Big data in health institutions

Big data in health institutions

Medicine industry is one of the beneficiaries in the evolvement of Big data which have changed how health institution manage, analyze, and collect data useful in decision making. Mainly, analyzed data in the medical field help in solving management issues, reducing the cost of treatment, predicting epidemics, combating preventable diseases, reduce the workload as well as improving the quality of life. Notably,  data collected and stored in the health system facilitate a review of patients personalize treatments, improve treatment methods, enhances better communication between medics,  and reduce discharge time. Importantly, health data analytics will assist the doctors to detect early sign of an illness which will be easily treated and less costly. Therefore, there is a need for health institutions to enroll individuals with personal electronic health records ( EHR), which will facilitate the collection of patients’ health information from different sources.

Treatment models driven by data and improved technologies enable the more accessible collection of data, which provides insight in offering better health care to patients. Notably,  data collected can be either quantitative, that is in number form, or qualitative, which means it is in the form of words. Mostly, medical information is collected using intergrated customer relationship management(CRM), electronic health record systems (EHR), and use mobile applications(SAKOVICH,  2019).To effectively offer adequate treatment and prevent health deterioration a patient needs close monitoring. Ideally, It is achievable through individually collected data in clinical observations, diagnoses, test results, medication is taken, and the current health using (EHR).

Mostly, information recorded in the (EHR) comes from questionnaires, observation, and examining the patient. For example, using the medical card, a patient can receive notifications about the need to undergo a new lab test and to track individual compliance with prescriptions. Additionally, using digitized medical records, the medics are in a position to differentiate symptoms, improve diagnostic, practice efficiencies, and offer adequate treatment.

Increase adoption of (EHR) globally has achieved numerous benefits such as enhanced records security and confidentiality of patient information, which can be easily retrieved by health providers. Also,  Improved communications between the healthcare provider and enhanced accountability in the management of patients. However,  (EHR)is accompanied by design flaws and financial challenges that hinder the adequate provision of better health care(Lebied, 2019). Therefore, from the data collected, health care institutions should realize the need to have useful medical software in providing comprehensive patient management practices. Eventually, this will simplify the medics activities such as scheduling treatment, prescriptions, controlling individual data, and billing. As a result, the development of other apps, as well as the use of digital records, will increase doctors’ productivity and improve individuals’ data security.

Importantly,nurse leaders should be in a position to implement EMR systems to better management of the patient and to offer effective collaboration among the healthcare workers involved in caring for patients. Additionally, other benefits acquired from the integration of (EMR) systems include a sufficient flow of information in making better clinical decisions, accurate data, and patient satisfaction through improved quality care. Besides, the nurse leader should embrace the use of data applications in the healthcare sector because data analysis is vital in changing individuals’ health for the better. Health predictive analysis assists in identify patient illness, preventing diseases at an early stage, and reducing the cost of treatment. Therefore, applying Big Data in the medical field will help in improving the well being of an individual through the development of crucial preventative measures and providing adequate treatment.

 

References

Lebied, M. (2019, January 4). 12 Examples of Big Data In Healthcare That Can Save People. Retrieved from https://www.datapine.com/blog/big-data-examples-in-healthcare/

SAKOVICH, N. (2019, November 20). The Importance of Data Collection in Healthcare and Its Benefits. Retrieved from https://www.sam-solutions.com/blog/the-importance-of-data-collection-in-healthcare/