Background: The likelihood of inpatient mortality has been found to be reduced by increased nurse staffing in\nseveral settings, including general wards, emergency departments, and intensive care units. However, less research\nhas investigated cases where patients die in the community setting due to a health problem that occurred after\nthey were discharged post-surgery, because it is difficult to integrate hospital data and local community data.\nTherefore, this study investigated the association between the bed-to-nurse ratio and 30-day post-discharge\nmortality in patients undergoing surgery using national administrative data.\nMethods: The study analyzed data from 129,923 patients who underwent surgery between January 2014 and\nDecember 2015. The bed-to-nurse ratio was categorized as level 1 (less than 2.5), level 2 (2.5â??3.4), level 3 (3.5â??4.4),\nand level 4 (4.5 or greater). The chi-square test and GEE logistic regression analyses were used to explore the\nassociation between the bed-to-nurse ratio and 30-day post-discharge mortality.\nResults: 1355 (0.01%) patients died within 30 days post-discharge. The 30-day post-discharge mortality rate in\nhospitals with a level 4 was 2.5%, representing a statistically significant difference from the rates of 0.8, 2 and 1.8%\nin hospitals with level 1, level 2, and level 3 staffing, respectively. In addition, the death rate was significantly lower\nat hospitals with a level 1 (OR = 0.62) or level 2 (OR = 0.63) bed-to-nurse ratio, using level 4 as reference.\nConclusion: The results of this study are highly meaningful in that they underscore the necessity of in-hospital\ndischarge nursing and continued post-discharge nursing care as a way to reduce post-discharge mortality risk.\nFurthermore, the relationship between nurse staffing levels and 30-day post-discharge mortality implies the need\nfor a greater focus on discharge education. Policies are required to achieve proper nurse staffing levels in Korea,\nand thereby to enhance patient outcomes.
Loading....