Enhancing the accessibility and equity of primary healthcare (PHC) is a crucial objective of China’s healthcare reform. However, spatial barriers remain a significant factor contributing to the inequitable access to PHC services among residents. This study aims to quantify the spatial accessibility (SA) and evaluate the equity of PHC resources in a pilot province for healthcare reform, and its municipalities, thereby providing insights that can be generalized to the broader context of China. The study used the navigation function provided by Gaode Map to estimate the time it takes for residents to visit PHC institutions. The two-step floating catchment area (2SFCA) method, weighted by a Gaussian function, was employed to measure the SA of PHC institutions, general practitioners (GPs), and beds across various residential areas. The Gini coefficient was utilized to assess disparities in SA among different regions. Additionally, Getis-Ord Gi* analysis was conducted to visualize these spatial disparities. The study analyzed 25,601 residential and 1,451 healthcare points in Zhejiang Province, revealing significant disparities in SA of PHC. Urban residents reached PHC institutions faster than rural ones (7.05 ± 4.7 min vs. 9.17 ± 7.78 min, P < 0.001). Within 30 min, 98.4% of residential points and 99.1% of the population accessed PHC institutions. Disparities in PHC resources were notable, with Lishui having the highest SA for institutions and GPs, and Shaoxing for beds. Equity assessment showed high inequity for institutions (Gini 0.553), moderate for beds (Gini 0.497), and reasonable for GPs (Gini 0.332)​. Getis-Ord Gi* analysis demonstrated that areas further from urban centers were more likely to exhibit clusters of hotspots or cold spots. The study highlights substantial disparities in SA of PHC and equity across Zhejiang, underscoring the need for strategic resource distribution. Future research should include diverse transportation modes and more precise demand point data to enhance understanding of accessibility dynamics.

Background: To explore the key factors affecting prescription practices of essential medicines in Chinese county hospital. National essential medicine policy (NEMP) plays important roles in health care system, especially in developing countries. As a fundamental component in the Chinese health system reform, NEMP was implemented in primary health care institutions during the first stage of reform. As it is rolled out, priority usage and zero-mark-up policy of essential medicines are to be applied in every government-run healthcare institution. However, the intention and influence factors of physicians on priority selecting essential medicine remains unclear. Methods: Based on the theory of planned behavior, a cross-sectional questionnaire survey was conducted to analyze physicians’ intention, attitude, subjective norms (SNs) and perceived behavioral control (PBC) on prescrictions and their actual behavior on selection of essential medicines. Results: Two hundred eighty-two physicians participated in the structural questionnaire interview. The final structural equation model reflected influencing factors affecting physicians’ prescribing behavior (χ²/df = 1.32, GFI = 0.99, IFI = 0.99). Structural equation model analysis showed that attitude, other influencers and institutional environment, and PBC significantly affected behavioral intention. However, the control extent of cognition behavior of physicians prescribing had no significant positive effect on the priority usage of essential medicines. Conclusion: Investigation results demonstrate physicians are unaware of NEMP design and implementation plans. To help enhance rational use of essential medicines we suggest educating physicians on the value of NEMP, and integrating the drug shortage report into the essential medicine (EM) bidding system seamless communication with pharmaceutical manufacturers’ credit information system.

Background: The lack of medication standards is a serious problem in paediatrics mainly because of age-related differences in organ development and physiological functions in children. Consequently, dosage measurement becomes inaccurate. For this reason, methods for evaluating and monitoring rational paediatric medications should be developed. Drug use indicators, such as those similar to the drug utilisation index (DUI) based on the Anatomical Therapeutic Chemical/Defined Daily Dose (DDD) and widely used for the assessment of appropriate dosage in adults, should be explored in terms of their applicability to children. Methods: A total of 5,538 prescriptions of antibiotics selected from a general teaching hospital were included. Drug, dose, frequency and treatment duration were obtained from each prescription. The prescription daily dose (PDD) of each antibiotic drug was calculated as the average of the daily doses. Underdose and overdose were determined in terms of the PDD/DDD ratio for each prescription. Children’s DUI (cDUI) was explored in terms of the appropriate dosage for children as follows: the meaning of children’s DDD (cDDD) and the evaluation of paediatric drug dosage. Results: The top five antibiotics and their utilisation rates were as follows: cefmetazole sodium injection (18.47 %), erythromycin lactobionate injection (15.07 %), amoxicillin/clavulanate potassium injection (10.72 %), ceftriaxone sodium injection (9.50 %) and azithromycin dry suspension (8.02 %). The ratio of cDUI and PDD/cDDD was mostly not close to 1. Conclusions: The establishment of a cDUI system is an effective means of paediatric dosage evaluation. In addition to DDDs, cDUI and PDD/cDDD should be used to analyse the utilisation of antibiotics in children.

Objectives To describe the incidence and types of medication errors occurring during the transfer of patients from the intensive care unit (ICU) to the non-ICU setting and explore the key factors affecting medication safety in transfer care. Design Multicentre, retrospective, epidemiological study. Participants Patients transferred from the ICU to a non-ICU setting between 1 July 2019 and 30 June 2020. Main outcome measures Incidence and types of medication errors. Results Of the 1546 patients transferred during the study period, 899 (58.15%) had at least one medication error. Most errors (83.00%) were National Coordinating Council (NCC) for Medication Error Reporting and Prevention (MERP) category C. A small number of errors (17.00%) were category D. Among patients with medication errors, there was an average of 1.68 (SD, 0.90; range, 1–5) errors per patient. The most common types of errors were route of administration 570 (37.85%), dosage 271 (17.99%) and frequency 139 (9.23%). Eighty-three per cent of medication errors reached patients but did not cause harm. Daytime ICU transfer (07:00–14:59) and an admission diagnosis of severe kidney disease were found to be factors associated with the occurrence of medication errors as compared with the reference category (OR, 1.40; 95% CI 1.01 to 1.95; OR, 6.78; 95% CI 1.46 to 31.60, respectively).Orders for bronchorespiratory (OR, 5.92; 95% CI 4.2 to 8.32), cardiovascular (OR, 1.91; 95% CI 1.34 to 2.73), hepatic (OR, 1.95; 95% CI 1.30 to 2.91), endocrine (OR, 1.99; 95% CI 1.37 to 2.91), haematologic (OR, 2.58; 95% CI 1.84 to 3.64), anti-inflammatory/pain (OR, 2.80; 95% CI 1.90 to 4.12) and vitamin (OR, 1.73; 95% CI 1.26 to 2.37) medications at transition of care were associated with an increased odds of medication error. Conclusions More than half of ICU patients experienced medication errors during the transition of care. The vast majority of medication errors reached the patient but did not cause harm.

Aim: Modified electroconvulsive therapy (MECT) is an effective strategy for treatment-resistant depression (TRD); however, the mechanism underlying effects of MECT remains unclear. Accumulating evidence suggests that TRD is closely associated with dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis, anorexigenic peptides, and pro-inflammatory cytokines. However, MECT effects on the HPA axis, anorexigenic peptides, and pro-inflammatory cytokines in elderly patients with TRD remain unclear. In this study, we investigated whether the HPA axis (cortisol), anorexigenic peptides (nesfatin-1), and pro-inflammatory cytokines (C-reactive protein, tumor necrosis factor-α, and interleukin-6, and interleukin-1β) are involved in the mechanism underlying MECT effects in elderly patients with TRD.Methods: Elderly patients with TRD were enrolled in this study between December 2019 and October 2021; all patients underwent MECT after physical examination. Serum cortisol, nesfatin-1, and pro-inflammatory cytokine levels were measured before and after the first, third, and sixth MECT sessions. The Hamilton Depression Rating Scale-24 (HAMD-24) and the Mini-Mental State Examination (MMSE) were used to evaluate depression and cognitive impairment, respectively. We compared pre- and post-MECT serum cortisol, nesfatin-1, and pro-inflammatory cytokine levels to confirm the short-term effects of MECT on these serum indices. We compared these serum indices across three time points (before the first, third, and sixth MECT sessions) to determine the long-term effects of MECT on serum cortisol, nesfatin-1, and pro-inflammatory cytokine levels.Results: We observed no statistically significant changes in the pre- and post-MECT serum cortisol, nesfatin-1, or pro-inflammatory cytokine levels. No significant changes in serum cortisol, nesfatin-1, and pro-inflammatory cytokine levels were observed across the aforementioned time points. Moreover, there were no statistically significant sex-based differences in the aforementioned serum indices. Furthermore, the serum cortisol level was negatively correlated with the serum IL-6 level before and after the first MECT session in patients with high cortisol levels (> the 50^th percentile value of all samples). Additionally, the post-MECT HAMD-24 and MMSE scores were significantly lower.Conclusions: MECT reduced depressive symptoms despite an adverse effect on cognition and had no significant effect on the serum cortisol, nesfatin-1, and pro-inflammatory cytokine levels in elderly patients with TRD.