Nurse staffing, nurses prioritization, missed care, quality of nursing care, and nurse outcomes.

AIM: To examine the relationships among nurse staffing, nurses prioritization of nursing activities, missed care, quality of nursing care, and nurse outcomes. BACKGROUND: Inadequate staffing is associated with increased missed care, which threatens the quality of care and nurse outcomes. METHODS: The study sample included 2114 staff nurses from 156 medical or surgical units of 49 general hospitals who had participated in a cross-sectional survey conducted in 2015. Nurse staffing was measured using the patient-to-nurse ratio and perceived staffing adequacy. The Missed Nursing Care Survey was used to measure how frequently nurses had missed each of 24 activities. Multilevel regression analyses were employed to examine the relationships among variables. RESULTS: The prevalence of missed care differed by nursing activity. Poorer staffing was associated with an increased number of missed activities. A higher number of missed activities and poorer staffing were associated with poorer patient safety, quality of nursing care and job satisfaction, and a higher intent to leave. Nurses gave the highest priority to focused patient reassessments, timely medications, and patient teaching, under hypothetical conditions of improved staffing. CONCLUSION: Adequate staffing is required to reduce missed care and to improve quality of care and nurse outcomes.

[Validity and Reliability of the Clinical Teaching Behavior Inventory (CTBI) for Nurse Preceptors in Korea].

PURPOSE: The aim of this study was to evaluate the validity and reliability of the Korean version of the Clinical Teaching Behavior Inventory (CTBI). METHODS: The English CTBI-23 was translated into Korean with forward and backward translation. Survey data were collected from 280 nurses' preceptors at five acute-care hospitals in Korea. Content validity, construct validity, and criterion-related validity were evaluated. Cronbach's α was used to assess reliability. SPSS 24.0 and AMOS 22.0 software was used for data analysis. RESULTS: The CTBI Korean version consists of 22 items in six domains, including being committed to teaching, building a learning atmosphere, using appropriate teaching strategies, guiding inter-professional communication, providing feedback and evaluation, and showing concern and support. One of the items in the CTBI was excluded with a standardized factor loading of less than .05. The confirmatory factor analysis supported good fit and reliable scores for the Korean version of the CTBI model. A six-factor structure was validated (χ²=366.30, p<.001, CMIN/df=2.0, RMSEA=.06, RMR=.03, SRMR=.05, GFI=.90, IFI=.94, TLI=.92, CFI=.94). The criterion validity of the core competency evaluation tool for preceptors was .77 (p<.001). The Cronbach's α for the overall scale was .93, and the six subscales ranged from .72 to .85. CONCLUSION: The Korean version CTBI-22 is a valid and reliable instrument for identifying the clinical teaching behaviors of preceptors in Korea. The CTBI-22 also could be used as a guide for the effective teaching behavior of preceptors, which can help new nurses adapt to the practicalities of nursing.

Psychometric properties of the Korean version of the Copenhagen Burnout Inventory in Korean homecare workers for older adults.

BACKGROUND: Despite the increasing number of homecare workers, a reliable and valid tool with which to measure burnout among Korean homecare workers is still lacking. The aim of this study was to examine the reliability and construct validity of the Korean version of the Copenhagen Burnout Inventory (CBI-K). METHODS: The study population consisted of 465 homecare workers. Data were collected in 2016 through a self-administered questionnaire including the three subscales of the CBI-K, the Center for Epidemiologic Studies Depression Scale (CESD-10), a measure of work-life conflict, and questions about respondents' sociodemographic characteristics. RESULTS: The confirmatory factor analyses results showed that the model fit indices of the refined three-factor model, in which the PB, WRB, and CRB subscales each contained six items, were acceptable (CFI = 0.924, SRMR = 0.049, RMSEA = 0.091). Furthermore, based on the results for construct reliability, discriminant validity of the refined three-factor model and job characteristics of homecare workers, we proposed that an abbreviated two-factor scale using the PB and CRB subscales could be used, with appropriate model fit indices (CFI = 0.950, SRMR = 0.047, RMSEA = 0.084). Each of the PB, WRB, and CRB subscales of CBI-K were associated with depressive symptoms even after controlling for covariates. CONCLUSIONS: The CBI-K has adequate reliability and validity for use with homecare workers. To increase its practicality, we suggest a refined form comprising only PB and CRB subscales can be used rather than a three-factor model.

[Home health resource utilization measures using a case-mix adjustor model].

PURPOSE: The purpose of this study was to measure home health resource utilization using a Case-Mix Adjustor Model developed in the U.S. METHOD: The subjects of this study were 484 patients who had received home health care more than 4 visits during a 60-day episode at 31 home health care institutions. Data on the 484 patients had to be merged onto a 60-day payment segment. Based on the results, the researcher classified home health resource groups (HHRG). RESULT: The subjects were classified into 34 HHRGs in Korea. Home health resource utilization according to clinical severity was in order of Minimum (C0) < 'Low (C1) < 'Moderate (C2) < 'High (C3), according to dependency in daily activities was in order of Minimum (F0) < 'High (F3) < 'Medium (F2) < 'Low (F1) < 'Maximum (F4). Resource utilization by HHRGs was the highest 564,735 won in group C0F0S2 (clinical severity minimum, dependency in daily activity minimum, service utilization moderate), and the lowest 97,000 won in group C2F3S1, so the former was 5.82 times higher than the latter. CONCLUSION: Resource utilization in home health care has become an issue of concern due to rising costs for home health care. The results suggest the need for more analytical attention on the utilization and expenditures for home care using a Case-Mix Adjustor Model.