Evidence map›Paper›PMID 32684168›Full record

ArticleBMC family practice2020

Development of type 2 diabetes mellitus quality indicators in general practice by a modified Delphi method in Beijing, China.

Guanghui Jin, Yun Wei, Yanli Liu, Feiyue Wang, Meirong Wang, Yali Zhao, Juan Du, Shuqi Cui, Xiaoqin Lu

Open access · goldAbstract read
In one paragraph

Article in BMC family practice, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.9field-weighted citation impact, top 11% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

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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 at 1 institution in 1 country.

Guanghui JinDepartment of General Practice, School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China.
Yun WeiDepartment of General Practice, School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China.
Yanli LiuDepartment of General Practice, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China.
Feiyue WangDepartment of General Practice, School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China.
Meirong WangDepartment of General Practice, School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China.
Yali ZhaoDepartment of General Practice, School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China.
Juan DuDepartment of General Practice, School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China.
Shuqi CuiDepartment of General Practice, School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China.
Xiaoqin LuDepartment of General Practice, School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China. xq6518@163.com.
Capital Medical University · CN

Funding

Beijing Key Researcher Development Funding Program 2017000020124G286
6 · The paper itself

Abstract

backgroundThe service capacity of primary care has improved in China. General practice also takes growing responsibility in the management of type 2 diabetes mellitus, but there are concerns about the paucity of evidence of the quality of care delivered. And there is an absence of systematic quality indicators of type 2 diabetes mellitus in general practice in China. This study aimed to develop a set of type 2 diabetes mellitus quality indicators to facilitate quality measurement in general practice in China.

methodsPreliminary quality indicators were generated and refined by literature review and an expert consultation meeting. Two rounds of email-based Delphi survey and a consensus meeting were carried out to identify quality indicators. Delphi questionnaires with 43 indicators were sent to 30 participants in the first round. There were 16 general practitioners and 10 community health service center leaders from primary care, 3 endocrinologists and a primary care researcher in the first round. And 27 out of the 30 participants participated in the second round. The consensus meeting was held among 9 participants to refine the indicators and a last round of rating was carried out in the meeting. The indicators were rated in terms of importance and feasibility. The agreement criteria were defined as median ≥ 7.0 and ≥ 85.0% of ratings in the 7-9 tertile for importance; median ≥ 7.0 and ≥ 65.0, 70.0, 75.0% of ratings in the 7-9 tertile for feasibility respectively in the three rounds of rating.

resultsAfter 2 rounds of Delphi survey and the consensus meeting, total 38 indicators achieved consensus for inclusion in the final set of indicators. The final set of indicators were grouped into 7 domains: access (5 indicators), monitoring (12 indicators), health counseling (7 indicators), records (2 indicators), health status (7 indicators), patient satisfaction (2 indicators) and self-management (3 indicators).

conclusionsA set of 38 potential quality indicators of type 2 diabetes mellitus in general practice were identified by an iterative Delphi process in Beijing, China. Preliminary approach for measurement and data collection were described. However, the indicators still need to be validated by testing in a further study.

Indexed as

Diabetes Mellitus, Type 2General PracticeBeijingChinaDelphi TechniqueHumansQuality Indicators, Health CareBeijingDelphi methodGeneral practiceQuality indicatorsQuality of careType 2 diabetes mellitus

Identifiers

PMID32684168
PMCPMC7370510
OpenAlexW3042942919

What OpenQuestion holds

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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.