past years, but even advanced technology isn’t perfect. There are some negative aspects to using big data, as well. Ngiam and Khor (2019) explain how algorithms may pull from small sample sizes, which can lead to inappropriate or harmful clinical recommendations for some patients. This can be harmful to smaller clinical systems with less diversity, as providers may choose the wrong treatment plans based on the big data recommendations. Providers should still consider their own medical judgment and go with what they think is the best overall treatment for the patient. To combat these challenges, Jiang et al. (2023) suggest that big data must meet qualifications for actual data-focused judgment-making from high-quality data algorithms and must be thoroughly assessed and perfected prior to being implemented into practice. This means that there should be a multitude of research and testing with real world situations prior to implementation in clinical settings.
References
Jiang, S., Wang, T., & Zhang, K. H. (2023). Data-driven decision-making for precision diagnosis of digestive diseases. BioMedical Engineering OnLine, 22(1), 1–30. https://doi.org/10.1186/s12938-023-01148-1Links to an external site.
Ngiam, K. Y., & Khor, I. W. (2019). Big data and machine learning algorithms for health-care delivery. Lancet Oncology, 20(5), e262–e273. https://doi.org/10.1016/S1470-2045(19)30149-4Links to an external site.
Rolla, K. J. (2023). Trends and futuristic applications of big data and electronic health record data in empowering constructive clinical decision support systems. BioScience Research Bulletin-Biological Sciences, 39(2), 78–91. https://doi.org/10.48165/bpas.2023.39.2.6Links to an external site.
Venna, S. V., Reddy Narra, S., Sai Tadisetti, T. P., Nandanampati, S. S. R., Tata, R. K., A, S. (2023). Big data analysis in healthcare: A comprehensive overview: Exploring the benefits of big data for health care programs. 2023 9th International Conference on Advanced Computing and Communication Systems (ICACCS), Advanced Computing and Communication Systems (ICACCS), 2023 9th International Conference on. 2023; 1:441 448. https://doi:10.1109/ICACCS57279.2023.10113099
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