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Aim: This study aimed to develop a valid and reliable new intensive care unit nursing classification tool, including direct and indirect nursing activities, by measuring the nursing intensity provided to patients. Background: Prior tools primarily examine patients' medical records or disease severity/interactions, systematically failing to reflect comorbidity risk factors. Design: The Delphi technique was used to test the content validity of the Korean Patient Classification System on Nursing Intensity for Critical Care Nurses (KPCSNIC). Methods: Data were collected from four hospitals in two provinces from 26 December 2017 to 30 January 2018. To verify construct validity, staff nurses classified 365 patients, comparing differences by medical department and type of stay. To verify interrater reliability, data collectors and the head nurses of three intensive care units classified 87 patients. Results: The KPCSNIC had 8 categories, 44 nursing activities and 105 criteria. Reliability was high (r =.84). Construct validity was verified by revealing differences according to medical department and type of patient. Using total scores, four KPCSNIC groups were identified. Conclusion: The KPCSNIC developed in this study can support staffing for nursing intensity by providing more specific evaluation criteria. Moreover, it reflects nursing intensity, including direct and indirect nursing activities. Summary statement: What is already known about this topic? In order to secure the quality of nursing care, it is important to allocate an appropriate number of nurse staffing based on nursing demand and nursing time reflecting to the number and severity of patients, and shift of work.The patient acuity tools used in Korea are limited as they primarily examine patients' physiological characteristics based on medical records or quantify disease severity and interactions, systematically failing to reflect risk factors for comorbidities.The intensive care unit patient classification tool that is currently used underestimates clinical nursing intensity, as it does not realistically evaluate patient‐related disease factors and indirect nursing activities. What this paper adds? This study developed a new patient classification tool that reflects patients' clinical characteristics and classified them according to nursing intensity.In addition to direct nursing activities, indirect nursing activities that were invisible and difficult to measure can be scored using this tool. The implications of this paper: Since this tool enables quantitative measurement of nursing workload, data using this tool can be used as evidence for invoicing for nursing care fees, previously calculated as a percentage of inpatient fees per day.This study was conducted in a first‐grade hospital with a high level of nurse staffing. To secure the validity and reliability of the tool, additional research is needed, using the tool in a greater number and wider range of hospitals. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study was to identify the patient and hospital characteristics related to nursing needs and nursing hours in acute hospital settings. Background: To determine appropriate staffing levels, accumulating empirical data through direct observation and surveys reflecting the actual situation is necessary. Methods: In this cross‐sectional study, we conducted direct observations of nurses in acute care hospitals from 1 May to 31 August 2020. Twenty‐six hospitals in five cities participated, and 747 nursing personnel collected 1,681 patients' data while performing nursing activities. The data of 1,605 nurses were analysed using descriptive statistics, t tests, analysis of variance and linear regression. Results: Hospital size, admission day, patients' dependence level, high fall risk and disease diagnoses were variables associated with nursing needs (F = 73.49, P <.001) and nursing hours (F = 57.7, P <.001). Comparing the correlates of nursing needs and nursing hours revealed that, unlike nursing needs, nursing hours were not significantly associated with surgery and certain diagnoses. Conclusion: This study confirmed the variables associated with nursing needs and nursing hours in acute hospitals; based on this, determining appropriate staffing levels, which is an important step in improving inpatients' health outcomes, is necessary. Implications for Nursing Management: In acute hospitals, an increased number of nurse staffing should be employed based on the number of newly hospitalized patients, patients with high dependence levels and specific diagnoses, and those at high risk of falling. [ABSTRACT FROM AUTHOR]

Aim: To develop a new general wards patient classification tool based on the nursing intensity level that reflects patients' clinical characteristics and indirect nursing activities. Design: A cross‐sectional design was adopted. This methodological study developed a patient classification system to sort general ward patients based on the intensity of their nursing needs and verified the validity and reliability of this classification system. Methods: Thirteen experts verified the tools' content validity. Data collectors and head nurses classified 150 patients from two hospitals with four general wards and various nurse staffing levels. Inter‐rater reliability was analysed. Staff nurses classified 846 patients following the Korean patient classification system on nursing intensity scores that reflected patients' clinical status. Content validity was verified based on the classification results. Using K‐group cluster analysis, score ranges for four groups were identified. Results: The developed tool includes 8 domains, (symptom management, infection control, nutrition and medication, personal hygiene and secretion, activity, sleep and rest, guidance in nursing/emotional support, nursing activity planning and coordination, indirect activity), 24 subdomains, 66 nursing activities and 124 criteria. Inter‐rater reliability showed high agreement. [ABSTRACT FROM AUTHOR]