Evidence map›Paper›PMID 29165139›Full record

ArticleEnvironmental health and preventive medicine2017

Analysis of the evidence-practice gap to facilitate proper medical care for the elderly: investigation, using databases, of utilization measures for National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB).

Takeo Nakayama, Yuichi Imanaka, Yasushi Okuno, Genta Kato, Tomohiro Kuroda, Rei Goto, Shiro Tanaka, Hiroshi Tamura, Shunichi Fukuhara, Shingo Fukuma and 4 more

Open access · goldAbstract readValidation Study
In one paragraph

Article in Environmental health and preventive medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 19% of its field
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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.

  1. Pooled it
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  5. Observational
  6. National trends in hospitalizations for gastrointestinal bleeding in Japan.Journal of clinical biochemistry and nutrition · 2024
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  17. 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

14 authors at 2 institutions in 1 country.

Takeo NakayamaDepartment of Health Informatics, Kyoto University, School of Public Health, Yoshida Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan. nakayama.takeo.4a@kyoto-u.ac.jp.
Yuichi ImanakaDepartment of Healthcare Economics and Quality Management, Kyoto University Graduate School of Medicine, School of Public Health, Kyoto, Japan.
Yasushi OkunoDepartment of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Genta KatoSolutions Center for Health Insurance Claims, Kyoto University Hospital, Kyoto, Japan.
Tomohiro KurodaDivision of Medical Information Technology and Administration Planning, Kyoto University Hospital, Kyoto, Japan.
Rei GotoGraduate School of Business Administration, Keio University, Yokohama, Japan.
Shiro TanakaFaculty of Economics, Kyoto University, Kyoto, Japan.
Hiroshi TamuraDivision of Medical Information Technology and Administration Planning, Kyoto University Hospital, Kyoto, Japan.
Shunichi FukuharaDepartment of Clinical Biostatistics, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Shingo FukumaDepartment of Clinical Biostatistics, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Manabu MutoDepartment of Healthcare Epidemiology, School of Public Health in the Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Motoko YanagitaDepartment of Therapeutic Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Yosuke YamamotoDepartment of Clinical Biostatistics, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
BiDAME: Big Data Analysis of Medical Care for the Elderly in Kyoto
Kyoto University · JPKyoto University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As Japan becomes a super-aging society, presentation of the best ways to provide medical care for the elderly, and the direction of that care, are important national issues. Elderly people have multi-morbidity with numerous medical conditions and use many medical resources for complex treatment patterns. This increases the likelihood of inappropriate medical practices and an evidence-practice gap. The present study aimed to: derive findings that are applicable to policy from an elucidation of the actual state of medical care for the elderly; establish a foundation for the utilization of National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), and present measures for the utilization of existing databases in parallel with NDB validation.Cross-sectional and retrospective cohort studies were conducted using the NDB built by the Ministry of Health, Labor and Welfare of Japan, private health insurance claims databases, and the Kyoto University Hospital database (including related hospitals). Medical practices (drug prescription, interventional procedures, testing) related to four issues-potential inappropriate medication, cancer therapy, chronic kidney disease treatment, and end-of-life care-will be described. The relationships between these issues and clinical outcomes (death, initiation of dialysis and other adverse events) will be evaluated, if possible.

Indexed as

Databases, FactualQuality of Health CareTerminal CareAgedAged, 80 and overCross-Sectional StudiesFemaleHospitalsHospitals, UniversityHumansInsurance Claim ReportingInsurance, HealthJapanMaleMedication ErrorsNeoplasmsClaims dataDatabaseElderlyEvidence-practice gapValidation

Identifiers

PMID29165139
PMCPMC5664421
OpenAlexW2621776077

What OpenQuestion 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 OpenQuestion graph.