Dataset Information

Resilience and learning from insurance firms: Dataset on British long-term insurance market performance.

ABSTRACT: This data article revealed data about the UK long-term insurance market performance for over a decade. The data was acquired from the ABI and contains important trading results (i.e. premiums generated) across different types of long-term insurance. It also revealed the outgoings (i.e. claims incurred) and data on total individual business in force at year end - relating to number of policies. The data relates specifically to life and annuities, individual pensions, occupational pensions, income protection and other insurance business. The dataset revealed some important information on long-term insurance products within the UK insurance market which could serve as a high-quality resource for longitudinal analysis in the field. Thus, the data can provide crucial insights about UK long-term insurance market resilience during the global financial crisis and can be compare with different era, sectors and countries to show hidden business resilience factors, competitiveness and survival strategies.

SUBMITTER: Mafimisebi OP

PROVIDER: S-EPMC6280597 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Resilience and learning from insurance firms: Dataset on British long-term insurance market performance.

Mafimisebi Oluwasoye P OP Nworie Ifeanyichukwu I Hadleigh-Dunn Sara S

Data in brief 20181124

This data article revealed data about the UK long-term insurance market performance for over a decade. The data was acquired from the ABI and contains important trading results (i.e. premiums generated) across different types of long-term insurance. It also revealed the outgoings (i.e. claims incurred) and data on total individual business in force at year end - relating to number of policies. The data relates specifically to life and annuities, individual pensions, occupational pensions, income ...[more]

PMID: 30555874

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Project description:IntroductionIn brain-computer interfaces (BCI) research, recording data is time-consuming and expensive, which limits access to big datasets. This may influence the BCI system performance as machine learning methods depend strongly on the training dataset size. Important questions arise: taking into account neuronal signal characteristics (e.g., non-stationarity), can we achieve higher decoding performance with more data to train decoders? What is the perspective for further improvement with time in the case of long-term BCI studies? In this study, we investigated the impact of long-term recordings on motor imagery decoding from two main perspectives: model requirements regarding dataset size and potential for patient adaptation.MethodsWe evaluated the multilinear model and two deep learning (DL) models on a long-term BCI & Tetraplegia (ClinicalTrials.gov identifier: NCT02550522) clinical trial dataset containing 43 sessions of ECoG recordings performed with a tetraplegic patient. In the experiment, a participant executed 3D virtual hand translation using motor imagery patterns. We designed multiple computational experiments in which training datasets were increased or translated to investigate the relationship between models' performance and different factors influencing recordings.ResultsOur results showed that DL decoders showed similar requirements regarding the dataset size compared to the multilinear model while demonstrating higher decoding performance. Moreover, high decoding performance was obtained with relatively small datasets recorded later in the experiment, suggesting motor imagery patterns improvement and patient adaptation during the long-term experiment. Finally, we proposed UMAP embeddings and local intrinsic dimensionality as a way to visualize the data and potentially evaluate data quality.DiscussionDL-based decoding is a prospective approach in BCI which may be efficiently applied with real-life dataset size. Patient-decoder co-adaptation is an important factor to consider in long-term clinical BCI.

Project description:BackgroundSwallowing/feeding difficulty is a serious hidden health problem in the older population. Although oral intake services based on the degree of this difficulty have been provided and revised in Japanese public long-term care (LTC) insurance since 2006, their implementation has not been examined. We evaluated the impact of policy changes on these services.MethodsThe nationwide database of LTC service uses in Japan was analysed for three oral intake services: Enhanced Oral Function in daycare facilities whose users were slightly disabled, Maintenance of Oral Ingestion and Transition to Oral Ingestion from tube feeding in residential facilities. Data were extracted for each June from 2015 to 2020 when monthly usage of these services was aligned and each June from 2009 to 2020 for the proportion of users according to LTC insurance certification. The major policy changes were the addition of municipal provision in Enhanced Oral Function and a requirement for multidisciplinary collaboration in Maintenance of Oral Ingestion in 2015. The impact of the medical fee reduction for developing percutaneous gastro-tubing to Transition to Oral Ingestion was also examined.ResultsBetween 2015 and 2020, the use of Enhanced Oral Function and Maintenance of Oral Ingestion increased and Transition to Oral Ingestion decreased, resulting in a total increase in use of 275,000 times or approximately 5,000 times per 100,000 among all older adults with LTC insurance certification. Concerning the proportion of users' disability status, the major users of Enhanced Oral Function in 2020 were slightly disabled and independent older adults (70%, up from 55% to 2009). Regarding the major users of Maintenance of Oral Ingestion between 2013 and 2020, care-need level 5 (most severe) decreased by 11%, whereas the total of care-need levels 4 and 3 increased by 9%. The use of Transition to Oral Ingestion, which had been declining, showed a further decline after reduction of the medical fee for percutaneous gastro-tubing in 2014.ConclusionsDue to policy changes, Enhanced Oral Function and Maintenance of Oral Ingestion have increased in the number of use among slightly disabled persons. However, this increase may be insufficient given the hidden swallowing/feeding difficulty.

Dataset Information

Resilience and learning from insurance firms: Dataset on British long-term insurance market performance.

Publications

Resilience and learning from insurance firms: Dataset on British long-term insurance market performance.

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