Zhilin Yong 1 , Li Luo 1 , Yonghong Gu 2 , Chunyang Li 2 Show Affiliations »
Abstract
OBJECTIVE: Air pollution has potential risk on asthma patients, further prolongs the length of stay. However, it is unclear that the impact of air pollution on excessive length of stay (ELoS) of heterogeneous asthma patients. In this study, we proposed a K-Nearest Neighbor (KNN) embedded approach incorporating with patient status to analyze the impact of short-term air pollution on the ELoS of asthma patients. METHODS: The KNN embedded approach includes two stages. Firstly, the KNN algorithm was employed to search for the most similar patient community and approximate kernel proxy of each index patient by Euclidean distance. Then, we built the differential fixed-effect linear model to estimate the risk of air pollution to the ELoS. RESULTS: We analyzed 6563 asthma patients' medical insurance records in a large city of China from January to December in 2014. It was found that when the duration of exposure to air pollution (i.e., PM2.5, PM10, SO2, NO2, and CO) reaches around 4-5 days, the risk of increasing the ELoS becomes the largest. But only O3 shows the opposite effect. What's more, CO is the dominant risk to increase the ELoS. With a 1 mg/m3 increment of CO average concentration in 5 days, the ELoS will go up by 0.8157 day (95%CI:0.72,0.9114). Based on the kernel proxy in the top 1% similar patient community, the additional financial burden posed on each patient increases by RMB 488.6002 (95%CI:430.1962,547.0043) due to the ELoS. CONCLUSIONS: The KNN embedded approach is an innovative method that takes into account the heterogeneous patient status, and effectively estimates the impact of air pollution on the ELoS. It is concluded that air pollution poses adverse effects and additional financial burdens on asthma patients. Heterogeneous patients should adopt different strategies in health management to reduce the risk of increasing the ELoS due to air pollution, and improve the efficiency of medical resource utilization. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40201-020-00584-8. © Springer Nature Switzerland AG 2021.
OBJECTIVE: Air pollution has potential risk on asthma patients, further prolongs the length of stay. However, it is unclear that the impact of air pollution on excessive length of stay (ELoS) of heterogeneous asthma patients. In this study, we proposed a K-Nearest Neighbor (KNN) embedded approach incorporating with patient status to analyze the impact of short-term air pollution on the ELoS of asthma patients. METHODS: The KNN embedded approach includes two stages. Firstly, the KNN algorithm was employed to search for the most similar patient community and approximate kernel proxy of each index patient by Euclidean distance. Then, we built the differential fixed-effect linear model to estimate the risk of air pollution to the ELoS. RESULTS: We analyzed 6563 asthma patients' medical insurance records in a large city of China from January to December in 2014. It was found that when the duration of exposure to air pollution (i.e., PM2.5, PM10, SO2, NO2, and CO) reaches around 4-5 days, the risk of increasing the ELoS becomes the largest. But only O3 shows the opposite effect. What's more, CO is the dominant risk to increase the ELoS. With a 1 mg/m3 increment of CO average concentration in 5 days, the ELoS will go up by 0.8157 day (95%CI:0.72,0.9114). Based on the kernel proxy in the top 1% similar patient community, the additional financial burden posed on each patient increases by RMB 488.6002 (95%CI:430.1962,547.0043) due to the ELoS. CONCLUSIONS: The KNN embedded approach is an innovative method that takes into account the heterogeneous patient status, and effectively estimates the impact of air pollution on the ELoS. It is concluded that air pollution poses adverse effects and additional financial burdens on asthma patients. Heterogeneous patients should adopt different strategies in health management to reduce the risk of increasing the ELoS due to air pollution, and improve the efficiency of medical resource utilization. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40201-020-00584-8. © Springer Nature Switzerland AG 2021.
Entities: Chemical
Keywords:
Air pollution; Excessive length of stay; Financial burden; Heterogeneous patient; K-nearest neighbor algorithm
Year: 2021
PMID： 34150221 PMCID： PMC8172679 DOI： 10.1007/s40201-020-00584-8
Source DB: PubMed Journal: J Environ Health Sci Eng