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Prediction of total hospital expenses of patients undergoing breast cancer surgery in Shanghai, China by comparing three models.

ABSTRACT: BACKGROUND:Breast cancer imposes a considerable burden on both the health care system and society, and becomes increasingly severe among women in China. To reduce the economic burden of this disease is crucial for patients undergoing the breast cancer surgery, hospital managers, and medical insurance providers. However, few studies have evidenced the prediction of the total hospital expenses (THE) for breast cancer surgery. The aim of the study is to predict THE for breast cancer surgery and identify the main influencing factors. METHODS:Data were retrieved from the first page of medical records of 3699 patients undergoing breast cancer surgery in one tertiary hospital from 2017 to 2018. Multiple liner regression (MLR), artificial neural networks (ANNs), and classification and regression tree (CART) were constructed and compared. RESULTS:The dataset from 3699 patients were randomly divided into training and test sets at a 70:30 ratio (2599 and 1100 records, respectively). The average total hospital expenses were 12520.54 ± 7844.88 ¥ (US$ 1929.20 ± 1208.11). MLR results revealed six factors to be significantly associated with THE: age, LOS, type of disease, having medical insurance, minimally invasive surgery, and receiving general anesthesia. After comparing three models, ANNs was the best model to predict THEs in patients undergoing breast cancer surgery, and its strong predictive performance was also validated. CONCLUSIONS:To reduce the THEs, more attention should be paid to related factors of LOS, major and minimally invasive surgeries, and general anesthesia for these patient groups undergoing breast cancer surgery. This may reduce the information asymmetry between doctors and patients and provide more reliable cost, practical inpatient medical consumption standards and reimbursement standards reference for patients, hospital managers, and medical insurance providers ,respectively.

SUBMITTER: Chen M

PROVIDER: S-EPMC8667393 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo determine the predictive factors of postoperative hospital stay and total hospital medical cost among patients who underwent total laryngectomy.MethodsA total of 213 patients who underwent total laryngectomy in a tertiary referral center for tumor ablation were enrolled retrospectively between January 2009 and May 2018. Statistical analyses including Pearson's chi-squared test were used to determine whether there was a significant difference between each selected clinical factors and outcomes. The outcomes of interest including postoperative length of hospital stay and inpatient total medical cost. Logistic regression analyses were performed to reveal the relationship between clinical factors and postoperative length of hospital stay or total inpatient medical cost.ResultsPreoperative radiotherapy (p = 0.007), method of wound closure (p < 0.001), postoperative serum albumin level (p = 0.025), and postoperative serum hemoglobin level (p = 0.04) were significantly associated with postoperative hospital stay in univariate analysis. Postoperative hypoalbuminemia (odds ratio [OR]: 2.477; 95% confidence interval [CI]: 1.189-5.163; p = 0.015) and previous radiotherapy history (OR 2.194; 95% CI: 1.228-3.917; p = 0.008) are independent predictors of a longer postoperative hospital stay in multiple regression analysis. With respect to total inpatient medical cost, method of wound closure (p < 0.001), preoperative serum albumin level (p = 0.04), postoperative serum albumin level (p < 0.001), and history of liver cirrhosis (p = 0.037) were significantly associated with total inpatient medical cost in univariate analysis. Postoperative hypoalbuminemia (OR: 6.671; 95% CI: 1.927-23.093; p = 0.003) and microvascular free flap reconstruction (OR: 5.011; 95% CI: 1.657-15.156; p = 0.004) were independent predictors of a higher total inpatient medical cost in multiple regression analysis.ConclusionsPostoperative albumin status is a significant factor in predicting prolonged postoperative hospital stay and higher inpatient medical cost among patients who undergo total laryngectomy. In this cohort, the inpatient medical cost was 48% higher and length of stay after surgery was 35% longer among hypoalbuminemia patients.

Project description:BackgroundPrivate hospitals expanded rapidly in China since 2009 following its national health reform encouraging private investment in the hospital sector. Despite long-standing debates over the performance of different types of hospitals, empirical evidence under the context of developing countries remains scant. We investigated the disparities in health care quality and medical expenses among public, private not-for-profit, and private for-profit hospitals.MethodsA total of 64,171 inpatients (51,933 for pneumonia (PNA), 9,022 for heart failure (HF) and 3,216 for acute myocardial infarction (AMI)) who were admitted to 528 secondary hospitals in Sichuan province, China, during the fourth quarters of 2016, 2017, and 2018 were selected for this study. Multilevel logistic regressions and multilevel linear regressions were utilized to assess the relationship between hospital ownership types and in-hospital mortality, as well as medical expenses for PNA, HF, and AMI, after adjusting for relevant hospital and patient characteristics, respectively.ResultsThe private not-for-profit (adjusted OR, 1.69; 95% CI, 1.08, 2.64) and for-profit (adjusted OR, 1.67; 95% CI, 1.06, 2.62) hospitals showed higher in-hospital mortality than the public ones for PNA, but not for AMI and HF. No significant differences were found in medical expenses across hospital ownership types for AMI, but the private not-for-profit was associated with 9% higher medical expenses for treating HF, while private not-for-profit and for-profit hospitals were associated with 10% and 11% higher medical expenses for treating PNA than the public hospitals. No differences were found between the private not-for-profit and private for-profit hospitals both in in-hospital mortality and medical expenses across the three conditions.ConclusionThe public hospitals had at least equal or even higher healthcare quality and lower medical expenses than the private ones in China, while private not-for-profit and for-profit hospitals had similar performances in these aspects. Our results added evidences on hospitals' performances among different ownership types under China's context, which has great potential to inform the optimization of healthcare systems implemented among developing countries confronted with similar challenges.

Project description:Total pancreatectomy with islet cell autotransplantation (TPIAT) is a surgical treatment modality used for the management of painful chronic pancreatitis when medical and endoscopic therapies fail. Total pancreatectomy (TP) results in a number of clinical implications. However, the glucose-responsive insulin secretion can be preserved by combining TP with islet cell autotransplant (IAT). Despite the known clinical implications of TPIAT, the systemic molecular effects of TPIAT remains poorly investigated. Therefore, we performed the first hypothesis-generating study of the urinary proteome before and after TPIAT. The RAW- and processed data from the analysis can be found in this repository. Twenty-two chronic pancreatitis patients eligible for TPIAT were prospectively enrolled in the study at the University of Minnesota Medical Center between September 2011 and February 2014. Urine was collected within the week pre-TPIAT and 12-18 months post-TPIAT, resulting in 44 paired samples. The paired experimental design allowed us to subtract interpersonal differences. The unique set of urine samples were prepared for bottom-up label-free quantitative proteomics using the in-house developed ‘MStern’ protocol for the 96-well plate compatible processing of the urine samples. The samples were analyzed by LC-MS/MS and 2477 proteins were identified (FDR<0.01%). Five samples were found to have less than 30% of the cumulated list of proteins (<743 proteins) and so these samples and their respective matching sample were thus removed from the analysis. This resulted in a complete dataset with 17 matched pre- and post-TPIAT sample pairs. The final list of recommended included pairs for future analysis are indicated in the PX_TPIAT_Metadata.csv file. Note that extended clinical information only was available for the included samples. Furthermore, the information is only listed for the pre-TPIAT sample but applies to both the pre- and post-TPIAT participant sample. The data allows for studying the systemic molecular impact of the TPIAT procedure.

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Prediction of total hospital expenses of patients undergoing breast cancer surgery in Shanghai, China by comparing three models.

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