Association of disability level with polypharmacy and potentially inappropriate medication in community dwelling older people

Kojima, Takao; Hamaya, Hironobu; Ishii, Shinya; Hattori, Yukari; Akishita, Masahiro

doi:10.1016/j.archger.2022.104873

Cited by 5 publications

(5 citation statements)

References 33 publications

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“…See Tables 8-13. (7) The better classifiers and the less accurate classifiers were identified by the conducted experiments across 1 run and 10 runs, respectively. (8) From Table 14, it is implied that the rule filtering technique is an effective method for the RST classifier to improve classification accuracy and model stability and lower the total rule numbers generated.…”

Section: Conclusion Of the Study Resultsmentioning

confidence: 99%

“…From different perspectives, all the above signs show the key importance of data mining technology, and we can use and trace the application of "new" models for data mining technology to dig out any hidden information from the given data; in particular, treasure can be excavated from past insurance data. Therefore, this study serves to establish future effective decision-making rules and criteria from an amount of LTCI data [7] to help the insurance industry and insurers expand their operating performance. However, insurers face a mature insurance market full of highly uncertain and highly competitive risks now.…”

Section: Continuous Research Motivation and Research Originalitymentioning

confidence: 99%

“…(6) Add different conditional attributes into the LTCI data set to re-validate the practical application of the results of this study, and compare their results of the difference in effectiveness. (7) Use different feature selection methods to re-identify the important conditional attributes in influencing the issues related to LTCI. (8) Use different data discretization techniques to discretize the numerical data of conditional attributes for further measuring the performance of the proposed hybrid model.…”

Section: Subsequent Studiesmentioning

confidence: 99%

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A Study to Identify Long-Term Care Insurance Using Advanced Intelligent RST Hybrid Models with Two-Stage Performance Evaluation

Chen

Hung

Lin³

2023

Mathematics

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With the motivation of long-term care 2.0 plans, forecasting models to identify potential customers of long-term care insurance (LTCI) are an important and interesting issue. From the limited literature, most past researchers emphasize traditional statistics techniques to address this issue; however, these are lacking in some areas. For example, intelligent hybrid models for LTCI are lacking, performance measurement of components for hybrid models is lacking, and research results for interpretative capacities are lacking, resulting in a black box scenario and difficulty in making decisions, and the gap between identifying potential customers and constructing hybrid models is unbridged. To solve the shortcomings mentioned above, this study proposes some advanced intelligent single and hybrid models; the study object is LTCI customers. The proposed hybrid models were used on the experimental dataset collected from real insurance data and possess the following advantages: (1) The feature selection technique was used to simplify variables for the purpose of improving model performance. (2) The performance of hybrid models was evaluated against some machine learning methods, including rough set theory, decision trees, multilayer perceptron, support vector machine, genetic algorithm, random forest, logistic regression, and naive Bayes, and sensitivity analysis was performed in terms of accuracy, coverage, rules number, and standard deviation. (3) We used the C4.5 algorithm of decision trees and the LEM2 algorithm of rough sets to extract and provide valuably comprehensible decisional rules as decision-making references for the interested parties for their varied benefits. (4) We used post hoc testing to verify the significant difference in groups. Conclusively, this study effectively identifies potential customers for their key attributes and creates a decision rule set of knowledge for use as a reference when solving practical problems by forming a structured solution. This study is a new trial in the LTCI application field and realizes novel creative application values. Such a hybrid model is rarely seen in identifying LTCI potential customers; thus, the study has sufficient application contribution and managerial benefits to attract much concern from the interested parties.

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Section: Conclusion Of the Study Resultsmentioning

confidence: 99%

Section: Continuous Research Motivation and Research Originalitymentioning

confidence: 99%

Section: Subsequent Studiesmentioning

confidence: 99%

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A Study to Identify Long-Term Care Insurance Using Advanced Intelligent RST Hybrid Models with Two-Stage Performance Evaluation

Chen

Hung

Lin³

2023

Mathematics

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“…Total medication prescriptions and PIMs decreased among those with care needs levels 1-5 compared to those with support level 1-2. In older adults certi ed for longterm care (LTC), polypharmacy and rates of potentially inappropriate medications (PIMs) are signi cantly elevated compared to those without LTC certi cation (23). Polypharmacy reaches its peak at mild care need levels, while the prevalence of PIMs escalates with increasing levels of care needs (23).…”

Section: Multivariate Analysismentioning

confidence: 99%

“…In older adults certi ed for longterm care (LTC), polypharmacy and rates of potentially inappropriate medications (PIMs) are signi cantly elevated compared to those without LTC certi cation (23). Polypharmacy reaches its peak at mild care need levels, while the prevalence of PIMs escalates with increasing levels of care needs (23). While our ndings are consistent with those of previous research, our study analyzed a ve times larger number of exclusively certi ed care-needing individuals, which may enhance its reliability.…”

Section: Multivariate Analysismentioning

confidence: 99%

Polypharmacy and potentially inappropriate medications in older adults who use long-term care services: A cross-sectional study

Hagiwara,

Komiyama,

Iwagami

et al. 2024

Preprint

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Background: Older adults requiring care often have multiple morbidities that lead to polypharmacy, including the use of potentially inappropriate medications (PIMs), leading to increased medical costs and adverse drug effects. We conducted a cross-sectional study to clarify the actual state of drug prescriptions and the background of polypharmacy and PIMs. Methods: Using long-term care (LTC) and medical insurance claims data in the Ibaraki Prefecture from April 2018 to March 2019, we included individuals aged ≥ 65 who used LTC services. The number of drugs prescribed for ≥ 14 days and the number of PIMs were counted. A generalized linear model was used to analyze the association between the backgrounds of individuals and the number of drugs; logistic regression analysis was used for the presence of PIMs. Results: Herein, 67,531 older adults who received LTC services were included. The median number of total prescribed medications and PIMs was 7(IQR 5–9) and 1(IQR 0–1), respectively. The main PIMs were loop diuretics/aldosterone antagonists, benzodiazepines/similar hypnotics, and nonsteroidal anti-inflammatory drugs. Multivariate analysis revealed that the number of medications and presence of PIMs were significantly higher in patients with comorbidities and in those visiting multiple medical institutions. However, patients requiring care level ≧ 1, nursing home residents, users of short-stay service, and senior daycare were negatively associated with polypharmacy and PIMs. Conclusions: Polypharmacy and PIMs are frequently observed in older adults who require LTC. This was prominent among individuals with comorbidities and at multiple consulting institutions. Therefore, a nationwide cohort study is required.

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Development of the Japanese Anticholinergic Risk Scale: English translation of the Japanese article

Mizokami,

Mizuno,

Taguchi

et al. 2024

Geriatrics Gerontology Int

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BackgroundAnticholinergic burden, reflecting the cumulative impact of medications with anticholinergic properties, significantly predicts adverse drug reactions and geriatric syndromes in older adults. Although anticholinergic risk scales (ARS) have been developed and validated in various countries, none have been tailored specifically for Japan. The Japanese Anticholinergic Risk Scale (JARS) was developed to adapt the existing ARS frameworks to the Japanese context, considering unique medication profiles and cultural factors.ProcessFirst, a systematic review was performed to follow the protocol registered in PROSPERO (CRD42017076510). A PubMed search from October 2017 to March 2023 was conducted to identify ARS publications post‐September 2017. Based on two algorithms, average scores from the existing scores were used to develop JARS. The Delphi method, an expert consensus approach, was applied to determine the scores for medications that were not established by the algorithms. Sixteen articles identified in our systematic review contributed to JARS development. JARS categorizes 158 medications into three potency groups: 37 drugs scored as 3 (strong), 27 as 2 (moderate), and 94 as 1 (weak).ConclusionJARS, the newly developed ARS, could be a critical tool for anticholinergic burden assessment in older Japanese populations. Developed through a systematic review and Delphi‐based expert consensus, it encompasses 158 medications, offering a comprehensive anticholinergic burden assessment. Future studies and updates should be conducted to improve the accuracy and clinical applicability of this scale. Geriatr Gerontol Int 2024; ••: ••–••.

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Association of disability level with polypharmacy and potentially inappropriate medication in community dwelling older people

Cited by 5 publications

References 33 publications

A Study to Identify Long-Term Care Insurance Using Advanced Intelligent RST Hybrid Models with Two-Stage Performance Evaluation

A Study to Identify Long-Term Care Insurance Using Advanced Intelligent RST Hybrid Models with Two-Stage Performance Evaluation

Polypharmacy and potentially inappropriate medications in older adults who use long-term care services: A cross-sectional study

Development of the Japanese Anticholinergic Risk Scale: English translation of the Japanese article

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