|Tuesday, 13 February 2018, 10:27 HKT/SGT|
Source: Fujitsu Ltd
|Evaluating application of AI to the municipality's mission critical systems|
TOKYO, Feb 13, 2018 - (JCN Newswire) - Fujitsu Limited and Fujitsu Hokuriku Systems Limited today announced that, in partnership with Tokyo's Kita City, they are conducting a field trial to evaluate how AI can be used to streamline tasks associated with guidance and supervision of nursing-care benefit claims from service providers, which Kita City employees customarily process by hand. The field trial will utilize Fujitsu Human Centric AI Zinrai, Fujitsu's approach to artificial intelligence, and will be conducted from January through March 2018 as part of efforts to enhance social security benefits.
Japanese society continues to age rapidly, and Kita City is working to create an environment where the elderly can live in health and safety. With the increase in both the number of people certified as requiring care and in the number of care facilities, however, also growing is the volume of work related to guidance and the analysis of nursing-care benefit payment details, and this has become a serious issue. In this field trial, machine learning technology developed by Fujitsu Hokuriku Systems, which combines customer business expertise and software development technology, is put to use by systems engineers to create a model to analyze the appropriateness of claim details. The trial will apply machine learning to data, such as past nursing-care benefit claims from service providers that have accumulated in Kita City's nursing-care insurance system, and it will then evaluate the effectiveness of this model. Kita City aims to use the insights gained from this field trial not only to increase the efficiency of processing nursing-care benefit payments that employees previously had to spend time handling, but also to further rationalize nursing-care benefit claims.
As part of the Tokyo Metropolitan Government's Improvement Plan for Long-Term Care Benefits, 3rd Phase(1), Kita City employees analyze the appropriateness of certification applications from nursing-care service providers and nursing-care benefit claims. They are also responsible for the supervision and guidance of those same providers using the results of that analysis. In recent years, however, the number of people recognized as requiring nursing care and the number of nursing-care facilities have both been increasing, which has consequently increased the volume of analysis and guidance tasks associated with payments for nursing-care benefit claims, leading to problems with increased burdens on such employees. In order to resolve this issue, Kita City is now conducting a joint field trial with Fujitsu and Fujitsu Hokuriku Systems aiming to improve the efficiency of guidance tasks related to nursing-care benefit payments using Zinrai.
Details of the Field Trial
Because the analysis of the appropriateness of nursing-care benefit claims must be conducted in great detail, with reference to laws such as the Long-Term Care Insurance Act, it requires a high level of skill and a great deal of time. This field trial will evaluate factors such as the ability to reduce the burden on employees by using Zinrai to improve the efficiency of analyses.
2. Time Period and Location
Time period: January through March 2018 Trial location: Kita City office, Tokyo (Address: 1-15-22 Ojihoncho, Kita, Tokyo)
3. Trial Overview
Fujitsu will train machine learning algorithms on data--both appropriate nursing-care benefit claim data and claim data that required guidance and supervision--from past claims by nursing-care service providers stored in Kita City's nursing-care insurance system, and then build a model that can automatically analyze the appropriateness of claim data. Moreover, they will use the newly built model to analyze the appropriateness of nursing-care benefit claim data, and evaluate the results of those analyses against past guidance and supervision records.
Using the insights gained from this field trial, Kita City aims to improve the efficiency of nursing-care benefit payment operations, and to also further enhance the services nursing-care service providers offer to residents. Going forward, Fujitsu aims to offer the trained model built through this field trial as a service, contributing to the accuracy of social security benefits for local governments across Japan. Based on the concept of Fujitsu Knowledge Integration, the Fujitsu Group is working to create new value through ICT that utilizes knowledge and experience from a wide range of industries and businesses. Fujitsu will continue to work with various customers, especially local governments, to resolve local issues and societal problems through ICT, contributing to the promotion of prosperity for people and society.
(1) Improvement Plan for Long-Term Care Benefits, 3rd Phase Announced by the Tokyo Metropolitan Government in March 2015. Covering the period from April 2015 to March 2018, this is a plan that seeks to make nursing-care benefits fairer, after appropriately identifying the people who need nursing-care services (the beneficiaries), ascertaining the services beneficiaries truly need through appropriate care management, and promoting the delivery of appropriate services by providers in accordance with the rules.
About Fujitsu Ltd
Fujitsu is the leading Japanese information and communication technology (ICT) company, offering a full range of technology products, solutions, and services. Approximately 155,000 Fujitsu people support customers in more than 100 countries. We use our experience and the power of ICT to shape the future of society with our customers. Fujitsu Limited (TSE: 6702) reported consolidated revenues of 4.5 trillion yen (US$40 billion) for the fiscal year ended March 31, 2017. For more information, please see http://www.fujitsu.com.
* Please see this press release, with images, at:
Public and Investor Relations
Feb 13, 2018 10:27 HKT/SGT
Source: Fujitsu Ltd
Fujitsu Ltd (TSE: 6702)
Topic: Press release summary
Sectors: Enterprise IT
From the Asia Corporate News Network
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