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Healthcare Data Analytics
Name
Institutional Affiliation
Date
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Healthcare Data Analytics
Overview
Big data analytics in healthcare emerges as a new methodology providing new scope
for health providers to make decisions, optimize resources, and improve patient care
(Favaretto et al., 2019). Entailing BDA is inevitable for healthcare companies everywhere
since healthcare data grows like an avalanche from several sources, including medical
imaging, wearable technology, electronic health records, and genomic data.
It is a common perspective of academics and practitioners that big data can
significantly influence comprehension, prediction for, and combating health issues (Saif‐Ur‐
Rahman et al., 2023). For example, research conducted in Poland and Norway has yielded
essential insights on using BDA in healthcare settings. These studies demonstrate the
complex nature of BDA adoption in healthcare institutions by combining direct research with
a literature review (Razzak et al., 2020). They also demonstrate the extensive use of
structured and unstructured data for business, administrative, and clinical objectives.
The significance of BDA in healthcare has increased in light of international health
emergencies like the COVID-19 pandemic (Benzidia et al., 2021). The rise in “black swan”
incidents highlights the need for solid analytical frameworks to direct real-time resource
allocation and decision-making processes. The strategic ramifications of BDA adoption are
further clarified by research on big-data business models (Mikalef et al., 2020), highlighting
the role that BDA adoption plays in fostering organizational innovation and competitive
advantage.
The possibilities of BDA in healthcare are further enhanced by its integration with
artificial intelligence (AI) technology (Lee et al., 2023). Research has demonstrated that AIpowered BDAs can facilitate population health management, disease diagnosis, treatment
optimization, and predictive modeling. Healthcare organizations may improve clinical
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outcomes and operational efficiency by utilizing sophisticated analytics techniques like
machine learning and natural language processing to extract relevant insights from large
amounts of healthcare data.
Additionally, BDA makes it easier to create personalized medical strategies in which
each patient’s preferences and traits are considered while creating treatment regimens
(Ahmed et al., 2021). Healthcare specialists will be better placed to improve patients’ disease
states by examining patterns, trends, and potential dangers of patient data usage in real-time.
The undeniable power of BDA still encounters problems that need to be solved before
it becomes omnipresent in healthcare (Barrows et al., 2020). Security, privacy data privacy,
interoperability, and ethical issues are formidable obstacles to mainstream adoption. In
addition, because healthcare data is complicated, it calls for specialized analytical tools and
knowledge, which means infrastructure, talent acquisition, and training costs must be
covered.
Future studies in BDA in healthcare will concentrate on finding solutions to these
problems and breaking new ground (Batko & Ślęzak, 2022). In order to meet urgent
healthcare needs, researchers and practitioners will keep looking into creating cutting-edge
analytical models, prediction algorithms, and decision support systems (Sheng et al., 2021).
In conclusion, BDA has great potential to change the administration and provision of
healthcare. Healthcare businesses may use big data to promote innovation and improve
patient outcomes. They can also increase the efficacy and efficiency of healthcare systems
worldwide by utilizing cutting-edge analytical techniques and technology.
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References
Ahmed, I., Ahmad, M., Jeon, G., & Piccialli, F. (2021). A framework for pandemic
prediction using big data analytics. Big Data Research, 25, 100190.
https://doi.org/10.1016/j.bdr.2021.100190
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
Benzidia, S., Makaoui, N., & Bentahar, O. (2021). The impact of big data analytics and
artificial intelligence on green supply chain process integration and hospital
environmental performance. Technological forecasting and social change, 165,
120557. https://doi.org/10.1016/j.techfore.2020.120557
Favaretto, M., De Clercq, E., & Elger, B. S. (2019). Big Data and discrimination: perils,
promises and solutions. A systematic review. Journal of Big Data, 6(1), 1-27.
https://doi.org/10.1186/s40537-019-0177-4
Lee, H. Y., Lee, K. H., Lee, K. H., Erdenbayar, U., Hwang, S., Lee, E. Y., … & Youk, H.
(2023). Internet of medical things-based real-time digital health service for precision
medicine: Empirical studies using MEDBIZ platform. Digital health, 9,
20552076221149659. https://doi.org/10.1177/20552076221149659
Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020). Exploring the relationship
between big data analytics capability and competitive performance: The mediating
roles of dynamic and operational capabilities. Information & Management, 57(2),
103169. https://doi.org/10.1016/j.im.2019.05.004
Razzak, M. I., Imran, M., & Xu, G. (2020). Big data analytics for preventive
medicine. Neural Computing and Applications, 32, 4417-4451.
https://doi.org/10.1007/s00521-019-04095-y
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Saif‐Ur‐Rahman, K. M., Islam, M. S., Alaboson, J., Ola, O., Hasan, I., Islam, N., … &
Joarder, T. (2023). Artificial intelligence and digital health in improving primary
health care service delivery in LMICs: A systematic review. Journal of Evidence‐
Based Medicine, 16(3), 303-320. https://doi.org/10.1111/jebm.12547
Sheng, J., Amankwah‐Amoah, J., Khan, Z., & Wang, X. (2021). COVID‐19 pandemic in the
new era of big data analytics: Methodological innovations and future research
directions. British Journal of Management, 32(4), 1164-1183.
https://doi.org/10.1111/1467-8551.12441
Wiener, M., Saunders, C., & Marabelli, M. (2020). Big-data business models: A critical
literature review and multiperspective research framework. Journal of Information
Technology, 35(1), 66-91. https://doi.org/10.1177/0268396219896811
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Antibiotic Use in Healthcare
Name
Institutional Affiliation
Date
2
Antibiotic Use in Healthcare
Overview
One of the recent discoveries that modern science has made is the antibiotics that
enable doctors to treat dangerous bacterial infections quickly (Ababneh et al., 2022).
Antibiotics have given a stage in the reduction of pain, and a vast number of lives have been
saved since these drugs were discovered. Meanwhile, the abuse and misuse of antibiotics are
severe risks for the emergence of resistance, mainly because of the worldwide health threat
(Akande-Sholabi & Ajamu, 2021). This overview critically review the pros, cons, and
importance of antibiotics in health care management in society.
Antibiotics are paramount in managing bacterial infections in hospitals and clinics
(Ayhan et al., 2024). Such medical advances significantly reduce mortality and morbidity by
successfully treating various conditions, including both minor skin infections and more
critical conditions such as sepsis. However, the overuse of antibiotics can become
problematic if they are used too often, which is increasingly dangerous for humanity. The
situation is significantly worsened by patient demand and misuse of medical prescriptions
(Boszczowski et al., 2020). Essential stewardship strategies instilling conservation practices,
such as education, guidelines, and surveillance, are the best ways to go against antibiotic
resistance. These strategies focus on decreasing resistance development and maximizing
patient results accordingly (Fentie et al., 2022). A joint approach is vital for solving this
problem in the long run. The approach incorporates healthcare professionals, governments,
and the public.
Although antibiotic overuse has many benefits, it may result in the development of
antimicrobial-resistant organisms, posing a threat to everyone’s health. Factors such as wrong
prescription, patient pressure, and inadequate care procedures associated with this condition
play a catalytic role (Garedow & Tesfaye, 2022). Antibiotic resistance problem is one of the
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leading causes of treatment inefficiency, more extended sickness, increased medical costs,
and high mortality. A range of solutions could be adopted to combat this problem, including
reinforcement of antibiotic stewardship policies, establishing good prescribing standards, and
prompt implementation of proper infection prevention and control procedures. Through
collaboration, the public, industry stakeholders, legislators, and healthcare professionals can
effect a decrease in antibiotic misuse and ensure that these drugs will be available for future
generations.
The antibiotic stewardship plans will urge the appropriate use of antibiotics, and this
is a valuable intervention in the war against antibiotic resistance. Such schemes encourage
evidence-based prescription techniques and value the importance of choosing the drugs for
the correct indication and dose (Hawkes et al., 2023). Stewardship programs will lower the
dosage of antibiotics, improve patient outcomes by reducing the spread of resistant
microorganisms, and increase the education of healthcare staff on antimicrobial resistance
and appropriate antibiotic administration. They also allow us to see the changes in antibiotic
resistance and antibiotic consumption. This gives doctors a chance to take action against the
spread of resistance; on the road to implementing efficient antibiotic management strategies,
antibiotic stewardship programs give healthcare teams interdisciplinary collaboration (Hu et
al., 2022). This includes infection control specialists, pharmacists, and microbiologists.
Antibacterial stewardship programs enhance the public’s health protection and preserve the
efficacy of antibiotics by implementing these measures.
Antibiotic resistance is a multi-sectorial problem that needs experts and actors
working together to tackle it. Campaigns targeting strengthening antibiotic stewardship will
include use only when necessary. This means that the authorities will implement policies,
educate the public and healthcare professionals, and support interdisciplinary collaboration
(Lampi et al., 2020). Research and development efforts must focus on new antibiotics and
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other treatments in the fight for adequate comprehension of bacteria-resistant
microorganisms. Strengthening infection prevention and control policies is necessary to limit
the dissemination of resistant strains.
Equally essential is educating the public, medical professionals, and lawmakers about
the impact of irresponsible antibiotic use on spreading resistant bacteria (Romaní et al.,
2022). However, together, we could minimize antibiotic resistance, keep the efficacy of these
medicines, and therefore encourage future generations to live in a better, healthier world.
Finally, antibiotics have entirely transformed the healthcare industry by the wipeout of many
bacterial infections, which could cause serious problems as well as pain. Microorganisms
have not been resistant to antibiotics since they have been overused and misused for a long
time, posing a severe challenge to public health.
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References
Ababneh, M. A., Al Domi, M., & Rababa’h, A. M. (2022). Antimicrobial use and mortality
among intensive care unit patients with bloodstream infections: implications for
stewardship programs. Heliyon, 8(8). https://doi.org/10.1016/j.heliyon.2022.e10076
Akande-Sholabi, W., & Ajamu, A. T. (2021). Antimicrobial stewardship: Assessment of
knowledge, awareness of antimicrobial resistance and appropriate antibiotic use
among healthcare students in a Nigerian University. BMC Medical Education, 21, 18. https://doi.org/10.1186/s12909-021-02912-4
Ayhan, M., Coşkun, B., Kayaaslan, B., Hasanoğlu, İ., Kalem, A. K., Eser, F., … & Güner, R.
(2024). Point prevalence of antibiotic usage in major referral hospital in Turkey. Plos
one, 19(1), e0296900. https://doi.org/10.1371/journal.pone.0296900
Boszczowski, Í., Neto, F. C., Blangiardo, M., Baquero, O. S., Madalosso, G., de Assis, D. B.,
… & Levin, A. S. (2020). Total antibiotic use in a state-wide area and resistance
patterns in Brazilian hospitals: an ecologic study. The Brazilian Journal of Infectious
Diseases, 24(6), 479-488. https://doi.org/10.1016/j.bjid.2020.08.012
Fentie, A. M., Degefaw, Y., Asfaw, G., Shewarega, W., Woldearegay, M., Abebe, E., &
Gebretekle, G. B. (2022). Multicentre point-prevalence survey of antibiotic use and
healthcare-associated infections in Ethiopian hospitals. BMJ open, 12(2).
https://doi.org/10.1136%2Fbmjopen-2021-054541
Garedow, A. W., & Tesfaye, G. T. (2022). Evaluation of Antibiotics Use and its Predictors at
Pediatrics Ward of Jimma Medical Center: Hospital Based Prospective Crosssectional Study. Infection and Drug Resistance, 5365-5375.
https://www.tandfonline.com/doi/citedby/10.2147/IDR.S381999?scroll=top&needAc
cess=true
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Hawkes, B. A., Khan, S. M., Bell, M. L., Guernsey de Zapien, J., Ernst, K. C., & Ellingson,
K. D. (2023). Healthcare System Distrust and Non-Prescription Antibiotic Use: A
Cross-Sectional Survey of Adult Antibiotic Users. Antibiotics, 12(1), 79.
https://doi.org/10.3390/antibiotics12010079
Hu, L., Fu, M., Wushouer, H., Ni, B., Li, H., Guan, X., & Shi, L. (2022). The impact of
Sanming healthcare reform on antibiotic appropriate use in County hospitals in
China. Frontiers in Public Health, 10, 936719.
https://doi.org/10.3389/fpubh.2022.936719
Lampi, E., Carlsson, F., Sundvall, P. D., Torres, M. J., Ulleryd, P., Åhrén, C., & Jacobsson,
G. (2020). Interventions for prudent antibiotic use in primary healthcare: An
econometric analysis. BMC Health Services Research, 20(1), 1-11.
https://doi.org/10.1186/s12913-020-05732-2
Romaní, L., León-Figueroa, D. A., Rafael-Navarro, D., Barboza, J. J., & Rodriguez-Morales,
A. J. (2022). Association between the Use of Antibiotics and the Development of
Acute Renal Injury in Patients Hospitalized for COVID-19 in a Hospital in the
Peruvian Amazon. Journal of Clinical Medicine, 11(15), 4493.
https://doi.org/10.3390/jcm11154493
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