Assignment: Examine the role of health information technology and informatics in improving access to care and promoting patient safety and quality.

Assignment Examine the role of health information technology and informatics in improving access to care and promoting patient safety and quality.

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NUR-514 Topic 6 DQ 1

Technology is an indispensable part of today’s health practice, with many procedures giving way to machines and programmed software. Amid this, the evolutionary impacts of informatics are far-reaching, with the overall health practice outcomes improving immensely. Informatics reduces wastage, increases patient participation in health care delivery, and enhances coordination, among other significant outcomes. It is an evolution that will be critical in health care delivery for a long time as health care providers continue to seek ways of improving patient outcomes.

Concerning informatics’ role in overcoming barriers to care and increasing access to safe, quality health care, medication errors have been greatly reduced through informatics. With the consequences of misdiagnosing a patient or the wrong drug prescription being regretful, informatics prevents harmful treatment and prescription errors. Doing so prevents incomplete treatment of diseases and other medical-related harms such as improper use of medical equipment and incorrectly reading patient data (Stanhope & Matthews, 2019). In medication error reduction, clinical provider order entry (CPOE) systems are usually integrated with clinical decision support systems (CDSS) to enhance patient safety. Here, errors related to medical ordering and dispensing are avoided to improve safety. A typical CDSS identifies the values of drug doses and administration routes, among other sophisticated features (Patient Safety Network, 2019). However, the process also experiences some challenges. For instance, higher rates of adverse drug events are experienced in some hospitals despite using computerized order entry systems. In other cases, usability testing reveals that CPOE systems and CDSS still allow the entry and processing of some unsafe orders.

Generally, informatics is vital in enhancing safety and quality of care by reducing medication errors. Skochelak (2020) described informatics as a way to patients’ knowledge since it improves understanding of patients’ problems through knowledge sharing. It also helps to personalize care and increase coordination. Such outcomes are instrumental in the provision of safe and quality care.

 

 

References

Patient Safety Network. (2019, Sep 7) Computerized provider order entry. https://psnet.ahrq.gov/primer/computerized-provider-order-entry

Skochelak, S. E. (Ed.). (2020). Health systems science e-book. Elsevier Health Sciences.

Stanhope, V., & Matthews, E. B. (2019). Delivering person-centered care with an electronic health record. BMC Medical Informatics and Decision Making, 19(1), 1-9. https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-019-0897-6

A primary concern in healthcare practice today is the inefficiency and human errors in medical and health processes like surgery and other intensive care interventions. Medical errors emanating from human issues lead to increased delays, limited access to health care services and more mortality and morbidity rates. These issues have necessitated the development of autonomous and semi-autonomous medical equipment like robots through the use of artificial intelligence. The main purpose of artificial intelligence is to make computers more useful in generating solutions to problematic health care issues (Secinaro et al., 2021). The purpose of this paper is to discuss artificial intelligence as a healthcare technology that has the potential to address the emerging barriers in healthcare provision.

Overview of the Emerging Technology and Its Role in Health Care

Because it allows providers to interpret data to diagnose chronic conditions such as diabetes, Alzheimer’s disease,

and various types of cancer, artificial intelligence makes computers more important in resolving difficult health-care issues. In the future, using AI for clinical trials will aid the healthcare sector in developing biomarkers to detect various types of conditions such as cancers during the screening process. Data on the coronavirus disease 2019 (COVID-19) pandemic, for example, can be interpreted using AI. The next generation of radiology tools is being developed using artificial intelligence (AI). Brain-computer interfaces, according to studies, can significantly improve the quality of life for patients with terminal conditions such as Alzheimer’s disease, strokes, and people with spinal cord injuries all over the world (Secinaro et al., 2021). Deep learning models can assist in predicting the efficacy of both old and new drugs and treatments on COVID-19. Institutions are utilizing AI to create prototype COVID-19 vaccines and treatments. As a result, AI is an important part of combating the COVID-19 pandemic.

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Human beings improve their quality of life by incorporating technology into everyday tasks. The health care field has also incorporated many technologies to improve the quality of care and address safety and timeliness problems, among other issues that hamper effectiveness and efficiency. All populations deserve accessible health care services, and using technology to achieve this critical objective should be encouraged and supported. In the past decade, the application of artificial intelligence (AI) in health care has risen progressively. This paper provides an AI’s brief explaining the technology, ethical issues, nurse’s informatics role and the role of workflow analysis, human factors, and user-centered design concepts.

Overview of AI and Function in Health Care

AI represents technology functions that support or supplement human tasks. The technology works by investigating, synthesizing, learning, acting, and deducing intelligence from information sources and clinical systems. Alami et al. (2020) described AI as a form of technology improving traditional analytics and clinical decision-making by supporting or replacing humans in performing complex health functions, mainly related to data. Machine learning, natural language processing (NLP) systems and voice assistive technologies are suitable examples of AI methods in health care. Functions of AI vary depending on the level and type of technology used. When used appropriately, AI improves access to care by taking over human tasks in underserved areas. For instance, taking over diagnostic functions from human physicians and technicians can help address the shortage of health care providers, which improves access to care. AI integration in health care also enhances the quality and patient safety outcomes. It is among the technologies providing predictive insights about human health, leading to early and accurate interventions (Laï et al., 2020). AI also supports the discovery of patient problems and advanced monitoring enabling health care providers to quickly intervene when necessary and respond to patient problems with better precision.

Ethical Issues Accompanying AI Incorporation in Health Care

Technology incorporation in health care supplements human input and can interfere with it. Due to the increased use of data in present-day health practice, patient harm is a serious ethical issue, and AI is not immune. Laï et al. (2020) observed that AI could apply algorithms and predict patient information wrongly. Such instances lead to wrong diagnosis and treatment, risking people’s health. All technologies should promote the principle of beneficence, implying that they should be used for maximum benefit. AI is also associated with privacy issues. As a result, users should be highly trained to ensure that AI improves the quality of care and patient-related issues are as minimal as possible.

Nurse’s Informatics Role

In the recent past, nurses have increasingly used clinical information systems, support systems, and electronic health records. Informatics nurses work in areas that support the use of information technology in health care to enhance health outcomes (Farokhzadian et al., 2020). They should play a similar role to support the use of AI as an enabler of better patient outcomes. Informatics nurses should welcome AI as a technological solution to make recommendations, assist in decision-making, and forecast results. A suitable example of such roles is using voice assistance to answer patient questions. Machine learning can also be used to identify patients’ courses of their care plans and make automated follow-up appointments. Expert systems can also anticipate at-risk patient populations and serve as the reference for practical interventions.

Workflow Analysis, Human Factors, and User-Centered Design Concepts

AI successes in health care depend on continuous improvement and using it for the right purposes. Workflow analysis is critical for identifying areas that require process improvement and identifying inefficient layouts that can hamper AI’s effectiveness. Human factors supplement AI’s outcomes. The technology cannot work in isolation, and situation awareness is better when communication occurs between AI systems and clinicians (Asan & Choudhury, 2021). User-centered design concepts are critical for improving interoperability. Weller (2019) noted that smart technologies such as AI should be user-friendly, where intelligence patterns, ideas, and functions should be meaningful and user-centered. Clinicians should be able to apply such technologies and easily connect with how they operate.

In conclusion, nurses and other health care providers need a lot of technology-based support to serve patients better. AI is among the technologies whose application is yet to be maximized in health practice. It supplements or replaces human functions, enhancing care quality, access, and safety. However, it is crucial to address its ethical challenges to improve its outcomes as its reliance increases over time.

References

Alami, H., Rivard, L., Lehoux, P., Hoffman, S. J., Cadeddu, S. B. M., Savoldelli, M., … & Fortin, J. P. (2020). Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low-and middle-income countries. Globalization and Health, 16(1), 1-6.

Asan, O., & Choudhury, A. (2021). Research trends in artificial intelligence applications in human factors health care: Mapping review. JMIR Human Factors, 8(2), e28236. doi: https://doi.org/10.2196/28236

Farokhzadian, J., Khajouei, R., Hasman, A., & Ahmadian, L. (2020). Nurses’ experiences and viewpoints about the benefits of adopting information technology in health care: a Qualitative study in Iran. BMC Medical Informatics and Decision Making, 20(1), 1-12. https://doi.org/10.1186/s12911-020-01260-5

Laï, M. C., Brian, M., & Mamzer, M. F. (2020). Perceptions of artificial intelligence in healthcare: Findings from a qualitative survey study among actors in France. Journal of Translational Medicine, 18(1), 1-13. https://doi.org/10.1186/s12967-019-02204-y

Weller, A. J. (2019). Design thinking for a user-centered approach to artificial intelligence. She Ji: The Journal of Design, Economics, and Innovation, 5(4), 394-396. https://doi.org/10.1016/j.sheji.2019.11.015