Evidence map›Paper›PMID 39844251›Full record

ArticleLipids in health and disease2025

Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China.

Ningjing Yang, Yuning Wang, Ying Li, Dongying Xiao, Ruirui Cui, Nana Li, Rong Liu, Jing Chai, Xingrong Shen, Debin Wang

Abstract read
In one paragraph

Article in Lipids in health and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Ningjing Yang *School of Health Service Management, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China.
Yuning Wang *School of Health Service Management, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China.
Ying LiSchool of Health Service Management, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China.
Dongying XiaoSchool of Health Service Management, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China.
Ruirui CuiSchool of Health Service Management, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China.
Nana LiSchool of Health Service Management, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China.
Rong LiuSchool of Health Service Management, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China.
Jing ChaiSchool of Health Service Management, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China.
Xingrong ShenSchool of Health Service Management, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China. shenxr@ahmu.edu.cn.
Debin WangSchool of Health Service Management, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China. dbwang@vip.sina.com.

Funding

Natural Science Foundation of China 72374006
6 · The paper itself

Abstract

backgroundPrimary healthcare (PHC) plays a key role in hyperlipidemia (HL) management yet lacks adequate monitoring and feedback. This study aims at identifying pragmatic measures out from routinely collected electronic records to enable automatic monitoring and inform continuous optimization of HL-management at PHC settings.

methodsThe study used randomly selected electronic records of PHC (from the province-wide data center of Anhui-province, China) as the main data source and generated both procedure-based and encounter-based measures for assessing HL-management. The procedure-based measures were derived from specific quality-facts of 21 stages/procedures (e.g., lipid lowering medication prescription) using self-designed algorithms. While the encounter-based measures included number or rate of visits for HL, currently-noticed hyperlipidemia (CNHL, or HL noticed during the current consultation), and ever-diagnosed hyperlipidemia (EDHL). Analysis of these measures employed mainly simple descriptives and linear regression modeling.

resultsThe study revealed interesting findings including: low and varied rates of visits for HL(from 0.01 to 1.43%) and visits by patients with EDHL/CNHL(from 0.13 to 20.54% or from 0.02 to 2.99%) between regions; large differences (5.14 to 22.20 times) between the mean or cumulative proportions of visits by patients with EDHL versus CNHL among clinician groups; consistent increase in the ratio of visits for HL in all cause visits over the study period (from 0.087 to 1.000%) accompanied with relatively stable proportions of patients with CNHL/EDHL; Relatively low scores in the procedure-based measures (ranged from 0.00 to 36.08% for specific procedures by seasons).

conclusionsThe measures identified are not only feasible from real-world PHC records but also give some useful metrics about how well current HL-management is going and what future actions are needed.

Indexed as

HyperlipidemiasPrimary Health CareAgedAlgorithmsChinaElectronic Health RecordsFemaleHumansMaleMiddle AgedAutomatic monitoringChinaHyperlipidemiaMeasuresPrimary health care

Identifiers

PMID39844251
PMCPMC11753159

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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.