A game theoretic setting of capitation versus fee-for-service payment systems

Koenecke, Allison

doi:10.1371/journal.pone.0223672

Cited by 3 publications

(2 citation statements)

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“…A similar study developed by das Chagas Moura et al ( 32 ), who apply queue theory to improve the Stackelberg game model, focuses on the problems of medical service pricing and medical quality. Koenecke ( 33 ) analyses the non-extreme equilibrium between two different payment methods in medical insurance and medical institutions by applying a Stackelberg game model. These two payment methods include a charge on a per-service basis and a per-patient basis.…”

Section: Related Workmentioning

confidence: 99%

A Game Model for Medical Service Pricing Based on the Diagnosis Related Groups

Duan

Zhi-bin

Feng

2021

Front. Public Health

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Background: Currently there are various issues that exist in the medical institutions in China as a result of the price-setting in DRGs, which include the fact that medical institutions tend to choose patients and that the payment standard for complex cases cannot reasonably compensate the cost.Objective: The main objective is to prevent adverse selection problems in the operations of a diagnosis-related groups (DRGs) system with the game pricing model for scientific and reasonable pricing.Methods: The study proposes an improved bargaining game model over three stages, with the government and patients forming an alliance. The first stage assumes the alliance is the price maker in the Stackelberg game to maximize social welfare. Medical institutions are a price taker and decide the level of quality of medical service to maximize their revenue. A Stackelberg equilibrium solution is obtained. The second stage assumes medical institutions dominate the Stackelberg game and set an optimal service quality for maximizing their revenues. The alliance as the price taker decides the price to maximize the social welfare. Another Stackelberg equilibrium solution is achieved. The final stage establishes a Rubinstein bargaining game model to combine the Stackelberg equilibrium solutions in the first and second stage. A new equilibrium between the alliance and medical institutions is established.Results: The results show that if the price elasticity of demand increases, the ratio of cost compensation on medical institutions will increase, and the equilibrium price will increase. The equilibrium price is associated with the coefficient of patients' quality preference. The absolute risk aversion coefficient of patients affects government compensation and total social welfare.Conclusion: In a DRGs system, considering the demand elasticity and the quality preference of patients, medical service pricing can prevent an adverse selection problem. In the future, we plan to generalize these models to DRGs pricing systems with the effects of competition of medical institutions. In addition, we suggest considering the differential compensation for general hospitals and community hospitals in a DRGs system, in order to promote the goal of hierarchical diagnosis and treatment.

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Section: Related Workmentioning

confidence: 99%

A Game Model for Medical Service Pricing Based on the Diagnosis Related Groups

Duan

Zhi-bin

Feng

2021

Front. Public Health

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“…However, challenges such as inadequate incentive structures and concerns about limiting consumer choice hinder widespread adoption 10 . Kenya's National Hospital Insurance Fund (NHIF) predominantly employs capitation to nance primary healthcare services, contracting various organizations to provide outpatient care.…”

Section: Introductionmentioning

confidence: 99%

Determinants of Primary Healthcare Services Access by National Health Insurance Fund Capitated Members in Uasin Gishu County, Kenya

Were,

Mwangi,

Muiruri

2024

Preprint

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Purpose The study identifies provision of primary healthcare services using the capitated health model as a prerequisite for promoting positive healthcare outcomes for a country’s population. However, capitated members have continued to face challenges in accessing primary healthcare services despite enrolment in the National Health Insurance Fund (NHIF). This study sought to determine if variables such as patient knowledge of the NHIF benefit package, NHIF Premium Payment processes, selecting NHIF capitated health facilities, and NHIF Communication to citizens’ influences access to primary healthcare services. Method A cross-sectional analytical research design was adopted. Data was collected from patients who were using NHIF cards, who were drawn from health facilities. Data was collected using a structured questionnaire where some of the questions were rated using the Likert scale to enable the generation of descriptive statistics. Data was analysed using descriptive and inferential statistics which was conducted with the aid of SPSS version 25. Bivariate analysis was conducted utilizing Chi-square to facilitate the comparison of the independent and the dependent variables. Data was presented in tabular formats where each of the specific objectives was used as parameters of interest to the study. Results The study found that four independent variables (Patient knowledge of NHIF Benefit Package, NHIF Premium Payment processes, Selecting NHIF capitated Health Facility, and NHIF Communication to citizens) were significant predictors of access to capitated healthcare services with significance values of .001, .001, .001 and .001 respectively at 95% significance level. Conclusions The study found that familiarity with the NHIF benefit package significantly influenced NHIF capitated members' access to primary healthcare services in Uasin Gishu County. While most members were aware of their healthcare entitlements, there's a need for increased awareness regarding access to surgical services and dependents' inclusion. Facility selection also played a crucial role, influenced by factors like freedom of choice, NHIF facility selection rules, facility appearance, and proximity to members' homes. NHIF communication positively impacted access, with effective communication channels aiding service accessibility. Premium payment processes also significantly linked with service access, influenced by factors such as payment procedures, premium awareness, payment schedules, registration waiting periods, and penalties for defaults. Overall, patient knowledge, NHIF communication, premium payment processes, and facility selection all contributed positively to NHIF capitated members' access to primary healthcare services in Uasin Gishu County.

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