Frontiers in public health · 2026
The economic burden of Hospital-Acquired Infections on cancer patients under China's pioneering Diagnosis-Intervention Packet payment model: a retrospective study.
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Liu Jiao, Xu Min, Ju Xu, Peng Xue-Er, Xia Xue, Li Huan
Аннотация
BACKGROUND: This study aimed to analyze the distribution and economic burden of cancer-related nosocomial infections under the Diagnosis-Intervention Packet (DIP) payment model.
METHODS: A retrospective study was conducted using 2024 medical insurance and healthcare-associated infection (HAI) data from discharged patients at a regional cancer center. We compared the differences in medical insurance settlement indicators between HAI and non-HAI patients within major DIP categories, as well as among different HAI types. After adjusting for time-dependent bias and confounding factors via risk-set matching, we further compared the above indicators between HAI and non-HAI patients, and generalized linear model (GLM) was used to identify independent factors for DIP settlement difference.
RESULTS: HAIs were most concentrated in the DIP category Malignant neoplasm of thoracic esophagus: Partial esophagectomy via cervical-thoracic-abdominal three-incision approach. With major DIP categories, the infected group had significantly higher hospitalization costs, diagnostic test and procedure costs, longer length of stay, and greater DIP deficits (all p < 0.05). MDRO type count and surgical site wound contamination grade were positively correlated with the above indicators and DIP deficits (all p < 0.05). After risk-set matching adjustment, there were still differences between the infected and non-infected groups in the above medical insurance settlement indicators (all p < 0.05). HAIs led to an increase of $5,031.01 in hospitalization costs, $798.81 in diagnostic test and procedure costs, 9 days in prolonged hospital stay, and an additional $1,436.27 in DIP deficits. Generalized linear model analysis showed that HAI occurrence and the number of MDRO types were independent risk factors affecting DIP payment differentials (all p < 0.05). HAI occurrence and infection with ≥3 MDRO types led to an increase of $2,021.15 and $5,601.44 in DIP deficits, respectively.
CONCLUSION: Using DIP payment differentials to assess the economic burden of HAIs is more scientifically valid. Cancer-associated HAIs significantly increase medical resource consumption and economic burden. Implementing infection prevention and control strategies at the DIP categories, particularly for MDRO infections, may help reduce additional costs and improve the balance of medical insurance payments.
METHODS: A retrospective study was conducted using 2024 medical insurance and healthcare-associated infection (HAI) data from discharged patients at a regional cancer center. We compared the differences in medical insurance settlement indicators between HAI and non-HAI patients within major DIP categories, as well as among different HAI types. After adjusting for time-dependent bias and confounding factors via risk-set matching, we further compared the above indicators between HAI and non-HAI patients, and generalized linear model (GLM) was used to identify independent factors for DIP settlement difference.
RESULTS: HAIs were most concentrated in the DIP category Malignant neoplasm of thoracic esophagus: Partial esophagectomy via cervical-thoracic-abdominal three-incision approach. With major DIP categories, the infected group had significantly higher hospitalization costs, diagnostic test and procedure costs, longer length of stay, and greater DIP deficits (all p < 0.05). MDRO type count and surgical site wound contamination grade were positively correlated with the above indicators and DIP deficits (all p < 0.05). After risk-set matching adjustment, there were still differences between the infected and non-infected groups in the above medical insurance settlement indicators (all p < 0.05). HAIs led to an increase of $5,031.01 in hospitalization costs, $798.81 in diagnostic test and procedure costs, 9 days in prolonged hospital stay, and an additional $1,436.27 in DIP deficits. Generalized linear model analysis showed that HAI occurrence and the number of MDRO types were independent risk factors affecting DIP payment differentials (all p < 0.05). HAI occurrence and infection with ≥3 MDRO types led to an increase of $2,021.15 and $5,601.44 in DIP deficits, respectively.
CONCLUSION: Using DIP payment differentials to assess the economic burden of HAIs is more scientifically valid. Cancer-associated HAIs significantly increase medical resource consumption and economic burden. Implementing infection prevention and control strategies at the DIP categories, particularly for MDRO infections, may help reduce additional costs and improve the balance of medical insurance payments.