Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China
Abstract Background Primary 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 optimizat...
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| Language: | English |
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BMC
2025-01-01
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| Series: | Lipids in Health and Disease |
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| Online Access: | https://doi.org/10.1186/s12944-025-02435-7 |
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| author | Ningjing Yang Yuning Wang Ying Li Dongying Xiao Ruirui Cui Nana Li Rong Liu Jing Chai Xingrong Shen Debin Wang |
| author_facet | Ningjing Yang Yuning Wang Ying Li Dongying Xiao Ruirui Cui Nana Li Rong Liu Jing Chai Xingrong Shen Debin Wang |
| author_sort | Ningjing Yang |
| collection | DOAJ |
| description | Abstract Background Primary 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. Methods The 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. Results The 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). Conclusions The 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. |
| format | Article |
| id | doaj-art-e3488d24159140feb6e55b9985122152 |
| institution | Kabale University |
| issn | 1476-511X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Lipids in Health and Disease |
| spelling | doaj-art-e3488d24159140feb6e55b99851221522025-01-26T12:50:34ZengBMCLipids in Health and Disease1476-511X2025-01-0124111110.1186/s12944-025-02435-7Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, ChinaNingjing Yang0Yuning Wang1Ying Li2Dongying Xiao3Ruirui Cui4Nana Li5Rong Liu6Jing Chai7Xingrong Shen8Debin Wang9School of Health Service Management, Anhui Medical UniversitySchool of Health Service Management, Anhui Medical UniversitySchool of Health Service Management, Anhui Medical UniversitySchool of Health Service Management, Anhui Medical UniversitySchool of Health Service Management, Anhui Medical UniversitySchool of Health Service Management, Anhui Medical UniversitySchool of Health Service Management, Anhui Medical UniversitySchool of Health Service Management, Anhui Medical UniversitySchool of Health Service Management, Anhui Medical UniversitySchool of Health Service Management, Anhui Medical UniversityAbstract Background Primary 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. Methods The 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. Results The 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). Conclusions The 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.https://doi.org/10.1186/s12944-025-02435-7HyperlipidemiaMeasuresPrimary health careAutomatic monitoringChina |
| spellingShingle | Ningjing Yang Yuning Wang Ying Li Dongying Xiao Ruirui Cui Nana Li Rong Liu Jing Chai Xingrong Shen Debin Wang Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China Lipids in Health and Disease Hyperlipidemia Measures Primary health care Automatic monitoring China |
| title | Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China |
| title_full | Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China |
| title_fullStr | Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China |
| title_full_unstemmed | Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China |
| title_short | Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China |
| title_sort | automated process assessment of primary healthcare for hyperlipidemia preliminary findings and implications form anhui china |
| topic | Hyperlipidemia Measures Primary health care Automatic monitoring China |
| url | https://doi.org/10.1186/s12944-025-02435-7 |
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