Technological Advancement in Clinical

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Technological Advancement in Clinical

Technological Advancement in Clinical

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Health disparities is what I reflected on. Despite the fact that it is the responsibility of nurses to ensure health services are easily accessible to all patient populations, enhancing health care equity agenda has faced various barriers. For example, individuals are faced with inequalities based on their race in assessing health care services. Health disparities occur when a certain group of individuals has better access to health care services than the other. This is often illustrated in the differences in death rates among various diverse populations in the United States. The differences in the level of income for various individuals is the main cause of health disparities. For instance, poor blacks may find it difficult to access quality health care services compared to medium class whites (National Center for Health Statistics, 2016). Nurses play a key role in evaluating various health inequalities through a process called selection. Selection can be defined as the tendency of people to group themselves according to social gatherings, age or residential places.

The main focus in the development of new concepts in healthcare technology is patient care. Technological advancement in clinical applications has had a significant impact in the healthcare system and will continue to have a key role in the years to come (Gao, 2015). As a nurse, I have come to learn that nursing documentation is a very important element of healthcare information. Information systems are designed for nurses whereby documentation can be used to enhance a nurse’s knowledge regarding quality care. The field of nursing has received significant knowledge on how to improve patient care due to the new concepts that have been developed through information technology

(Sample) References

Burstin, H., Leatherman, S., & Goldmann, D. (2016). The evolution of healthcare quality measurement in the United States. Journal of internal medicine279(2), 154-159.

Char, D. S., Shah, N. H., & Magnus, D. (2018). Implementing machine learning in health care—addressing ethical challenges. The New England journal of medicine378(11), 981.

Gao, Y., Li, H., & Luo, Y. (2015). An empirical study of wearable technology acceptance in healthcare. Industrial Management & Data Systems115(9), 1704-1723.

National Center for Health Statistics (US. (2016). Health, United States, 2015: with special feature on racial and ethnic health disparities.

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