Transformation of potential medical demand in China: A system dynamics simulation model

Social Medical Insurances, Choices of Medical Institutions and the 'Siphon Effect' in the Health Service Market: Evidence from 2021 Yangtze River Delta Region of China

Purpose

The siphon effect in the health service market is notably pronounced in many countries. How to measure and identify the determinants contributing to the siphon effect presents a substantial challenge. This study aimed to analyse the effect of two different social medical insurances, the Basic Medical Insurance System for Urban Employees (BMISUE), and the Basic Medical Insurance System for Urban and Rural Residents (BMISURR), on the siphon effect in the health services market.

Methods

The data used in this study were from the 2021 Health Life Satisfaction Survey of Yangtze River Delta (HLSSYRD) conducted by Shanghai Jiao Tong University. The logistic model was used to evaluate the association between social medical insurances and individual choices of medical institutions, and the Propensity Score Matching method (PSM) was used to check the robustness of basic results.

Results

Residents covered by BMISUE were more likely to choose a general hospital when they first sought medical treatment (OR = 5.377, 95% CI: 4.887, 5.915) relative to those insured by BMISURR. Further analysis showed that BMISUE would accelerate the siphon effect of general hospitals, people insured by BMISUE were still more likely to choose general hospitals despite being close to primary hospitals compared to those insured by BMISURR (OR = 3.240, 95% CI: 2.945, 3.565). Heterogeneity analysis indicated BMISUE had a greater impact on residents aged 15-59 years and those with high income compared to older people and individuals with low income.

Conclusion

Different social medical insurances can substantially affect residents' first choice of medical institutions. BMISUE with higher benefits level could exacerbate the siphon effect in the health service market. More equitable medical security system should be strengthened to bridge the benefits gap between BMISUE and BMISURR.

Can Online Patient-Provider Communication Improve Emotional Well-Being? Examining the Roles of Social Presence and Patient Empowerment

China has long been suffering from the problem of having health care that is expensive and difficult to access. Online patient-provider communication (OPPC) can offer a viable channel to increase access to care. However, through what underlying mechanisms OPPC can be associated with better health outcome is under-researched. To fill this research gap, this study investigated OPPC usage in China and identified psychological processes linking OPPC to emotional well-being. With two-wave panel surveys conducted in China, we found that mobile health app, social media, and health information service website were three common platforms for OPPC, followed by patient portal, whereas e-mail was used least frequently. Overall, OPPC did not have any direct effect on emotional well-being. Instead, OPPC first increased users' perceived social presence of providers in OPPC, which in turn triggered sense of patient empowerment, which finally enhanced emotional well-being.

Evaluation Method for Urban Public Service Carrying Capacity (UPSCC): A Qualitative-Quantitative Bi-Dimensional Perspective

Urban Public Service Carrying Capacity plays an essential role in urban social and economic development. However, existing study has been focused on the evaluation of UPSCC from a quantitative perspective. It is necessary to evaluate UPSCC from a qualitative–quantitative bi-dimensional perspective. This paper establishes an innovative evaluation method for UPSCC based on a qualitative–quantitative bi-dimensional (QQBD) perspective. The proposed QQBD-based UPSCC evaluation method can help identify the weak areas of public services. The conclusions of this study are as follows. Firstly, public services are people-oriented social resources, which should be evaluated from both quantitative and qualitative perspectives. Secondly, the quantitative measurement of public service carrying capacity needs to consider both UPSCC load and carrier, while the qualitative measurement needs to consider the satisfaction among stakeholders. Thirdly, the demonstration of the case study cities shows the effectiveness of the qualitative–quantitative bi-dimensional UPSCC evaluation method. By applying the QQBD-based UPSCC evaluation method introduced in this study, decision makers can identify the specific areas that affect the UPSCC performance, and thus tailor-made policy can be designed for improving UPSCC performance by adjusting UPSCC quantity and quality.

Comparison of RetinaNet, SSD, and YOLO v3 for real-time pill identification

BACKGROUND

The correct identification of pills is very important to ensure the safe administration of drugs to patients. Here, we use three current mainstream object detection models, namely RetinaNet, Single Shot Multi-Box Detector (SSD), and You Only Look Once v3(YOLO v3), to identify pills and compare the associated performance.

METHODS

In this paper, we introduce the basic principles of three object detection models. We trained each algorithm on a pill image dataset and analyzed the performance of the three models to determine the best pill recognition model. The models were then used to detect difficult samples and we compared the results.

RESULTS

The mean average precision (MAP) of RetinaNet reached 82.89%, but the frames per second (FPS) is only one third of YOLO v3, which makes it difficult to achieve real-time performance. SSD does not perform as well on the indicators of MAP and FPS. Although the MAP of YOLO v3 is slightly lower than the others (80.69%), it has a significant advantage in terms of detection speed. YOLO v3 also performed better when tasked with hard sample detection, and therefore the model is more suitable for deployment in hospital equipment.

CONCLUSION

Our study reveals that object detection can be applied for real-time pill identification in a hospital pharmacy, and YOLO v3 exhibits an advantage in detection speed while maintaining a satisfactory MAP.

Exploring drivers for public engagement in social media communication with medical social influencers in China

Social networking sites offer an important means for increasing the accessibility and enabling new forms of health communication between the public and medical social influencers (MSIs). MSIs have a social presence and are perceived as a credible source of health-related information. A research gap, however, exists in understanding the communication strategies employed by MSIs and the factors driving the public to engage in health communication with MSIs. This study, therefore, developed a new conceptual framework incorporating health communication, dialogic and interpersonal communication by employing quantitative content analysis to examine public engagement with MSI communication on the largest microblogging site in China, Sina Weibo. The analysis yielded insights into how the usefulness of health-related information provided alongside the interactive dialogue and affective practices played an active role in engaging the public. The public sought health-related information primarily to address issues of concern for well-being and a high level of engagement in terms of online shares, likes, and comments was found. The use of multimedia made the site more appealing, resulting in likes while the expression of emotions by MSIs generated likes and comments. The need to connect with other online users and have a sense of community was reflected in engagement through sharing useful MSI posts by the public. By identifying influential MSIs on social networking sites, health information providers such as organizations and the government can raise awareness of health issues to foster a healthy lifestyle and contribute to better living in the community.

Control of unreasonable growth of medical expenses in public hospitals in Shanghai, China: a multi-agent system model

Background

This study aims to establish a multi-agent system model to provide accurate suggestions for the policy proposal of controlling the unreasonable growth of medical expenses charged by public hospitals in China.

Methods

A multi-agent system model was employed in this study. Agents of this model were divided into patients, doctors, medical institutions, the government, and medical insurance agencies. The model was composed of two subsystems: the disease and medical-seeking subsystem, and the medical expenses subsystem. Policy intervention experiments were conducted on patients’ medical-seeking preferences, doctors’ public welfare behaviors, and the government’s financial investment.

Results

At present, medical expenses in China are unreasonable and keep increasing, and the proportion of medicine and physical examination expenses to total medical expenses for public hospitals is unreasonable. Intervention experiments suggested that expanding the promotion and application of the community first-visit system could rationalize patients’ medical-seeking preferences, increasing doctors’ incomes and reducing workload could significantly restrict doctors’ over-prescription behaviors. Also, improving the government’s financial investment could guide public hospitals to strengthen their commitment to public welfare responsibilities. These interventions could decrease the unreasonable growth of medical expenses of public hospitals. The combined intervention effects on suppliers, demanders, and the government were better than the effect of these agents independently.

Conclusions

The main reasons for the unreasonable increase in patient medical expenses at public hospitals could be attributed to patients’ unreasonable medical-seeking preferences, doctors’ weak public welfare incentives, and the government’s inadequate financial investment. Policy-makers should consider proposals to restrict and guide the behaviors of suppliers, demanders, and the government, simultaneously. The government should consider the feasibility, response speed, and implementation cost of policies as well.

Mathematical modelling for health systems research: a systematic review of system dynamics and agent-based models

BACKGROUND

Mathematical modelling has been a vital research tool for exploring complex systems, most recently to aid understanding of health system functioning and optimisation. System dynamics models (SDM) and agent-based models (ABM) are two popular complementary methods, used to simulate macro- and micro-level health system behaviour. This systematic review aims to collate, compare and summarise the application of both methods in this field and to identify common healthcare settings and problems that have been modelled using SDM and ABM.

METHODS

We searched MEDLINE, EMBASE, Cochrane Library, MathSciNet, ACM Digital Library, HMIC, Econlit and Global Health databases to identify literature for this review. We described papers meeting the inclusion criteria using descriptive statistics and narrative synthesis, and made comparisons between the identified SDM and ABM literature.

RESULTS

We identified 28 papers using SDM methods and 11 papers using ABM methods, one of which used hybrid SDM-ABM to simulate health system behaviour. The majority of SDM, ABM and hybrid modelling papers simulated health systems based in high income countries. Emergency and acute care, and elderly care and long-term care services were the most frequently simulated health system settings, modelling the impact of health policies and interventions such as those targeting stretched and under resourced healthcare services, patient length of stay in healthcare facilities and undesirable patient outcomes.

CONCLUSIONS

Future work should now turn to modelling health systems in low- and middle-income countries to aid our understanding of health system functioning in these settings and allow stakeholders and researchers to assess the impact of policies or interventions before implementation. Hybrid modelling of health systems is still relatively novel but with increasing software developments and a growing demand to account for both complex system feedback and heterogeneous behaviour exhibited by those who access or deliver healthcare, we expect a boost in their use to model health systems.

How Does Online Patient-Provider Communication Heal? Examining the Role of Patient Satisfaction and Communication Experience in China

China is facing the problem of having health care that is difficult to access. Online patient-provider communication (OPPC) may bring a new option to deliver health services. However, online communication with doctors is still novel to many people in China. Little research has been conducted to examine how OPPC could improve health outcomes. With an integrated model that incorporates social cognitive theory into the three-stage model of health promotion using interactive media, this study tested the social mechanism underlying the impact of OPPC. Results indicated that self-efficacy, behavioral capability, and outcome expectation positively predicted OPPC at Stage 1, which in turn increased patient satisfaction at Stage 2, which finally improved three types of health outcomes (general, emotional, and physical) at Stage 3. In addition, quality of users' experience in OPPC positively moderated this mediation pathway. Theoretical and practical implications of this study were also discussed.

Public preferences for health care facilities in rural China: A discrete choice experiment

To successfully tackle the problems with the underutilization of primary care in rural China, it is important to align resource allocation with the preferences of the rural population. However, despite growing interest in the factors influencing the rural population's choice of facility, it is unclear how much weight should be placed on these factors, especially under different scenarios of disease severity. In the first study to elicit quantified trade-offs among influential factors in choosing health care facilities, we carried out a discrete choice experiment (DCE) in rural China. We used a Bayesian efficient design to construct 36 choice sets, and then divided them into three blocks. Each block formed one version of questionnaire that contained 12 choice questions. Each question was assigned a hypothetical perceived severity scenario of either minor or severe disease. 559 Rural residents completed the DCE through face-to-face interviews in December 2017-March 2018. We used mixed logit models to analyze the choice data. The factors regarding the availability and affordability of a facility, such as visit time, travel time, and out-of-pocket cost, were highly valued. When the facilities changed simultaneously from the worst to the best case, a huge increase (from 4.8% to 66.5%) in the predicted choice probability of choosing to visit a facility was observed under perceived minor disease scenario, whereas there was no significant change under perceived severe disease scenario. Improvements to drug availability, medical professional skill and equipment in rural primary care system can induce potential medical care seeking, and redirect patient flow from higher level hospitals to primary level. Especially, township health centers, which provide service to the residents in rural communities, have great potential to be the ideal facilities for first-contact care.

System dynamics modeling of public health services provided by China CDC to control infectious and endemic diseases in China

BACKGROUND

Infectious and endemic diseases are a serious public health concern worldwide, and their prevention and treatment are globally controversial. This study aimed to establish an system dynamics (SD) model to analyze the factors influencing public health services provided by the Chinese Centers for Disease Control and Prevention (China CDC) to implement infectious and endemic disease control in China, by establishing more effective interventions to provide public health services and thus achieving the goal of controlling infectious and endemic diseases.

MATERIALS AND METHODS

An SD model was constructed using the Vensim DSS program. Intervention experiments were performed using the SD model, which reflected the influences on disease control by adjusting the governmental investment and compensation level for public health products.

RESULTS

The experimental results showed that increasing the governmental investment in China CDC and compensation level for public health products will significantly increase the public health product rate provided by China CDC.

DISCUSSION

Problems with infectious and endemic disease prevention and treatment are the result of the system's incomplete functioning and limited health resources. To address the current problems and improve the system, the government should increase its investment in the public health service system and improve the compensation system to ensure smooth implementation of infectious and endemic disease prevention and treatment and, ultimately, improve public health in China.

Research of an emergency medical system for mass casualty incidents in Shanghai, China: a system dynamics model

OBJECTIVES

Emergency medical system for mass casualty incidents (EMS-MCIs) is a global issue. However, China lacks such studies extremely, which cannot meet the requirement of rapid decision-support system. This study aims to realize modeling EMS-MCIs in Shanghai, to improve mass casualty incident (MCI) rescue efficiency in China, and to provide a possible method of making rapid rescue decisions during MCIs.

METHODS

This study established a system dynamics (SD) model of EMS-MCIs using the Vensim DSS program. Intervention scenarios were designed as adjusting scales of MCIs, allocation of ambulances, allocation of emergency medical staff, and efficiency of organization and command.

RESULTS

Mortality increased with the increasing scale of MCIs, medical rescue capability of hospitals was relatively good, but the efficiency of organization and command was poor, and the prehospital time was too long. Mortality declined significantly when increasing ambulances and improving the efficiency of organization and command; triage and on-site first-aid time were shortened if increasing the availability of emergency medical staff. The effect was the most evident when 2,000 people were involved in MCIs; however, the influence was very small under the scale of 5,000 people.

CONCLUSION

The keys to decrease the mortality of MCIs were shortening the prehospital time and improving the efficiency of organization and command. For small-scale MCIs, improving the utilization rate of health resources was important in decreasing the mortality. For large-scale MCIs, increasing the number of ambulances and emergency medical professionals was the core to decrease prehospital time and mortality. For super-large-scale MCIs, increasing health resources was the premise.

Dynamic modeling approaches to characterize the functioning of health systems: A systematic review of the literature

Universal Health Coverage (UHC) is one of the targets for the United Nations Sustainable Development Goal 3. The impetus for UHC has led to an increased demand for time-sensitive tools to enhance our knowledge of how health systems function and to evaluate impact of system interventions. We define the field of "health system modeling" (HSM) as an area of research where dynamic mathematical models can be designed in order to describe, predict, and quantitatively capture the functioning of health systems. HSM can be used to explore the dynamic relationships among different system components, including organizational design, financing and other resources (such as investments in resources and supply chain management systems) - what we call "inputs" - on access, coverage, and quality of care - what we call "outputs", toward improved health system "outcomes", namely increased levels and fairer distributions of population health and financial risk protection. We undertook a systematic review to identify the existing approaches used in HSM. We identified "systems thinking" - a conceptual and qualitative description of the critical interactions within a health system - as an important underlying precursor to HSM, and collated a critical collection of such articles. We then reviewed and categorized articles from two schools of thoughts: "system dynamics" (SD)" and "susceptible-infected-recovered-plus" (SIR+). SD emphasizes the notion of accumulations of stocks in the system, inflows and outflows, and causal feedback structure to predict intended and unintended consequences of policy interventions. The SIR + models link a typical disease transmission model with another that captures certain aspects of the system that impact the outcomes of the main model. These existing methods provide critical insights in informing the design of HSM, and provide a departure point to extend this research agenda. We highlight the opportunity to advance modeling methods to further understand the dynamics between health system inputs and outputs.

Predicting Urban Medical Services Demand in China: An Improved Grey Markov Chain Model by Taylor Approximation

The sharp increase of the aging population has raised the pressure on the current limited medical resources in China. To better allocate resources, a more accurate prediction on medical service demand is very urgently needed. This study aims to improve the prediction on medical services demand in China. To achieve this aim, the study combines Taylor Approximation into the Grey Markov Chain model, and develops a new model named Taylor-Markov Chain GM (1,1) (T-MCGM (1,1)). The new model has been tested by adopting the historical data, which includes the medical service on treatment of diabetes, heart disease, and cerebrovascular disease from 1997 to 2015 in China. The model provides a predication on medical service demand of these three types of disease up to 2022. The results reveal an enormous growth of urban medical service demand in the future. The findings provide practical implications for the Health Administrative Department to allocate medical resources, and help hospitals to manage investments on medical facilities.