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2024 Vol. 31, No. 2
Published: 2024-04-25
 
 
81 Prediction model of PICC vein thrombosis in elderly cancer patients based on decision tree algorithm
Du Mengdi, Ding Juanying
DOI: 10.3969/j.issn.1006-5253.2024.02.001
Objective To establish a decision tree model of deep vein thrombosis associated with peripheral inserted central catheters (PICC) in elderly patients.Methods A total of 400 elderly cancer patients receiving PICC in a hospital from March 2017 to May 2021 were selected as the model group, and 120 elderly cancer patients receiving PICC in a hospital from June 2021 to February 2023 were selected as the validation group. Logistic regression was used to screen the risk factors of PICC-related deep vein thrombosis in elderly cancer patients. SPSS Modeler software was used to build a decision tree model of PICC-related deep vein thrombosis in elderly cancer patients, and the prediction efficiency of the decision tree model was analyzed.Results Among 400 elderly tumor patients, 74 cases developed PICC-associated DVT, and the incidence of DVT was 18.50%. Logistic regression analysis showed that body mass index, puncture times, catheter retention time, diabetes and chronic renal insufficiency were the risk factors for PICC-related deep vein thrombosis in elderly tumor patients (P<0.05). The classification nodes of the decision tree model of PICC-related deep vein thrombosis in elderly tumor patients were diabetes, catheter retention time, chronic renal insufficiency, puncture times and body mass index, among which diabetes was the most important predictor. The AUC of the decision tree model (AUC=0.749, 95%CI: 0.688~0.811) was higher than that of the logistic regression model (AUC=0.701, 95%CI: 0.633~0.770) (P<0.05), and that of the verification group was 0.812 (95%CI: 0.783~0.841).Conclusion Body mass index, puncture times, catheter retention time, diabetes and chronic renal insufficiency are risk factors for PICC-related DVT in elderly cancer patients. The decision tree model of PICC-related DVT in elderly cancer patients established in this study has high accuracy.
2024 Vol. 31 (2): 81-86 [Abstract] ( 26 ) HTML (1 KB)  PDF (4259 KB)  ( 133 )
87 Trend change and prediction of nosocomial infection prevalence in China based on grey GM (1,1) model
Jiang Xuejin， Li Yang， Ding Honghong，Lü Min，Sun Jihua
DOI: 10.3969/j.issn.1006-5253.2024.02.002
Objective To understand the trend of nosocomial infection prevalence in China, and to predict the nosocomial infection prevalence in hospitals of different scales in China with the gray GM (1,1) model, so as to provide data support and new ideas for prevention and control of nosocomial infection.Methods Descriptive epidemiological method was used to analyze the trend of nosocomial infection prevalence in China. The grey GM (1,1) model was constructed with data on nosocomial infection prevalence in China from 2008 to 2016, and the model was validated with data from 2018 to 2020. The constructed grey GM (1,1) model was used to predict the prevalence of nosocomial infection in China from 2022 to 2024.Results The prevalence of nosocomial infection in China showed a downward trend. The prevalence of nosocomial infection increased with the increase of hospital scales. The grey GM (1,1) model for the prevalence of nosocomial infection has good accuracy and high fitting effect. In 2024, the prevalence of nosocomial infection in China, in hospitals with<300 beds, in hospitals with 300-599 beds, in hospitals with 600-899 beds, and in hospitals with≥ 900 beds can be reduced to 1.00%, 0.49%, 0.90%, 1.13%, and 2.05%, respectively.Conclusion The prevention and control effect of nosocomial infection in China is obvious, and the grey GM (1,1) model has a good prediction effect on the prevalence of nosocomial infection in China.
2024 Vol. 31 (2): 87-89 [Abstract] ( 33 ) HTML (1 KB)  PDF (2692 KB)  ( 72 )
90 Retrospective cohort study on risk of acute coronary events in patients with type 2 diabetes mellitus
Fan Lihui, Jiang Xuexia, Zheng Yuhang, Ye Zhenmiao, Luo Yongyuan
DOI: 10.3969/j.issn.1006-5253.2024.02.003
Objective To analyze the risk of acute coronary events in patients with type 2 diabetes mellitus, and to provide basis for the management of patients.Methods Based on the data of Wenzhou chronic disease collaborative management system, a retrospective cohort study was conducted. A total of 277 205 newly diagnosed type 2 diabetes mellitus patients from 2010 to 2020 were included in the analysis. The incidence and death information were obtained by matching the ID number with the data of acute coronary events and deaths. COX regression model was used to analyze the relationship between the complications of diabetes patients at the time of diagnosis and the risk of acute coronary events.Results During the followup period, acute- coronary events occurred in 3 241 cases, and the incidence rate of coronary heart disease was 1 169.17/100 000; 1 083 diabetes patients died from coronary heart disease, with a fatality rate of 390.69/100 000. Taking the patients diagnosed without complications as the reference, the HR of acute coronary disease in patients with one complication and two or more was 1.382 (95%CI:1.266-1.508) and 1.661 (95%CI:1.221-2.259) respectively.Conclusion Type 2 diabetes patients have a high risk of morbidity and mortality from acute coronary events , so intervention should be strengthened in patient management to actively prevent and treat complications.
2024 Vol. 31 (2): 90-94 [Abstract] ( 26 ) HTML (1 KB)  PDF (3336 KB)  ( 114 )
95 Risk prediction model for early diabetic kidney disease constructed based on BP neural network algorithm
Du Yanhua， Zhu Hongting
DOI: 10.3969/j.issn.1006-5253.2024.02.004
Objective To investigate the risk factors of early diabetic nephropathy and construct a risk prediction model based on BP neural network algorithm. Methods A total of 1 048 diabetic patients admitted to Yongkang Hospital of Traditional Chinese Medicine from January 2020 to December 2022 were retrospectively analyzed, including 115 diabetic nephropathy patients (10.97%), and were divided into the DKD group (115 diabetic nephropathy patients) and the DM group (933 diabetic patients). The relevant data of patients were collected and matched according to 1∶1 nearest proximity method after the confounding factors were excluded by propensity score matching (PSM). The prediction model was built based on the correlation factors by using the statistically significant indicators in the single factor analysis and BP neural network algorithm. Mean absolute error (MAE) was used to analyze the model efficacy, the predictive value of the risk prediction model was evaluated by receiver operating characteristic curve (ROC), and external validation was performed. The model consistency was evaluated by calibration curve.Results The confounding factors were gender, hypertension, fasting blood glucose and uric acid. After the modeling set was 1∶1 and PSM was performed by the nearest method, the confounding factors were excluded: 95 cases in DKD group and 95 cases in DM group. Univariate results indicated that there were significant differences in age, type 2 diabetes, total cholesterol, urinary protein excretion rate, diabetes course, and cystatin C(CysC) between groups (P<0.05). The prediction accuracy was BP neural network algorithm, decision tree, support vector machine and logistic regression in the descending order. The results of BP neural network showed that the top 4 factors affecting the occurrence of early diabetic nephropathy were proteinuria excretion rate, age, diabetes course and cystatin C(CysC) in order. The AUC  of the prediction model was 0.959 (95%CI: 0.917-1.000), the Yoden index was 0.867, and the corresponding sensitivity and specificity were 0.867 and 1.000, respectively. The external validation-AUC was 0.958 (95%CI: 0.922-0.995), and its sensitivity and specificity were 0.804 and 1.000, respectively. The calibration curve in the calibration diagram was close to the standard curve.Conclusion The BP neural network algorithm model based on machine learning, which takes age, disease course, urinary protein excretion rate, TC, CysC and type 2 diabetes as predictive features, has good predictive value for early diabetic nephropathy, and can be clinically applied to the management and identification of high-risk population.
2024 Vol. 31 (2): 95-101 [Abstract] ( 32 ) HTML (1 KB)  PDF (4839 KB)  ( 203 )
102 Characteristics of death cases in a tertiary general hospital in Hangzhou from 2015 to 2022
Dai Jingyuan，Xiao Yun，Shen Qionglian，Zhou Jing， Zhang Zhe
DOI: 10.3969/j.issn.1006-5253.2024.02.005
Objective To analyze the death cases in a tertiary general hospital from 2015 to 2022, and to provide a basis for rational allocation of medical resources and improvement of medical service quality.Methods Death data of a tertiary hospital in Hangzhou from January 1, 2015 to December 31, 2022 were extracted by using the population information registration system of the Chinese Center for Disease Control and Prevention (CDC). Minitab 18 software was used to draw Pareto charts to analyze the main factors and order of the patients′ death cause disease spectrum. Excel 2016 and SPSS 21.0 software were used for data sorting and analysis, and statistical description and chi-square test were for retrospective analysis.Results A total of  1 938-deaths were reported in the hospital from 2015 to 2022, including 287 inpatients and 1 651 non-inpatients. The male to female ratio was 2.22∶1, and there were statistically significant differences between genders in age, marital status, educational level, and distribution of death cases (P<0.05). According to the Pareto plot, the causes of death were circulatory system diseases (633, 32.66%), injury-poisoning (547, 28.22%), tumors (286, 14.76%), and respiratory system diseases (203, 10.47%), with a cumulative composition ratio of 86.12%. The main causes of death in patients were sudden cardiac death, acute-myocardial infarction, cerebral hemorrhage, severe traumatic brain injury, multiple injuries, thoracic injury, lung cancer, liver cancer, and pulmonary infection.Conclusion The hospital should improve the level of prehospital and in-hospital first aid, strengthen the treatment of circulatory system diseases, injury-poisoning, tumors, and respiratory system diseases, and allocate medical resources reasonably.
2024 Vol. 31 (2): 102-107 [Abstract] ( 36 ) HTML (1 KB)  PDF (3751 KB)  ( 51 )
108 ]Statistical analysis of inpatients with malignant tumors in a tertiary hospital from 2017 to 2021
Ye Lixian
DOI: 10.3969/j.issn.1006-5253.2024.02.006
Objective To study the medical records of patients with malignant tumors in a tertiary hospital, to grasp the composition and change trend of the main malignant tumor diseases, and to provide scientific reference for the prevention and treatment of malignant tumors in the local area.Methods Data of the first page of medical records of malignant tumor patients in a hospital from 2017 to 2021 were collected and retrospectively analyzed in terms of disease composition, sequence structure, age and gender distribution of patients with malignant tumors in the hospital.Results Totally 19 198 patients with malignant tumor were admitted, and the gender ratio was 1.3∶1. The proportion of hospitalized patients aged 50-69 was the highest (50.66%), and the mortality rate of malignant tumor was 4.96%. The top 5 malignant tumors were lung cancer, liver cancer, nasopharynx cancer, breast cancer, and colon cancer. The average medical cost of malignant tumor patients was 23 711.55 yuan, the average medicine cost was 4 851.93 yuan and the average hospitalization days were 13.03 days.Conclusion It should be aimed at highrisk groups and common types of malignant tumors. It is necessary to formulate comprehensive prevention and treatment measures for local population with malignant tumors over 50 years old, carry out cancer screening for early diagnosis and treatment, and strengthen control over medical expenses.
2024 Vol. 31 (2): 108-112 [Abstract] ( 25 ) HTML (1 KB)  PDF (3870 KB)  ( 94 )
113 New gray correlation and structural variation degree analysis of average hospitalization costs of patients with hepatitis B cirrhosis at decompensated stage
Deng Shumin，Shi Wenqi，Li Lili，Chen Xiaoxia，Liu Zifeng，Chen Jingjing
DOI: 10.3969/j.issn.1006-5253.2024.02.007
Objective To understand the average hospitalization cost structure of patients with hepatitis B cirrhosis at decompensated stage from January, 2018 to August, 2023, so as to provide a reference for reducing the medical burden of patients, optimizing the hospitalization cost structure and controlling the growth of medical costs.Methods The medical costs of 7 459  patients with hepatitis B cirrhosis at decompensated stage in a tertiary hospital in Guangdong Province from a January, 2018 to August, 2023 were selected. Grey correlation and structural variation degree analysis method were used to analyze the correlation degree, variation degree and contribution rate of each item cost of patients.Results The average hospitalization cost of patients with decompensated post-hepatitis B cirrhosis increased year by year from 2018 to 2021, with an average annual growth of 7.01%, and then decreased in 2022 and 2023, with a decline rate of 7.64% and 8.04%, respectively. The top four costs were the drug cost, the diagnosis cost, the consumables cost, and the treatment cost. The drug cost (0.915), the diagnosis cost (0.909) and the consumables cost (0.770) had the highest correlation coefficient. The top three items with the highest structural contribution rate were drug cost (43.27%), diagnostic cost (19.12%), and consumables cost (17.91%), and the cumulative structural change contribution rate of the three was over 80%.Conclusion The drug cost, diagnostic cost and consumables cost were the main factors affecting hospitalization costs, and were the key points to reduce the hospitalization cost of patients. It is necessary to further adjust and optimize the structure of hospitalization costs, reflect the labor and technology value of medical staff, and reduce the burden of patients′ medical expenses.
2024 Vol. 31 (2): 113-117 [Abstract] ( 26 ) HTML (1 KB)  PDF (3247 KB)  ( 34 )
118 Construction of hospital breakeven level regression prediction model based on grey system
Lu Yunfei
DOI: 10.3969/j.issn.1006-5253.2024.02.008
Objective To investigate the influencing factors affecting the level of hospital revenue and expenditure balance, and construct a regression prediction model under the payment of diagnosis related groups (DRGs) point method in Ningbo City.Methods The income and expenditure balance level of a Hospital of Ningbo city from January to December 2021 and 20 related factors indicators were collected, typical indicators were selected by similarity cluster analysis, and the weights of the typical indicators were calculated by using gray correlation analysis, so as to construct a gray system multivariate regression prediction model.Results The key indicators influencing the balance of revenue and expenditure included two positive indicators which were the proportion of lowmagnification cases and total weight, and 3 negative indicators which were the proportion of normal cases, cost consumption index, and proportion of DRG settlement cases. The correlation and weight of each indicator were in the following descending order: proportion of low-magnification cases, total weight, proportion of DRG settlement cases, proportion of normal cases, and cost consumption index. By applying these five indicators, we constructed a grey system multivariate regression prediction model, which was proven to meet the criteria for effectiveness and accuracy testing. This model could accurately fit and predict the level of income and expenditure balance in hospitals.Conclusion The multi-factor gray system regression prediction model is beneficial for hospital management to accurately formulate strategic goals and decisions, improve the level of hospital revenue and expenditure balance, and ensure the long-term stable development of hospitals.
2024 Vol. 31 (2): 118-123 [Abstract] ( 30 ) HTML (1 KB)  PDF (3912 KB)  ( 54 )
124 Practical impact of DRGs categorization under E-CHAID decision model on the hospitalization costs of myelodysplastic syndromes
Hua Shibin, Ren Jinwen, Zhu Jiaying
DOI: 10.3969/j.issn.1006-5253.2024.02.009
Objective To analyze the practical effect of the diagnosisrelated groups (DRGs) of myelodysplastic syndromes (MDS) on hospitalization costs under the ECHAID decision model.Methods Data of patients with myelodysplastic syndrome as the first discharge diagnosis were retrospectively collected in the first page of medical records in the Hospital Information System (HIS) records from a tertiary hospital in Zhejiang Province from February 2021 to February 2023. All indicators of the medical record home page were tested via multiple linear regression tests between groups, Mann-Whitney-U- tests, and KruskalWallis H-tests. With indicators of variance inflation factor (VIF)<10 and  P<0.05 in the univariate screen as the independent variable, and hospitalization costs as the dependent variable, the DRGs grouping decision tree model was established by using the E-CHAID exhaustive algorithm. The maximum cost was determined as the "median hospitalization cost+1.5 times the standard deviation" for each DRGs case combination, and the ratio of maximum cost for each DRGs grouping to the maximum cost for all cases was calculated to analyze the distribution characteristics of hospitalization costs.Results A total of 2 223 MDS patients were included. The three variables of whether monoclonal antibodies were used, whether the patients were admitted to the ICU, and the number of transfusions were the hierarchical classification variable nodes of the E-CHAID decision tree model. Twelve nodes were established, generating 7 terminal nodes. Variance coefficient -CV-s were 0.40, 0.15, 0.23, 0.21, 0.25, 0.51, and 0.46 respectively, and the Kruskal-Wallis -H- test between the DRGs groupings held statistical significance (H=2816.568, P<0.001). Among the 2 223 patients, 76 (3.42%) exceeded the maximum cost. The total hospitalization cost of patients exceeding the cost ceiling was 662 241.71yuan, accounting for 1.40% of the total DRGs hospitalization cost. The relative weights of DRGs groups 1 to 7 were 1.49, 2.42, 2.14, 1.33, 1.10, 0.47 and 0.24.Conclusion DRGs grouping of myelodysplastic syndromes under the E-CHAID decision model is more heterogeneous and the distribution among groups is reasonable, which can be used for the future development of DRGs in Zhejiang Province. It can provide some basis for the subsequent development of local DRGs medical payment reform for malignant hematological diseases such as myelodysplastic syndromes.
2024 Vol. 31 (2): 124-128 [Abstract] ( 26 ) HTML (1 KB)  PDF (4296 KB)  ( 99 )
129 Cost efficiency of clinical wards in a tertiary hospital based on COST-DEA index method
Zhang Junlong, Guo Jiayi, Zhang Hongyi, He Guobin, Huang Yanhong, Yuan Jianlie
DOI: 10.3969/j.issn.1006-5253.2024.02.010

Objective To measure the cost efficiency, technical efficiency and allocation efficiency of each clinical ward of a tertiary hospital, so as to provide reference for realizing its high-quality development and fine management.Methods CCR, BCC and COST-DEA models in data envelopment method were used to measure the relevant efficiency values of clinical wards in the tertiary hospital.Results In 2019, the average cost efficiency of each clinical ward of the tertiary hospital was 0.675, the average allocation efficiency was 0.782, the average technical efficiency was 0.853, the average pure technical efficiency was 0.902 , and the average scale efficiency was 0.944; 7 (13.73%) clinical wards were in the state of increasing returns to scale, 23 (45.10%) clinical wards were in the state of unchanged returns to scale, and 21 (41.17%) clinical wards were in the state of decreasing returns to scale.Conclusion The cost efficiency of clinical wards in the tertiary hospital is mainly affected by the allocation efficiency, which requires reasonable allocation of medical resources. Most clinical wards need to improve the internal fine management level to increase output.
2024 Vol. 31 (2): 129-133 [Abstract] ( 42 ) HTML (1 KB)  PDF (3443 KB)  ( 89 )
134 Mediation effect analysis of social rhythm of undergraduate nursing students between mobile phone addiction and sleep quality
Chen Xingru, Sun Wenyue, Zhang Xiaofeng, Zhang Jingwen, Zhao Xiaomin
DOI: 10.3969/j.issn.1006-5253.2024.02.011
Objective To understand the current status and association between sleep quality, mobile phone addiction, and social rhythm among undergraduate nursing students, and explore the mediating role of social rhythm between mobile phone addiction and sleep quality of undergraduate nursing students.Methods A survey of 386 undergraduate nursing students from the 2018 to 2021 grades at a medical university was conducted by means of the general information questionnaire, Mobile Phone Addiction Index, the Brief Social Rhythm Scale, and Pittsburgh Sleep Quality Index.Results Undergraduate nursing students had a total score of (27.38±10.67) for social rhythm; a total score of (36.71±15.73) for mobile phone addiction, with a detection rate of 20.2% for mobile phone addiction; and a score of (4.82±2.87) for sleep quality, with a detection rate of 14.2% for sleep disorder. There was a positive correlation between the social rhythm, mobile phone addiction, and sleep quality of undergraduate nursing students (r=0.393, 0.489, 0.460, P<0.001). After controlling the demographic variables, social rhythm was a partial mediator between mobile phone addiction and sleep quality, with a mediation effect value of 0.124, accounting for 22.14% of the total effect.Conclusion  Mobile phone addiction may affect sleep quality not only directly, but also indirectly through the social rhythm. Nursing educators should concentrate on the social rhythm of undergraduate nursing students to improve their sleep quality.
2024 Vol. 31 (2): 134-139 [Abstract] ( 35 ) HTML (1 KB)  PDF (3706 KB)  ( 73 )
140 Screening effect of different obesity indexes on diabetes in middle-aged and elderly people
Zhu Huiyun，Wang Yanan，Chen Xiaoqian，Wang Jiang，Tian Feng
DOI: 10.3969/j.issn.1006-5253.2024.02.012
Objective To explore the screening effect of different obesity indicators on diabetes in middle-aged and elderly people, and determine the optimal cutting point values and optimal indicators of different obesity indicators, so as to provide data support and scientific basis for early screening, prevention and control of diabetes.Methods A total of 12 630 people aged 45-79 years old with physical examination in a hospital were investigated by questionnaire. Receiver operating characteristic curve (ROC) was used to determine the optimal index and the optimal cutting point. Delong test was used to compare the screening effect of different obesity indicators on diabetes, and the logistic regression was used to evaluate the predictive effect of different obesity indicators at different cutting points.Results  (1) The prevalence of diabetes in males was higher than that in females; (2) the area under the receiver operating characteristic curve (AUROC) of waist-to-height ratio (WHtR) index of different genders was the largest, and the AUROC of WC and WHtR was significantly different from that of body mass index (BMI) and waist-to-hip ratio (WHR); (3) at different cutting points, WC and WHtR had higher -OR-values and AUROC values.Conclusion For middleaged and elderly people, WC and WHtR have better screening ability and prediction effect for diabetes than other indicators.
2024 Vol. 31 (2): 140-144 [Abstract] ( 26 ) HTML (1 KB)  PDF (2890 KB)  ( 32 )
145 Study on the influence of economic burden on the demoralization of prostate cancer patients
Jin Zhenzhen, Li Ping, Yu Xiuxiu
DOI: 10.3969/j.issn.1006-5253.2024.02.013
Objective To understand the influence of economic burden on the demoralization of prostate cancer patients, and to provide a theoretical basis for the formulation of intervention measures.Methods A total of 249 patients with prostate cancer who were hospitalized in a hospital from December 2020 to December 2022 were selected as subjects by convenience sampling method. The Comprehensive Scores for Financial Toxicity Based on the PatientReported Outcome Measures, and the Chinese Version of the Demoralization Scale-Ⅱ were used for the questionnaire survey.Results The economic burden score of prostate cancer patients was (27.05±8.14) points, and the demoralization score was (14.93±4.87) points. There were statistically significant differences in demoralization scores among prostate cancer patients with different ages, educational backgrounds, per capita monthly family income, working position, years of diagnosis, clinical stages of cancer and complications (P<0.05). Economic burden score of prostate cancer patients was positively correlated with the total score of demoralization and scores of all dimensions (P<0.01). The clinical staging of tumor, economic burden, educational background and complications of prostate cancer patients were the main influencing factors of patients with demoralization (P<0.05).Conclusion The economic burden of prostate cancer patients is heavy, and the level of demoralization is high. Therefore, appropriate intervention measures should be taken to alleviate the level of demoralization of patients according to the diagnosis years, economic burden, educational background and complications of patients.
2024 Vol. 31 (2): 145-148 [Abstract] ( 32 ) HTML (1 KB)  PDF (2567 KB)  ( 69 )
149 Quality analysis of ICD code for appendicitis in a hospital in 2022
Ma Yingli
DOI: 10.3969/j.issn.1006-5253.2024.02.014
Objective To analyze the coding quality of ICD for appendicitis and provide theoretical basis for the reform of medical insurance payment methods.Methods A coding quality control team consisting of 2 coding personnel with intermediate titles in medical record information technology and 1 attending physician in gastrointestinal surgery was formed to retrieve the medical insurance settlement data of appendicitis patients in the hospital in 2022. The medical records were reviewed and analyzed one by one, and the coding errors were recoded. Excel was used to record error types of appendicitis for statistical analysis.Results The number of appendicitis discharge cases in 2022 was 630, and the number of coding error cases was 154, with a coding error rate of 24.44%. Among them, 87 cases (56.49%) were not corrected according to pathological results, 22.73% were not combined with coding, 18.83% were acute and chronic appendicitis, and 1.95% were not distinguished.Conclusion Medical institutions need to strengthen the supervision of the quality of medical record coding. Coders should strengthen the study of coding theory and related clinical knowledge to improve the quality of coders. Clinicians should standardize the writing of diagnosis and related medical documents to do the basic work for the accuracy of coding.
2024 Vol. 31 (2): 149-152 [Abstract] ( 30 ) HTML (1 KB)  PDF (2538 KB)  ( 40 )
153 Discussion on the ICD-9-CM-3 encoding of proximal gastrectomy with double tract reconstruction
Guo Xusheng, Yang Zhibin, Zhang Xuan
DOI: 10.3969/j.issn.1006-5253.2024.02.015
Dual-tract reconstruction is theoretically an ideal digestive tract reconstruction method for proximal gastrectomy. Because the update of ICD-9-CM-3 dictionary database is stagnant and the current operation and procedur dictionary database in the hospital is insufficient in code expansion, there is some controversy about the encoding of proximal gastrectomy with double tract reconstruction. From the angles of connotation and historical evolution of related operations, the ICD-9-CM-3 coding for the operation was analyzed and discussed.
2024 Vol. 31 (2): 153-155 [Abstract] ( 26 ) HTML (1 KB)  PDF (2750 KB)  ( 29 )
156 Surgical coding and case analysis of implantable cardiac electronic devices
Ye Qian, Wu Lijuan, Chu Wenya
DOI: 10.3969/j.issn.1006-5253.2024.02.016
In recent years, there has been a rapid increase in the clinical use of implantable cardiac electronic devices. These devices consist mainly of electronic components such as pulse generators and electrode leads, encompassing artificial cardiac pacemakers and implantable cardioverter defibrillators. This article focuses on the clinical understanding of cardiac pacing and defibrillation technology, providing an analysis of the operational proce dures. It adheres to the classification principles of ICD-9-CM-3 for organizing and summarizing corresponding codes, offering a valuable reference for coding work. Coding personnel are required to maintain a thorough grasp of the latest clinical technological advancements, adhere to the principles of surgical classification, and diligently review medical records to ensure accurate coding and comprehensive representation of medical information.
2024 Vol. 31 (2): 156-160 [Abstract] ( 27 ) HTML (1 KB)  PDF (3039 KB)  ( 46 )
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