Database Elements For Acute Respiratory Distress Syndrome Patients Free Sample

Adult patients with acute respiratory distress syndrome (ARDS) require the inclusion of particular elements into a database. It is assumed that certain key data that are not connected to ARDS are already incorporated into relevant database tables. For instance, it is routine to consider gender and age, as well as socioeconomic and marriage statuses (Misulis & Frisse, 2019). Such variables are not discussed in detail in this paper because they are not ARDS-specific, but the features that can help to track the development of ARDS are going to be reviewed.

First, it is important to include the information about the patient’s diagnosis, the disease’s progression, and related dates. ICD-10 codes provide the standardization that other methods do not; the result should consist of numeric data (Misulis & Frisse, 2019). For each patient, dates that mark ARDS onset, its progress (for instance, from acute to chronic), and its resolution are also to be collected (Bellani et al., 2016). ARDS status data can use some text information, and time-related elements should consist of date and time formats used by the database. In addition, it is logical to include the data about treatment, especially since ARDS is often undertreated (Bellani et al., 2016; Thompson, Chambers, & Liu, 2017); the variable should probably use text.

Other elements are supposed to cover the data needed to discern the progress of the illness. It is reasonable to collect the textual information about risk factors since, depending on the ARDS definition, they might be integral for the diagnosis (Thompson et al., 2017). Given the specifics of the disease, it is also necessary to include a text-based description of the test results used to determine the presence of lung infiltrates (for instance, radiography or tomography) (Sweeney & McAuley, 2016). ARDS severity should also be recorded with the help of severity categories (from mild to severe) or oxygenation criteria (Bellani et al., 2016; Sweeney & McAuley, 2016). It may be logical to introduce two variables here; one can be text-based and describe the category, and the other one may specify the number-based (ratio) value of oxygenation. Thus, ARDS in adult patients requires including some specific elements into a database in order to track the patients’ state. The data types depend on an individual variable, but it will not be necessary to make one variable use different types of data.

References

Bellani, G., Laffey, J. G., Pham, T., Fan, E., Brochard, L., Esteban, A.,… Ranieri, M. (2016). Epidemiology, patterns of care, and mortality for patients with acute respiratory distress syndrome in intensive care units in 50 countries. JAMA, 315(8), 788-800. Web.

Misulis, K., & Frisse, M. (2019). Representation and organization of health information. In M. Frisse & K. Misulis (Eds.), Essentials of clinical informatics (pp. 45-52). New York, NY: Oxford University Press.

Sweeney, R., & McAuley, D. (2016). Acute respiratory distress syndrome. The Lancet, 388(10058), 2416-2430. Web.

Thompson, B., Chambers, R., & Liu, K. (2017). Acute respiratory distress syndrome. New England Journal of Medicine, 377(6), 562-572. Web.

Clinical Interventional Studies Definition

Clinical intervention studies (CIS) play an essential role in investigating the scientific problem, which needs to be addressed in order to form a concise and full knowledge base. There are three main approaches in CIS, which include pre-experimental, quasi-experimental, and true experimental research designs (Holly, 2014). Each methodology possesses unique target points and is done under different circumstances. On the one hand, pre-experimental intervention studies mostly focus on explorative researches, where there is no sufficient knowledge to target a specific set of questions. On the other hand, true experimental CIS aims to give a full and precise explanation of the scientific phenomenon, where various independent variables are altered in order to acquire the results (Holly, 2014). Quasi-experimental research design is a transitionary phase between the given approaches, which is conducted with a goal of describing and depicting the topic of interest. It mostly uses data from pre-experimental studies and narrows the scope of focus by specifying and categorizing the raw information (Campbell et al., 2017). The quasi-experimental design also lacks the randomization factor, because no clear set of independent variables are present to alter.

Another key difference between quasi-experimental and true experimental researches is present in the control and target groups of study because the latter does not specifically assign the objects of analysis. It is important to note that randomization acts as a key factor in acquiring the most precise and unbiased results, but the quasi-experimental approach does not possess the given components. It is due to the lack of categorization of data, which enable identify interchangeable variables (Xu et al., 2019). The biggest advantage of pre-experimental methods is its relative inexpensiveness and simplicity, which gives a researcher an opportunity to conduct several studies simultaneous and in time efficient manner (Holly, 2014). All of the CIS designs are steps in the entire research process, where the study elements are explored, described, and explained.

References

Campbell, B. K., Fillingim, R. B., Lee, S., Brao, R., Price, D. D., & Neubert, J. K. (2017). Effects of high-dose capsaicin on TMD subjects: A randomized clinical study. JDR Clinical & Translational Research, 2(1), 58-65.

Holly, C. (2014). Scholarly inquiry and the DNP capstone. New York, US: Springer Publishing Company.

Xu, J., Huang, L., Yao, Z., Xu, Z., Zalkikar, J., & Tiwari, R. (2019). Statistical methods for clinical study site selection. Therapeutic Innovation & Regulatory Science, 1(1), 2-7.

Health Informatics Trends

Executive Summary

Health informatics is the scientific field that addresses biomedical information, insights and data as regards their maintenance, retrieval and use in the resolution of issues and decision making. The informatics website creates a dependable source of enterprise information technology resolutions and software development services. American Medical Informatics Association (AMIA) is dedicated to the enrichment and application of health and biomedical informatics in the enhancement of quality care, research, administration and teaching. Philips is a company that offers integrated healthcare informatics for enhanced patient care. To avoid technological dangers, hospitals should maintain sufficient staffing and support quality assurance practices.

Introduction

Medical or health informatics denotes the scientific discipline that is concerned with biomedical data, knowledge and details with respect to their storage, retrieval and application for the solution of setbacks and making of decisions. It focuses on all fundamental and applied fields in biomedical science and is closely associated with modern information expertise, particularly in the sectors of communication and computing (Owolabi & Evans, 2018). The promotion of collaboration and networking by health informatics enhances the work of caregivers and plays a vital role in the improvement of patients’ lives.

Health Informatics Websites

The informatics website acts as a trustworthy source of enterprise information technology resolutions and software advancement services and is available at www.informaticstec.com. Informatics is a company that has highly competent and experienced sources which offer top-notch solutions to the expertise presently sought after by organizations across the globe (Informatics, n.d.). Its significance is based on its capability to promptly enhance capacity, impact and performance devoid of compromising on quality. The influence of the company on the health care industry is based on the rising trend of commitment to excellence in the provision of intelligent information technology solutions and services. It centers on assisting organizations to function at their level best.

AMIA is an American non-profit company based in Maryland and its website is available at www.amia.org. From its website, it is clear that the company is dedicated to the enhancement and application of health and biomedical informatics for the facilitation of quality care, research, administration and teaching. AMIA’s more than 5000 members are subject matter experts in the science and practice of informatics with regard to research, medical care, strategy and education (AMIA, n.d.). Its members encompass doctors, nurses, pharmacists, dentists and other health professionals. Others include educators and researchers, learners pursuing informatics-related careers, health science and biomedical librarians, government representatives and policymakers, consultants, scientists and industrial experts.

Professionals in the Philips Company are convinced that quality care is realized when state-of-the-art expertise in placed in the hands of caregivers. The company’s website is available at www.usa.philips.com. Health professionals’ decisions and the strategy they choose are only a few of the unseen approaches to the improvement of care delivery. The work of caregivers becomes complicated when systems cannot communicate effectively, valuable details are not available, and some health professionals are so overwhelmed with data that they strain to perceive the bigger picture (Philips, n.d.). The practices of the company are geared towards the reinforcement of trends in the medical field of helping to incorporate systems, aggregate information, speed up workflows and offer health professionals the knowledge required to realize what matters most, quality care and positive patient outcomes.

American Medical Informatics Association

From AMIA’s website and the company’s practices, it is evident that it will influence the healthcare industry through offering valuable insights to health professionals and advancement of their knowledge to facilitate patient outcomes and care provision. Through training, education, certification and accreditation, the company will support the present and future cohort of informatics professionals by giving members the chance to grow competently irrespective of the level of their career or discipline. The company and its counterparts in the field of informatics will influence the healthcare industry by providing the information and policies necessary to accelerate the current objectives of restructuring the sector. Trends in the health care industry show that millions of patients gain from informatics’ capability to improve processes in the field anchored in the collection, examination and application of data to medical decisions. Since members of AMIA are crucial to the discovery of insights, the company is dedicated to becoming the professional hub of informatics and upholding the future of care delivery (AMIA, n.d.). Data generated in the medical field is the driving force of informatics and has the capacity to innovate crucial developments that benefit patients and other people directly.

Dangers of Technology

Irrespective of their numerous advantages, information and medical technologies have the possibility of creating health hazards and risks that threaten patient safety. Dangers may emanate from software setbacks, interoperability involving systems and poor network (Owolabi & Evans, 2018). Spelling mistakes or keying in details in the incorrect field over and above other data-entry errors may be dangerous to the point of even causing patients’ death. In some instances, the dangers of technology occur in the form of domino effect where alterations to a given element of the system impinge on the function of another. To avoid such dangers, health facilities should maintain adequate staffing and uphold quality assurance practices.

Conclusion

Health informatics focuses on all deep-seated and applied fields in biomedical science and backs modern information expertise, mainly in the sectors of communication and computing. Promoting cooperation and networking in health informatics advances the work of caregivers and improves the lives of patients. Avoidance of technological dangers calls for the maintenance of adequate staffing and support of quality assurance practices.

References

American Medical Informatics Association. (n.d.). Clinical informatics. 

Informatics. (n.d.). Industry- Healthcare. 

Owolabi, K., & Evans, N. (2018). Clinical informatics tools for healthcare quality improvement: A literature review. Inkanyiso: Journal of Humanities and Social Sciences, 10(1), 74-89.

Philips. (n.d.). Healthsuite digital platform. 

error: Content is protected !!