Posted: September 9th, 2022

Clinical Information Systems to Improve Outcomes

Clinical Information Systems to Improve Outcomes
Introduction
Clinical information systems are essential in improving patient outcomes. The information systems go beyond the human ability to diagnose diseases or to analyze data. The adoption of artificial intelligence information systems in healthcare will improve the quality of care. The essay examines four peer-reviewed journals on the adoption of artificial intelligence in the health sector. Rabbani et al. (2018) suggest that the use of computer-aided systems can improve early diagnosis of lung cancer. Ahuja (2019) suggests that with the ongoing development in healthcare technology, artificial technology can augment radiologists. Schonberger et al. (2019) appreciate that innovation has led to the decision-making capacities of the technology. Dankwa-Mullan et al. (2019) appreciate that artificial intelligence is critical in transforming care provision to diabetic patients. The purpose of the essay is to examine artificial intelligence and its impact on the provision of care using peer-reviewed studies.
Summary of Each Study, Improvement to Outcomes, and Lessons Learned
Rabbani et al. (2018) carried out a study on artificial intelligence’s role in the provision of care suffering from lung cancer. While lung cancer is one of the leading causes of death globally, the study suggests that artificial intelligence can improve diagnosis, treatment, and management of the disease. Rabbani et al. (2018) suggest that the use of computer-aided systems can improve early diagnosis of lung cancer. The study shows that one of the challenges in the fight against lung cancer is a late diagnosis which compromises treatment and management. The technology can improve the efficiency of diagnosing the disease early before the cancerous cells spread graduate to chronic stages and threaten the life of a patient.
I have learned that artificial technology can improve the diagnosis, treatment, and management of non-small cell lung cancer. According to Rabbani et al. (2018), computer systems can develop custom diagnoses and treatments. Physicians and customize the treatment method depending on the patient’s genetics, molecular, and histological features. Customizing the diagnosis and treatment can bear more fruits in the fight against cancer. Healthcare workers can enjoy the efficiency of providing care to patients by customizing the treatment plans. The outcomes will lead to early detection and diagnosis, better treatment, and reduced mortality rates (Rabbani et al., 2018). Despite the shortcomings of the technology in the healthcare sector, it can improve the patients’ quality of care and safety.
Ahuja (2019) examined the impact of artificial intelligence in medicine on the physician’s future role. The study examines the future of technology on the role of healthcare workers. Ahuja (2019) suggests that with the ongoing development in healthcare technology, artificial technology can replace radiologists. The study’s findings suggest that although complete replacement of the healthcare workers is impossible, the systems will augment the healthcare processes. Ahuja (2019) notes that the technology will augment professionals, including pathologists, cardiologists, radiologists, and ophthalmologists. Augmenting the various healthcare positions will improve the efficiency of providing care to a large population.
Ahuja (2019) appreciates that the technology will not replace the healthcare workers. One of the reasons is that patient-physician or nurse relationship is necessary. Patients need to experience a real person when they go to healthcare for a checkup or treatment. I have learned that the human aspect is not easy to replace in the healthcare sector. Human emotional and social relationships are important in the provision of care. Patients are not just looking for machines to fix their ailing bodies but for human beings to connect with. Another lesson is that human beings are necessary to provide care to eliminate the risk of medical errors that can undermine patient trust.
A study by Schonberger et al. (2019) describes the current status of artificial intelligence in the healthcare sector. According to the findings, recent innovations in the healthcare sector improve imaging and signal detection accuracy. Schonberger et al. (2019) appreciate that innovation has led to the decision-making capacities of the technology. While the technology will improve the lives of patients, it will present various ethical challenges. Schonberger et al. (2019) note that some ethical issues include fairness and discrimination, moral responsibility, and autonomy. Although artificial intelligence assumes human capabilities, it cannot observe ethical issues such as fairness and discrimination. The findings strengthen the results of other scholars that technology cannot eliminate human involvement.
I have learned that artificial intelligence has great capabilities that can improve the quality of care. Despite the strengths, the healthcare players must understand that the technology has weaknesses. For example, artificial intelligence is biased since its decisions are based on multiple choices supported by algorithms. Another risk of using the technology is the inconclusive correlations. Schonberger et al. (2019) note that artificial intelligence has been used with diverse, challenging law enforcement sectors. Embracing the technology in the healthcare sector presents challenges that can limit the quality of care. Human involvement can alleviate the risk of artificial intelligence.
Dankwa-Mullan et al. (2019) appreciate that artificial intelligence is critical in transforming care provision to diabetic patients. The study focuses on innovative approaches to improve the quality of care. Quality of care can improve clinical decision support, automated retinal screening, and patient self-management tools. Another area is to enhance data analysis through predictive population risk stratification. Dankwa-Mullan et al. (2019) indicate that the technology features in diabetic management can improve the diagnosis, treatment, and management of the disease. Other outcomes include reducing the mortality rates and treatment of diabetes among pediatrics. The technology will improve efficiency to take care of the ever-rising number of diabetic patients.
I have learned that artificial intelligence provides in-depth learning of health data. The data analysis improves predictive population risk stratification. The approach is essential in improving the response to diabetes that is responsible for thousands of death annually. Informaticists and knowledge workers in the healthcare sector can use artificial intelligence to develop mechanisms of responding to the chronic diseases affecting the world (Dankwa-Mullan et al., 2019). The response mechanisms will involve training the nurses, physicians, and technical clinicians. Patient education will be essential to improve the disease’s self-management from diagnosis to death or complete recovery.
Conclusion
Artificial intelligence has a positive impact on the healthcare sector since its adoption in diagnosis, treatment, management of diseases, and data analysis. The adoption of artificial intelligence information systems in healthcare will improve the quality of care. The four peer-reviewed articles appreciate that computer-aided systems can improve the early diagnosis of lung cancer and diabetes. Innovation has led to the decision-making capacities of the technology and augmentation of specialists. The technology has the potential to transform the provision of care. Transformation involves early diagnosis of chronic diseases, supporting healthcare workers’ decisions, and analyzing data to identify important health trends.

References
Ahuja, A. S. (2019). The impact of artificial intelligence in medicine on the future role of the physician. PEERJ, 7, e7702.
Dankwa-Mullan, I., Rivo, M., Sepulveda, M., Park, Y., Snowdon, J., & Rhee, K. (2019). Transforming diabetes care through artificial intelligence: the future is here. Population Health Management, 22(3), 229-242.
Rabbani, M., Kanevsky, J., Kafi, K., Chandelier, F., & Giles, F. J. (2018). Role of artificial intelligence in the care of patients with nonsmall cell lung cancer. European Journal of Clinical Investigation, 48(4), e12901.
Schonberger, D. (2019). Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications. International Journal of Law and Information Technology, 27(2), 171-203.

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