The Impact of Nursing Informatics on Patient Outcomes and Patient Care Efficiencies
The Impact of Nursing Informatics on Patient Outcomes and Patient Care Efficiencies
Among the ways that informatics has helped to transform care is improved documentation systems, where care providers can easily access important patient and staff information that leads to coordinated care. The introduction of nurse informatics also helps to improve the processes in care and hence to generate improved care outcomes (Robert, 2019). Also, with informatics, healthcare givers can identify at-risk patients in a timely fashion and give them more priority to care.
Description of Proposed Project: The Integration of Artificial Intelligence in Nurse Informatics
Artificial intelligence, commonly known as AI, is the simulation of intelligence of humans to machines to make these machines adopt human functions. Over the years, there have been improvement of the AI functions as technologies continue improving. Today AI applications include but are not limited to speech recognition, machine vision, natural language processing, and expert systems.
Healthcare implements AI by using complex software and algorithms to interpret and comprehend complex medical data (Clancy, 2020). The fact that AI uses technologies that can gain information and process it to refined outputs means that it can have limitless applications in healthcare. In this project, the implementation of AI in the field of nurse informatics is closely examined.
Stakeholders Impacted by the Project
There are several stakeholders who are impacted by the project, with the patients being on the first line. Most of the actions in the project involve patient care, as the objective of the project is to improve the patient care outcomes. The second most impacted stakeholders are the healthcare givers and specifically the nurses, who also play a crucial role in coordinating patient care with other healthcare givers. Nurses are the individuals who are in contact with the patients for the longest periods hence it becomes easy to monitor them.
Patient families are also influential stakeholders in this project as much of the actions will require their consent as well as their opinion output on the options available. Regulators will also take a primary position in the project, especially because machine learning and other elements of artificial intelligence can also have drastic patient outcomes if reckless researchers or healthcare providers are allowed to take the center-stage in implementing non-proven measures. Lastly, the healthcare financiers will be part of the stakeholders since AI is an expensive field that requires strategic financing.
Patient Outcomes or Patient Care Efficiencies that the Project is aimed at Improving
The first patient outcome that the project is aimed at improving is the diagnostic procedures of care. Through application of AI in nursing informatics, nurses can efficiently perform nursing diagnoses to improve the detection of the presence of absence of disease and determine the best care operations for specific patents. Among the diseases that can be efficiently diagnosed using AI is cardiovascular disease and diabetes, which are among the leading causes of mortality worldwide.
AI is also expected to help in the integration of telehealth in the care of patients. Telemedicine or telehealth helps in monitoring of patient information using strategic and remote techniques, and using automated means. It allows patients with chronic conditions to have long contact with the healthcare providers regardless of the physical barriers (Erikson & Salzmann-Erikson, 2016). Using AI in telehealth improves the efficiency of administration of drugs, as patients can consult physicians at their convenience of their homes. Also, these programs allow the education and advice of patients, remote admissions, as well as constant monitoring.
The project is also aimed at showing the relevant drug interactions that could help the patients achieve synergy of the drugs and improve the effects. Also, in the same way, AI technology can help to identify lethal interactions that could lead to risking of the patients’ lives. Specifically, the project helps patients to identify the most suitable options when it comes to drug administration. It is easy to find that most chronic disease patients experience polypharmacy, and they are confused whether taking an additional drug would lead to improved outcomes. With AI, healthcare givers do not have to take multiple lab tests to determine the suitability of an additio