Evidence map›Paper›PMID 29125585›Full record

ArticleInternational journal of environmental research and public health2017

Estimation and Evaluation of Future Demand and Supply of Healthcare Services Based on a Patient Access Area Model.

Shunsuke Doi, Hiroo Ide, Koichi Takeuchi, Shinsuke Fujita, Katsuhiko Takabayashi

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
11.9field-weighted citation impact, top 2% 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

5 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Article
  3. Mapping Access to Children's Hospitals in Texas.International journal of environmental research and public health · 2024
    Article
  4. Accessibility of Rural Life Space on the Jianghan Plain, China: The Role of Livelihood.International journal of environmental research and public health · 2021
    Article
  5. Article
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

5 authors at 2 institutions in 1 country.

Shunsuke DoiDepartment of Healthcare and Information Management, University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan. s.doi@hcc.h.u-tokyo.ac.jp.
Hiroo IdeDepartment of Welfare and Medical Intelligence, Chiba University Hospital, 1-8-1 Inohana, Chuo-ku, Chiba 260-8677, Japan. ide@chiba-u.jp.
Koichi TakeuchiDepartment of Welfare and Medical Intelligence, Chiba University Hospital, 1-8-1 Inohana, Chuo-ku, Chiba 260-8677, Japan. koichist@chiba-u.jp.
Shinsuke FujitaDepartment of Welfare and Medical Intelligence, Chiba University Hospital, 1-8-1 Inohana, Chuo-ku, Chiba 260-8677, Japan. fujitan@faculty.chiba-u.jp.
Katsuhiko TakabayashiDepartment of Internal Medicine, Sanwa Hospital, Medical Incorporated Association Kanae-kai, 7-379 Higurashi, Matsudo, Chiba 270-2253, Japan. takaba@kanae-kai.or.jp.
Chiba University Hospital · JPUniversity of Tokyo Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accessibility to healthcare service providers, the quantity, and the quality of them are important for national health. In this study, we focused on geographic accessibility to estimate and evaluate future demand and supply of healthcare services. We constructed a simulation model called the patient access area model (PAAM), which simulates patients' access time to healthcare service institutions using a geographic information system (GIS). Using this model, to evaluate the balance of future healthcare services demand and supply in small areas, we estimated the number of inpatients every five years in each area and compared it with the number of hospital beds within a one-hour drive from each area. In an experiment with the Tokyo metropolitan area as a target area, when we assumed hospital bed availability to be 80%, it was predicted that over 78,000 inpatients would not receive inpatient care in 2030. However, this number would decrease if we lowered the rate of inpatient care by 10% and the average length of the hospital stay. Using this model, recommendations can be made regarding what action should be undertaken and by when to prevent a dramatic increase in healthcare demand. This method can help plan the geographical resource allocation in healthcare services for healthcare policy.

Indexed as

Health Services AccessibilityHealth Services Needs and DemandFemaleGeographic Information SystemsHospitalizationHumansMaleTokyoestimationgeographic information systemshealth services demandhealth services geographic accessibility

Identifiers

PMID29125585
PMCPMC5708006
OpenAlexW2767698564

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.