The Agreement Between Virtual Patient and Unannounced Standardized Patient Assessments in Evaluating Primary Health Care Quality: Multicenter, Cross-sectional Pilot Study in 7 Provinces of China.

BACKGROUND: The unannounced standardized patient (USP) is the gold standard for primary health care (PHC) quality assessment but has many restrictions associated with high human and resource costs. Virtual patient (VP) is a valid, low-cost software option for simulating clinical scenarios and is widely used in medical education. It is unclear whether VP can be used to assess the quality of PHC. OBJECTIVE: This study aimed to examine the agreement between VP and USP assessments of PHC quality and to identify factors influencing the VP-USP agreement. METHODS: Eleven matched VP and USP case designs were developed based on clinical guidelines and were implemented in a convenience sample of urban PHC facilities in the capital cities of the 7 study provinces. A total of 720 USP visits were conducted, during which on-duty PHC providers who met the inclusion criteria were randomly selected by the USPs. The same providers underwent a VP assessment using the same case condition at least a week later. The VP-USP agreement was measured by the concordance correlation coefficient (CCC) for continuity scores and the weighted κ for diagnoses. Multiple linear regression was used to identify factors influencing the VP-USP agreement. RESULTS: Only 146 VP scores were matched with the corresponding USP scores. The CCC for medical history was 0.37 (95% CI 0.24-0.49); for physical examination, 0.27 (95% CI 0.12-0.42); for laboratory and imaging tests, -0.03 (95% CI -0.20 to 0.14); and for treatment, 0.22 (95% CI 0.07-0.37). The weighted κ for diagnosis was 0.32 (95% CI 0.13-0.52). The multiple linear regression model indicated that the VP tests were significantly influenced by the different case conditions and the city where the test took place. CONCLUSIONS: There was low agreement between VPs and USPs in PHC quality assessment. This may reflect the "know-do" gap. VP test results were also influenced by different case conditions, interactive design, and usability. Modifications to VPs and the reasons for the low VP-USP agreement require further study.

Geographical variation in dementia prevalence across China: a geospatial analysis.

Background: Dementia poses great health and social challenges in China. Dementia prevalence may vary across geographic areas, while comparable estimations on provincial level is lacking. This study aims to estimate dementia prevalence by provinces across China, taking into account risk factors of individual level and potential spatial correlation of provinces. Methods: In this study, 17,176 adults aged 50 years or older were included from the fourth wave of the China Health and Retirement Longitudinal Study (CHARLS 2018), covering 28 provinces, autonomous regions and municipalities. To improve provincial representativeness, we constructed provincial survey weights based on China 7th census (2020). The prevalence of dementia and 95% Bayesian credible intervals (BCIs) were estimated using a Bayesian conditional autoregressive (CAR) model with spatially varying coefficients of covariates. Findings: The weighted prevalence of dementia at provincial level in China in 2018 ranged from 2.62% (95%BCI: 1.70%, 3.91%) to 13.53% (95%BCI: 8.82%, 20.93%). High dementia prevalence was concentrated in North China, with a prominent high-high cluster, while provinces of low prevalence were concentrated on East and South China, characterized by a low-low cluster. Ordered by the median estimation of prevalence, the top 10% of provinces, include Xinjiang, Jilin, and Beijing. Meanwhile, Fujian, Zhejiang, and Guangdong rank among the last. The association between dementia prevalence and drinking, smoking, social isolation, physical inactivity, hearing impairment, hypertension, and diabetes exhibits provincial variation. Interpretation: Our study identifies a geospatial disparity in dementia prevalence and risk factor effects across China's provinces, with high-high and low-low clusters in some northern and southern provinces, respectively. The findings emphasize the need for targeted strategies, such as addressing hypertension and hearing impairment, in specific regions for more effective dementia prevention and treatment. Funding: National Science Foundation of China/the Economic and Social Research Council, UK Research and Innovation joint call: Understanding and Addressing Health and Social Challenges for Ageing in the UK and China. UK-China Health And Social Challenges Ageing Project (UKCHASCAP): present and future burden of dementia, and policy responses (grant number 72061137003, ES/T014377/1).

Projection for dementia burden in China to 2050: a macro-simulation study by scenarios of dementia incidence trends.

Background: It is unclear how temporal trends in dementia incidence, alongside fast-changing demography, will influence China's future dementia burden. We developed a Markov model that combines population trends in dementia, mortality, and dementia-related comorbidities, to forecast and decompose the burden of dementia in China to 2050. Methods: Population-based Chinese ageing cohorts provided input data for a 10-health-state Markov macrosimulation model, IMPACT-China Ageing Model (CAM), to predict sex- and age-specific dementia prevalence among people aged 50+ by year to 2050. We assumed three potential future scenarios representing the range of likely dementia incidence trends: upward (+2.9%), flat (0%) or downward (-1.0%). Sensitivity analyses were conducted to examine uncertainty associated with trends in mortality rates and CVD incidence. The projected dementia burden was decomposed into population growth, population ageing, and changing dementia prevalence corresponding to the three incidence trend scenarios. Findings: Under the upward trend scenario, the estimated number of people living with dementia is projected to rise to 66.3 million (95% uncertainty interval (UI) 64.7-68.0 million), accounting for 10.4% of the Chinese population aged 50+ by 2050. This large burden will be lower, 43.9 (95% UI 42.9-45.0) million and 37.5 (95% UI 36.5-38.4) million, if dementia incidence remains constant or decreases. Robustness of the projection is confirmed by sensitivity analyses. Decomposition of the change in projected dementia cases indicates dominate effects of increasing dementia prevalence and population ageing, and a relatively minor contribution from negative population growth. Interpretation: Our findings highlight an impending surge in dementia cases in China in the forthcoming decades if the upward trend in dementia incidence continues. Public health interventions geared towards dementia prevention could play a pivotal role in alleviating this burgeoning disease issue. Funding: National Science Foundation of China/UK Economic and Social Research Council.