Reduction of medical errors
Reduction of medical errors
Provide further suggestions on how their database search might be improved. Use 2 sources. The PICO(T) question is, “Among hospitalized patients, does using two identifiers compared to one reduce medical errors?” My clinical issue of interest is the reduction of medical errors. Medical errors are gaps in care that bear potential or actual capacity to harm the patient, such as inaccurate diagnosis and incomplete diagnosis (Aljabari & Kadhim, 2021). These have the ripple effect of inappropriate investigations and treatment, then adverse care outcomes (Aljabari & Kadhim, 2021). Some solutions to medical errors include proper identification of patients, thorough history taking, and comprehensive physical examination. One evidence-based method for patient identification is using two identifiers rather than one (Mroz et al., 2019). Therefore, I am prompted to investigate whether using two identifiers compared to one among hospitalized patients reduces medical errors. Search results discussion Regarding my search results, 19,600 articles appeared on the initial original search. As I added search terms such as two identifiers, one identifier, medical errors, and hospitalized patients using Boolean operators such as AND, NOT, and AND NOT, the number of articles appearing kept reducing. At first, they declined to 18,500, then to 17,200, and so on, in a declining trend. Strategies to optimize database search on my PICO(T) question
There are several strategies I can apply to optimize how effective a database search is while searching my PICO(T) question. These include having a specific search question, using Boolean operators, using more specific keywords, and using fewer synonyms (Degbelo & Teka, 2019). An example of a particular question is a PICO(T) question, which narrows down to a particular population, intervention, control, outcome, and timing. A more specific example is my PICO(T) question that reads, “Among hospitalized patients, does the use of two identifiers compared to one identifier reduce medical errors?” Besides, examples of Boolean operators are OR, AND, NOT, and AND NOT (Degbelo & Teka, 2019). Specific keywords, like particular search questions, direct the search further, optimizing it to give the best results. An example of keywords in my case includes “hospitalized patients,” “two identifiers,” “one identifier,” and “reduce medical errors.”
Lastly, using fewer synonyms helps fetch more search results, broadening your search outcome and choosing relevant resources (Degbelo & Teka, 2019). Applying such strategies helps to make the search process more effective and thorough. ReferencesAljabari, S., & Kadhim, Z. (2021). Common barriers to reporting medical errors. The Scientific World Journal, 2021, 1–8. https://doi.org/10.1155/2021/6494889 Links to an external site. Degbelo, A., & Teka, B. B. (2019). Spatial search strategies for Open Government Data. Proceedings of the 13th Workshop on Geographic Information Retrieval. https://doi.org/10.1145/3371140.3371142 Links to an external site. Mroz, J. E., Borkowski, N., Keiser, N., Kennel, V., Payne, S., & Shuffler, M. (2019). Learning from medical error: Current directions in research and practice on medical error prevention. Academy of Management Proceedings, 2019(1), 18084.https://doi.org/10.5465/ambpp.2019.18084symposium Links to an external site.