Evidence map›Paper›PMID 30356462›Full record

ArticleJournal of global health2018

Factors of hospitalization expenditure of the genitourinary system diseases in the aged based on "System of Health Account 2011" and neural network model.

Junlin He, Zhuo Yin, Wenjuan Duan, Yushan Wang, Xin Wang

Open access · goldAbstract read
In one paragraph

Article in Journal of global health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
4.0field-weighted citation impact, top 6% 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

10 citing papers in PubMed, 23 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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 3 institutions in 1 country.

Junlin HeSchool of Public Health, China Medical University, Wuxi No. 2 People's Hospital Affiliated to Nanjing Medical University, Wuxi, China.
Zhuo YinCollege of Metropolitan Transportation, Beijing University of Technology, Beijing, China.
Wenjuan DuanCollege of the Humanities and Social Sciences, China Medical University, Shenyang, China.
Yushan WangChina Medical University, Shenyang, China.
Xin WangCollege of the Humanities and Social Sciences, China Medical University, School of Public Health, Xinjiang Medical University, Urumqi, China.
China Medical University · CNBeijing University of Technology · CNCapital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHospitalization expenditure of genitourinary system diseases among the aged is often overlooked. The aim of our research is to analyze the basic situation and influencing factors of hospitalization expenditure of the genitourinary system diseases and provide better data for the health system.

methodsA total of 1 377 681 patients aged 65 years and over were collected with multistage stratified cluster random sampling in 252 medical institutions in Liaoning China, and "System of Health Account 2011" (SHA2011) was conducted to analyze the expenditure of the diseases. The corresponding samples were extracted, the neural network model was utilized to fit the regression model of the diseases among the aged, and sensitivity analysis was used to rank the influencing factors.

resultsTotal hospitalization expenditure in Liaoning was 51.286 billion yuan, and curative care expenditure of diseases of the genitourinary system was 3.350 billion yuan, accounting for 6.53%. In the neural network model, the training set of R2 was 0.71. The test set of R2 was 0.74. In the sensitivity analysis, top-three influencing factors were the length of stay, type of institutions and type of insurances; the weight was 0.28, 0.19 and 0.14, respectively.

conclusionsThis research used SHA2011 to grab a large amount of data and analyzed them depending upon the corresponding dimensions. The neural network can analyze the influencing factors of hospitalization expenditure of genitourinary diseases in elderly patients accurately and directly, and can clearly describe the extent of its impact by combining sensitivity analysis.

Indexed as

AgedChinaComputer SimulationDatabases, FactualFemaleFemale Urogenital DiseasesHealth ExpendituresHospitalizationHumansMaleMale Urogenital DiseasesNeural Networks, Computer

Identifiers

PMID30356462
PMCPMC6184416
OpenAlexW2896183107

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.