Hospitalization cost mining method and device

Abstract

The invention discloses a hospitalization cost mining method and device. The method comprises the steps that original hospitalization cost data of a disease is pre-processed to acquire sample data; the sample data is partitioned into equal-number sample sections with a preset number according to a preset cluster number and hospitalization all-in cost, and the hospitalization cost divisor average value of the equal-number sample sections is adopted as an initial cluster core; the equal-number sample sections are clustered according to the proximity clustering rule, and the cluster core is recalculated; whether the recalculated cluster core meets the convergence conditions or not is judged, if yes, the next step is carried out, and if not, the initial cluster core is updated; the all-in cost in the sample sections is calculated, and cost divisors with the proportion larger than a preset value in the sample section with the maximum all-in cost is inquired. Based on the K-means clustering analysis method, the key factors influencing hospitalization all-in cost are mined from the mass hospitalization cost data, and a hospital can reasonably price the hospitalization cost.

Description

technical field [0001] The invention relates to the technical field of data mining, in particular to a medical expense mining method and device. Background technique [0002] In recent years, the phenomenon of "difficult to see a doctor and expensive to see a doctor" has become increasingly serious, and high medical expenses have become a hot spot of concern to the society and the public. In order to understand the influencing factors of medical expenses, effectively reduce medical expenses, and reduce medical burden, many scholars have carried out in-depth research and discussion on the influencing factors of medical expenses by using various data mining methods. The composition of medical expenses for diseases mainly includes drug expenses, diagnosis and treatment expenses, hospitalization expenses, examination expenses, operation expenses, laboratory examination expenses and other expenses. The application of data mining technology in the analysis of patient cost composi...

AI Technical Summary

Problems solved by technology

[0003] At present, there are various research methods for mining medical expenses at home and abroad. However, due to the unfair geographical distribution of medical and health resources, or related to local living income levels, or affected by local medical policies, there is currently no specific and unified measurement reference standard. Most of the research is still at the level of mathematical statistical analysis in the general sense, and no in-depth research has been done

Images