Evidence map›Paper›PMID 34770221›Full record

ArticleInternational journal of environmental research and public health2021

The Unmet Medical Demand among China's Urban Residents.

Pengfei Sheng, Tingting Yang, Tengfei Zhang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Pengfei ShengSchool of Economics, Henan University, Kaifeng 475002, China.
Tingting YangSchool of Economics, Henan University, Kaifeng 475002, China.
Tengfei ZhangSchool of Public Finance and Taxation, Southwestern University of Finance and Economics, Chengdu 611130, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our work aimed to build a reasonable proxy for unmet medical demands of China's urban residents. We combined health demand modeling and stochastic frontier analysis to produce a frontier medical demand function, which allowed us to disentangle unmet medical demands from the unobservable effects. We estimated unmet medical demands by using China's provincial dataset that covered 2005-2018. Our estimates showed that unmet medical demand at the national level was 12.6% in 2018, and regions with high medical prices confronted more unmet medical demands than regions with moderate or low medical prices during 2005-2018. Furthermore, medical prices and education were the main factors that affected unmet medical demand; therefore, policy making should pay more attention to reducing medical costs and promoting health education.

Indexed as

Urban PopulationChinaHumansfrontier demand functionmedical demandMundlak specificationthe unmet medical demand

Identifiers

PMID34770221
PMCPMC8583618

What OpenQuestion holds

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Registered trials

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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.