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Objective:To analyze consecutive patients visits in a community health service station in Beijing.Methods:The basic information and behavior of the patients who visited Sanliheerqu Health Service Station in Beijing Xicheng district from January 1, 2015 to December 31, 2019 were retrieved from the electronic health records. The visiting situation, the stratification of the number of visits, and the correlation between the basic information and the consecutive visit was analyzed.Results:A total of 4 696 patients visited 202 560 times during 2015 to 2019, of whom 1 162 were consecutive patients (24.7%) with a total of 100 083 visits (49.4%).The annual number of visits, the total number of visits and the number of consecutive visits all showed an upward trend during the five years.The top 5 reasons for consecutive visit were all chronic diseases (hypertension, type 2 diabetes, dyslipidemia, coronary heart disease, and stroke) with median annual visits of 11 to 18, and it was increasing with the year. The rates of incidental visits (1-3/year, 66/1 162, 5.7%) and continuous visits (4-26/year, 1 020/1 162, 87.8%) in 2015 were higher than those in other years; while the rates of frequent visits (27-52/year, 71/1 162, 6.1%) and very frequent visits (>52/year, 5/1 162, 0.4%) were lower. The rates of frequent visits (181/1 162, 15.6%) and very frequent visits (78/1 162, 6.7%) in 2019 were higher than those in other years (χ 2=182.40, P<0.001).Compared with the non-consecutive visit group, the proportion of women (38.1%,735/1 930) and overweight/obesity (39.6%, 777/1 960) in the consecutive visit group was higher (χ 2=36.09, 69.69, P <0.001). Conclusion:The consecutive visit rate of residents in this institution needs to be improved. The utilization rate of primary medical resources for patients with consecutive visit is high and the number of medical visits is on the rise. Gender and BMI of patients may be related to consecutive visit.
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Objective To investigate the influence of meteorological factors on the number of patients and the time patients visiting the emergency department for medical care.Methods The data of meteorological variation and air pollution associated with the characteristics of distribution of time when the patients visited the emergency department in a tertiary grade A class hospital in Shanghai were collected in 2016.Quasi Poisson generalized additive model (GAM) applied for time series analysis was used to find the correlation between daily temperature and number of patients visiting emergency department,and with the distributed lag nonlinear model (DLNM) the relationship between the temperature and humidity was established and the confounding factors related with time visiting the emergency department was controlled in this model.Results In 2016,the average number of emergency visits in a tertiary grade A class hospital in Shanghai was 1027.The peak flow of patients occurred between 18:00 to-22:00 and trough emerged between 2:00 to-8:00.The number of visits in winter was greater than that in spring and autumn,and the number of patients on weekends and holidays was more than that on weekdays.The response of temperature exposure to the change of emergency volume in the hospital showed a J shape distribution.The low temperature and high temperature caused increase in visits,and the low temperature effect could last more than 2 weeks.The lowest number of visits occurred when the temperature (that is the lowest suitable temperature for medical treatment) was about 7 degrees Celsius,and the daily number of patients in emergency internal medicine was increased to 1.09 times (95％CI:1.03～1.16) compared with the optimum temperature.Compared with the optimum temperature,the daily visits increased to 1.27 times (95％CI:1.08～1.50) in the highest temperature.When the suitable temperature decreased by 1 degree,the visiting quantity increased by 2.43％ (95％CI:0.83％～4.18％),and the number of visits increased by 0.96％ (95％CI:0.31％～1.64％) every 1 degree rise.Conclusions There was a difference in the number of emergency visits between different times,and low temperature and high temperature had an obvious influence on the amount of emergency visits,and the effect of low temperature on the volume of visits was more lasting.
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The self-book renewing information in medical library was classified, which showed that the 3 months in a year and the period in a day with the largest number of readers who visited the medical library Website were characterized by their rigid need. In addition, the evidence was provided for the issuing time of information on li-brary information issuing platform in order to optimize the popularizing effect of library.