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Big Data in Health Care or Retail

Introduction

Big data in healthcare refers to the collection, analysis, and utilization of patient, consumer, physical, and clinical data sets that are too large or complicated to be processed conventionally. Big data in healthcare is an important aspect that enables healthcare and doctors to make appropriate decisions in patients’ healthcare process. In this research, I will discuss how big data is used in healthcare.

Patient’s prediction for improved staffing

For my first example of big data in healthcare, I will look at one typical dilemma that each shift manager faces: how many employees do I put on staff at any given period? When you hire too many people, you must pay them for their time (Dash et al., 2019). With too few staff, you might have poor customer service results, which can be disastrous for patients in that business. At least in certain Parisian hospitals, large amounts of data are being used to find a solution. A white paper by Intel describes how four Assistance Publique-Hôpitaux de Paris hospitals have been forecasting patient volume daily and hourly using data from a wide range of sources.

Follow up care

Healthcare prevention and long-term care monitoring are two areas where big data may make a huge difference. To avoid hospital readmissions among the most vulnerable patients, big data technology has been used to forecast which patients are and aren’t likely to comply with their doctors’ orders. Now, GPS-enabled inhalers are being created to monitor asthma patients’ medication use. This data aids the doctor in developing more effective and individualized treatment plans for each patient, which in turn assists in preventing additional damage or disease. Firms like Ginger.io are utilizing data advantages by introducing mobile applications to the healthcare industry that monitor patients’ progress. With the patient’s permission, the app may collect data, including calls, location, physical movement, and sleep patterns, to inform physicians or loved ones if the patient is likely feeling sick or is in danger of an anxiety attack or other psychological crisis. Undoubtedly, the technology behind this smartphone app is beginning to open a new door in the realm of patient follow-up tools. Still, its effectiveness depends on collecting the necessary data.

Prevention of medication errors

Mistakes are inevitable for doctors and other medical workers, but patients’ lives are on the line in many cases. Hospital medication mistakes are sadly more prevalent than many would like to admit. Such catastrophic mistakes, however, can be avoided, or their frequency can be significantly reduced with big data (Senthilkumar et al., 2018). Allergies, previously prescribed drugs, dose amounts, and other pertinent information may be analyzed in each patient’s medical file thanks to big data techniques. When all records have been studied, the data analysis software can highlight any gaps in the data or suspicious items that have been detected.

Conclusion

Big data in healthcare is an important topic because it helps us to understand the importance of big data in healthcare. For instance, big data can enable healthcare to reduce costs; by digitizing medical information and enhancing preventative treatment, big data technology helps bring healthcare expenses down. Care is enhanced by better data tracking, which also reduces patients’ hospital stays. Lastly, big data can improve health by improving patient care; the primary advantage of big data in healthcare is how it enhances the quality of care for individual patients. All the data gathered by big data technologies, from preventative measures to more excellent real-time health information, aids clinicians in making quicker and more accurate diagnoses.

References

Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis, and prospects. Journal of Big Data6(1), 1-25.

Senthilkumar, S. A., Rai, B. K., Meshram, A. A., Gunasekaran, A., & Chandrakumarmangalam, S. (2018). Big data in healthcare management: a review of the literature. American Journal of Theoretical and Applied Business4(2), 57-69.

Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological forecasting and social change126, 3-13.

 

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