↓ Skip to main content

Geographical Variation in Psychiatric Admissions Among Recipients of Public Assistance

Overview of attention for article published in Journal of Epidemiology, July 2019
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#10 of 461)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

twitter
85 tweeters
googleplus
1 Google+ user

Readers on

mendeley
5 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Geographical Variation in Psychiatric Admissions Among Recipients of Public Assistance
Published in
Journal of Epidemiology, July 2019
DOI 10.2188/jea.je20180066
Pubmed ID
Authors

Yasuyuki Okumura, Nobuo Sakata, Hisateru Tachimori, Tadashi Takeshima

Abstract

Understanding the area-specific resource use of inpatient psychiatric care is essential for the efficient use of the public assistance system. This study aimed to assess the geographical variation in psychiatric admissions and to identify the prefecture-level determinants of psychiatric admissions among recipients of public assistance in Japan. We identified all recipients of public assistance who were hospitalized in a psychiatric ward in May 2014, 2015, or 2016 using the Fact-finding Survey on Medical Assistance. The age- and sex-standardized number of psychiatric admissions was calculated for each of the 47 prefectures, using direct and indirect standardization methods. A total of 46,559 psychiatric inpatients were identified in May 2016. The number of psychiatric admissions per 100,000 population was 36.6. We found a 7.1-fold difference between the prefectures with the highest (Nagasaki) and lowest (Nagano) numbers of admissions. The method of decomposing explained variance in the multiple regression model showed that the number of psychiatric beds per 100,000 population and the number of recipients of public assistance per 1,000 population were the most important determinants of the number of psychiatric admissions (R2 = 28% and R2 = 23%, respectively). The sensitivity analyses, using medical cost as the outcome and data from different survey years and subgroups, showed similar findings. We identified a large geographical variation in the number and total medical cost of psychiatric admissions among recipients of public assistance. Our findings should encourage policy makers to assess the rationale for this variation and consider strategies for reducing it.

Twitter Demographics

The data shown below were collected from the profiles of 85 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 60%
Researcher 2 40%
Lecturer 1 20%
Readers by discipline Count As %
Unspecified 2 40%
Economics, Econometrics and Finance 1 20%
Pharmacology, Toxicology and Pharmaceutical Science 1 20%
Psychology 1 20%
Medicine and Dentistry 1 20%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 65. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 April 2019.
All research outputs
#250,958
of 13,194,266 outputs
Outputs from Journal of Epidemiology
#10
of 461 outputs
Outputs of similar age
#10,161
of 266,273 outputs
Outputs of similar age from Journal of Epidemiology
#1
of 8 outputs
Altmetric has tracked 13,194,266 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 461 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 266,273 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them