Background The COVID-19 pandemic has become a global public health event, attracting worldwide attention. As a tool to monitor public awareness, internet search engines have been widely used in public health emergencies. Objective This study aims to use online search data (Baidu Index) to monitor the public’s attention and verify internet search engines’ function in public attention monitoring of public health emergencies. Methods We collected the Baidu Index and the case monitoring data from January 20, 2020, to April 20, 2020. We combined the Baidu Index of keywords related to COVID-19 to describe the public attention’s temporal trend and spatial distribution, and conducted the time lag cross-correlation analysis. Results The Baidu Index temporal trend indicated that the changes of the Baidu Index had a clear correspondence with the development time node of the pandemic. The Baidu Index spatial distribution showed that in the regions of central and eastern China, with denser populations, larger internet user bases, and higher economic development levels, the public was more concerned about COVID-19. In addition, the Baidu Index was significantly correlated with six case indicators of new confirmed cases, new death cases, new cured discharge cases, cumulative confirmed cases, cumulative death cases, and cumulative cured discharge cases. Moreover, the Baidu Index was 0-4 days earlier than new confirmed and new death cases, and about 20 days earlier than new cured and discharged cases while 3-5 days later than the change of cumulative cases. Conclusions The national public’s demand for epidemic information is urgent regardless of whether it is located in the hardest hit area. The public was more sensitive to the daily new case data that represents the progress of the epidemic, but the public’s attention to the epidemic situation in other areas may lag behind. We could set the Baidu Index as the sentinel and the database in the online infoveillance system for infectious disease and public health emergencies. According to the monitoring data, the government needs to prevent and control the possible outbreak in advance and communicate the risks to the public so as to ensure the physical and psychological health of the public in the epidemic.

ObjectivesThe internet data is an essential tool for reflecting public attention to hot issues. This study aimed to use the Baidu Index (BDI) and Sina Micro Index (SMI) to confirm correlation between COVID-19 case data and Chinese online data (public attention). This could verify the effect of online data on early warning of public health events, which will enable us to respond in a more timely and effective manner.MethodsSpearman correlation was used to check the consistency of BDI and SMI. Time lag cross-correlation analysis of BDI, SMI and six case-related indicators and multiple linear regression prediction were performed to explore the correlation between public concern and the actual epidemic.ResultsThe public's usage trend of the Baidu search engine and Sina Weibo was consistent during the COVID-19 outbreak. BDI, SMI and COVID-19 indicators had significant advance or lag effects, among which SMI and six indicators all had advance effects while BDI only had advance effects with new confirmed cases and new death cases. But compared with the SMI, the BDI was more closely related to the epidemic severity. Notably, the prediction model constructed by BDI and SMI can well fit new confirmed cases and new death cases.ConclusionsThe confirmed associations between the public's attention to the outbreak of COVID and the trend of epidemic outbreaks implied valuable insights into effective mechanisms of crisis response. In response to public health emergencies, people can through the information recommendation functions of social media and search engines (such as Weibo hot search and Baidu homepage recommendation) to raise awareness of available disease prevention and treatment, health services, and policy change.

Background The WeChat platform has become a primary source for medical information in China. However, no study has been conducted to explore the quality of information on WeChat for the treatment of hypertension, the leading chronic condition. Objective This study aimed to explore the quality of information in articles on WeChat that are related to hypertension treatment from the aspects of credibility, concreteness, accuracy, and completeness. Methods We searched for all information related to hypertension treatment on WeChat based on several inclusion and exclusion criteria. We used 2 tools to evaluate information quality, and 2 independent reviewers performed the assessment with the 2 tools separately. First, we adopted the DISCERN instrument to assess the credibility and concreteness of the treatment information, with the outcomes classified into five grades: excellent, good, fair, poor, and very poor. Second, we applied the Chinese Guidelines for Prevention and Treatment of Hypertension (2018 edition) to evaluate the accuracy and completeness of the article information with regard to specific medical content. Third, we combined the results from the 2 assessments to arrive at the overall quality of the articles and explored the differences between, and associations of, the 2 independent assessments. Results Of the 223 articles that were retrieved, 130 (58.3%) full texts were included. Of these 130 articles, 81 (62.3%) described therapeutic measures for hypertension. The assessment based on the DISCERN instrument reported a mean score of 31.22 (SD 8.46). There were no articles rated excellent (mean score >63); most (111/130, 85.4%) of the articles did not refer to the consequences—in particular, quality of life—of no treatment. For specific medical content, adherence to the Chinese Guidelines for Prevention and Treatment of Hypertension was generally low in terms of accuracy and completeness, and there was much erroneous information. The overall mean quality score was 10.18 (SD 2.22) for the 130 articles, and the scores differed significantly across the 3 types (P=.03) and 5 sources (P=.02). Articles with references achieved higher scores for quality than those reporting none (P<.001). The results from the DISCERN assessment and the medical content scores were highly correlated (ρ=0.58; P<.001). Conclusions The quality of hypertension treatment–related information on the WeChat platform is low. Future work is warranted to regulate information sources and strengthen references. For the treatment of hypertension, crucial information on the consequences of no treatment is urgently needed.

BACKGROUND The outbreak of the COVID-19 epidemic in 2019 exerted an enormous global public reaction. OBJECTIVE The online big data reflects public attention of hot issues. This study aimed to use the Baidu Index (BDI) and Sina Micro Index (SMI) to confirm the primitive correlation between COVID-19 related data and Chinese online data. METHODS Bivariate correlation statistics was used to check the relationship between epidemic trends of the BDI and SMI, and identify the difference of public concerns about COVID-19 between the epidemic area (Hubei province) and non-epidemic area (all other provinces). RESULTS The public's usage trend of the Baidu search engine and Sina Weibo was consistent during the COVID-19 outbreak (Pearson correlation coefficient =0.807, P<0.001). But compared with the SMI, the BDI was more closely related to the actual epidemic. The BDI and SMI had correlations with new confirmed cases (P<0.01), cumulative confirmed cases (P<0.01), cumulative death cases (P<0.01), new cured discharged cases (P<0.01), and cumulative cured discharged cases (P<0.01), but not with new death cases. Besides, the public's demand for information on COVID-19 was consistent and urgent across the country (Spearman correlation coefficient=0.930, P<0.001), regardless of the location of the epidemic area. CONCLUSIONS The public paid more attention to indicators of confirmed cases due to numerous irresistible factors and cured circumstances with positive outcomes. But the public had a lag in the attention of COVID-19 in the non-epidemic area. In the risk communication of public health emergencies, relevant departments can effectively use the information dissemination characteristics of the Baidu search engine and Sina Weibo, to convey front-line information to the public timely and accurately, and improve the effectiveness of risk communication.

BACKGROUND The COVID-19 pandemic has become a major global public health event, attracting worldwide public attention. As a tool to monitor public awareness, the internet search engine has been widely used in public health emergencies. OBJECTIVE This study aimed to use online search data (Baidu Index) to monitor the public's attention and verify internet search engines' function in public attention monitoring of public health emergencies. METHODS We collected the Baidu Index and the case monitoring data from January 20, 2020, to April 20, 2020. We combined Baidu Index of keywords related to COVID-19 to describe public attention's temporal trend and spatial distribution and conducted the time lag cross-correlation analysis. RESULTS Baidu Index temporal trend indicated that the changes of Baidu Index had a clear correspondence with the development time node of pandemic. Baidu Index spatial distribution showed that in the regions of central and eastern China with denser populations, larger internet user bases, and higher economic development levels, the public was more concerned about COVID-19. Also, Baidu Index was significantly correlated with six case indicators of new confirmed cases, new death cases, new cured discharge cases, cumulative confirmed cases, cumulative death cases, and cumulative cured discharge cases. Moreover, Baidu Index was 0-4 days earlier than new confirmed and new death cases, and about 20 days earlier than new cured and discharged cases, while 3-5 days later than the change of three cumulative cases. CONCLUSIONS The national public's demand for epidemic information is urgent regardless of whether it is located in the hardest hit area. The public was more sensitive to the daily new case data that represents the progress of the epidemic, but the public's attention to the epidemic situation in other areas may lag behind. We could set Baidu Index as the sentinel and the database in the online surveillance system for infectious disease and public health emergencies. According to the monitoring data, the government need to prevent and control the possible outbreak in advance and communicate the risks to the public, so as to ensure the physical and psychological health of the public in the epidemic.

Objectives: Discuss the experience and practice of multidisciplinary cooperation of diabetic foot in China and analyze its impact on the quality of care.Methods: This study observed the medical procedure by interviewing 12 key personnel in-depth. We extracted data from medical records and assessed the effect of MDT in three dimensions: quality, efficiency, and cost, to eventually achieve a final conclusion.Results: The studied reform includes the following three aspects: the adjustment of hospital buildings layout and disciplines, one-stop outpatient, and one-stop inpatient service. After the multidisciplinary collaboration, the rate of above-knee amputation is reduced by 3.63%, the disability score per 100 diabetic foot patients decreases by 6.12, the average length of stay decreases significantly, and the cost of hospitalization shows an increasing trend.Conclusions: Multidisciplinary collaboration is performed based on spatial layout adjustment and clinical pathway optimization, which provide more comprehensive and integrated care than a general medical team or a single specialist, thereby reducing the rate of disability, shortening the length of hospitalization. Besides, the new measurable indicator called disability score per 100 diabetic foot patients has been verified to evaluate the living ability of patients after surgery. This paper provides a reference for organizational reform of multidisciplinary diseases to support treatment and management of other multiorgan diseases.