Improvement in nurse staffing ratios according to policy changes: a prospective cohort study

• Main Authors: Yunmi Kim (Author), Kyounga Lee (Author), Minho Jung (Author)
• Format: Book
• Published: BMC, 2024-05-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s12912-024-01995-w; 1472-6955
• Keywords: Nursing staff; Personnel staffing and scheduling; Policy; Reimbursement; Incentive; Nursing; RT1-120
• Source: BMC Nursing, Vol 23, Iss 1, Pp 1-13 (2024)

Abstract Background Since 1999, reimbursements for nursing services for inpatients have been paid differentially according to the nurse staffing ratios in Korea. However, differentiated nursing fees are insufficient for nurse staffing; thus, steps have been taken to improve the policy. This study aimed to identify the impact of a policy that changed the method of calculating nurse staffing ratios from the nurse-to-bed ratio to the nurse-to-patient ratio on improving the nurse staffing ratio in medical institutions. Methods Data were collected from 1,339 medical institutions that continuously provided medical services from 2017 to of 2021, and a prospective cohort was used for analysis. A generalized estimating equation for longitudinal ordered logistic regression was used to identify the impact of this policy change on the nurse staffing ratios in medical institutions. Results During the cohort study, 59.8% of the first-applied group of medical institutions and 65.6% of the second-applied group of medical institutions improved their nurse staffing ratios. However, only 22.6% of the medical institutions to which the revised calculation method was not applied improved their nurse staffing ratios. A statistically significant difference was found in the improved nurse staffing ratio depending on whether and when the revised calculation method was applied (χ2 = 89.830, p < .001). The analysis of nurse staffing ratios of medical institutions from 2017 to 2021 showed that the likelihood of improving the nurse staffing ratio increased gradually after the revised calculation method was adopted. Also,the likelihood of the nurse staffing ratio improving in the first-applied group was 1.41 times higher (odds ratio = 1.41, 95% confidence interval = 1.04-1.92) than in the non-applied group. The odds ratio for the improvement of nurse staffing ratio in the second-applied group was 2.35 (95% confidence interval = 1.76-3.14). Conclusions Financial incentives inherent in the new policy can be regarded as the driving force behind improvements in nurse staffing ratios. The revised calculation method should be extended to all medical institutions nationwide, and the law should be revised to secure the minimum number of nurses.