Objective:Exploring the association rules of factors influencing high hospitalization costs for cancer patients, providing references for hospitals to optimize medical cost management measures.Methods:In the inpatient case information system of a tertiary general hospital, the medical record homepages of inpatients in the DRG groups of the oncology department in 2022 were obtained. The upper four scores of hospitalization costs was used as the threshold for patient grouping. Patients with hospitalization costs≥this threshold were the high-cost group, while other patients were control group; 12 factors, including age, gender, and admission condition, etc, were considered as potential influencing factors of high hospitalization costs. FP-Growth and Apriori algorithms were used to excavate the potential association rules between the influencing factors of high hospitalization costs. Logistic regression was used to analyze the independent influencing factors of high hospitalization costs.Results:A total of 5 512 hospitalized patients were included, including 1 378 patients in the high-cost group. Thirteen validated strong association rules for factors influencing high hospitalization costs were obtained, of which the rule antecedents included age (≥70 years), number of days in hospital (≥7 days), other diagnoses (≥5), surgery, planned readmission, use of antibiotics, admission (general/critical), living admission score (61~99), level of care (level 1/level 2), non-day ward, criticality during hospitalisation. Logistic regression results showed that all nine influencing factors except gender, use of antibiotics, and readmission plans were independent influences on high hospitalization costs ( P<0.05). Conclusions:The joint application of FP-Growth and Apriori algorithm could effectively explore the association rules of high hospitalization costs for oncology patients. The early warning information mainly included the number of hospitalization days, the number of other diagnoses, surgeries, and so on. It was suggested that medical institutions can reasonably control the high hospitalization costs through clinical pathway management, diagnosis and treatment process reengineering, admission risk assessment, and multidisciplinary collaborative diagnosis and treatment strategies.

Objective:To analyze the influencing factors of China′s DRG payment system reform(DRG reform) and its hierarchical relationship, for references for the in-depth promotion of China′s medical insurance payment reform.Methods:Relevant literature on DRG reform in China from databases such as CNKI, Wanfang Database, Pubmed, etc, were obtained. Content analysis method was used to extract the influencing factors of DRG reform. The correlation between each influencing factor was determined through expert discussion. An interpretive structural model(ISM) was constructed to analyze the hierarchical relationship of factors influencing DRG reform.Results:After analysis, the influencing factors(12) of DRG reform in China were included such as medical level, hospital management, and medical staff′s cognition and behavior. Among them, the local situation was the deep-level factor affecting DRG reform, 9 factors such as data quality assurance and policy design/implementation were the middle-level factors, and patients′ interests/needs and disease grouping were the surface-level factors.Conclusions:There were many influencing factors on the reform of China′s DRG payment system. It was suggested that relevant management departments in various regions should focus on the actual situation of the locality, take data quality and policy design and implementation as the key points of reform, formulate a scientific and reasonable DRG grouping scheme, safeguard the interests of patients, so as to promote the deepening of DRG reform.

Objective:Exploring the association rules of factors influencing high hospitalization costs for cancer patients, providing references for hospitals to optimize medical cost management measures.Methods:In the inpatient case information system of a tertiary general hospital, the medical record homepages of inpatients in the DRG groups of the oncology department in 2022 were obtained. The upper four scores of hospitalization costs was used as the threshold for patient grouping. Patients with hospitalization costs≥this threshold were the high-cost group, while other patients were control group; 12 factors, including age, gender, and admission condition, etc, were considered as potential influencing factors of high hospitalization costs. FP-Growth and Apriori algorithms were used to excavate the potential association rules between the influencing factors of high hospitalization costs. Logistic regression was used to analyze the independent influencing factors of high hospitalization costs.Results:A total of 5 512 hospitalized patients were included, including 1 378 patients in the high-cost group. Thirteen validated strong association rules for factors influencing high hospitalization costs were obtained, of which the rule antecedents included age (≥70 years), number of days in hospital (≥7 days), other diagnoses (≥5), surgery, planned readmission, use of antibiotics, admission (general/critical), living admission score (61~99), level of care (level 1/level 2), non-day ward, criticality during hospitalisation. Logistic regression results showed that all nine influencing factors except gender, use of antibiotics, and readmission plans were independent influences on high hospitalization costs ( P<0.05). Conclusions:The joint application of FP-Growth and Apriori algorithm could effectively explore the association rules of high hospitalization costs for oncology patients. The early warning information mainly included the number of hospitalization days, the number of other diagnoses, surgeries, and so on. It was suggested that medical institutions can reasonably control the high hospitalization costs through clinical pathway management, diagnosis and treatment process reengineering, admission risk assessment, and multidisciplinary collaborative diagnosis and treatment strategies.

Objective:To analyze the influencing factors of China′s DRG payment system reform(DRG reform) and its hierarchical relationship, for references for the in-depth promotion of China′s medical insurance payment reform.Methods:Relevant literature on DRG reform in China from databases such as CNKI, Wanfang Database, Pubmed, etc, were obtained. Content analysis method was used to extract the influencing factors of DRG reform. The correlation between each influencing factor was determined through expert discussion. An interpretive structural model(ISM) was constructed to analyze the hierarchical relationship of factors influencing DRG reform.Results:After analysis, the influencing factors(12) of DRG reform in China were included such as medical level, hospital management, and medical staff′s cognition and behavior. Among them, the local situation was the deep-level factor affecting DRG reform, 9 factors such as data quality assurance and policy design/implementation were the middle-level factors, and patients′ interests/needs and disease grouping were the surface-level factors.Conclusions:There were many influencing factors on the reform of China′s DRG payment system. It was suggested that relevant management departments in various regions should focus on the actual situation of the locality, take data quality and policy design and implementation as the key points of reform, formulate a scientific and reasonable DRG grouping scheme, safeguard the interests of patients, so as to promote the deepening of DRG reform.

Objective To observe the feasibility of photon-counting detector(PCD)-CT combined with"four-lows"protocol(low contrast agent concentration,low contrast dose,low contrast agent flow rate,low radiation dose)for coronary CT angiography(CCTA).Methods Totally 106 patients with suspected coronary artery disease were prospectively enrolled and randomized into energy-integrating detector(EID)-CCTA(group A,using conventional scanning protocol,n=52)or PCD-CCTA(group B,using"four-lows"scanning protocol,n=54)groups and underwent relative examinations.The radiation dose,subjective and objective evaluation results of imaging quality were compared between groups.Results The contrast agent dose and flow rate,volume CT dose index,dose length product and effective dose in group B were all lower than those in group A(all P＜0.001).The subjective scores in group B were higher than in group A(5[4,5]vs.4[4,5],Z=-2.310,P=0.021).Compared with group A,CT value,signal-to-noise ratio and contrast-to-noise ratio of aortic root and most of the main branches of coronary arteries increased in group B,while standard deviation of CT value decreased(all P＜0.05).Conclusion PCD-CT combined with"four-lows"protocol could be used for CCTA,which could improve imaging quality and reduce contrast agent usage and radiation dose.

Objective:To assess the viability of reducing radiation dose, contrast media volume, injection flow rate and contrast medium concentration (quadruple low-dose protocol) by utilizing virtual monoenergetic images (VMI) in photon-counting detector CT (PCD-CT) for aortic CT angiography (CTA), while maintaining image quality in comparison to images obtained from energy-integrating detector CT (EID-CT).Methods:From April 2024 to June 2024, a total of 40 participants who underwent aortic CTA on PCD-CT were prospectively enrolled in the experimental group (PCD-CT group), while 40 patients with similar baseline characteristics who had previously undergone aortic CTA using EID-CT were retrospectively selected for the conventional group (EID-CT group). The EID-CT group used a tube voltage of 90 kVp, a contrast media volume of 60 ml of contrast, an injection flow rate of 3 ml/s, and a contrast concentration of 350 mgI/ml; the PCD-CT group used the QuantumPlus mode, with a tube voltage of 140 kVp, a total amount of iodine in the contrast media of 140 mgI/kg, and an injection flow rate=contrast media volume/(delay time+scan time), and a contrast media concentration of 320 mgI/ml. VMIs in PCD-CT group were reconstructed in 5-keV intervals ranging from 45 to 65 keV. The effective radiation dose and contrast injection protocols were recorded and compared between two groups. Objective image quality assessment was performed for each group. CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured at five anatomical locations (ascending aorta, aortic arch, descending aorta, abdominal aorta, and right common iliac artery), and image noise was recorded. Subjective image quality was independently evaluated by two readers using a 5-point Likert scale in a blinded manner. Based on data normality, the one-way ANOVA or Kruskal-Wallis test was used for image quality assessment, with Bonferroni-corrected post-hoc analysis for multiple comparisons.Results:There were no significant differences in the baseline characteristics between two groups (all P0.05). The PCD-CT group demonstrated significantly lower effective radiation dose [(3.88±0.65) mSv vs. (5.97±1.15)mSv], contrast media volume [(29.25±4.56) ml vs. 60 ml], and injection rate [(2.65±0.42) ml/s vs. 3 ml/s] than the EID-CT group, with reductions of 35%, 51%, and 12%, respectively (all P0.001). For objective image quality, except for the ascending aortic CT attenuation, the CT attenuation, SNR, and CNR of other vessels in the 55 keV PCD-CT group were comparable to those in the EID-CT group. Additionally, the difference in image noise between these two groups was not statistically significant ( P0.05). Concerning subjective image quality, at 55 keV, the PCD-CT group had similar image noise scores and vessel attenuation scores (both P0.05) and better visualization of renal artery branching ( P=0.001) compared to the EID-CT group. Conclusion:In comparison to EID-CT, the use of a 55 keV image in PCD-CT for aortic CTA has demonstrated reductions in radiation dose, contrast media volume, injection flow rate and contrast medium concentration, while maintaining image quality.

Objective:To evaluate the feasibility of head and neck vascular imaging using photon-counting detector computed tomography (PCD-CT) combined with a “quadruple lows” protocol—characterized by low contrast media volume, low iodine concentration, low injection rate, and low radiation dose—and to compare the image quality with that obtained by energy-integrating detector CT (EID-CT).Methods:A total of 105 patients with suspected cerebrovascular disease were prospectively enrolled at the First Affiliated Hospital of Zhengzhou University between April and June 2024. Patients were randomly assigned to three groups ( n=35). Group A underwent conventional head and neck CTA using EID-CT. Group B underwent PCD-CT with a protocol involving ultra-low contrast media volume, low iodine concentration, and low injection rate. Group C underwent PCD-CT with the full “quadruple low” protocol. Objective image quality parameters—including CT attenuation, image noise (standard deviation, SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR)—were measured at the ascending aorta, common carotid artery, internal carotid artery, vertebral artery, basilar artery, posterior cerebral artery, and middle cerebral artery. Two radiologists independently rated subjective image quality using a 5-point Likert scale. Differences among groups were analyzed using one-way ANOVA and the Kruskal-Wallis test. Results:Compared to Group A [contrast volume: (42.78±6.64)ml], contrast agent volume was significantly reduced in Groups B and C[ (26.26±4.45) ml and (26.54±3.83)ml, respectively], demonstrating reductions of 39% and 38% (both P<0.01). The iodine concentration was 320 mg/ml in Groups B and C, lower than 350 mg/ml in Group A (8.5%). The injection rate was also reduced in Groups B and C [(3.39±0.61) and (3.55±0.51)ml/s, respectively] compared to Group A [(4.28±0.66) ml/s], with reductions of 21% and 17% (both P<0.01). The effective dose (ED) was similar between Groups A and B [(1.40±0.15) vs. (1.40±0.19)mSv, P>0.05], while Group C demonstrated a significantly lower ED [(0.99±0.09) mSv], with a reduction of 30% compared to Group A and 29% compared to Group B (both P<0.01).In terms of objective image quality, significant differences in image noise (SD) were observed among the three groups at the vertebral artery, internal carotid artery, posterior cerebral artery, and middle cerebral artery (all P<0.05). Groups B and C showed significantly lower SD compared to Group A ( P<0.05), with no significant difference between B and C ( P>0.05). SNR was significantly higher in Groups B and C than in Group A at multiple vascular segments (all P<0.05). CNR differed only at the internal carotid artery, where Groups B and C demonstrated superior performance compared to Group A ( P<0.05).Subjective image quality scores showed no significant difference between Groups A and C ( P>0.05), while Group B had significantly higher scores than both A and C ( P<0.05). All images were deemed diagnostically acceptable. Conclusion:Compared with conventional EID-CT, PCD-CT combined with a “quadruple lows” protocol enables substantial reductions in contrast media and radiation dose while further improving image quality in head and neck CTA.

Objective To explore the influence of the coupling and coordination of DRG and clinical pathways on Antibiotics Use Density.Methods The data of 7 clinical departments in a sample hospital from 2021 to 2022 were selected,the data were collated through descriptive statistics,and the coupling coordination degree model was used to measure the coordinated development level of DRG and clinical pathways.Taking the per-average drug cost and the average hospital stay of patients as the threshold variables,the threshold regression model was used to calculate the threshold value of Antibiotics Use Density at the level of coordinated development.Results There was a single threshold(F=21.98,P<0.05)of 6334.69 and a double threshold(F=160.53,15.99,P<0.1)of 6.74 and 8.20 for the average length of stay of patients.The statistical values between the level of coordinated development and Antibiotics Use Density in the two threshold variables were positive.Conclusion There is a nonlinear relationship between the level of coordinated development of DRG and clinical pathway with Antibiotics Use Density,and there is a positive promotion effect,and there are differences in the impact size in different threshold variable intervals.Medical institutions should pay attention to the nonlinear relationship,make good use of hospital informatization,do a good job in reasonable monitoring,and reasonably promote the management of antimicrobial drugs.

The design of the salary structure in public hospitals is an important part of the salary system reform.The salary structure is in a dynamic evolutionary process as the reform deepens,and at this stage,it is gradually shifting towards a development direction that emphasizes incentive-based salary performance.Continuous optimization of the salary structure is key to exploring the accurate measurement of doctors' value and the sustainable development of the hospital's public welfare attributes.Through literature research and comparative analysis,it presented a tabular presentation of the four incentive compensation models formed so far in the dynamic optimization of China's public hospitals after the new healthcare reform,and to conduct a comparative analysis of their respective advantages and disadvantages,in order to provide reference and information for the continuous optimization of the pay structure of public hospitals.

Objective To observe the value of deep learning image reconstruction(DLIR)algorithm in brain CT perfusion(CTP)using a protocol of 70 kVp and 40 ml contrast agent dose.Methods Totally 105 patients with suspected acute ischemic stroke(AIS)were prospectively enrolled and randomly divided into 3 groups,who underwent standard dose CTP scanning with 80 kVp and 150 mA combined with reconstruction as adaptive statistic iterative reconstruction V(ASIR-V)at 50％level(CN group,n=35),low dose(LD)scanning with 70 kVp and 100 mA combined with DLIR reconstruction at the highest level(DLIR-H)(LD group,n=35),or ultra-low dose(ULD)scanning with 70 kVp and 70 mA combined with DLIR-H reconstruction(ULD group,n=35).Radiation doses were compared among 3 groups.CT values and standard deviations(SDCT)of ROI of gray matter and white matter in the frontal,parietal and temporal lobes were measured.Signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)between gray and white matter were calculated and compared among groups.Then pseudo-color images of cerebral blood volume(CBV),cerebral blood flow(CBF),mean transit time(MTT)and time to maximum of the tissue residual function(Tmax)were generated.The imaging quality of CTP pseudo-color images was evaluated,and the compatibility of the subjective scores within every kind of CTP pseudo-color images were assessed using Kappa test.Quantitative perfusion parameters were measured and compared among groups.Results Compared with CN group,both LD and ULD groups demonstrated significantly reduced volume CT dose index(CTDIvol),dose-length product(DLP)and effective dose(ED)(all adjusted P＜0.05).In ULD group,SDCT of white matter in frontal,parietal and temporal lobes were higher than those in CN group,and SDCT of white matter in parietal lobe was also higher than that in LD group(all adjusted P＜0.05).No significant difference of SDCT of gray matter was observed among groups(all P＞0.05).SNR of white matter in parietal and temporal lobes in both LD and ULD groups were lower than those in CN group(all P＜0.05),while no significant difference of SNR of white matter in frontal lobe,nor of gray matter in frontal,parietal and temporal lobes was found among groups(all P＞0.05).CNR of gray and white matter in the frontal,parietal and temporal lobes were not significantly different among groups(all P＞0.05).High consistency of inter-observer subjective scores of CBV maps,CBF maps and Tmax maps(Kappa of 0.623,0.644 and 0.638,respectively)were noticed,which of MTT maps had moderate consistency(Kappa=0.560).No significant difference of intra-obsever subjective scores of CTP pseudo-color images was found among groups(all P＞0.05).CBV,CBF,MTT and Tmax values of gray and white matter in frontal,parietal and temporal lobes were not significantly different among groups(all P＞0.05).Conclusion DLIR algorithm applicated in low radiation dose and reduced contrast agent dosage might ensure imaging quality.