scholarly journals Predicting Incidence of Long-term Care Insurance Certification in Japan with the Kihon Checklist for Frailty Screening Tool: Analysis of Local Government Survey Data

2020 ◽  
Author(s):  
Kumiko Ito ◽  
Hisashi Kawai ◽  
Harukazu Tsuruta ◽  
Shuichi Obuchi
Keyword(s):  
Logistic Regression ◽  
Local Government ◽  
Long Term Care ◽  
Multiple Logistic Regression ◽  
Short Term ◽  
Term Care ◽  
Specificity And Sensitivity ◽  
Long Term Care Insurance ◽  
Level 1

Abstract Background: Predicting incidence of long-term care insurance (LTCI) certification in the short term is of increasing importance in Japan. The present study examined whether the Kihon Checklist (KCL) can be used to predict incidence of LTCI certification (care level 1 or higher) in the short term among older Japanese persons.Methods: In 2015, the local government in Tokyo, Japan, distributed the KCL to all individuals older than 65 years who had not been certified as having a disability or who had already been certified as requiring support level 1–2 according to LTCI system. We also collected LTCI certification data within the 3 months after collecting the KCL data. The data of 17785 respondents were analyzed. First, we selected KCL items strongly associated with incidence of LTCI certification, using stepwise forward-selection multiple logistic regression. Second, we conducted receiver operating characteristic (ROC) analyses for three conditions (1: Selected KCL items, 2: The main 20 KCL items (nos. 1–20), 3: All 25 KCL items). Third, we estimated specificity and sensitivity for each condition.Results: During a 3-month follow-up, 81 (0.5%) individuals required new LTCI certification. Eight KCL items were selected by multiple logistic regression as predictive of certification. The area under the ROC curve in the three conditions was 0.92–0.93, and specificity and sensitivity for all conditions were greater than 80%.Conclusions: Three KCL conditions predicted short-term incidence of LTCI certification. This suggests that KCL items may be used to screen for the risk of incident LTCI certification.

scholarly journals Predicting Incidence of Long-term Care Insurance Certification in Japan with the Kihon Checklist for Frailty Screening Tool: Analysis of Local Government Survey Data

2020 ◽  
Author(s):  
Kumiko Ito ◽  
Hisashi Kawai ◽  
Harukazu Tsuruta ◽  
Shuichi Obuchi
Keyword(s):  
Logistic Regression ◽  
Local Government ◽  
Long Term Care ◽  
Multiple Logistic Regression ◽  
Short Term ◽  
Term Care ◽  
Specificity And Sensitivity ◽  
Long Term Care Insurance ◽  
Level 1

Abstract Background: Predicting incidence of long-term care insurance (LTCI) certification in the short term is of increasing importance in Japan. The present study examined whether the Kihon Checklist (KCL) can be used to predict incidence of LTCI certification (care level 1 or higher) in the short term among older Japanese persons.Methods: In 2015, the local government in Tokyo, Japan, distributed the KCL to all individuals older than 65 years who had not been certified as having a disability or who had already been certified as requiring support level 1–2 according to LTCI system. We also collected LTCI certification data within the 3 months after collecting the KCL data. The data of 17785 respondents were analyzed. First, we selected KCL items strongly associated with incidence of LTCI certification, using stepwise forward-selection multiple logistic regression. Second, we conducted receiver operating characteristic (ROC) analyses for three conditions (1: Selected KCL items, 2: The main 20 KCL items (nos. 1–20), 3: All 25 KCL items). Third, we estimated specificity and sensitivity for each condition.Results: During a 3-month follow-up, 81 (0.5%) individuals required new LTCI certification. Eight KCL items were selected by multiple logistic regression as predictive of certification. The area under the ROC curve in the three conditions was 0.92–0.93, and specificity and sensitivity for all conditions were greater than 80%.Conclusions: Three KCL conditions predicted short-term incidence of LTCI certification. This suggests that KCL items may be used to screen for the risk of incident LTCI certification.

scholarly journals Predicting incidence of long-term care insurance certification in Japan with the Kihon Checklist for frailty screening tool: analysis of local government survey data

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kumiko Ito ◽  
Hisashi Kawai ◽  
Harukazu Tsuruta ◽  
Shuichi Obuchi
Keyword(s):  
Logistic Regression ◽  
Local Government ◽  
Long Term Care ◽  
Multiple Logistic Regression ◽  
Short Term ◽  
Term Care ◽  
Specificity And Sensitivity ◽  
Long Term Care Insurance ◽  
Level 1

Abstract Background Predicting incidence of long-term care insurance (LTCI) certification in the short term is of increasing importance in Japan. The present study examined whether the Kihon Checklist (KCL) can be used to predict incidence of LTCI certification (care level 1 or higher) in the short term among older Japanese persons. Methods In 2015, the local government in Tokyo, Japan, distributed the KCL to all individuals older than 65 years who had not been certified as having a disability or who had already been certified as requiring support level 1–2 according to LTCI system. We also collected LTCI certification data within the 3 months after collecting the KCL data. The data of 17,785 respondents were analyzed. First, we selected KCL items strongly associated with incidence of LTCI certification, using stepwise forward-selection multiple logistic regression. Second, we conducted receiver operating characteristic (ROC) analyses for three conditions (1: Selected KCL items, 2: The main 20 KCL items (nos. 1–20), 3: All 25 KCL items). Third, we estimated specificity and sensitivity for each condition. Results During a 3-month follow-up, 81 (0.5%) individuals required new LTCI certification. Eight KCL items were selected by multiple logistic regression as predictive of certification. The area under the ROC curve in the three conditions was 0.92–0.93, and specificity and sensitivity for all conditions were greater than 80%. Conclusions Three KCL conditions predicted short-term incidence of LTCI certification. This suggests that KCL items may be used to screen for the risk of incident LTCI certification.

scholarly journals Predicting Incidence of Long-term Care Insurance Certification in Japan with the Kihon Checklist for Frailty Screening Tool: Analysis of Local Government Survey Data

2020 ◽  
Author(s):  
Kumiko Ito ◽  
Hisashi Kawai ◽  
Harukazu Tsuruta ◽  
Shuichi Obuchi
Keyword(s):  
Logistic Regression ◽  
Local Government ◽  
Long Term Care ◽  
Multiple Logistic Regression ◽  
Short Term ◽  
Term Care ◽  
Specificity And Sensitivity ◽  
Long Term Care Insurance ◽  
Level 1

Abstract Background Predicting incidence of long-term care insurance (LTCI) certification in the short term is of increasing importance in Japan. The present study examined whether the Kihon Checklist (KCL) can be used to predict incidence of LTCI certification (care level 1 or higher) in the short term among older Japanese persons. Methods In 2015, the local government in Tokyo, Japan, distributed the KCL to all individuals older than 65 years who had not been certified as having a disability or who had already been certified as requiring support level 1–2 according to LTCI system. We also collected LTCI certification data within the 3 months after collecting the KCL data. The data of 17785 respondents were analyzed. First, we selected KCL items strongly associated with incidence of LTCI certification, using stepwise forward-selection multiple logistic regression. Second, we conducted receiver operating characteristic (ROC) analyses for three conditions (1: Selected KCL items, 2: The main 20 KCL items (nos. 1–20), 3: All 25 KCL items). Third, we estimated specificity and sensitivity for each condition. Results During a 3-month follow-up, 81 (0.5%) individuals required new LTCI certification. Eight KCL items were selected by multiple logistic regression as predictive of certification. The area under the ROC curve in the three conditions was 0.92–0.93, and specificity and sensitivity for all conditions were greater than 80%. Conclusions Three KCL conditions predicted short-term incidence of LTCI certification. This suggests that KCL items may be used to screen for the risk of incident LTCI certification.

scholarly journals Prevention Services via Public Long-term Care Insurance can be Effective Among a Specific Group of Older Adults: A City Claim Data Analysis

2020 ◽  
Author(s):  
Tomoko Ito ◽  
Takahiro Mori ◽  
Natsumi Shimafuji ◽  
Katsuya Iijima ◽  
Satoru Yoshie ◽  
...  
Keyword(s):  
Older Adults ◽  
Long Term Care ◽  
Preventive Services ◽  
Preventive Service ◽  
Term Care ◽  
Prevention Services ◽  
Support Level ◽  
Long Term Care Insurance ◽  
Level 1

Abstract BackgroundTo evaluate the effects of prevention services provided by long-term care insurance (LTCI) for older adults who require support from LTCI in Kashiwa City, Japan MethodsWe conducted an analysis using the following population-based longitudinal data in Kashiwa City between April 2012 and March 2015: Data of National Health Insurance and LTCI claims, the survey for certification of LTCI, the register, and premium tier classification. All data was linked using the pre-assigned anonymous identifying numbers. We analyzed the Cox regression model using the time for the deteriorations of long-term care levels as an outcome and the use of preventive care services as the primary exposure among participants aged 75 years or older, who had either support levels 1 or 2 at the beginning of this analysis. The study was further stratified by both age and initial support level. ResultsThe final analysis included 1,289 participants. The primary result showed, among all participants, that preventive service was not effective (hazard ratio 0.96, 95% confidence interval 0.78-1.19). In our sub-analysis, the preventive service was effective in avoiding deteriorations only among those aged 85 and older with support level 1 (HR 0.65, 95% CI 0.43-0.97) out of four groups.ConclusionsThe preventive services of LTCI in Kashiwa City showed a significant effect on the deterioration among subjects aged 85 or older, whose disabled level were low (support level 1). Our results suggest that the prevention services provided by LTCI may not be effective for all older individuals; to provide these services efficiently, local governments, as insurers of LTCI, will need to identify the specified groups that may benefit from the preventive services.

scholarly journals Predictors for Increasing Eligibility Level among Home Help Service Users in the Japanese Long-Term Care Insurance System

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Kuniyasu Kamiya ◽  
Kenji Sasou ◽  
Makoto Fujita ◽  
Sumio Yamada
Keyword(s):  
Risk Factors ◽  
Memory Impairment ◽  
Long Term Care ◽  
Service Users ◽  
Term Care ◽  
Care Level ◽  
Home Help ◽  
Long Term Care Insurance ◽  
Level 1

Objectives. This cross-sectional study described the prevalence of possible risk factors for increasing eligibility level of long-term care insurance in home help service users who were certified as support level 1-2 or care level 1-2 in Japan.Methods. Data were collected from October 2011 to November 2011. Variables included eligibility level, grip strength, calf circumference (CC), functional limitations, body mass index, memory impairment, depression, social support, and nutrition status.Results. A total of 417 subjects (109 males and 308 females, mean age 83 years) were examined. There were 109 subjects with memory impairment. When divided by cut-off values, care level 2 was found to have higher prevalence of low grip strength, low CC, and depression.Conclusions. Some potentially modifiable factors such as muscle strength could be the risk factors for increasing eligibility level.

scholarly journals BURDEN OF FAMILY CARE-GIVERS AND THE RATIONING IN THE LONG-TERM CARE INSURANCE BENEFITS OF JAPAN

2008 ◽  
Vol 53 (01) ◽  
pp. 121-144 ◽  
Author(s):  
WATARU SUZUKI ◽  
SEIRITSU OGURA ◽  
NOBUYUKI IZUMIDA
Keyword(s):  
Long Term Care ◽  
Family Care ◽  
Well Being ◽  
Positive Contribution ◽  
Short Term ◽  
Term Care ◽  
Care Givers ◽  
Home Helper ◽  
Long Term Care Insurance

Long-Term Care Insurance (LTCI), introduced in Japan in 2000, is rapidly turning into a system of rationed benefits due to financial difficulty. Based on our survey of 2,530 family care-givers and the Zarit Care-Giver Burden Index, we have examined how LTCI is affecting their subjective burden. We have found that, as Kishida and Tanigaki (2004) had shown, (i) insufficient provision of short-term stays, day services and home-helper services, as well as (ii) disruptive or antisocial behaviors of the elderly, increase the care-giver's burden. We then argue that (iii) these results establish the positive contribution of LTCI in the well-being of family care-givers, (iv) short-term stay is the most efficient service, followed by home-helper service, and day service is the least efficient, and we show that (v) J-ZBIC-8 works well enough for many practical purposes.

scholarly journals Prevention services via public long-term care insurance can be effective among a specific group of older adults in Japan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Tomoko Ito ◽  
Takahiro Mori ◽  
Hideto Takahashi ◽  
Natsumi Shimafuji ◽  
Katsuya Iijima ◽  
...  
Keyword(s):  
Older Adults ◽  
Long Term Care ◽  
Preventive Services ◽  
Preventive Service ◽  
Term Care ◽  
Prevention Services ◽  
Support Level ◽  
Long Term Care Insurance ◽  
Level 1

Abstract Background To evaluate the effects of prevention services provided by long-term care insurance (LTCI) for older adults who require support from LTCI in Kashiwa City, Japan. Methods We conducted an analysis using the following population-based longitudinal data in Kashiwa City between April 2012 and March 2015: Data of National Health Insurance and LTCI claims, the survey for certification of LTCI, the register, and premium tier classification. All data was linked using the pre-assigned anonymous identifying numbers. We analyzed the Cox regression model using the time for the deteriorations of levels of certified care need in LTCI as an outcome and the use of preventive care services as the primary exposure among participants aged 75 years or older, who had either support levels 1 or 2 at the beginning of this analysis. The study was further stratified by both age and initial support level. Results The final analysis included 1289 participants. The primary result showed, among all participants, that preventive service was not effective (hazard ratio 0.96, 95% confidence interval 0.78–1.19). In our sub-analysis, the preventive service was effective in avoiding deteriorations only among those aged 85 and older with support level 1 (HR 0.65, 95% CI 0.43–0.97) out of four groups. Conclusions The preventive services of LTCI in Kashiwa City showed a significant effect on the deterioration among subjects aged 85 or older, whose disability level were low (support level 1). Our results suggest that the prevention services provided by LTCI may not be effective for all older individuals; to provide these services efficiently, local governments, as insurers of LTCI, will need to identify the specified groups that may benefit from the preventive services. Additionally, it is necessary to re-examine what preventive interventions may be effective, or redesign the health system if necessary, for those who were not affected by the intervention.

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