Measuring patient acuity and nursing care needs in South Korea: application of a new patient classification system

• Published in: BMC nursing Vol. 21; no. 1; pp. 1 - 332
• Main Authors: Kim, Jeounghee, Kang, TaeRim, Seo, Hyun-Ju, Seo, So-Young, Kim, Myoungsook, Jung, Youngsun, Kim, Jinhyun, Lee, Jung- Bok
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 29-11-2022; BioMed Central; BMC
• Subjects: Classification; Clinical medicine; Electronic health records; Emergency medical care; Hospitals; Intensive care; Medical records; Nurses; Nursing care; Nursing care needs; Nursing workload; Patient acuity; Patient classification system; Patients; Payment systems; Validity; Workforce; Workforce planning; Workloads; South Korea
• ISSN: 1472-6955; 1472-6955
• DOI: 10.1186/s12912-022-01109-4

Background An accurate and reliable patient classification system (PCS) can help inform decisions regarding adequate assignments for nurse staffing. This study aimed to evaluate the criterion validity of the Asan Patient Classification System (APCS), a new tertiary hospital-specific PCS, by comparing its rating and total scores with those of KPCS-1 and KPCS-GW for measuring patient activity and nursing needs. Methods We performed a retrospective analysis of the medical records of 50,314 inpatients admitted to the general wards of a tertiary teaching hospital in Seoul, South Korea in March, June, September, and December 2019. Spearman's correlation and Kappa statistics according to quartiles were calculated to examine the criterion validity of the APCS compared with the KPCS-1 and KPCS-GW. Results The average patient classification score was 28.3 points for APCS, 25.7 points for KPCS-1, and 21.6 points for KPCS-GW. The kappa value between APCS and KPCS-1 was 0.91 (95% CI:0.9072, 0.9119) and that between APCS and KPCS-GW was 0.88 (95% CI:0.8757, 0.8810). Additionally, Spearman's correlation coefficients among APCS, KPCS-1, and KPCS-GW showed a very strong correlation. However, 10.8% of the participants' results were inconsistent, and KPCS-1 tended to classify patients into groups with lower nursing needs compared to APCS. Conclusion This study showed that electronic health record-generated APCS can provide useful information on patients' severity and nursing activities to measure workload estimation. Additional research is needed to develop and implement a real-world EHR-based PCS system to accommodate for direct and indirect nursing care while considering diverse population and dynamic healthcare system. Keywords: Patient classification system, Nursing workload, Patient acuity, Electronic health records, Nursing care needs