Based on knowledge capital value for disease cost accounting of diagnosis related groups

Background The National Health Commission and the other relevant departments in China have initiated testing of the Diagnosis Related Groups (DRGs) system in 30 pilot locations since 2019. In the process of DRG payment reform, accounting for the costs of diseases has become a highly challenging issue. The traditional method of disease accounting method overlooks the compensation for the knowledge capital value of medical personnel. Objective The primary objective of this study is to analyze the cost accounting scheme of China’s Diagnosis Related Groups (C-DRG), focusing on the value of knowledge capital. Methods The study initially proposes a measurement index system for the value of knowledge-based capital, including the difficulty of disease treatment, labor intensity of disease treatment, risk of disease treatment, and operation/treatment time for diseases. The Analytic Hierarchy Process (AHP) is then utilized to weigh the features of medical workers’ knowledge capital value. First, pairwise comparisons are conducted in this stage to develop a two-pair judgment matrix of the primary indicators. Second, the eigenvectors corresponding to the maximum eigenvalues of the matrix are calculated to generate the weight coefficient of each feature. The consistency test is carried out after this stage. An empirical analysis is conducted by collecting data, including the full costs of treating three types of diseases—hip replacement, acute simple appendicitis, and heart bypass surgery—from one public medical institution. Results The empirical analysis examines whether this DRG costing accounting can address the issue of neglecting the value of medical workers’ knowledge capital. The methods reconfigure the positive incentive mechanism, stimulate the endogenous motivation of the medical service system, foster independent changes in medical behavior, and achieve the goals of reasonable cost control. Conclusion In the cost accounting system of C-DRG, the value of medical workers’ knowledge capital is acknowledged. This acknowledgment not only boosts the enthusiasm and creativity of medical workers in optimizing and standardizing the diagnosis and treatment process but also improves the transparency and authenticity of DRG pricing. This is particularly evident in the optimization and standardization of the diagnosis and treatment processes within medical institutions and in monitoring inadequate medical practices within these institutions.


Introduction
Knowledge capital encompasses both explicit and implicit knowledge owned or controlled by an organization, capable of bringing value to it (1).This concept aligns with intangible assets (knowledge capitals) in traditional accounting practices (2) and aids in discerning disparities between an organization's book value and market value.However, recent research has criticized practitioners and academics for being ensnared by the notion of 'Quantification' , assuming that because some knowledge capital cannot be objectively and fairly measured, it should not be included in the cost element (3).
Furthermore, the measurement and disclosure of knowledge capital in real practice primarily concentrate on the static knowledge capital stock, neglecting the dynamic aspect of knowledge capital in 'action' (4).In this study, we propose a disease cost accounting method based on the value of knowledge capital within the DRG payment system.
Knowledge-based human capital constitutes the fundamental production factor in medical institutions.However, due to the scarcity of knowledge capital and ownership separation of knowledge capital, as well as the high acquisition costs associated with it, the cost accounting method for knowledge capital differs from the traditional costing accounting method (5).In addition, the organizational structure and service process management in medical institutions diverge significantly from those in traditional manufacturing industries (6).Consequently, specialized cost accounting and management models are necessary for medical institutions (7).The cost accounting system based on manufacturing costs is inadequate for the accounting system in medical institutions, as it cannot reflect the intrinsic logic of innovative behaviors of medical workers and the core value of innovative elements in medical institutions (8).
As integrated innovators, medical workers, particularly doctors who work on the frontlines, contribute valuable implicit knowledge accumulated from their long-term service (9).This knowledge enables them to manage uncertainties for patients and provide value-added services for medical institutions.According to Becker's related theories, the time required to accomplish a task comprises two components: the time required to perform the task and the time needed to acquire the knowledge necessary to complete the task (10).Therefore, the time necessary for medical workers to execute the integration and coordination of medical services should encompass two aspects, including the time allocated for delivering basic services and the time dedicated to integrating and coordinating medical services.The former entails providing medical services to patients, such as the time spent on consultation, decision-making, and evaluating decisions around diagnostic and treatment activities.The latter involves accumulating activities essential for effectively innovating medical activities.In reality, the process of acquiring knowledge often requires more time than making and evaluating decisions.
Significant quantities of implicit knowledge demand extended periods for accumulation (11)(12)(13)(14)(15).This implicit knowledge requisite for medical integration activities encompasses disease-specific insights, patient-specific knowledge, medical diagnostic and treatment technologies, including drug treatment methodologies, and insights into the behavioral habits and foundational knowledge of relevant medical team members, essential for effectively navigating uncertainty (14,(16)(17)(18)(19).This part of knowledge necessitates substantial accumulation in the initial education stage; meanwhile, it highly relies on the accumulation of doctors' long-term clinical practice.Furthermore, doctors must consistently attend to patients to effectively apply relevant expertise.In this regard, current costing processes applied in medical institutions struggle to acknowledge the working time that medical workers invest in the abovementioned service, particularly the time required for medical workers to accumulate and complete tasks.The corresponding value of this time is rarely acknowledged (20,21).
Full cost accounting of diseases considers the value of knowledge capital essential for medical workers to carry out medical service projects.The value of medical workers' knowledge capital primarily manifests in the realization pathway, encompassing explicit and tacit knowledge (22)(23)(24).Explicit knowledge capital primarily pertains to the professional qualifications and other attributes of medical personnel, while tacit knowledge primarily pertains to their risk perception and ability to navigate uncertainty in medical service projects (25)(26)(27)(28).Tacit knowledge is mainly evaluated through the difficulty and risk coefficients associated with medical services performed by medical workers for specific diseases (29,30).
The rest of this article is organized as follows: Section 2 examines the evaluation of medical workers' knowledge capital within the DRG cost accounting system.Section 3 provides an empirical analysis illustrating the cost accounting process based on knowledge of capital value.Section 4 applies the discussion to the cost accounting result.Finally, Section 5 offers a conclusion and proposes potential future research avenues.

Methods
The full-cost accounting index system The disease cost index system includes labor costs, drug costs, health material costs, inspection costs, and depreciation and sharing costs (31).The calculation of labor costs is based on the evaluation model of the value of the knowledge capital of medical workers (32), including 4 primary indicators, namely the difficulty of the disease project, the labor intensity of the disease project, the risk degree of the disease project, and the operation time of the disease project, and 11 secondary indicators, which are the difficulty of disease treatment, level of technical commitment, knowledge requirement for operators, the requirement for operator's decision -making ability, levels of physical exertion per unit of time, ability, levels of physical exertion per unit of time, levels of concentration per unit time, risk hazards for patients in treatment, occupational exposure of medical workers, consultation time (including surgery time), time for nursing and time for examining.These indicators are summarized and shown in Table 1.

Determination of weight
In this study, the analytic hierarchy process (AHP) was used to determine the weight of medical workers' knowledge of cost accounting indicators.

The establishment of a hierarchical framework
At the highest level of the hierarchy usually lies a single element, which is the decision goal.The intermediate level comprises criteria and sub-criteria, which may further branch into multiple layers.The criteria are guided by the decision-making goal, and the sub-criteria are influenced by the criteria at the preceding level, reflecting a top-down dominance relationship within the hierarchy.The knowledge capital value of costing indicators for medical workers is shown in Table 2.

The construction of a two-pair judgment matrix
Once the hierarchical framework is established, the connection between the upper and lower elements becomes apparent.The expert group conducts an in-depth analysis of the accounting book data.Simultaneously, they invite cost accountants, clinicians, nurses, and medical technicians from the public hospitals where DRG trials are taking place.These participants are tasked with comparing the importance of indicators and constructing a two-by-two comparison matrix.The analytic hierarchy method typically employs the 9-level scale method to assign values to the elements of the judgment matrix, as shown in Table 3.
Table 3 shows that a value of 9 means "absolutely important, " a value of 7 means "very important, " and a value of 5 means "important, " so a median rating such as "the degree of importance is between very important and important" is awarded 6 points.The experts evaluated and weighed four primary indicators of the cost of knowledge for medical workers, and the resulting pairwise matrix is scored as shown in Table 4.

According to the scoring table provided by the decision expert, a pairwise comparison judgment matrix A of the primary indicators can be constructed:
The calculation of the weight coefficient In brief, the eigenvectors corresponding to the maximum eigenvalues of matrix A can be calculated by approximate calculation methods such as the square root method λ max and normalized to the weight of each evaluation index.The calculation of the weight coefficient is divided into three steps, using the square root method.The specific steps to adopt the square root method are as follows: (1) calculate the product M i of all elements a ij of each row of the judgment matrix A.
(3) Normalization of vectors , , , n , , n is the desired feature vector, and the weight of the primary index is obtained ω = ( )

Consistency test
Upon obtaining the judgment matrix of the primary indicators, a consistency test is conducted.Due to the considerable number of pairwise comparisons, achieving complete consistency can be challenging.In reality, some inconsistency is inevitable in any pairwise comparison.To mitigate this issue, AHP offers a method to gauge the consistency of decision-makers when making such comparisons.If the desired level of agreement is not met,

Risks of disease treatment
The operating time of disease treatment   decision-makers should reassess the pairwise comparisons and make necessary adjustments before proceeding with the AHP analysis to minimize bias in subjective judgment.The consistency of pairwise comparisons is measured through a consistency metric (Table 5).The consistency check is conducted in three steps: The first step is to calculate the maximum eigenroot λ max in the pairwise comparison matrix A Then, Since C I . .< 0 1 and C R . .< 0 1, it is acceptable to compare the inconsistencies of matrix A, that is, the obtained weight-weight coefficients are valid.Similarly, the weights of secondary indicators can be obtained, and the summary table of the weights of primary and secondary indicators is shown in Table 6.

Empirical analysis
This study collects data on the full costs of treating three types of diseases: hip replacement, acute simple appendicitis, and heart bypass surgery.The dataset includes a patient settlement list, the first page of medical records, and the knowledge costs of medical workers, all sourced from a single public hospital.Specifically, the components of full cost within DRG encompass the knowledge capital of medical workers, sanitary material costs (blood transfusion cost, oxygen usage cost, costs of imaging materials, and costs of laboratory materials), drug costs, depreciation expense of fixed assets, amortization expense of intangible assets, withdrawal of medical risk fund, and other operating expenses (office expenses, utility costs, costs of postage and telecommunications, internet bills, official car operation and maintenance fees and travel expenses, training fees, union funds, and other expenses) (33).
The depreciation expenses of fixed assets and office expenses, salaries of management staff, and utilities and Internet bills that need to be apportioned in disease treatment are shown in Table 7.
Taking the data from hip replacement, acute simple appendicitis, and heart bypass surgery as examples, the full cost accounting results are shown in Tables 8-10.

Discussion
In this study, considering the compensation of the value of the intellectual capital of medical workers, the cost of DRG diseases was calculated.This calculation is achieved by considering four primary indicators: technical difficulty, labor intensity, risk degree, and operation time of the disease project.In addition, factors such as the complexity of the operation steps, knowledge requirements, decision-making ability, physical exertion, concentration levels, and the likelihood of potential safety hazards to patients and occupational exposure to medical workers are taken into account.Through the refinement of eight secondary-level indicators related to service item operation time, the study calculates the knowledge capital value compensation for the disease and establishes a comprehensive cost accounting model.This endeavor addresses a longstanding issue in China's disease cost accounting, which historically neglected the value of medical workers' knowledge-based capital.The study has successfully redefined the positive incentive mechanism, stimulated endogenous motivation within the medical service system, instigated independent changes in medical behavior, and achieved goals of cost control and rational expenditure.Ultimately, this study provides decision-makers with valuable insights and a viable policy pathway for reforming the implementation of DRG payment systems.

Conclusion
This study establishes a framework for compensating the knowledge capital value in cost accounting of DGR diseases, with the

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D 1 : 1 :D 2 : 2 : 2 : 3 : 3 : 4 :
The difficulty of disease treatment I 1 : Levels of physical exertion per unit of time R Risk hazards for patients in treatment T 1 : Consultation time (including surgery time) Level of technical commitment I 2 :Levels of concentration per unit of time R Occupational exposure of medical workers T Time for nursing D Knowledge requirement for operators T Time for examing D The requirement for operators' decision-making ability cost of utilities and other expenses share in the disease treatment = The cost of utilities borneby the department × The cost of dis sease treatement The overall medical expenses of the depar t tment administrative and logistics management = The number of staff in the department The overall staff in t the hospital The cost of adminstrative and logistics mana × g gement × The cost of disease treatement The overall medical e expenses of the department Secondary allocation Apportioned according to the income from disease treatment Registration fee The registration cost for disease treatment = The income of the department The overall income of the hosp i ital The cost of disease tre × × The current registation cost a atement The overall medical expenses of the department Apportioned according to workload Outpatient office costs Outpatient office costs in disease treatment = The number of patients in the department The overall patien t ts in the hospital The current cost of outpatient office × c cost × The number of patients in this disease treatement The overall patients in the department Inpatient and food supply Costs of inpatient and food supply in disease treatment = The number ofinpatients in the department The overall inpat i ients in the hospital The current cost of inpatient depar × t tment × The number of inpatients in this disease treatement T The overall inpatients in the department instruments= The value of fixed proprietary equipment in the department T The overall value of fixed proprietary equipment in the h o ospital × The current cost of deparment of health instrument ts × The value of fixed proprietary equipment in this diseas se treatement The overall value of fixed proprietary equip m ment in the department Apportioned according to the number of discharged patients Department of Medical History Costs of the Department of Medical History The number of discharged patients in the department The num b ber of discharged patients in the hospital The current co × s st of Deparment of Medical History × The number of discharge ed patients in this disease treatement The number of disch a arged patients in the department of medical supply, oxygen supply, and other medical assistance = The service consumption inone assistantive department The se r rvice capacity inone assistantive department The current c × o ost inone assistantive department he service consumption ino × n ne assistantive department for disease treatement The servi c ce consumption inone assistantive department Department of Medical Care Design = The income fromnewmedical techologies or serivce in the de p partment The income fromnewmedical techologies or serivce i in the hospital The current cost of deparment of medical × c care design × The cost of medical technologies or service in n this disease treatement The income fromnewmedical techol o ogies or serivce in the department 10.3389/fpubh.2024.1269704Frontiers in Public Health 07 frontiersin.org

TABLE 1
Disease cost accounting index system.

TABLE 2
Knowledge capital value costing indicators for medical workers.

TABLE 3
Scale explanation on value 1 to 9.
ReciprocalIf the j element is compared with the i element, the judgment value is the reciprocal of the aforementioned scale value TABLE 4 Pairwise comparison of expert scores on decision criteria.

TABLE 6
Weight of knowledge capital value of accounting indicators for medical workers.

TABLE 5
The corresponding R.I value.

TABLE 8
DRG costing results for "Hip Replacement."

TABLE 9
DRG costing results for "acute simple appendicitis.", such as excessive prescriptions and examinations, thereby reducing disease costs in support of DRG payment reform.Subsequently, hospitals conduct disease cost accounting based on the knowledge value compensation of medical workers, thereby enhancing the transparency and authenticity of DRG pricing; furthermore, this strategy facilitates the monitoring of medical institutions' inadequacies through DRG cost accounting.

TABLE 10
Cost accounting results of DRG disease "Heart bypass surgery."