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Similar to any other scientific area, healthcare and medicine have a vast knowledge background. Countless students, practitioners, and scholars consult with the healthcare database to improve their understanding, provide a better service and ultimately improve societal quality of life. The database is gradually improving thanks to the constant research; however, the research will have little use to the medical community if its results remain undocumented. Since there are no worldwide accepted guides for the results documentation, it might be challenging to acquire specific information systematically. Nevertheless, on the example of data acquisition for the patient wait times in the emergency departments (ED), it will be shown how important reports are for the knowledge base development.
Showing the data processing, visualizing, and drawing a conclusion (in other words, making a report) serves a single and clear purpose strengthening the knowledge. For instance, Gold et al. (2020) statistically assessed the victims of the COVID-19 outbreak to help improve healthcare services. The researchers uncovered significant racial disparity in deaths associated with the disease, which implied the inequity in minorities health treatment; they also provided a graphical representation to visually support their statistical evidence (Gold et al., 2020). In other words, reporting contributes to the understanding of the individual, which is improving during the research and summary of its results, and the community as well. The reported data will save time and effort to acquire the knowledge without needing to conduct the experiment.
Unfortunately, the data acquisition might have specific difficulties due to incomplete clinical documentation, disparate electronic records, and inconsistent policy. Incomplete clinical documentation might result in the ambiguity and unreliability of the documented information (Chen et al., 2017). Disparate electronic records occur when the system is being updated from different sources; it also increases ambiguity due to the difference in the interpretations of the same data (Chen et al., 2017). Lastly, inconsistent policy implies the frequency of changes in specific rules or approaches, which might additionally change the data interpretation and relevance (Chen et al., 2017). In the latters context, the frequency of data acquisition can vary significantly, depending on several factors, such as the subject and the object of the given research. For instance, when developing a new vaccine, it is important to monitor the test subjects health frequently to check for possible issues. In the meantime, the drugs that showed consistently positive results for years do not require increased attention.
Despite the reported data imperfection, its value still cannot be overemphasized. The reported results might be used decades later after the conducted study. For example, according to Morley et al. (2018), the crowding occurring in the ED presents an issue of great importance. To begin with, the collective needed to understand the problems background to develop a successful solution. Consequently, to perform the workflow study on wait times in ED, Morley et al. (2018) searched for the reports conducted between 2000 and 2018 and analyzed the data those reports collected for the evaluation. The reports stated that, concerning the number and type of people attending and timely discharging from ED, the most frequent patients in the ED are the elderly with chronic and complex conditions (Morley et al., 2018). In addition, various interventions, such as increased in-hospital transfers and extended hours of primary care, demonstrated promising outcomes. In other words, to assess the problem of ED crowding, the data collection should concern the people who crowd the ED and the already attempted strategies for the problems solution.
In conclusion, it becomes clear how essential are the conducted reports for the future of science. They allow individuals to improve their skills, while the community might benefit from the accumulated knowledge. Report specifications and guidelines may vary; nevertheless, they are still helpful for both current and future generations. The example of patients wait time in ED that used the data collected in eighteen years proves the discussed reports value.
References
Chen, Y., Yang, K., Maruai, A., Qaseem, A., Meerpohl, J. J., Flottorp, S.,& & RIGHT (Reporting Items for Practice Guidelines in Healthcare) Working Group. (2017). A reporting tool for practice guidelines in health care: The RIGHT statement. Annals of Internal Medicine, 166(2), 128-132. Web.
Gold, J., Rossen, L. M., Ahmad, F. B., Sutton, P., Li, Z., Salvatore, P. P., Coyle, J. P., DeCuir, J., Baack, B. N., Durant, T. M., Dominguez, K. L., Henley, S. J., Annor, F. B., Fuld, J., Dee, D. L., Bhattarai, A., & Jackson, B. R. (2020). Race, ethnicity, and age trends in persons who died from COVID-19 United States, May-August 2020. MMWR. Morbidity and mortality weekly report, 69(42), 15171521. Web.
Morley, C., Unwin, M., Peterson, G. M., Stankovich, J., & Kinsman, L. (2018). Emergency department crowding: A systematic review of causes, consequences and solutions. PloS One, 13(8). Web.
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