Evidence map›Paper›PMID 42192012›Full record

ArticleAesthetic plastic surgery2026

Progress of Plastic and Aesthetic Industry in Mainland China: A National Data Comparison between Public and Private Hospitals.

Mingzi Zhang, Loubin Si, Nan Zhao, Jiaojie Zheng, Yuelun Zhang, Kai Sun, Hongda Chen, Xiaojun Wang, Xiao Long

Abstract readComparative Study
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In one paragraph

Article in Aesthetic plastic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Mingzi Zhang *National Medical Quality Control Center of Plastic and Aesthetic Major, Beijing, China.
Loubin Si *National Medical Quality Control Center of Plastic and Aesthetic Major, Beijing, China.
Nan Zhao *Institute of Clinical Medicine, National Infrastructures for Translational Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
Jiaojie ZhengNational Medical Quality Control Center of Plastic and Aesthetic Major, Beijing, China.
Yuelun ZhangInstitute of Clinical Medicine, National Infrastructures for Translational Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
Kai SunInstitute of Clinical Medicine, National Infrastructures for Translational Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
Hongda ChenInstitute of Clinical Medicine, National Infrastructures for Translational Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
Xiaojun WangNational Medical Quality Control Center of Plastic and Aesthetic Major, Beijing, China. pumchwxj@163.com.ORCID http://orcid.org/0000-0003-4312-6036
Xiao LongNational Medical Quality Control Center of Plastic and Aesthetic Major, Beijing, China. pumclongxiao@126.com.

Funding

National High Level Hospital Clinical Research Funding 2022-PUMCH-B-042Peking Union Medical College Hospital Talent Cultivation Program Category D: UHB12264
6 · The paper itself

Abstract

backgroundThe expansion of plastic and aesthetic industries is heavily market-driven. With socioeconomic advancement, the plastic and aesthetic industries have experienced extraordinarily rapid growth over the past several decades, exhibiting distinct patterns between public and private hospitals.

methodsWe collected national data from public and private hospitals across mainland China through the National Clinical Information System (NCIS) and the National Medical Quality Control Platform (NMQCP) for Plastic and Aesthetic Major. Data encompassed hospital profiles, practitioner demographics, inpatient clinical case mix, ambulatory therapeutic modalities, and the consultation rate for aesthetic injection complications.

resultsAmong public hospitals offering plastic/aesthetic services, 99.20% were general hospitals, while 80.60% of private hospitals were specialized in plastic and aesthetic procedures. We also found significant differences between public and private hospitals regarding physician qualifications, professional backgrounds, inpatient case mix, and ambulatory therapeutic modalities. The consultation rate for aesthetic injection complications was additionally higher in public hospitals relative to private hospitals.

conclusionBoth public and private hospitals have established plastic and aesthetic specialties with distinct scale characteristics. Driven by greater operational autonomy and their market-driven nature, private hospitals exhibited greater flexibility in development within this specialty and demonstrated a stronger preference for minimally invasive treatments. However, despite their perceived minimal invasiveness, aesthetic injections carried significant complication risks; and particularly, severe cases resulted in substantial physical trauma and financial burdens for aesthetic patients. We recommend that government authorities formulate tailored quality-control measures based on the divergent developmental paths of public and private hospitals to safeguard patient safety. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Indexed as

Cosmetic TechniquesHospitals, PrivateHospitals, PublicSurgery, PlasticChinaEstheticsFemaleHumansMalePlastic and aesthetic industryPrivate hospitalsProgressPublic hospitals

Identifiers

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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.