Evidence map›Paper›PMID 31718596›Full record

ArticleBMC cancer2019

Factors analysis on the use of key quality indicators for narrowing the gap of quality of care of breast cancer.

Chao Wang, Xi Li, Shaofei Su, Xinyu Wang, Jingkun Li, Xiaoqiang Bao, Meina Liu

Abstract read
In one paragraph

Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

6 citing papers in PubMed.

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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

7 authors.

Chao WangDepartment of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin, 150081, China.
Xi LiDepartment of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin, 150081, China.
Shaofei SuDepartment of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin, 150081, China.
Xinyu WangDepartment of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin, 150081, China.
Jingkun LiDepartment of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin, 150081, China.
Xiaoqiang BaoDepartment of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin, 150081, China.
Meina LiuDepartment of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin, 150081, China. liumeina369@163.com.ORCID http://orcid.org/0000-0002-3790-8069

Funding

National Natural Science Foundation of China 81573255
6 · The paper itself

Abstract

backgroundThere are differences in the quality of care among breast cancer patients. Narrowing the quality differences could be achieved by increasing the utilization rate of indicators. Here we explored key indicators that can improve the quality of care and factors that may affect the use of these indicators.

methodsA total of 3669 breast cancer patients were included in our retrospective study. We calculated patient quality-of-care composite score based on patient average method. Patients were divided into high- and low-quality groups according to the mean score. We obtained the indicators with large difference in utilization between the two groups. Multilevel logistic regression model was used to analyze the factors influencing quality of care and use of indicators.

resultsThe mean composite score was 0.802, and the number of patients in the high- and low-quality groups were 1898 and 1771, respectively. Four indicators showed a difference in utilization between the two groups of over 40%. Histological grade, pathological stage, tumor size and insurance type were the factors affecting the quality of care. In single indicator evaluation, besides the above factors, age, patient income and number of comorbidities may also affect the use of these four indicators. Number of comorbidities may have opposite effects on the use of different indicators, as does pathological stage.

conclusionsIdentifying key indicators for enhancing the quality-of-care of breast cancer patients and factors that affect the indicator adherence may provide guides for enhancing the utilization rate of these indicators in clinical practice.

Indexed as

Quality Indicators, Health CareQuality of Health CareAdultAgedBreast NeoplasmsFactor Analysis, StatisticalFemaleHumansMiddle AgedNeoplasm StagingYoung AdultBreast cancerComprehensive evaluationInfluence factorSingle indicator evaluation

Identifiers

PMID31718596
PMCPMC6852954

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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.