The purpose of this study was to measure home health resource utilization using a Case-Mix Adjustor Model developed in the U.S.

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).

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.

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.

The purpose of this study was to construct and test a hypothetical model of self-management in patients with hemodialysis based on the Self-Regulation Model and resource-coping perspective.

Data were collected from 215 adults receiving hemodialysis in 17 local clinics and one tertiary hospital in 2016. The Hemodialysis Self-management Instrument, the Revised Illness Perception Questionnaire, Herth Hope Index and Multidimensional Scale of Perceived Social Support were used. The exogenous variable was social context; the endogenous variables were cognitive illness representation, hope, self-management behavior, and illness outcome. For data analysis, descriptive statistics, Pearson correlation analysis, factor analysis, and structural equation modeling were performed.

The hypothetical model with six paths showed a good fitness to the empirical data: GFI=.96, AGFI=.90, CFI=.95, RMSEA=.08, SRMR=.04. The factors that had an influence on self-management behavior were social context (β=.84), hope and cognitive illness representation (β=.37 and β=.27) explaining 92.4% of the variance. Self-management behavior mediated the relationship between psychosocial coping resources and illness outcome.

This research specifies a more complete spectrum of the self-management process. It is important to recognize the array of clinical resources available to support patients' self-management. Healthcare providers can facilitate self-management through collaborative care and understanding the ideas and emotions that each patient has about the illness, and ultimately improve the health outcomes. This framework can be used to guide self-management intervention development and assure effective clinical assessment.

This study was conducted to examine whether the level of classification for long-term care service under long-term care insurance reflects resource utilization level for residents in nursing homes.

From 2 long-term care facilities, the researchers selected 95 participants and identified description and time of care services provided by nurses, certified caregivers, physical therapists and social workers during a 24-hr-period.

Resource utilization level was: 281.04 for level 1, 301.05 for level 2 and 270.87 for level 3. Resource utilization was not correlated with level. Differences in resource utilization within the same level were similar with the coefficient of variance, 22.7-27.1%. Physical function was the most influential factor on long-term care scores (r=.88, p<.001). The level for long-term care service did not reflect differences in resource utilization level of residents on long-term care insurance.

The results of this study indicate that present grading for long-term care service needs to be reconsidered. Further study is needed to adjust the long-term care classification system to reflect the level of resource utilization for care recipients on the long-term care insurance.