Supply-demand matching of medical services at a city level under the background of hierarchical diagnosis and treatment - based on Didi Chuxing Data in Haikou, China

Shao, Haiyan; Jin, Cheng; Xu, Jing; Zhong, Yanfei; Xu, Bing

doi:10.1186/s12913-022-07762-4

Cited by 23 publications

(14 citation statements)

References 40 publications

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“…On the other hand, the results illustrated that sub-urban and rural areas need more high-quality human resources and financial resources in the next few years ( 44 ). Decision-makers for EMS planning should further focus on three aspects: the spatial layout and optimal allocation of medical service facilities, the accessibility and equity of medical facilities, and the supply–demand matching of medical services, according to variations in EMS supply and demand characteristics among urban, sub-urban, and rural areas ( 27 ).…”

Section: Discussionmentioning

confidence: 99%

“…Urban–sub-urban–rural disparities in EMS supply have become a current crucial public health issue ( 26 ). To address this limitation, the Outline of Healthy China 2030 Plan highlighted that we should improve the medical and health service system from both the supply and demand sides in October 2016 ( 27 ). China has set up reform pilot programs of purely prehospital care models in several cities (i.e., Tianjin, Shanghai, Nanjing, Wuhan, and Hangzhou) to further deepen the reform of the medicine and healthcare system.…”

Section: Introductionmentioning

confidence: 99%

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Urban–sub-urban–rural variation in the supply and demand of emergency medical services

Geng

et al. 2023

Front. Public Health

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BackgroundEmergency medical services (EMSs) are a critical component of health systems, often serving as the first point of contact for patients. Understanding EMS supply and demand is necessary to meet growing demand and improve service quality. Nevertheless, it remains unclear whether the EMS supply matches the demand after the 2016 healthcare reform in China. Our objective was to comprehensively investigate EMS supply–demand matching, particularly among urban vs. sub-urban vs. rural areas.MethodsData were extracted from the Tianjin Medical Priority Dispatch System (2017–2021). From supply and demand perspectives, EMS resources and patient characteristics were analyzed. First, we performed a descriptive analysis of characteristics, used Moran's I to explore the spatial layout, and used the Gini coefficient to evaluate the equity of EMS supply and demand. Second, we analyzed urban–sub-urban–rural variation in the characteristics of EMS supply and demand by using the chi-square test. Finally, we examined the association between the EMS health resource density index and the number of patients by using the Spearman correlation and divided supply–demand matching types into four types.ResultsIn 2021, the numbers of medical emergency stations and ambulances were 1.602 and 3.270 per 100,000 population in Tianjin, respectively. There were gradients in the health resource density index of the number of emergency stations (0.260 vs. 0.059 vs. 0.036; P = 0.000) in urban, sub-urban, and rural areas. There was no spatial autocorrelation among medical emergency stations, of which the G values by population, geographical distribution, and the health resource density index were 0.132, 0.649, and 0.473, respectively. EMS demand was the highest in urban areas, followed by sub-urban and rural areas (24.671 vs. 15.081 vs. 3.210 per 1,000 population and per year; P = 0.000). The EMS supply met the demand in most districts (r = 0.701, P = 0.003). The high supply–high demand types with stationary demand trends were distributed in urban areas; the low supply–high demand types with significant demand growth trends were distributed in sub-urban areas; and the low supply–low demand types with the highest speed of demand growth were distributed in rural areas.ConclusionEMS supply quantity and quality were promoted, and the supply met the demand after the 2016 healthcare reform in Tianjin. There was urban–sub-urban–rural variation in EMS supply and demand patterns.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Urban–sub-urban–rural variation in the supply and demand of emergency medical services

Geng

et al. 2023

Front. Public Health

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“…Hierarchical diagnosis and treatment is a good tool used to assign patients to matched medical institutions for treatment [ 32 ]. In 1920, the concept of tertiary care was introduced in the UK [ 33 ].…”

Section: Related Workmentioning

confidence: 99%

Patient allocation method in major epidemics under the situation of hierarchical diagnosis and treatment

Huang

Wang

et al. 2022

BMC Med Inform Decis Mak

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Objectives Patients are classified according to the severity of their condition and graded according to the diagnosis and treatment capacity of medical institutions. This study aims to correctly assign patients to medical institutions for treatment and develop patient allocation and medical resource expansion schemes among hospitals in the medical network. Methods Illness severity, hospital level, allocation matching benefit, distance traveled, and emergency medical resource fairness were considered. A multi-objective planning method was used to construct a patient allocation model during major epidemics. A simulation study was carried out in two scenarios to test the proposed method. Results (1) The single-objective model obtains an unbalanced solution in contrast to the multi-objective model. The proposed model considers multi-objective problems and balances the degree of patient allocation matching, distance traveled, and fairness. (2) The non-hierarchical model has crowded resources, and the hierarchical model assigns patients to matched medical institutions. (3) In the “demand exceeds supply” situation, the patient allocation model identified additional resources needed by each hospital. Conclusion Results verify the maneuverability and effectiveness of the proposed model. It can generate schemes for specific patient allocation and medical resource amplification and can serve as a quantitative decision-making tool in the context of major epidemics.

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“…Continuous improvement in medical services also helps reverse the backwardness of the level of medical services in these regions. Presently, the need for medical services has been a fast ascent ( 31 ), forcing some migrants who sacrifice part of their medical service needs in the face of dual pressures from the household registration system and financial conditions to return home ( 25 ). If medical services in the city of registered residence continue to improve to a considerable extent, the city of registered residence will have a significant appeal to the migrants even if the absolute level of medical services still lags behind that of the more developed regions in the east.…”

Section: Research Hypothesismentioning

confidence: 99%

The impact of medical service on the return behavior: A city-level study in China

Meng

Wang²,

Yu³

2022

Front. Public Health

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Due to the constraints of the rural-urban household registration systems, the migrants of China currently receive varying degrees of medical services. The fact that many migrants choose to return to their hometowns due to the inequality in medical care has been a social phenomenon. Using data from the 2017 China Migrant Dynamic Survey (CMDS), this paper explores the effect of medical services on population migration. Probit regression analysis method was utilized to examine the relationship between medical service level (MSL) and medical service improvement (MSI) and return behavior (RB), as well as the interaction effect between MSL and MSI, and the moderating effect of health status (HS) and health education (HE). Multiple heterogeneity tests were performed. Grouping regressions were conducted using rural household registration (RHR), grouping regressions were conducted using new rural cooperative medical system (NRCMS), and multinomial Probit regressions were conducted using migration distance and age factors. The following findings were obtained. First, when MSL is low but MSI is high in the locality of household registration, the return probability of migrants will increase. MSL also has a positive interaction effect with MSI, and they jointly increase the return probability of migrants; Second, HS and HE have a positive moderating effect on the relationships between MSL and RB and between MSI and RB; Third, heterogeneity analysis indicates that the migrants with RHR or the migrants not covered by the NRCMS are more prone to return due to the reason of medical service. In addition, the analysis also shows that middle-aged and older people who return across provinces have the highest tendency to return due to medical services and young people have the lowest propensity to return across and within provinces. The study could help local governments change their public medical care policies and close the gap between medical services in different areas. As a result, it is necessary to understand population migration trends and promote New Urbanization Strategies.

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Supply-demand matching of medical services at a city level under the background of hierarchical diagnosis and treatment - based on Didi Chuxing Data in Haikou, China

Cited by 23 publications

References 40 publications

Urban–sub-urban–rural variation in the supply and demand of emergency medical services

Urban–sub-urban–rural variation in the supply and demand of emergency medical services

Patient allocation method in major epidemics under the situation of hierarchical diagnosis and treatment

The impact of medical service on the return behavior: A city-level study in China

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