ABSTRACT
Chronic diseases have become an important public health problem for people under 70 years of age worldwide， while also causing a great economic burden. The establishment of clinical prediction models can help to predict the risk of a disease or the prognostic effect of a study subject in advance by means of index testing at the early stage of chronic diseases， and plays an increasingly important role in clinical practice. This study introduces clinical diagnostic prediction models and clinical prognostic prediction models， and reviews clinical data processing， clinical prediction model building， visualization methods and model evaluation from the perspective of the application of clinical prediction models， which contribute to the correct and reasonable use of prediction models in clinical research.
ABSTRACT
Objective:To construct and verify a model of excessive medical behavior clues enrichment, for the technical support for the safe and rational use of medical insurance fund.Methods:A model of excessive medical behavior clues enrichment was constructed by the rank assignment method. The inpatient transaction records of medical insurance for employees and residents in 5 tumor hospitals in Beijing from 2016 to 2019 were obtained to verify the validity of the model. The patients were grouped according to age and gender, and each transaction record was converted into a standardized score V(0-100 scores), all transactions were divided into 22 groups according to V value. The Cochran-Armitage trend test was used to analyze the variation trend of enrichment rate with the increase of V value. Chi-square test was used to compare the chargeback rates of different groups. The correlation between the standardized score V and the amount of chargeback was tested by Pearson.Results:There were 872 599 and 86 356 hospitalization transactions for employee and resident medical insurance patients, with included 1 164 and 103 chargeback records respectively. The average score and median of V-value of employee and resident medical insurance transactions were scores of 49 and 50 respectively.When V>0, the enrichment rates of the employee and resident medical insurance were on the rise with the increasing of V( Z=23.86, P<0.001; Z=11.02, P<0.001), the refusal rates among different groups was significant different( χ2=1 307.16, P<0.001)and the correlation between V value and the chargeback amount was statistically significant( r=0.29, P<0.001; r=0.30, P=0.003). Conclusions:This study established a clue enrichment model of excessive medical behavior based on the rank assignment method. By analyzing a large number of medical insurance transaction records, the model can focus on the medical insurance transaction with suspected excessive medical treatment behavior, and has a certain guiding role in the management of medical insurance fund.
ABSTRACT
Constructing a scientific, standardized and reasonable dynamic adjustment model of medical service price has important reference value for the dynamic adjustment of medical service price in public hospitals. In view of the current situation at home and abroad, the authors analyzed the influencing factors of such adjustment, and constructed a dynamic adjustment model of medical service price, referring on the resource-based relative value scale theory. This model could calculate the intrinsic price of individual medical services, taking into full account the basic human resource consumption and time consumption, as well as the technical difficulty and risk degree of such services. On such basis, the economic development and price level of individual regions were integrated into the model to calculate the extrinsic price of these services. Taking the debridement(suture) service of a hospital as an example, this model was used for empirical research. It was estimated that the extrinsic price of a debridement(suture)(small) service was 54.82 yuan, that of a debridement(suture)(medium) service was 104.34 yuan, and that of a debridement(suture)(large) was 142.93 yuan. The price gap between the actual price and these estimated prices was 10.18 yuan, -26.34 yuan and -51.93 yuan respectively. This research proved that the model could be helpful to sort out the price ratio relationship and better reflect the technical labor value of medical workers.