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Introduction
Nursing informatics is presently the discipline that combines computer science, nursing, and data systems to transmit information, knowledge, as well as intelligence in the nursing profession. Nursing informatics empowers health care institutions to convert data into information which allows healthcare workers, such as doctors and nurses, to provide the highest quality of care to patients. It blends information science, nursing science, and systems-driven analytics to find, capture, manage and distribute health care data. Nursing informatics primary goal is to provide physicians involved in healthcare choices with fast, reliable patient health data to provide patient-centered care and enhance results.
Role of Informatics Nurse
Nurse informatics plays a critical function in assisting the nursing workforce in documenting and submitting correct data and using that data to establish evidence-based practices for optimum care delivery. First, nurse informatics integrates new technology and procedures into health care facilities (Strudwick et al., 2019). Any significant electronic implementation, such as a patient portal, results in a shift in the clinical process. The healthcare team will assess and adjust existing processes to accommodate the new technology before implementing it. With more data available, health systems can find further care gaps and potential for improvement, emphasizing the vital role of nurse informatics in new process teaching and implementation.
While new procedures provide chances for advancement, without adequate education and implementation, these technologies may languish, fail to achieve adoption, jeopardize the safety of patients and teamwork satisfaction. Competent nurse informatics must lead the implementation process from the beginning to the conclusion to ensure the success of a new technique. For instance, an intensive care unit (ICU) nurse may need to utilize a new electronic health record (EHR) component to track a patients physiological status (Strudwick et al., 2019). The new module needs data to be captured immediately from the monitor device and verified, rather than manually inputting it in an automated format or recording it on a paper-based flow chart in the past. Assuring testing completion and providing hands-on orientation within the EHR, together with a detailed description of the new approachs advantages over the old way, should be a nurse informatics role before and after deployment.
Data-driven clinical decision-making is promoted by nurse informatics through successful data use and adoption. Health care systems have an endless volume of data at their disposal. Nurse informatics recognizes the abundance of data such as clinical notes and test findings an institution may utilize to assist data-driven decision-making (Strudwick et al., 2019). Furthermore, validating data requires informatics to be familiar with the many data sources. Todays electronic world contains discrete data, unstructured data, graphics, and data from linked devices requiring validation (Strudwick et al., 2019). Nurse informatics are familiar with several data sources to create a coherent narrative concerning the patient and population.
Nursing informatics achievement paves the way for a bright future in fields such as patient data analysis. According to a report at the 13th International Forum on Nursing Informatics in 2016, big data science is a critical topic of focus (Pramanik et al., 2020). With regard to the field of health informatics, big data refers to the computer analysis of data collections to find statistics that might optimize healthcare quality (Pramanik et al., 2020). The use of big data science entails sophisticated analytics techniques such as data harmonization. Unstructured data may be collected, trends can be discovered, and information can be combined to provide meaningful conclusions using these tactics. It will promote clinical trials and contribute to the diagnosis and other therapeutic approaches (Strudwick et al., 2019). To achieve this future vision, faster systems that communicate effectively with one another are required.
Connected Health
The existing system of health care delivery is struggling from a significant shortage of health care providers. The only way to overcome this obstacle is to establish a connected health network. Connected health is a conceptual paradigm of interconnected health devices that keeps telemedicine and telehealth running effectively (Griggs et al., 2018). It provides a myriad of implications for both the healthcare corporation and the patient. Connected health examples are remote patient monitoring (RPM), decentralized clinical trials (DCTs), and telemedicine.
RPM is the process of observing and collecting clinical and other health data from clients and digitally transmitting this information to healthcare personnel for review. Health workers benefit from easy access to patient information, the capacity to provide higher-quality treatment to a greater number of patients, and a reduced risk of burnout when using RPM (Griggs et al., 2018). Patients also benefit from RPM in various ways, including increased access to medical care due to having their own gadgets, better treatment since patients own their health, enhanced support, and education. However, RPM has a set of drawbacks that include inaccessibility to everyone- not everyone possesses a smartphone, and the elderly frequently struggle with advanced technologies such as cell phones. Additionally, the validity of RPM statistics is also brought into doubt. For example, according to a paper published in JAMA Dermatology, smartphone applications for melanoma diagnosis had a 30% failure rate (Griggs et al., 2018). The most important issue that has to be addressed before devices and software may be utilized by healthcare practitioners is a lack of reliability.
Decentralized clinical trials (DCTs) are operational approaches for enhanced technological clinical trials that are more convenient to participants by relocating clinical trial operations to more local locations. DCTs minimize the number of organizational review boards and duplicate applications with reduced central research locations, lowering expenses and site-specific discrepancies (Griggs et al., 2018). Remote patient engagements can occur more often, thus boosting compliance and perhaps improving both long and short-term research safety. DCTs may help streamline the logistics of running a clinical study by increasing subject enrollment and retention.
While technological advancements enable DCTs, they also pose a significant barrier to DCT study design implementation. Biometric monitoring devices, for instance, are in the early stages of research and therefore need clinical validation before they can be generally recognized in regulatory decisions (Griggs et al., 2018). The devices performance is also dependent upon the existence of technical assistance, transmission techniques, and network infrastructure, like cellular towers in rural areas or hard-wired internet access in households that lack it.
Telemedicine provides healthcare via computer systems and mobile devices. It usually employs video conferencing; however other suppliers prefer to communicate by email or phone. According to some studies, patients who use telehealth spend fewer days in the hospital, resulting in cost savings (Griggs et al., 2018). Additionally, reduced commuting time may result in lower secondary expenditures such as daycare and fuel energy. Telemedicine enables patients to get care in the privacy and luxury of their own homes. Telemedicine can increase access for other demographics such as the elderly, geographically isolated individuals, and those who are imprisoned. Despite the wide range of enjoyed advantages, telemedicine also has some disadvantages. Medical data security is a problem that has to be addressed (Griggs et al., 2018). Cybercriminals may obtain a clients records if the person utilizes an open network or an unencrypted connection to access telemedicine.
Impacts of Informatics on Public Health
In order to fulfill the specific information and communication needs of the public health sector, public healthcare informatics technologies have been developed. An example is a statistical assessment method focused on software-enhanced simulations applied at birth control facilities to improve timetables as well as the sequence of care provision, therefore minimizing wastage of time and boosting efficiency. Epi Info system is a minicomputer application that epidemiologists use in the field to gather, verify, and evaluate epidemic data, allowing for more rapid development of management strategies (Camp et al., 2018). These examples highlight how public health informatics role as an information systems provider for public health service may facilitate operations at the state, federal, and local levels.
Informatics also has a positive effect on public health by improving access to information. Information system approaches are based on computer systems which include routines for transforming data into figures or information. It assists public health services in enhancing simply as well as fast access to data. A frequently utilized information system approach is the AIDS Reporting Systems, which collects data on AIDS monitoring. It enables federal as well as local health authorities to register, check, and compile relevant data (Camp et al., 2018). The databases consistency and state-level analysis are enhanced by this systems integration of data input and transmission.
Data systems are structured methods for collecting, modifying, and disseminating data. They contribute to the practice of public health by the standardization of data collection and processing. The end consumer must build computer programs to produce reports. A frequently utilized system is the National Vital Statistics System transmits information to the Centers for Disease Control and Prevention for accumulation into the nationwide database. (Camp et al., 2018). The accuracy, timeliness, and security of data systems might be enhanced by using technology more efficiently. Reliability can be increased by expanding the utilization of computer-assisted interviews, in which data are cross-examined as they are entered.
Ultimately, informatics helps increase communication and data access through a continuous flow of data. Improvements in telecommunications cover all the technologies and methods that help to speed up data transfer. Greater connections have simplified public healthcare services by increasing the access to convenient interfaces, owing to the accessibility of minicomputers, which are typically simpler for using than supercomputers. The effect of communications aimed at lay audiences may be enhanced by the utilization of advanced audio, film, and computer visuals. Media agencies will make it possible for all healthcare employees to have access to enormous volumes of data in a convenient manner over the next years. The concern for public healthcare representatives will be to convey this advancing innovation toward health implementation.
Conclusion
Todays world has increased the prospect of communication and information technology to improve nursing domain outcomes. Nurses always have the best contact with patients and are more frequently with technology. Utilizing technology should foster a more optimistic attitude toward nursing performance. Nurses must participate in the early development of systems to enhance care quality and influence their mindset in this direction. The introduction of new technology has given nurses more power to make decisions. Nurses familiar with information technology, computer competence, and informatics experience must integrate the electronic healthcare reporting system properly.
References
Camp, B., Mandivarapu, J. K., Ramamurthy, N., Wingo, J., Bourgeois, A. G., Cao, X., & Sunderraman, R. (2018). A new cross-platform architecture for epi-info software suite. BMC Bioinformatics, 19(11), 1-8.
Griggs, K. N., Ossipova, O., Kohlios, C. P., Baccarini, A. N., Howson, E. A., & Hayajneh, T. (2018). Healthcare blockchain system using smart contracts for secure automated remote patient monitoring. Journal of Medical Systems, 42(7), 1-7.
Pramanik, M. I., Lau, R. Y., Azad, M. A. K., Hossain, M. S., Chowdhury, M. K. H., & Karmaker, B. K. (2020). Healthcare informatics and analytics in big data. Expert Systems with Applications, 152, 113388.
Strudwick, G., Nagle, L., Kassam, I., Pahwa, M., & Sequeira, L. (2019). Informatics competencies for nurse leaders: A scoping review. JONA: The Journal of Nursing Administration, 49(6), 323-330.
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