Purpose: Although the launch delay of new drugs in China has been a deep concern during the past few years, research on this topic is scarce. The effect of recent regulatory efforts, such as initiating fast review channels to improve access to medical innovations, remains unclear. In this work, we measure the launch delay in China and study whether the fast channels contribute to shorter delays. We also offer an examination of the effect of launch delay on patients ' health. Methods: We examined the launch delays of 40 new drugs engaged in the 3 national price negotiations in China. Launch delay was defined as the differences between the approval dates of the United States or the European Union and that of China and was measured according to approved indications of every specific drug. Thirty-four health impact models comparing the new drugs and their corresponding comparator therapies were populated with open data from published studies to assess the loss of health attributable to launch delay. The time horizon for each model was the specified delay time. Findings: A total of 40 new drugs with 54 approvals were studied. The median delay was 44.40 months (range, 7.30-196.24 months). For the 20 approvals granted with the fast channels, the median delay was 38.14 months, which was shorter than the 68.25 months of those 34 approvals on the track of standard procedure (P = 0.0276). Moreover, among the 34 health models for 27 new drugs, the largest loss of health was 5.76 life-years and 4.14 qualityadjusted life-years per potential patient, whereas the least loss was 0.006 life-years per head and 0.0035 quality-adjusted life-years per head, respectively. Implications: Access to new drugs is delayed significantly in China, which may undermine patient benefit by causing loss of life-years and quality of life. The fast review procedures in China have appeared to mitigate the launch delay. (c) 2020 The Author(s). Published by Elsevier Inc.

Informed consent and patient autonomy rights require an optimal cancer diagnosis disclosure strategy to be used to update the patients and caregivers with the bad news. However, a cancer diagnosis disclosure may arouse anxiety and distress which increase patients’ and caregivers’ psychological burden. This study aims to explore the influence of cancer diagnosis disclosure on the quality of life in elderly cancer patients and their caregivers, and to introduce an effective way to disclose cancer diagnosis. A total of 120 participants were randomly selected in the study. The Medical Coping Modes Questionnaire was used to select informed person. The SPIKES was used to guide the disclosure procedures. The informed patients’ or caregivers’ quality of life were evaluated by the Generic Quality of Life Inventory-74 or Caregiver Quality of Life Scale before and after the cancer diagnosis disclosure and at the discharge time. After cancer diagnosis disclosure, no significant change was found on the quality of life of the informed person. With multiple psychological interventions implemented, a significant increase was noticed on the quality of life of the informed person. Applying the cancer diagnosis disclosure strategies and psychological intervention were essential to improve cancer patients’ and caregivers’ quality of life.

Background: Medical service prices play a crucial role in cost containment in China. This study aimed to assess the change in medical service price levels at the macro level and the relationship with relevant macroeconomic factors. Methods: Data from the 2022 China Statistics Yearbook, the 2022 China Health Statistics Yearbook, and the 2020 China National Health Accounts Report were used. Time trends of health price levels, utilization, and health expenditure were examined. A time-series regression model was employed to measure the impact of service utilization and medical service prices on total medical service expenditure growth from 2000 to 2021. The Johansen cointegration test was conducted to test the cointegrating relationship between medical service price levels and total medical service expenditure, average wage of employees and CPI. The Granger causality test was performed to observe the direction of causality. Results: Descriptive analyses showed consistent growth in utilization and medical service price levels from 2000 to 2021. The time-series model indicated that medical service expenditure was influenced by the rise in inpatient admissions and price levels of medical service and medicine. The Johansen cointegration test identified a long-term equilibrium relationship between medical service price levels and total medical service expenditure, average wage and CPI. The change in medical service price levels was the Granger cause of the change in medical service expenditure, but it had no impact on average wage and CPI. However, the change in medical service price levels was influenced by these three macroeconomic factors. Conclusions: The growth of medical service expenditure in China was driven by inpatient use and price level. There was a long-term equilibrium relationship between medical service price levels and relevant macroeconomic factors. However, medical service price levels only affected medical service expenditure and have no impact on average wage and CPI. It is necessary to improve the value transmission mechanism of medical service prices.

Background: Price differences of medical services across regions may affect equity in health financing. This study aimed to estimate the spatial price index of medical services to measure price levels across regions in the Yangtze River Delta, China. Methods: Gini-Éltetö-Köves-Szulc method and minimum spanning tree method based on the purchasing power parities were used in this study. Results: According to the Gini-Éltetö-Köves-Szulc method, Shanghai and Anhui province had price levels that are 127.55% and 103.45% respectively of the price level in Zhejiang province, whereas in Jiangsu medical services were priced at 92.71% of that in Zhejiang province. The spatial price index of medical services in the Yangtze River Delta based on the minimum spanning tree method provided similar results. Conclusions: Regions in the Yangtze River Delta had significant gaps in medical services price levels. And the price levels tended to not correlate with socioeconomic levels. It is necessary to promote the regional coordination of medical services price and better achieve equity in health.

Introduction: How the launch delay of drugs and other factors of interest can influence the length of the review period by drug agencies is still unknown, and understanding this can help better strike the trade-off related to review speed.Methods: We included all new oncology drug applications submitted to China’s National Medical Product Administration (NMPA) between 1 January 2018 and 31 December 2021, and ultimately succeeded in achieving marketing approval. For each drug, the length of the NMPA review process and other major characteristics were collected, including the registration class, approval class, priority review designation, and launch delay relative to the United States, as well as the number of patients enrolled, comparator, and primary endpoint of the pivotal trials supporting the approval. Linear regression model was employed to analyze the effects of factors of interest on the NMPA review time.Results: From 2018 to 2021, NMPA received 137 oncology applications that were ultimately approved. Half of the approvals [76 (55.5%)] were first licensed in the US, leaving a median launch delay of 2.71 years (IQR, 1.03–5.59) in China. In the pivotal studies, the median enrollment was 361 participants (IQR, 131–682), and the use of control groups [90 (65.7%)] and surrogate endpoints [101 (73.7%)] was prevalent. The median review time was 304 days (IQR, 253–376). Multivariate analysis for log-transformed review time showed that larger enrollment (> 92) was associated with a drop of 20.55% in review time (coefficient = −0.230; 95% CI, −0.404 to −0.055; p = 0.010); and a short delay (0 < delay ≤ 1.95 years) was associated with a drop of 17.63% in review time (coefficient = −0.194; 95% CI, −0.325 to −0.062; p = 0.004).Discussion: The short launch delay relative to the US was one important driver to the review speed of NMPA, which might suggest its latent regulatory reliance on the other global regulator during the post-marketing period when new information on the drug’s clinical benefit was still lacking.

Multimorbidity has emerged as a significant challenge for healthcare systems globally. This study aims to examine the associations between key determinants of lifestyle behavior and various multimorbidity patterns. In a cross-sectional sample of older adults (aged 60–79) from the Fifth National Physical Fitness Surveillance in Shanghai, latent class analysis (LCA) was used to identify multimorbidity patterns among 9 chronic diseases. Multinomial logistic regression was performed to analyze the associations between sedentary time, sleep duration, physical exercise, and the different multimorbidity patterns. Weighted analysis was performed to appropriately account for complex sampling designs and provide more robust results. Among 13,465 study participants (unweighted mean age 69.3 years; weighted mean age 67.4 years, 50.7% female), the overall prevalence of multimorbidity was 40.9%–42.3%. Four latent classes among the older adults were identified, with the relatively healthy class (63.6%–64.6%) had an average of less than 1 chronic disease. The other 3 classes, namely the metabolic-cardiovascular-joint-digestive-respiratory disease class (2.9%–3.0%), the metabolic-cardiovascular disease class (14.5%–15.5%), and the joint-digestive-respiratory disease class (17.9%–18.0%), each had an average of more than 2 chronic diseases, representing different multimorbidity patterns. Prolonged sedentary time (> 3 h/day) increased the odds of belonging to the metabolic-cardiovascular-joint-digestive-respiratory disease class by 56%–57% (unweighted odds ratio [OR] 1.57, 95% confidence interval [CI] 1.27–1.94; weighted OR 1.56, 95% CI 1.36–1.80), the metabolic-cardiovascular disease class by 38% (unweighted OR 1.38, 95% CI 1.25–1.53; weighted OR 1.38, 95% CI 1.29–1.48), and the joint-digestive-respiratory disease class by 30%–32% (unweighted OR 1.32, 95% CI 1.19–1.45; weighted OR 1.30, 95% CI 1.22–1.38). Shorter sleep duration (< 7 h/day) also increased the odds of membership in the metabolic-cardiovascular disease class by 48%–49% (unweighted OR 1.49, 95% CI 1.35–1.65; weighted OR 1.48, 95% CI 1.38–1.58), the metabolic-cardiovascular-joint-digestive-respiratory disease class by 37%–47% (unweighted OR 1.47, 95% CI 1.19–1.80; weighted OR 1.37, 95% CI 1.19–1.58), and the joint-digestive-respiratory disease class by 41%–42% (unweighted OR 1.42, 95% CI 1.29–1.56; weighted OR 1.41, 95% CI 1.32–1.50). Each additional daily hour of low-intensity physical exercise (LIPE) reduced the odds of membership in the metabolic-cardiovascular-joint-digestive-respiratory disease class by 24%–25% (unweighted OR 0.76, 95% CI 0.64–0.90; weighted OR 0.75, 95% CI 0.66–0.84), the joint-digestive-respiratory disease class by 20%–21% (unweighted OR 0.79, 95% CI 0.73–0.86; weighted OR 0.80, 95% CI 0.76–0.85), and the metabolic-cardiovascular disease class by 11%–12% (unweighted OR 0.88, 95% CI 0.81–0.95; weighted OR 0.89, 95% CI 0.85–0.94). Compared to LIPE, high-intensity physical exercise (HIPE) showed a significant advantage only in reducing the odds of the metabolic-cardiovascular disease class by 18%–23% (unweighted OR 0.77, 95% CI 0.62–0.97; weighted OR 0.82, 95% CI 0.71–0.95). Over 40% of older adults in Shanghai, China, suffer from multimorbidity. Prolonged sedentary behavior and shorter sleep duration were associated with membership in the metabolic-cardiovascular-joint-digestive-respiratory disease class, the metabolic-cardiovascular disease class, and the joint-digestive-respiratory disease class. Physical exercise showed varying degrees of protection against these 3 multimorbidity patterns, with special attention warranted for LIPE. Identifying the relationship between determinants of lifestyle behavior and patterns of multimorbidity can help develop more targeted prevention and management strategies.