Patients' Willingness of First Visit in Primary Medical Institutions and Policy Implications: A National Cross-Sectional Survey in China

Quality and Dependability of ChatGPT and DingXiangYuan Forums for Remote Orthopedic Consultations: Comparative Analysis

BACKGROUND

The widespread use of artificial intelligence, such as ChatGPT (OpenAI), is transforming sectors, including health care, while separate advancements of the internet have enabled platforms such as China's DingXiangYuan to offer remote medical services.

OBJECTIVE

This study evaluates ChatGPT-4's responses against those of professional health care providers in telemedicine, assessing artificial intelligence's capability to support the surge in remote medical consultations and its impact on health care delivery.

METHODS

We sourced remote orthopedic consultations from "Doctor DingXiang," with responses from its certified physicians as the control and ChatGPT's responses as the experimental group. In all, 3 blindfolded, experienced orthopedic surgeons assessed responses against 7 criteria: "logical reasoning," "internal information," "external information," "guiding function," "therapeutic effect," "medical knowledge popularization education," and "overall satisfaction." We used Fleiss κ to measure agreement among multiple raters.

RESULTS

Initially, consultation records for a cumulative count of 8 maladies (equivalent to 800 cases) were gathered. We ultimately included 73 consultation records by May 2023, following primary and rescreening, in which no communication records containing private information, images, or voice messages were transmitted. After statistical scoring, we discovered that ChatGPT's "internal information" score (mean 4.61, SD 0.52 points vs mean 4.66, SD 0.49 points; P=.43) and "therapeutic effect" score (mean 4.43, SD 0.75 points vs mean 4.55, SD 0.62 points; P=.32) were lower than those of the control group, but the differences were not statistically significant. ChatGPT showed better performance with a higher "logical reasoning" score (mean 4.81, SD 0.36 points vs mean 4.75, SD 0.39 points; P=.38), "external information" score (mean 4.06, SD 0.72 points vs mean 3.92, SD 0.77 points; P=.25), and "guiding function" score (mean 4.73, SD 0.51 points vs mean 4.72, SD 0.54 points; P=.96), although the differences were not statistically significant. Meanwhile, the "medical knowledge popularization education" score of ChatGPT was better than that of the control group (mean 4.49, SD 0.67 points vs mean 3.87, SD 1.01 points; P<.001), and the difference was statistically significant. In terms of "overall satisfaction," the difference was not statistically significant between the groups (mean 8.35, SD 1.38 points vs mean 8.37, SD 1.24 points; P=.92). According to how Fleiss κ values were interpreted, 6 of the control group's score points were classified as displaying "fair agreement" (P<.001), and 1 was classified as showing "substantial agreement" (P<.001). In the experimental group, 3 points were classified as indicating "fair agreement," while 4 suggested "moderate agreement" (P<.001).

CONCLUSIONS

ChatGPT-4 matches the expertise found in DingXiangYuan forums' paid consultations, excelling particularly in scientific education. It presents a promising alternative for remote health advice. For health care professionals, it could act as an aid in patient education, while patients may use it as a convenient tool for health inquiries.

Effects of medical consortium policy on health services: an interrupted time-series analysis in Sanming, China

Objectives

China has implemented reforms to enhance the operational efficiency of three-level medical services through medical consortiums (MCs). This study evaluated the impact of MCs reform on health services in Sanming, China.

Methods

An interrupted time-series analysis (ITSA) was conducted to assess the impact of MCs on changes in health service levels and trends across the overall situation of MCs and different institutional types within MCs, including county hospitals and grassroots medical institutions. The evaluation focused on various indicators such as outpatient and emergency visits, inpatients, average length of stay, occupancy rate of hospital beds, and hospital bed turnover times. Monthly data were collected from April 2015 to June 2019 through reports on the Sanming Municipal Health Commission website and the Sanming public hospital management monitoring platform.

Results

After the intervention of MCs reform, a significant increase was observed in the total number of inpatients (β3 = 174.28, p < 0.05). However, no statistically significant change was observed in the total number of outpatient and emergency visits (β3 = 155.82, p = 0.91). Additionally, the implementation of MCs reform led to an amplification in service volumes provided by county hospitals, with significant increases in the number of outpatient and emergency visits (β3 = 1376.54, p < 0.05) and an upward trend in the number of inpatients (β3 = 98.87, p < 0.01). However, no significant changes were observed under the MCs policy for grassroots medical institutions regarding the number of outpatient and emergency visits (β3 = -1220.72, p = 0.22) and number of inpatients (β3 = 75.42, p = 0.09).

Conclusion

The Sanming MCs reform has achieved some progress in augmenting service volumes. Nevertheless, it has not led to an increase in service volumes at the grassroots medical institutions. There persists an insufficiency in the efficiency of services and a need for further improvement in primary healthcare. To address these concerns, it is imperative for county hospitals to offer targeted assistance that can enhance motivation among grassroots medical institutions. Besides the MCs should explore initiatives, including improved management of medical equipment, allocation of funding, and personnel resources.

The relationship between individual-level socioeconomic status and preference for medical service in primary health institutions: a cross-sectional study in Jiangsu, China

Background

While China's primary health care (PHC) system covers all citizens, the use of medical services supplied by primary health institutions (PHIs) is not at ideal levels. This study explored the impact of socioeconomic status (SES) on residents' first choice of medical services provided by PHIs.

Methods

This community-based, cross-sectional study was conducted in Jiangsu Province, China, from October 2021 to March 2022. A custom-designed questionnaire was used to evaluate 4,257 adults, of whom 1,417 chose to visit a doctor when they were sick. Logistic regression was used to test the relationships among SES, other variables and the choice of medical services, and interaction effects were explored.

Results

A total of 1,417 subjects were included in this study (48.7% female; mean age 44.41 ± 17.1 years). The results showed that older age (p < 0.01), rural residence (p < 0.01), a preference for part-time medical experts in PHIs (p < 0.01), and lack of coverage by basic medical insurance (p < 0.05) were associated with the first choice to use PHIs. In the multiple logistic regression model, SES was not associated with the first choice of medical services supplied by PHIs (p > 0.05), but it interacted with three variables from the Commission on Social Determinants of Health Framework (material circumstances, behaviors and biological factors, and psychosocial factors).

Conclusion

Vulnerable individuals who are the target visitors to PHIs are older, live in rural areas, and suffer from chronic diseases. SES, as a single factor, did not impact whether medical services at PHIs were preferred, but it mediated relationships with other factors.

Variation in quality of care by medical institute level in China: a systematic review protocol

INTRODUCTION

Quality variation has been widely witnessed and discussed in China. However, limited evidence reveals quality gaps by the medical institute level, especially between hospitals and primary care institutes. This systematic review will synthesise the available evidence on quality variation between medical institutes at different levels in China. By adopting a quality framework, we will also explore the detailed domains (structure, process and outcomes) and dimensions (safety, effectiveness, timeliness, patient-centredness, efficiency, integration and equity) of quality gaps.

METHODS AND ANALYSIS

An extensive literature search will be conducted on eight key electronic databases: MEDLINE, Web of Science, Cochrane Library, Scopus, EMBASE, ProQuest, China National Knowledge Infrastructure and WANFANG database. The Grey Matter Checklist will be used to screen relevant grey literature. The publication time limit should be before 31 December 2022 when we plan to conduct a literature search. All kinds of studies that revealed the quality difference between medical institutes at different levels will be included, no matter if quality improvement intervention is involved. All quality measures and indicators will be recorded and sorted into appropriate domains and dimensions. For those studies that took the completion rate of standard operations to assess the quality, we will also record the name of the clinical pathways, guidelines or checklists used. Two reviewers will independently perform the study selection, data extraction and quality assessment process. A narrative or quantitative synthesis will be performed based on the available data.

ETHICS AND DISSEMINATION

Ethics approval is not applicable. The results of this study will be submitted to a widely accepted peer-review journal. The findings will also be used to inform administration about quality gaps by different medical institute levels and, therefore, help them to design policies that will minimise the quality variation.

PROSPERO REGISTRATION NUMBER

CRD42022345933.

Coping with COVID: Performance of China's hierarchical medical system during the COVID-19 pandemic

Objective

The COVID-19 pandemic has challenged the health system worldwide. This study aimed to assess how China's hierarchical medical system (HMS) coped with COVID-19 in the short-and medium-term. We mainly measured the number and distribution of hospital visits and healthcare expenditure between primary and high-level hospitals during Beijing's 2020-2021 pandemic relative to the 2017-2019 pre-COVID-19 benchmark period.

Methods

Hospital operational data were extracted from Municipal Health Statistics Information Platform. The COVID-19 period in Beijing was divided into five phases, corresponding to different characteristics, from January 2020 to October 2021. The main outcome measures in this study include the percentage change in inpatient and outpatient emergency visits, and surgeries, and changing distribution of patients between different hospital levels across Beijing's HMS. In addition, the corresponding health expenditure in each of the 5 phases of COVID-19 was also included.

Results

In the outbreak phase of the pandemic, the total visits of Beijing hospitals declined dramatically, where outpatient visits fell 44.6%, inpatients visits fell 47.9%; emergency visits fell 35.6%, and surgery inpatients fell 44.5%. Correspondingly, health expenditures declined 30.5% for outpatients and 43.0% for inpatients. The primary hospitals absorbed a 9.51% higher proportion of outpatients than the pre-COVID-19 level in phase 1. In phase 4, the number of patients, including non-local outpatients reached pre-pandemic 2017-2019 benchmark levels. The proportion of outpatients in primary hospitals was only 1.74% above pre-COVID-19 levels in phases 4 and 5. Health expenditure for both outpatients and inpatients reached the baseline level in phase 3 and increased nearly 10% above pre-COVID-19 levels in phases 4 and 5.

Conclusion

The HMS in Beijing coped with the COVID-19 pandemic in a relatively short time, the early stage of the pandemic reflected an enhanced role for primary hospitals in the HMS, but did not permanently change patient preferences for high-level hospitals. Relative to the pre-COVID-19 benchmark, the elevated hospital expenditure in phase 4 and phase 5 pointed to hospital over-treatment or patient excess treatment demand. We suggest improving the service capacity of primary hospitals and changing the preferences of patients through health education in the post-COVID-19 world.

How to Make Primary Healthcare More Popular: Evidence from the Middle-Aged and Elderly in China

Since 2001, China has been an aging society; it is expected to become superaged by 2033. This rapid aging trend poses a challenge to the elderly regarding their pension services and healthcare. Primary healthcare has great potential for serving older adults in the community, yet it is not popular. This study used 1977 samples from the 2018 China Health and Retirement Longitudinal Study database to explore the use of outpatient services in primary care institutions among the middle-aged and elderly. Using a structural equations model, we constructed a framework to explore pathways leading to primary outpatient use. We discovered that the supply of primary health services had a significant direct and mediating effect on the utilization of primary outpatient services, and that community pension services may indirectly discourage it. In addition, the supply of primary health services has a suppressor effect between medical insurance and primary outpatient utilization. Health insurance directly promotes primary outpatient utilization, while the supply of primary care institutions suppresses the positive influence of medical insurance on the utilization of primary outpatient services. Therefore, community pension services should pay attention to differentiated services. Moreover, adjusting the coordinated development of medical insurance and the supply of primary healthcare could enhance the positive effects of medical insurance for outpatients.