Evidence map›Paper›PMID 33490004›Full record

ArticleFrontiers in public health2020

Text Mining and Quantitative Research of Medical Service Policy: Sichuan Province as an Example.

Huiqin Zhang, Liping Zhu, Chen Zeng, Xudong Chen

Abstract read
In one paragraph

Article in Frontiers in public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

4 authors.

Huiqin ZhangCollege of Management Science, Chengdu University of Technology, Chengdu, China.
Liping ZhuCollege of Management Science, Chengdu University of Technology, Chengdu, China.
Chen ZengCollege of Management Science, Chengdu University of Technology, Chengdu, China.
Xudong ChenCollege of Management Science, Chengdu University of Technology, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical service policy plays a prominent role in the development of a "Healthy China." This paper constructs a three-dimensional framework for text mining of medical service policy using the elements of policy instruments, policy strength, and types of medical service activity. Taking Sichuan Province as an example, 221 medical service policy documents, issued by the government and related departments, are selected as the research sample; the policy instruments, policy strength, and medical service activity types are analyzed using ROST and Nvivo 11.0 software. It is concluded that the government needs to optimize the structure of policy instruments, to appropriately reduce the use of environmental policy instruments in particular, while increasing the use of demand-based policy instruments. It is necessary to strengthen the interaction between the various sub-policy instruments, and to increase the use of financial services, fiscal taxes, overseas communications, and strategic measures. An increase in the implementation of government policy assists the acceleration of the policy landing, the further improvement of the supervision system, and the safeguard mechanism of the three medicine policy linkage, which can improve the sustainability of the medical service policy, and further resolve the difficulty and expense of seeing a doctor.

Indexed as

Environmental PolicyGovernmentChinaData MiningTaxesmedical service activitiesmedical service policypolicy instrumentspolicy strengthtext mining

Identifiers

PMID33490004
PMCPMC7820774

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.