Healthcare Informatics Foundations and Concepts | Free Essay Example

Healthcare Informatics Foundations and Concepts

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Topic: Health & Medicine
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Clinical Informatics and Multi-Agent System

Whenever it comes to the description of clinical informatics, the theory of a multi-agent system (MAS) arrives as the most suited to cope with the mentioned task. The major advantage of a multi-agent model is that it considers the whole cycle of a clinic’s decision-making process and not some particular part of it (Shen, Colloc, Jacquet-Andrieu, & Lei, 2015). When the theory is applied, one takes a complex approach to informatics management, paying maximum attention to such aspects of medical intervention as the prognosis, diagnosis, treatment, and therapeutic monitoring.

The system combines disease histories, ontologies, knowledge bases, and other sources of information to assist one with making a balanced and well-informed decision regardless of a task at hand. By utilizing a specialized software application, clinicians can sum up the results acquired from medical interventions and upload them to a clinical database with no delay (Shen et al., 2015). Thus, one can plan a therapy course in reliance on the evidence he/she already has.

The Theory Applied to a Real-Case Scenario

One of the theories that have excellent applicability to clinical informatics and which I associate my practice with is called the novice to expert theory. The given model can be applied to a wide range of tasks, including the education of medical students, development of clinical informatics skills, the transition from a graduate nurse to expert, and more. The theory involves passing the five stages of professional growth: a novice, beginner, competent, proficient, and expert stage (Batras, Duff, & Smith, 2016).

It is expected that a learner gradually gains knowledge and advances to the next level as his/her skills, perception, wisdom, and intuition become expanded. Batras et al. (2016) estimate that it usually takes up to five years for a nurse practitioner to move through all phases. However, once the final stage is achieved, the level of a practitioner’s competence allows him/her to significantly improve the working performance and guide others in matters of professional development.

Changes to Implement in Mayo Clinic

Patient portals and electronic medical records (EMR) are recognized by both scholars and clinicians as effective mechanisms to stimulate greater patient engagement. With regards to Mayo Clinic, one needs to implement a range of changes in the existing health recording system to provide easier information exchange between physicians and patients. The changes that directly relate to the functionality of EMRs/portals include a summary to the patient after every visit, secure messaging (SM), and the ability to download personal health data (Irizarry, Dabbs, & Curran, 2015). Other requirements comprise such activities as educating customers, establishing patient reminders for preventative services, and reconciling medications.

The study done at Mayo Clinic indicates the increasing importance of SM for the adherence to interoperability within a hospital (Irizarry et al., 2015). The researchers also stress that in other clinics, “email reminders, in combination with scheduling functionality within the patient portal, demonstrated significant declines in ‘no-shows’” (Irizarry et al., 2015, p. 6). The given fact proves that electronic data recording tools positively influence patients’ accessibility to medical services and need to be established elsewhere.

Difference Between EMR, Patient Portals, and Personal Health Records

The role of an electronic medical record is to allow everyone who contacts a patient to have access to his/her entire health history regardless of a seeker’s location. EMR gathers data from a variety of disciplines, including nursing, pharmacy, radiology, and other branches (Sarkar & Bates, 2014). This robust application provides sufficient storage for ever-changing clinical information. In contrast to EMR, personal health record (PHR) does not cover such a wide range of disciplines when collecting information on a given request. Its goal is to be simply a summation of medical history and provide data access to the key stakeholders.

Patient portals fulfill a similar role but are more oriented at establishing effective doctor-patient communication (Sarkar & Bates, 2014). With this application, one does not need to visit a hospital on a regular basis since all answers can be acquired online at practically any time. Basically, a patient portal is an extension of EMR, which provides a patient with a secure login to a registered account. When entering a system, one can share messages with healthcare providers and request the renewal of medications.

In the meantime, PHR grants access to more than one person. It is designed to involve family members in the process of treatment in case an ill person requires constant care. A notable fact about PHR is that it is not even connected to a hospital or a doctor and is usually shared at the discretion of a patient, who is in control of all operations. The way this system is arranged and controlled makes a contrast to how EMR is being operated. The latter is usually controlled by a health unit itself and comprises the data of all patients at once. Such massive storage of information allows a clinic to be guided by the extensive evidence collected over the years of practice.

References

Batras, D., Duff, C., & Smith, B. J. (2016). Organizational change theory: Implications for health promotion practice. Health Promotion International, 31(1), 231-241.

Irizarry, T., Dabbs, A. D., & Curran, C. R. (2015). Patient portals and patient engagement: A state of the science review. Journal of Medical Internet Research, 17(6), 1-15.

Sarkar, U., & Bates, D. W. (2014). Care partners and online patient portals. JAMA, 311(4), 357-358.

Shen, Y., Colloc, J., Jacquet-Andrieu, A., & Lei, K. (2015). Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system. Journal of Biomedical Informatics, 56, 307-317.