| Background: Entering the 21 st century,the digital wave has swept the world,and the impact of data on management decision-making,industrial upgrading,and sustained and stable economic growth is increasing day by day.Industrial digitization and digital industrialization have become an inevitable direction for economic and social transformation.In the context of the national strategy of vigorously developing the digital economy and advocating the empowerment of the real economy with data elements,data as a key production factor is of great significance in accelerating the deep integration of the digital economy and the real economy.The "14th Five Year Plan for the Development of the Digital Economy" proposes to fully unleash the value of data elements and activate their potential,focusing on the realization of the value of data elements.The ultimate goal of realizing the value of data elements is to fall into the application scenarios of various industries,and empower the development of thousands of industries through full integration with various industries.Currently,countries around the world are facing a series of problems such as aging population,increasing number of chronic disease patients,and mismatched supply and demand of medical service resources."Difficulty and high cost of medical treatment" has become a universal phenomenon worldwide.With the continuous promotion of the national decision of "Healthy China 2030",the combination of data elements and traditional medical service industry will inevitably promote the transformation of medical service behavior and mode.It will play a huge role in optimizing hospital diagnosis and treatment processes,improving the quality of hospital medical services,optimizing the allocation of hospital medical service resources,and reducing hospital medical service costs,Becoming one of the effective ways to alleviate the problem of "difficult and expensive medical treatment".This study takes this as the starting point.Against the backdrop of the rapid growth of the digital economy and the widespread application of big data and information technology,starting from the perspective of the data element value chain and guided by multidisciplinary theory,it explores the allocation mode of hospital medical service resources from the perspective of the data element value chain,providing ideas for the transformation of resource management in the medical service industry,and achieving scientific management of modern hospitals to better meet the needs of patients,Provide theoretical and practical support for cultivating innovative digital management models for the medical service industry.Objectives:(1)By sorting out the value realization path of data elements,analyzing the process of data elements empowering the rapid and high-quality development of the real economy,and combining equilibrium theory,lean thinking,and production scheduling theory,we construct a hospital medical service resource allocation model from the perspective of data element value chain,explore the value realization problem of data elements in hospital medical service resource allocation,and fully explore the value of data elements,Guide the rational and optimized allocation of medical service resources in hospitals,provide ideas for the transformation of resource management in the medical service industry,and promote innovation in the allocation mode of medical service resources.(2)Verify the completeness,applicability,and feasibility of the model through empirical verification.Further clarify the value realization of data elements in the field of medical service resource allocation,and enhance the practical application level of data element value creation in relevant application scenarios.Methods: This study consists of two parts.The first part is theoretical research,based on a review of the current research status of data elements,value chain theory,medical service resource allocation and allocation models.By defining relevant concepts such as "data elements","medical service resources",and "medical service resource allocation",literature analysis and pattern construction methods are used.Guided by data element value chain theory,equilibrium theory,lean thinking,and production scheduling theory,Construct a hospital medical service resource allocation model from the perspective of data element value chain,sort out the model construction framework,analyze the composition modules and relationships between modules,explain the operation process and mechanism of the model,and propose specific application scenarios of the model.The second part is empirical research,which uses mathematical modeling and field research methods to conduct empirical research on the theoretical model constructed based on the operation process of the model,using the Obstetrics and Hospitals Department of J Hospital as the application scenario.Firstly,guided by patient needs,analyze the influencing factors of obstetric patients’ medical service needs,and identify and classify patient needs based on significant factors.On the basis of analyzing the influencing factors of demand,predict the medical service demand of obstetric patients in a certain period of time in the future,and obtain the demand volume,demand trend,and pattern of patients’ medical service demand.Furthermore,based on the analysis of demand influencing factors and the results of demand forecasting,the load management of medical service resources is carried out to match the hospital’s resource supply capacity with patient demand,achieve reasonable allocation of hospital obstetric inpatient resources,and verify the process of reasonable allocation of hospital medical service resources in the model.Secondly,conduct on-site research on the operation of the obstetric inpatient department of J Hospital,formulate optimization configuration goals based on patient needs,and re plan and mathematically model the obstetric ward.Based on the modeling results,lean management of obstetric wards is carried out to optimize the configuration of hospital obstetric wards,improve the utilization rate of obstetric wards while meeting patient needs,and validate the process of optimizing the allocation of hospital medical service resources in the model.Results: Part 1: Research on constructing a hospital medical service resource allocation model from the perspective of data element value chain.This model includes two basic operational processes: rational allocation and optimization of hospital medical service resources.It is composed of three modules: data collection module,data processing and analysis module,and data application module.The three modules have the characteristics of integrity,order,and correlation.Operate the model based on the value realization and value appreciation mechanism of data elements,and ultimately achieve the value creation process of empowering the medical service industry with data elements.Based on the gradual introduction of national "two child" and "three child" policies and the need to accelerate the implementation of various supporting measures for childbirth,this paper takes the obstetrics and inpatients department of hospitals as the application scenario and empirically verifies the theoretical model based on its operation process.Part 2:(1)Analysis of factors influencing the demand for medical services for obstetric patients.Taking the obstetric inpatient department as the application scenario,guided by the needs of obstetric patients for hospitalization diagnosis and treatment,and based on the flow of obstetric inpatients as the basis for reflecting the needs of obstetric patients for hospitalization diagnosis and treatment,data such as historical flow,temperature,and humidity of obstetric inpatients at J Hospital were collected.Poisson regression model was used to analyze the significant factors that affect the needs of obstetric patients for hospitalization diagnosis and treatment,including labor,holidays,enrollment,and temperature.Comprehensively analyze the impact of the above influencing factors on the diagnosis and treatment needs of obstetric inpatients,and based on this,achieve early identification and demand classification of obstetric inpatient diagnosis and treatment needs,in order to better allocate corresponding medical service resources for the hospital.(2)Prediction of medical service demand for obstetric patients and rational allocation of obstetric inpatient resources.Using the obstetric inpatient department as an application scenario,guided by the needs of obstetric inpatient diagnosis and treatment,and based on the flow of obstetric inpatients as a reflection of obstetric inpatient diagnosis and treatment needs,historical flow data of obstetric inpatients in J Hospital is collected.The Decompose function in R software is applied to decompose the time series data,and the Holt Winters model is used to predict the monthly flow of obstetric inpatients in the next year.The applications include XGBoost,SVM Seven models,including RF and NNAR,predict the daily flow of obstetric inpatients over the next 14 days.Based on the analysis of demand influencing factors,propose a reasonable allocation strategy for hospital obstetric inpatient resources,manage the load of medical service resources in the hospital obstetric inpatient department,and combine the national strategic deployment of DRG payment for medical insurance.Propose a hospital medical insurance fund allocation strategy based on patient flow prediction and weight.(3)Optimize the configuration of obstetric wards in hospitals.Using the obstetric inpatient department as an application scenario,the obstetric ward can be divided into three types of wards from a spatial perspective: observation ward,cesarean section ward,and natural delivery ward.Combining constraints for mathematical modeling,the obstetric ward planning problem was solved using the CPLEX solver.After the obstetric ward planning,the inpatient capacity of obstetrics increased by about 19-25% compared to before the planning.Through GLM regression model analysis,it was found that the positive correlation factors affecting obstetric patient capacity were mainly the number of accommodations in various types of wards,while the negative correlation factors were mainly hospitalization days and cesarean section ratio.From the perspective of positive correlation factors,improve the capacity of hospitalized obstetric patients in hospitals,and minimize its impact on patient capacity from the perspective of negative correlation factors.Propose strategies for optimizing the configuration of obstetric wards in hospitals,implement lean management of obstetric wards,shorten patient waiting time before admission,and improve the comfort and convenience of obstetric patients after hospitalization.Conclusion: This study constructs a hospital medical service resource allocation model from the perspective of data element value chain,which has high completeness,clarity,feasibility,and practicality.The deep integration of data elements with traditional production factors in the medical service industry will drive profound changes in the medical treatment industry,fully explore and use the value of data,and explore the value realization mode of data elements in hospital medical service resource allocation,Promote lean hospital management and precise allocation of hospital medical service resources,forming a complete research framework that connects theory with practice. |
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