Evidence map›Paper›PMID 36324547›Full record

ArticleBulletin of the World Health Organization2022

Rehabilitation services and related health databases, Japan.

Kaori Yamaguchi, Yasuhiro Nakanishi, Viroj Tangcharoensathien, Makoto Kono, Yuichi Nishioka, Tatsuya Noda, Tomoaki Imamura, Manabu Akahane

Abstract read
In one paragraph

Article in Bulletin of the World Health Organization, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Kaori YamaguchiDepartment of Health and Welfare Services, National Institute of Public Health, 2-3-6 Minami, Wako, Saitama, 351-0197, Japan.
Yasuhiro NakanishiDepartment of Health and Welfare Services, National Institute of Public Health, 2-3-6 Minami, Wako, Saitama, 351-0197, Japan.
Viroj TangcharoensathienInternational Health Policy Program, Ministry of Public Health, Nonthaburi, Thailand.
Makoto KonoSchool of Health Sciences, International University of Health and Welfare, Odawara, Japan.
Yuichi NishiokaDepartment of Public Health, Health Management and Policy, Nara Medical University, Kashihara, Japan.
Tatsuya NodaDepartment of Public Health, Health Management and Policy, Nara Medical University, Kashihara, Japan.
Tomoaki ImamuraDepartment of Public Health, Health Management and Policy, Nara Medical University, Kashihara, Japan.
Manabu AkahaneDepartment of Health and Welfare Services, National Institute of Public Health, 2-3-6 Minami, Wako, Saitama, 351-0197, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The demographic transition towards an ageing population and the epidemiological transition from communicable to noncommunicable diseases have increased the demand for rehabilitation services globally. The aims of this paper were to describe the integration of rehabilitation into the Japanese health system and to illustrate how health information systems containing real-world data can be used to improve rehabilitation services, especially for the ageing population of Japan. In addition, there is an overview of how evidence-informed rehabilitation policy is guided by the analysis of large Japanese health databases, such as: (i) the National Database of Health Insurance Claims and Specific Health Checkups; (ii) the long-term care insurance comprehensive database; and (iii) the Long-Term Care Information System for Evidence database. Especially since the 1990s, the integration of rehabilitation into the Japanese health system has been driven by the country's ageing population and rehabilitation is today provided widely to an increasing number of older adults. General medical insurance in Japan covers acute and post-acute (or recovery) intensive rehabilitation. Long-term care insurance covers rehabilitation at long-term care institutions and community facilities for older adults with the goal of helping to maintain independence in an ageing population. The analysis of large health databases can be used to improve the management of rehabilitation care services and increase scientific knowledge as well as guide rehabilitation policy and practice. In particular, such analyses could help solve the current challenges of overtreatment and undertreatment by identifying strict criteria for determining who should receive long-term rehabilitation services.

Indexed as

Insurance, Long-Term CareLong-Term CareAgedDatabases, FactualHumansInsurance, HealthJapan

Identifiers

PMID36324547
PMCPMC9589382

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.