Analysis of Medication Utilization in Isolated Areas of Fever Clinics During the COVID-19 Epidemic Outbreak: A Multicenter Study in General Hospitals in China

Analysis of Medication Utilization in Isolated Areas of Fever Clinics During the COVID-19 Epidemic Outbreak: A Multicenter Study in General Hospitals in China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysis of Medication Utilization in Isolated Areas of Fever Clinics During the COVID-19 Epidemic Outbreak: A Multicenter Study in General Hospitals in China Zhiqing Zhang, Yaru Zang, Jingyi Yang, Kaining Yang, Yue Zhao, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3908849/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: To analyze the demographic characteristics and patterns of medication use among patients in fever clinics (FCs) during the COVID-19 outbreak in China and provide information for COVID-19 treatment. Method : Various-grade general hospitals in China were selected, and patient information was extracted during the initial wave of the COVID-19 epidemic. Demographic characteristics were analyzed, including visit time, age, sampling morbidity rate, and disease distribution. Prescription information from the FC database was extracted to analyze drug use and the rationality of the medication. Result: Between September 1 and December 31, 2022, 41,445 patients received treatment at FCs in 11 included hospitals. After the relaxation of COVID-19 control measures, there was a rapid increase in the number of daily patient visits (peaking >1,000 people/day, with a growth rate of 158.8%). The highest sampling morbidity rate was observed among individuals over 85 years old (>100 person-times/million population), followed by children (60-94 person-times/million population). Respiratory system diseases (39,295 cases) were the most diagnosed, with respiratory system infections (21,201 cases) and fever (15,132 cases) the most common. The proportion and frequency of use of essential national drugs were 34.3% and 73.1%, respectively, while those for the drugs recommended in the national COVID-19 treatment guidelines were 6.1% and 43.2%, respectively. Ibuprofen, acetaminophen, and Lianhua Qingwen had the highest frequency of drug use. The most prescribed drugs by cost were immunoglobulin, azivudine, and cefoperazone sulbactam. The water-electrolyte balance regulator drugs, respiratory system drugs, anti-infective drugs, and traditional Chinese patent drugs were the most frequently used. In contrast, immunomodulators, anti-infectives, and Chinese patent drugs had the largest monetary amounts. There was a significant difference in medication rationality between different hospital grades (P<0.001), with tertiary teaching hospitals having the highest rate. Conclusion: Strict epidemic control measures and the role of FCs played a crucial role in controlling the spread of the COVID-19 epidemic. Patients treated in FCs predominantly suffered from respiratory diseases, with older patients and children identified as high-risk populations. Physicians often choose national guidelines, essential drugs, and traditional Chinese for COVID-19 treatment. Tertiary teaching hospitals played a crucial role during the epidemic outbreak. COVID-19 Fever Clinics Isolated Area Demographic Characteristics Medication Use Multicenter Study Figures Figure 1 Figure 2 Figure 3 Introduction COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first identified in December 2019 and quickly became a global pandemic. In August 2023, worldwide COVID-19 infections had surpassed 769 million, resulting in approximately 6.955 million deaths [ 1 , 2 ]. Most COVID-19 patients receive outpatient treatment, while some require hospitalization or succumb to the progression of the disease [ 3 , 4 ]. During the initial global outbreak, the mortality rate among hospitalized patients ranged from 16.4–32.3% [ 5 ]. The primary approach to epidemic prevention and control is to implement effective measures to curb the spread of COVID-19 [ 6 ]. Experience has shown that maintaining social distancing, wearing masks, and contact tracing are fundamental public health strategies to reduce virus transmission [ 7 , 8 ]. Vaccination is another potent tool for infection prevention, significantly decreasing infection rates, severe cases, and mortality among the population [ 9 , 10 ]. In China, an effective strategy to control COVID-19 transmission within hospitals involves establishing isolated areas known as outpatient fever clinics (FCs) in health facilities. Preventing hospital-acquired infections is a crucial aspect of the clinical management of COVID-19 [ 11 ]. This outbreak is caused by SARS-CoV-2, which belongs to the same family of viruses as Severe Acute Respiratory Syndrome (SARS) and Middle Eastern Respiratory Syndrome (MERS) [ 12 , 13 ]. During the 2003 SARS outbreak in China, FCs were established, independent units designed to isolate infected or suspected patients by providing dedicated consultation channels, effectively preventing the spread of infection. Following the outbreak of COVID-19, the China National Health Commission recommended upgrading and renovating the outpatient FCs established during the SARS outbreak for COVID-19 screening [ 14 ]. During the COVID-19 epidemic in China, confirmed cases of COVID-19 were centralized and managed by designated medical institutions. The fever clinics in large, comprehensive hospitals served as dedicated channels for COVID-19 screening, isolation, and diagnosis. They played a crucial role in early detection, isolation, and treatment, serving as a critical strategy in combating nosocomial transmission and epidemic spread [ 15 ]. Due to the highly contagious nature of COVID-19, the medical personnel in FCs have been tirelessly working on the frontlines of epidemic prevention and control. Their daily tasks are demanding, and they have endured significant physical and psychological stress, increasing the risk of medical errors [ 16 , 17 ]. On the other hand, fever patients are a primary focus of clinical surveillance during the COVID-19 epidemic, increasing emphasis on patient treatment and intervention has also placed a considerable psychological burden on patients. Patients and their families are more concerned about medical safety, and medication safety is becoming a focal point [ 18 ]. However, research on medication safety in FCs has not yet received sufficient attention from the academic community. This study selected comprehensive hospitals of different grades in China and extracted patient information from their FCs during the outbreak period of the COVID-19 epidemic. The analysis focused on the demographic characteristics of the patients, the distribution of the disease, and the use of medications. This research aimed to provide valuable information for the treatment and rational use of drugs in COVID-19. Methods Study design This cross-sectional study was conducted in three tertiary teaching hospitals, three tertiary general hospitals, and five secondary general hospitals in China. The study period was during the initial wave of the COVID-19 epidemic in China from September 1 to December 31, 2022. Ethical approval was granted by the Ethics Committee of the Second Hospital of Hebei Medical University, which served as the leading institution (approval number 2022-C055). Other research centers followed the central ethics approval. Informed consent was obtained from all subjects and/or their legal guardians. Inclusion and exclusion criteria of prescriptions Only complete prescriptions were analyzed. A prescription is deemed complete when it has the following details: 1) heading (medical institution name, prescription number, patient's name, sex, age, department, clinical diagnosis, and issue date); 2) body (drug name, specifications, quantity, dosage, and administration); and 3) footer (physician's signature or seal, drug cost, signature of the prescription-reviewing pharmacist, and signature of the dispensing pharmacist). Prescriptions were excluded if they contained information that could not be recognized or had errors in the prescription information. Data collection Data were obtained from the hospital information systems (HIS) of each center, which included the following categories: 1) Basic prescription details: Center number, patient medical record number, prescription type, and prescription number; 2) Patient demographic and clinical information: sex, age, visit date, hospital visited, and clinical diagnosis; and 3) Medication information: Drug name, category, specifications, usage, dosage, treatment duration, medication cost, and drug attributes. he corresponding tables were designed using EXCEL 2013 to facilitate the import of research data. Data extracted from each center were standardized to create a database of patient medication information within the fever centers. Assessment of patients and diseases For the study period, we calculated the total number of patients and the daily count of patients. We analyzed the distribution of patient visits over time and computed the weekly growth rate. We conducted a statistical analysis of patient information based on age. This involved calculating the number of patient visits and their proportions within each age group. Additionally, we calculated the sampled incidence rate of COVID-19 for patients in each age group, taking into account the age composition of the Chinese mainland population [ 19 ]. This allowed us to investigate the correlation between age and the incidence rate of COVID-19. We extracted clinical diagnoses from the FCs databases and categorized them by individual disease entities and disease classifications. This analysis aimed to gain insight into diseases observed among patients treated at FCs. Analysis of medication use The number of prescriptions and the quantity of medications within the prescriptions were analyzed and grouped according to hospital tiers. The analysis examined patient admission and prescription trends within fever centers during the COVID-19 epidemic, considering hospitals of different levels. All prescription drug information was collected and analyzed, including the number of drugs prescribed, the frequency of drug use measured in defined daily doses (DDDs), and the total cost of medications. The top 20 drugs ranked were also identified. The number of drugs used, DDDs, and the medication cost for each drug were organized according to their classification of pharmacological effects. Specifically, DDDs were calculated using the drug's DDD, with larger DDDs indicating a higher clinical preference for the drug. The DDD data for drugs were referenced from the WHO ATC&DDD (2023 edition) [ 20 ] and the drug instructions. DDDs = total drug usage / DDD value of the drug According to the Chinese COVID-19 infection diagnosis and treatment guidelines [ 21 ], the national essential drug catalog [ 22 ], and the first and second batches of the national key monitoring and rational use drug catalogs [ 23 , 24 ], a statistical analysis was conducted on the use of guideline-recommended drugs, the national essential drugs, and the key monitoring drugs, respectively. Rationality of medication use Basic prescription details and medication status were consolidated in the FC database, and an assessment of the clinical medication's rationality was conducted according to the "Prescription Management Measures" and "Prescription Evaluation Quality Management Standards" [ 25 , 26 ]. The rational utilization of the drugs was then summarized according to hospital grade, and an analysis of the influencing factors was performed. Statistical analysis Statistical analysis was performed using SPSS 28.0 software. Measurement data were subjected to a normality test. Data are presented as mean ± standard deviation (𝑥̅± 𝑆𝐷) if they conform to a normal distribution. Otherwise, they are represented by the median and interquartile [IQR]. For intergroup comparisons, if the normal distribution and homogeneity of variance were met, the t-test or analysis of variance was used for the difference analysis; if not, the rank sum test was used. The count data are presented as the constituent or relative ratios, and the comparisons between groups were made using the χ 2 test. Statistical tests were performed using bilateral tests, with a significance level (α) set at 0.05. Results Demographic characteristics of patients From September 1 to December 31, 2022, 41,445 patients attended FCs in 11 hospitals. This comprised 22,991 males (55.5%) and 18,454 females (44.5%), resulting in a male-to-female ratio of 1.25:1. Figure 1 shows the distribution of daily patient visits and the weekly growth rate during the study period. Between September 1 and December 6, 2022, China implemented stringent epidemic prevention and control measures, leading to relatively stable daily patient visits. However, following the relaxation of national epidemic prevention and control measures on December 7, 2022, there was a rapid surge in the number of patients seeking medical treatment. The maximum daily patient visits to FCs sampled exceeded 1,000, with a maximum weekly growth rate of 158.8%. The age distribution of the patients and the sampling morbidity rate for each age group are presented in Fig. 2 . As is evident from the figure, the number of cases per age group was highest among children under 6 years of age. When comparing the age composition of the Chinese mainland population at 0:00 on November 1, 2020, as calculated by the seventh national population census, the sampling morbidity rate was highest among individuals 85 years and older in the 11 hospitals sampled. The morbidity rate exceeded 100 cases per million people, with those aged 98 years having a morbidity rate of 904 cases per million people. The second-highest morbidity rate was observed in children, with the morbidity rate for each age group under 6 years ranging between 60 and 94 cases per million people. To minimize possible sample errors in individual age groups, age was divided into 5-year intervals, and a graph was generated illustrating the relationship between patients and the population base in each age group. The equation of the fitted relationship between the sampling morbidity rate ( y ) and age ( x ) is y = 1.4961 x 2 − 24.657 x + 101.25 ( r = 0.9008). Disease distribution of patients seeking medical treatment The distribution of diseases among patients seeking medical treatment is presented in Table 1 . The prescriptions involved 64,565 disease diagnoses, involving 1,013 types of disease diagnoses. Most patients (24,420) had a single diagnosis, and 2,261 and 3,093 individuals experienced two and three diseases simultaneously, respectively. Nine individuals were diagnosed with a maximum of seven diseases simultaneously. Regarding organ systems, the highest morbidity rate was observed in the respiratory system (39,295 person-times), followed by the digestive system, infectious diseases, the central nervous system, endocrine/metabolic diseases, and the circulatory system. When considering specific diseases, the highest morbidity rates were for respiratory system infections (21,201 person-times) and fever (15,132 person-times), followed by gastrointestinal dysfunction, sepsis, electrolyte disorders, cough, COVID-19 infection, epilepsy/convulsion, and gastrointestinal bleeding, all exceeding 1,000 person-times. Table 1 Distribution of disease among patients seeking medical treatment systems diseases number of cases systems diseases number of cases respiratory system 39295 circulatory system 2487 respiratory system infection 21201 hypertension 906 fever/febrile convulsion 15132 shock 344 cough 1355 coronary heart disease 327 dyspnea/asthma 551 heart failure 326 sore throat 302 myocardial damage 227 respiratory and cardiac arrest/respiratory failure 270 arrhythmias 203 acute exacerbation of COPD/COPD 155 hypotension 79 chest tightness/chest pain 150 congenital heart disease 36 pulmonary heart disease 50 others 39 pleural effusion 34 urinary system 956 emphysema 30 urinary system infection 378 others 65 renal insufficiency 325 digestive system 6780 nephritis/nephrotic syndrome 100 gastrointestinal dysfunction 3456 abnormal urination 56 gastrointestinal bleeding 1020 urinary system stones 51 gastrointestinal inflammation 757 others 46 liver disease 693 surgery 951 biliary diseases 406 joint/muscle disease 294 pancreatitis 234 infect 223 peptic ulcer 87 dehydration/edema 166 intestinal obstruction 70 trauma 141 others 57 vascular disease 98 infectious diseases 4938 others 29 sepsis 2909 blood system 921 COVID-19 infection 1305 abnormal coagulation 284 atypical pathogen infection 496 anemia 210 bacterial infection 214 leukemia 165 varicella 14 agranulocytosis 144 central nervous system 3696 leukopenia 65 epilepsy/convulsion 1089 bone marrow suppression 32 cerebrovascular disease 946 others 21 dizziness/dizziness 402 dermatology 680 central nervous system infection 396 rash/dermatitis 531 consciousness disorders/loss/coma 219 skin infection 69 sleep disorders 198 allergy 63 mental disorders 158 others 17 cerebral edema 116 other system 1218 weakness 83 tumour 346 others 89 oral diseases 144 endocrine/metabolic 2643 obstetrics and gynecology diseases 142 electrolyte disorders 1536 nasal diseases 123 abnormal blood sugar 765 eye diseases 82 hypoalbuminemia 81 ear diseases 64 hyperlipidemia 71 immune diseases 44 vitamin and trace element deficiency 57 others 273 thyroid disease 49 hyperuricemia 42 others 42 total 64565 Prescription analysis The number of patient visits and medication items in different hospital grades is presented in Table 2 . In particular, three tertiary teaching hospitals accounted for more than 70% of the medical treatment tasks for fever patients. The predominant type of prescriptions in FCs was regular prescriptions (30,978, 74.7%), with a relatively high proportion of pediatric prescriptions (9,734, 23.5%). There were fewer prescriptions for psychotropic drugs (708, 1.7%) and anesthetic drugs (25, 0.1%). Table 2 Number of patient visits and prescription items in hospital of different grades classification number of hospitals number of visits proportion number of prescription items proportion tertiary teaching hospital 3 29402 70.9% 45324 71.2% tertiary general hospital 3 9062 21.9% 13324 20.9% secondary general hospital 5 2981 7.2% 4982 7.8% total 11 41445 100.0% 63630 100.0% A total of 635 types of drugs were used by patients, with national essential drugs accounting for 34.3% in terms of variety and 73.1% in frequency of use. Guideline-recommended medications constituted only 6.1% of the total number of drugs but had a high proportion in terms of frequency of the medication, reaching 43.2%. The proportion of the first and second batches of nationally key monitored drugs was notably small, as illustrated in Table 3 . Table 3 The use of national essential drugs, guideline-recommended drugs, and key monitored drugs classification number of drug varieties proportion usage count /times proportion sum of money /thousand yuan proportion total 635 63630 3211.9 national essential drugs 218 34.3% 46487 73.1% 581.9 18.1% guideline drugs 39 6.1% 27512 43.2% 1955.6 60.9% key monitored drugs 21 3.3% 5222 8.2% 428.2 13.3% Table 4 shows the 20 main drugs according to the number of prescriptions, DDDs, and cost of the drug. The drugs prescribed most frequently included sodium chloride, ibuprofen, and acetaminophen (including compound formulations). Regarding DDDs, ibuprofen, acetaminophen (including compound preparations), and Lianhua Qingwen were ranked highest, excluding the sodium chloride solvent. Regarding the medication cost, the top three were immunoglobulin, zidovudine, and cefoperazone sulbactam. Table 5 presents the rankings of the number and cost for various drug categories. The most commonly used drugs belonged to water-electrolyte balancing drugs, respiratory system drugs, and antiinfective drugs. Regarding cost, the top three were immunomodulators, anti-infective drugs, and traditional Chinese patent medicines. Table 4 Top 20 drugs with prescription frequency, DDDs, and medication cost orders prescription frequency DDDs sum of medication cost drug name number drug name DDDs drug name cost/ thousand yuan 1 sodium chloride 12827 ibuprofen 97025 immunoglobulin 1374.5 2 ibuprofen 4450 acetaminophen/compound 13473 azvudine 309.9 3 acetaminophen/compound 2684 lianhua qingwen 11705 cefoperazone and sulbactam 218.5 4 lianhua qingwen 2387 azvudine 7832 lianhua qingwen 70.7 5 potassium chloride 2292 ambroxol 6537 omeprazole 57.3 6 glucose 2281 cefixime 5128 cyclic ester erythromycin 57.0 7 ambroxol 2159 omeprazole 3626 piperacillin tazobactam 52.9 8 ceftriaxone 2022 budesonide 3242 ostavir 46.2 9 glucose sodium chloride 1737 dexamethasone 2748 uladil 37.5 10 insulin 1735 pudi lan anti-inflammatory 2585 sodium chloride 35.0 11 cefoperazone and sulbactam 1347 antiviral 2573 pudi lan anti-inflammatory 30.2 12 cefixime 1074 potassium chloride 2511 abidor 29.5 13 azvudine 1036 ceftriaxone 2194 butylphthalide 27.8 14 lysine aspirin 979 methylprednisolone 1977 budesonide 27.8 15 levofloxacin 831 compound liquorice 1960 norepinephrine 27.6 16 budesonide 815 azithromycin 1935 valproic acid 25.5 17 piperacillin tazobactam 769 moxifloxacin 1878 phenobarbital 23.6 18 dexamethasone 767 levofloxacin 1787 namatvir/litonavir 23.0 19 moxifloxacin 752 cyclic ester erythromycin 1546 levofloxacin 22.9 20 injection water 723 cefadinib 1528 xiaoer chiqiaoqingre 21.6 ostavir 1528 Table 5 Sorting of medication frequency and amount of medication for various drugs classification sorting of medication frequency number amount of medication money/ thousand yuan water-electrolyte balance regulator drugs 1 20443 8 63.0 respiratory system drugs 2 13023 4 132.9 Anti-infective drugs 3 11992 2 902.6 traditional Chinese patent drugs 4 6391 3 244.9 digestive system drugs 5 2269 7 107.0 endocrine/metabolic drugs 6 1828 9 28.8 circulatory system drugs 7 1665 5 129.7 central nervous system drugs 8 1549 6 121.3 hormonal drugs 9 1220 13 11.5 vitamin trace elements 10 1010 15 8.4 hematological drugs 11 604 10 24.6 surgical medication 12 516 12 13.7 antiallergic drugs 13 294 18 2.2 urinary system drugs 14 284 16 4.6 immunomodulatory drugs 15 276 1 1378.5 dermatological medication 16 98 17 2.7 medication for facial features 17 58 20 1.4 nutritional drugs 18 57 11 20.5 antitumor drugs 19 25 14 10.8 obstetrics and gynecology medication 20 20 21 1.1 contrast agent 21 5 19 1.6 antidote 22 3 22 0.1 total 63630 3212.0 Rationality of medication use Table 6 and Fig. 3 illustrate the distribution of the reasons for unreasonable drug use between hospitals of different grades. Tertiary teaching hospitals exhibited the highest rational drug use rate, while tertiary general hospitals had the lowest rate, only 67.5%. A comparative analysis of the factors that influence irrational drug use in the three hospital grades revealed significant differences ( P < 0.001) in both overall and pairwise comparisons between the groups. The elevated proportion of unreasonable drug use in tertiary teaching hospitals was attributed to inappropriate drug usage and dosage. In contrast, tertiary and secondary general hospitals showed higher rates of improper drug selection, followed by incorrect usage and dosage. Furthermore, some prescription formats in these hospitals were not standardized. Table 6 Evaluation results of rational use of medications hospital grade total irrational proportion format not standardized improper drug selection inappropriate route of administration incorrect dosage improper combination of medication p tertiary teaching hospital 45324 4957 10.90% 0.11% 2.81% 1.05% 6.91% 0.06% < 0.001 tertiary general hospital ** 13324 4326 32.50% 2.18% 14.58% 3.90% 11.65% 0.17% secondary general hospital **## 4982 1104 22.20% 3.17% 9.47% 1.63% 7.83% 0.06% Note: ** P < 0.001, compared to tertiary teaching hospitals; ## P < 0.001, compared to tertiary general hospitals Discussion During the COVID-19 pandemic, infected patients received treatment primarily in outpatient clinics. The effective management of patients by FCs has proven instrumental in reducing hospitalization rates, particularly among vulnerable populations such as older patients, who face an elevated risk of severe outcomes, and individuals with underlying conditions such as obesity, cardiovascular disease, and diabetes [ 27 – 30 ]. FCs operate as specialized facilities within large general hospitals, playing a crucial role in the screening, diagnosing, and treating COVID-19 cases and curbing the spread of the epidemic. An essential component of this effort involves analyzing the spectrum of the disease and the medication status of patients seeking treatment. Demographic characteristics of patients seeking medical treatment The time distribution chart of the patients indicates a notable increase in the number of individuals seeking medical treatment after the relaxation of the epidemic prevention and control measures in China on December 7, 2022. This increase is evident compared to the period of stringent control, and the numbers gradually stabilized after that. The global impact of the COVID-19 pandemic has resulted in a substantial disease burden [ 6 ]. In the context of a vast country with a population exceeding 1.4 billion, implementing rigorous epidemic control measures during the initial wave of the outbreak in China played a pivotal role in effectively managing the infection morbidity rate. Analysis of the age distribution of the patients attending FCs and the sampling morbidity rate in 11 hospitals reveals that the highest morbidity rate was observed among individuals over 85 years, and children were closely followed. Among children, those under 6 years of age had the highest morbidity, consistent with findings from previous studies [ 31 , 32 ]. After fitting, the morbidity rate shows a quadratic equation relationship with age. The fitted relationship equation exhibits good correlation, providing a reference for infection prediction across various age groups. Patient disease spectrum There were 1,013 different diagnoses of the disease among the patients, highlighting the complexity of the types of disease observed in individuals seeking medical treatment in FCs. Examining the distribution of diseases reveals a concentration of cases within the respiratory system, where respiratory infections and fever rank highest. These conditions serve as primary indicators and common accompanying diagnoses of COVID-19 infection [ 3 , 12 ], aligning with the diagnostic and therapeutic functions of FCs. Additionally, symptoms such as coughing, gastrointestinal dysfunction, and epilepsy/convulsions, which are commonly associated with COVID-19 [ 21 ], also exhibit a high morbidity rate. Furthermore, the diagnosis of sepsis, electrolyte disorders, gastrointestinal bleeding, and other diseases with elevated morbidity rates suggests the presence of severe and critical cases of COVID-19 [ 21 ]. Regarding drug use, drugs to regulate the water-electrolyte balance are the most commonly prescribed. Other commonly used medications include cefoperazone/sulbactam, piperacillin-tazobactam, and immunoglobulin, thus confirming the aforementioned results. Analysis of medications A total of 635 different medications were prescribed for FC patients. Based on the ranking of the number of drugs used, DDDs, and costs of medications, the selection of prescription drugs for FCs aligns well with the types of disease observed in patients. This includes antipyretic and analgesic, antiviral, and respiratory system medications. Among medications, drugs in the essential national formulary account for 34.3% of the variety and 73.1% of the total frequency of use. This indicates that physicians in FCs frequently recommend safe, effective, and cost-efficient national essential drugs to patients, thus alleviating the economic burden on patients. The proportion of guideline-recommended drugs is relatively low, reflecting the limited number of drugs recommended in the national COVID-19 diagnosis and treatment guidelines [ 21 ]. However, the frequency of drugs recommended by the guideline is 43.2%. This indicates that physicians effectively followed the recommended treatment protocols for diagnosing and treating COVID-19 patients. The role of traditional Chinese medicine The findings of this study underscore the significant role of TCM in managing COVID-19. Among the medications administered to patients, 148 types of TCM are identified. TCM ranks fourth in terms of medication frequency and third in terms of medication cost. In particular, Lianhua Qingwen emerges as the most commonly used drug within TCM, securing the third position in both medication frequency and DDDs, and the fourth position in medication cost. Clinical studies have shown that Lianhua Qingwen can alleviate the clinical symptoms associated with COVID-19, substantially improve overall treatment efficacy, and reduce hospitalization and treatment duration [ 33 , 34 ]. Molecular biology research and network pharmacology predictions suggest that the active components of Lianhua Qingwen may exert therapeutic effects on COVID-19 infection by targeting angiotensin-converting enzyme 2 (ACE2), 3C-like protease (3CLpro), and interleukin (IL)-6 [ 35 ]. Additionally, six components within their formulation have the potential to interact with the active sites of the Akt1 gene, implicated in lung injury, pulmonary fibrosis, and viral infection, indicating a prospective therapeutic role in COVID-19 infection [ 36 ]. Analysis of medication rationality reveals a comparatively lower rate of medication rationality of 83.68% in FCs, significantly below that observed in outpatient, emergency, or inpatient services [ 37 , 38 ]. This suggests that the medical staff in the FCs experienced increased work pressure, compounded by the challenges of epidemic control and patient care, leading to an increased likelihood of medical errors. Studies indicate that physicians are more susceptible to input errors in emergencies, and the time taken to complete prescription tasks is inversely correlated with the error rate [ 39 , 40 ]. Inappropriate prescriptions can lead to medication errors, elevated morbidity rates, or increased hospitalization rates, imposing economic burdens on patients [ 41 ]. Consequently, it is imperative to implement measures to mitigate prescription errors in FCs. This may include establishing standardized drug charts based on error analysis and system improvement evaluations and enhancing practical prescription education and training programs. Analysis of the number of prescriptions from 11 hospitals indicates the distinct roles that different grades of hospitals played during COVID-19, with tertiary teaching hospitals assuming primary reception tasks. In particular, there are significant variations in the distribution of the reasons for irrational medication use between hospitals of different grades. Tertiary teaching hospitals exhibit the highest rate of rational drug use. Reasons for unreasonable drug use are attributed to inappropriate drug use and dosage, representing a technical error in drug use. In contrast, the reason for irrational medication use in tertiary and secondary general hospitals was inappropriate drug selection, indicating a significant and unreasonable use of drugs. The second most common issue is incorrect usage and dosage, coupled with a notable prevalence of non-standardized prescription formats. Differences in the quality of drug utilization levels are observed between hospitals of different grades, and tertiary teaching hospitals demonstrate higher quality levels of drug use, consistent with findings in the existing literature [ 43 ]. Research suggests that, compared to other hospital grades, teaching hospitals possess robust teaching resources and advantages in talent development within universities, boasting a higher proportion of clinical experts. Consequently, they can provide more extensive and higher-quality medical services to the public [ 44 , 45 ]. The contemporary academic medical model of university hospitals, originating in the late 18th century, plays a pivotal role in present-day medical activities and is expected to be instrumental in driving future medical advancements. This study has several limitations. Research subjects are patients from FCs; assessing the patient's prognosis is impossible, and treatment outcomes remain unknown. Additionally, access to electronic prescription information is restricted due to the incomplete nature of the Hospital Information System in grassroots hospitals, such as community health centers and township health centers. As a result, this information was not included. Declarations Data availability We can share the raw data of this manuscript, the datasets generated are not publicly available due the reasons for patient privacy protection, but can be obtained from the corresponding author upon reasonable request. Declaration of interests The authors declare that there are no conflicts of interest. Funding This study was supported by the Hebei Pharmaceutical Association Hospital Pharmacy Special Research Project (2022-HBsyxhqjyxzd01). Acknowledgments The authors acknowledge the contributions from other members of the team including Zhenzhen Yang, Kai Wang, Jie Dong, and Yang Gao who provided data review, cleaning and proofreading. Author contribution In the research team, Yaru Zang, Jingyi Yang, Kaining Yang, Yue Zhao, Wei Zhang, Shuanghu Guo, Chaoxu Han, Chaoxing Liu, Xiangzheng Mi, and Xiaoli Wang participated in data extraction and preliminary review, Zhiqing Zhang and Chuanping Wang conducted data validation. All authors read and approved the final version of the manuscript, had full access to all the data in the study, and had final responsibility for the decision to submit for publication. Consent to Publication We agree to publish this paper by the BMC Department of Public Health. References WHO coronavirus (COVID-19) dashboard. Geneva: World Health Organization. (https //covid19. who. int/table). Gottlieb RL, Vaca CE, Paredes R, et al. 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Psychother Psychosom. 2020; 89(4): 252-254. doi: 10. 1159/000507453. Yan S, Xu R, Stratton T D, et al. Sex differences and psychological stress：Responses to the COVID-19 pandemic in China. BMC Public Health, 2021, 21(1): 79. Hong X, Cao J, Wei J, et al. Stress and psychological impact of the COVID-19 epidemic outbreak on the healthcare staff at the fever clinic of a tertiary general hospital in Beijing: a cross sectional study. B J Psych Open, 2021, 7(3): 76. Office of the Leading Group for the Seventh National Population Census of the State Council, National bureau of statistics of China announcement of the seventh national population census (No. 5) - Age composition of the population, May 11, 2021. http://www.stats.gov.cn/sj/tjgb/rkpcgb/qgrkpcgb/202302/t20230206_1902005.html. WHO Collaborating Centre for Drug Statistics Methodology. https://www.whocc.no/atc_ddd_index/ National Health Commission of the People's Republic of China, State Administration of Traditional Chinese Medicine. Diagnosis and treatment plan for novel coronavirus infection (Tenth version on trial) http://www.nhc.gov.cn/xcs/zhengcwj/202301/32de5b2ff9bf4eaa88e75bdf7223a65a.shtml National Health Commission of the People's Republic of China. National essential drug catalogue (2018 Edition) https://www.gov.cn/zhengce/zhengceku/2018-12/31/5435470/files/5802d337476e4953b0e9f388a6309f9a.pdf. National Health Commission of the People's Republic of China, State Administration of Traditional Chinese Medicine. The first batch of national key monitoring and rational drug use drug catalogs (chemical and biological products) https://www.gov.cn/fuwu/2019-07/02/content_5405241.htm. National Health Commission of the People's Republic of China. The second batch of national key monitoring and rational drug use drug catalogs. http://www.nhc.gov.cn/xcs/zhengcwj/202301/5b291aaae64b4e56a10f9ea910e11426.shtml. Ministry of Health of the People's Republic of China. Prescription Management Measures http://www.nhc.gov.cn/wjw/c100022/202201/601940f66bbe4f24b0c5734f04e53543.shtml. Ministry of Health of the People's Republic of China. Management standards for hospital prescription evaluation (Trial). http://www.nhc.gov.cn/yzygj/s3590/201810/6103f922f61440d1b48ba1571b6b6b72.shtml. Gallo Marin B, Aghagoli G, Lavine K, et al. Predictors of COVID-19 severity: a literature review. Rev Med Virol 2021; 31: 1-10. Stokes EK, Zambrano LD, Anderson KN, et al. Coronavirus disease 2019 case surveillance - United States, January 22-May 30, 2020. MMWR-Morb Mortal W. 2020; 69: 759-765. Verity R, Okell LC, Dorigatti I, et al. Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis 2020; 20: 669-677. Guan WJ, Ni ZY, Hu Y, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020; 382: 1708-1720. Zhang JJ, Dong X, Liu GH, et al. Risk and protective factors for COVID-19 morbidity, severity, and mortality. clin rev allergy immunol. 2023 Feb;64(1):90-107. doi: 10.1007/s12016-022-08921-5. Demeterco-Berggren C, Ebekozien O, Rompicherla S, et al. Age and hospitalization risk in people with type 1 diabetes and COVID-19: Data from the T1D exchange surveillance study. J Clin Endocrinol Metab. 2022 Jan 18;107(2):410-418. doi: 10.1210/clinem/dgab668. Fan SJ, Liao JK, Wei L, et al. Treatment efficacy of Lianhua Qingwen capsules for eraly-stage COVID-19. Am J Transl Res. 2022 Feb 15;14(2):1332-1338. eCollection 2022. Zeng M, Li L, Wu Z. Traditional Chinese medicine Lianhua Qingwen treating corona virus disease 2019(COVID-19): Meta-analysis of randomized controlled trials. PLoS One. 2020 Sep 11;15(9): e0238828. doi: 10.1371/journal.pone.0238828. eCollection 2020. Huang K, Zhang P, Zhang Z, Y et al. Traditional Chinese Medicine (TCM) in the treatment of COVID-19 and other viral infections: Efficacies and mechanisms. Pharmacol Ther. 2021 Sep; 225:107843. doi: 10.1016/j.pharmthera.2021.107843. Epub 2021 Mar 31. Xia QD, Xun Y, Lu JL, et al. Network pharmacology and molecular docking analyses on Lianhua Qingwen capsule indicate Akt1 is a potential target to treat and prevent COVID-19. Cell Prolif. 2020 Dec;53(12): e12949. doi: 10.1111/cpr.12949. Epub 2020 Nov 3. Devarajan V, Nadeau NL, Creedon JK, et al. Reducing Pediatric Emergency Department Prescription Errors. Pediatrics. 2022 Jun 1;149(6): e2020014696. doi: 10.1542/peds.2020-014696. Fajreldines A, Bazzano M, Pellizzari M. A strategy to reduce medication prescription error in hospitalized patients. Medicina (B Aires). 2021;81(2):224-228. Wu X, Wu C, Zhang K, Wei D. Residents' numeric inputting error in computerized physician order entry prescription. Int J Med Inform. 2016 Apr; 88:25-33. doi: 10.1016/j.ijmedinf.2016.01.002. Epub 2016 Jan 15. Tallentire VR, Hale RL, Dewhurst NG, et al. The contribution of prescription chart design and familiarity to prescribing error: a prospective, randomised, cross-over study. BMJ Qual Saf. 2013 Oct;22(10):864-9. doi: 10.1136/bmjqs-2013-001837. Epub 2013 Jun 1. Batta A, Singh B. Rational approach to prescription writing: A preview. Neurol India. 2018 Jul-Aug;66(4):928-933. doi: 10.4103/0028-3886.236960. Coombes I, Reid C, Stowasser D, et al. Reducing prescription errors. Lancet. 2010 Feb 6;375(9713):462. doi: 10.1016/S0140-6736(10)60197-3. Burke LG, Frakt AB, Khullar D, et al. Association between teaching status and mortality in US hospitals. JAMA. 2017 May 23;317(20):2105-2113. doi: 10.1001/jama.2017.5702. Niedzwiecki MJ, Machta RM, Reschovsky JD, et al. Characteristics of academic-affiliated health systems. Acad Med. 2020 Apr; 95(4):559-566. doi: 10.1097/ACM.0000000000003149. Lai PM, Lin N, Du R. Effect of teaching hospital status on outcome of aneurysm treatment. World Neurosurg. 2014 Sep-Oct;82(3-4):380-385.e6. doi: 10.1016/j.wneu.2013.07.015. Raus K, Mortier E, Eeckloo K. Past, present and future of university hospitals. Acta Clin Belg. 2020 Jun;75(3):177-184. doi: 10.1080/17843286.2019.1590024. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3908849","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":271521146,"identity":"7c69c98b-e5fd-4ebf-9c48-2dbfadbca939","order_by":0,"name":"Zhiqing Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYBACfvb+BwcSDCTq+yUY2CBCBwhokew5w/jgQ4UN48wZxGoxuOHDbDjjTBrjhhvEamG4wXtMmrftMLPx7eZjj262Mcjx3Uhg/FyARwfj7L40kBY2szvH0o1z2xiMJW8kMEvPwKOFWeaAGUgLj9mNHDNpoJbEDTcS2Jh58Ghhk0gAa5EwnpH/DaSlnqAWHokcY5D3DQwkcthAWhIMCGmR4DmWCArkBIkbaebGOeckDGeeedgsjU+L/fHmA6CoTOCfkfzscU6ZjTzf8eSDn/FpwbAViBkbSNAwCkbBKBgFowAbAAAw9U/awrrKoQAAAABJRU5ErkJggg==","orcid":"","institution":"Second Hospital of Hebei Medical University","correspondingAuthor":true,"prefix":"","firstName":"Zhiqing","middleName":"","lastName":"Zhang","suffix":""},{"id":271521147,"identity":"2c5b3c69-d930-459b-aa6b-f2dbc6f9ff8f","order_by":1,"name":"Yaru Zang","email":"","orcid":"","institution":"Affiliated Hospital of Chengde Medical College","correspondingAuthor":false,"prefix":"","firstName":"Yaru","middleName":"","lastName":"Zang","suffix":""},{"id":271521149,"identity":"f854d88c-e0f8-4163-82a7-c929a3ef621f","order_by":2,"name":"Jingyi Yang","email":"","orcid":"","institution":"First Hospital of Qinhuangdao","correspondingAuthor":false,"prefix":"","firstName":"Jingyi","middleName":"","lastName":"Yang","suffix":""},{"id":271521150,"identity":"553b1987-2a41-442d-9bb8-01ad1fd0c9dd","order_by":3,"name":"Kaining Yang","email":"","orcid":"","institution":"Baoding Second Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kaining","middleName":"","lastName":"Yang","suffix":""},{"id":271521151,"identity":"ddca5704-d286-4591-a9c7-6466676d6bc4","order_by":4,"name":"Yue Zhao","email":"","orcid":"","institution":"Sanhe City Hospital in Hebei Province","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Zhao","suffix":""},{"id":271521152,"identity":"686da028-ef32-4d7d-ae3e-939ac36be432","order_by":5,"name":"Wei Zhang","email":"","orcid":"","institution":"Qian'an People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Zhang","suffix":""},{"id":271521153,"identity":"393242af-b227-4544-9604-37fba5b81d16","order_by":6,"name":"Shuanghu Guo","email":"","orcid":"","institution":"Affiliated Hospital of Hebei Engineering University","correspondingAuthor":false,"prefix":"","firstName":"Shuanghu","middleName":"","lastName":"Guo","suffix":""},{"id":271521154,"identity":"d0a17707-5261-4c3a-a025-13cc7d9e02f9","order_by":7,"name":"Chaoxu Han","email":"","orcid":"","institution":"Handan Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chaoxu","middleName":"","lastName":"Han","suffix":""},{"id":271521155,"identity":"9889647b-482c-4cc7-b5b2-2bf0ede84d3d","order_by":8,"name":"Chaoxing Liu","email":"","orcid":"","institution":"Xingtai Ninth Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chaoxing","middleName":"","lastName":"Liu","suffix":""},{"id":271521156,"identity":"26520b5e-309f-4bf1-add5-2444c416e2b5","order_by":9,"name":"Xiangzheng Mi","email":"","orcid":"","institution":"Gucheng Country Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiangzheng","middleName":"","lastName":"Mi","suffix":""},{"id":271521157,"identity":"d40afb67-0e4f-4c36-a6a1-c1aeb3766ce4","order_by":10,"name":"Xiaoli Wang","email":"","orcid":"","institution":"Nanpi Country People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaoli","middleName":"","lastName":"Wang","suffix":""},{"id":271521158,"identity":"61ad6b9f-5e16-4cbb-9488-7fad8aaf441b","order_by":11,"name":"Chuanping Wang","email":"","orcid":"","institution":"Second Hospital of Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chuanping","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-01-29 12:03:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3908849/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3908849/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50927655,"identity":"04fa8cdb-390f-4c56-a314-2e173329f3b2","added_by":"auto","created_at":"2024-02-09 17:16:53","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":62993,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of patient visit times\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3908849/v1/e2bb13941742cb5225c53e0a.jpg"},{"id":50925826,"identity":"88b452fb-36dc-4e18-a8b0-e0fea60919ef","added_by":"auto","created_at":"2024-02-09 17:08:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":101467,"visible":true,"origin":"","legend":"\u003cp\u003eSampling morbidity situation of patients in different age groups\u003c/p\u003e\n\u003cp\u003eA: Number of patient visits, population base, and sampling morbidity rate for each age group; B: Relationship between the sampling morbidity rate and age\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3908849/v1/3ca534c00eac513cd5db1690.jpg"},{"id":50925827,"identity":"2d21aa1c-263f-43af-86cb-ad9419a2d9f8","added_by":"auto","created_at":"2024-02-09 17:08:52","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":83998,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of reasons for unreasonable drug use in hospitals of different grades\u003c/p\u003e\n\u003cp\u003eA: Distribution of frequency of irrational medication use, B: Distribution of the proportion of irrational medication use\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3908849/v1/03950788cfb5e6bf28b00f30.jpg"},{"id":61384538,"identity":"bca9a560-a28e-4ef0-ac7e-5a006ff11d89","added_by":"auto","created_at":"2024-07-30 06:45:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1367268,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3908849/v1/699885af-bc10-4a2d-9031-35596a828879.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of Medication Utilization in Isolated Areas of Fever Clinics During the COVID-19 Epidemic Outbreak: A Multicenter Study in General Hospitals in China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCOVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first identified in December 2019 and quickly became a global pandemic. In August 2023, worldwide COVID-19 infections had surpassed 769\u0026nbsp;million, resulting in approximately 6.955\u0026nbsp;million deaths [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Most COVID-19 patients receive outpatient treatment, while some require hospitalization or succumb to the progression of the disease [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. During the initial global outbreak, the mortality rate among hospitalized patients ranged from 16.4\u0026ndash;32.3% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The primary approach to epidemic prevention and control is to implement effective measures to curb the spread of COVID-19 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Experience has shown that maintaining social distancing, wearing masks, and contact tracing are fundamental public health strategies to reduce virus transmission [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Vaccination is another potent tool for infection prevention, significantly decreasing infection rates, severe cases, and mortality among the population [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In China, an effective strategy to control COVID-19 transmission within hospitals involves establishing isolated areas known as outpatient fever clinics (FCs) in health facilities.\u003c/p\u003e \u003cp\u003ePreventing hospital-acquired infections is a crucial aspect of the clinical management of COVID-19 [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This outbreak is caused by SARS-CoV-2, which belongs to the same family of viruses as Severe Acute Respiratory Syndrome (SARS) and Middle Eastern Respiratory Syndrome (MERS) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. During the 2003 SARS outbreak in China, FCs were established, independent units designed to isolate infected or suspected patients by providing dedicated consultation channels, effectively preventing the spread of infection. Following the outbreak of COVID-19, the China National Health Commission recommended upgrading and renovating the outpatient FCs established during the SARS outbreak for COVID-19 screening [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. During the COVID-19 epidemic in China, confirmed cases of COVID-19 were centralized and managed by designated medical institutions. The fever clinics in large, comprehensive hospitals served as dedicated channels for COVID-19 screening, isolation, and diagnosis. They played a crucial role in early detection, isolation, and treatment, serving as a critical strategy in combating nosocomial transmission and epidemic spread [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDue to the highly contagious nature of COVID-19, the medical personnel in FCs have been tirelessly working on the frontlines of epidemic prevention and control. Their daily tasks are demanding, and they have endured significant physical and psychological stress, increasing the risk of medical errors [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. On the other hand, fever patients are a primary focus of clinical surveillance during the COVID-19 epidemic, increasing emphasis on patient treatment and intervention has also placed a considerable psychological burden on patients. Patients and their families are more concerned about medical safety, and medication safety is becoming a focal point [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, research on medication safety in FCs has not yet received sufficient attention from the academic community.\u003c/p\u003e \u003cp\u003eThis study selected comprehensive hospitals of different grades in China and extracted patient information from their FCs during the outbreak period of the COVID-19 epidemic. The analysis focused on the demographic characteristics of the patients, the distribution of the disease, and the use of medications. This research aimed to provide valuable information for the treatment and rational use of drugs in COVID-19.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted in three tertiary teaching hospitals, three tertiary general hospitals, and five secondary general hospitals in China. The study period was during the initial wave of the COVID-19 epidemic in China from September 1 to December 31, 2022.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003e was granted by the Ethics Committee of the Second Hospital of Hebei Medical University, which served as the leading institution (approval number 2022-C055). Other research centers followed the central ethics approval. Informed consent was obtained from all subjects and/or their legal guardians.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eInclusion and exclusion criteria of prescriptions\u003c/h2\u003e \u003cp\u003eOnly complete prescriptions were analyzed. A prescription is deemed complete when it has the following details: 1) heading (medical institution name, prescription number, patient's name, sex, age, department, clinical diagnosis, and issue date); 2) body (drug name, specifications, quantity, dosage, and administration); and 3) footer (physician's signature or seal, drug cost, signature of the prescription-reviewing pharmacist, and signature of the dispensing pharmacist). Prescriptions were excluded if they contained information that could not be recognized or had errors in the prescription information.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eData were obtained from the hospital information systems (HIS) of each center, which included the following categories: 1) Basic prescription details: Center number, patient medical record number, prescription type, and prescription number; 2) Patient demographic and clinical information: sex, age, visit date, hospital visited, and clinical diagnosis; and 3) Medication information: Drug name, category, specifications, usage, dosage, treatment duration, medication cost, and drug attributes. he corresponding tables were designed using EXCEL 2013 to facilitate the import of research data. Data extracted from each center were standardized to create a database of patient medication information within the fever centers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of patients and diseases\u003c/h2\u003e \u003cp\u003eFor the study period, we calculated the total number of patients and the daily count of patients. We analyzed the distribution of patient visits over time and computed the weekly growth rate. We conducted a statistical analysis of patient information based on age. This involved calculating the number of patient visits and their proportions within each age group. Additionally, we calculated the sampled incidence rate of COVID-19 for patients in each age group, taking into account the age composition of the Chinese mainland population [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This allowed us to investigate the correlation between age and the incidence rate of COVID-19. We extracted clinical diagnoses from the FCs databases and categorized them by individual disease entities and disease classifications. This analysis aimed to gain insight into diseases observed among patients treated at FCs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of medication use\u003c/h2\u003e \u003cp\u003eThe number of prescriptions and the quantity of medications within the prescriptions were analyzed and grouped according to hospital tiers. The analysis examined patient admission and prescription trends within fever centers during the COVID-19 epidemic, considering hospitals of different levels.\u003c/p\u003e \u003cp\u003eAll prescription drug information was collected and analyzed, including the number of drugs prescribed, the frequency of drug use measured in defined daily doses (DDDs), and the total cost of medications. The top 20 drugs ranked were also identified. The number of drugs used, DDDs, and the medication cost for each drug were organized according to their classification of pharmacological effects. Specifically, DDDs were calculated using the drug's DDD, with larger DDDs indicating a higher clinical preference for the drug. The DDD data for drugs were referenced from the WHO ATC\u0026amp;DDD (2023 edition) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and the drug instructions.\u003c/p\u003e \u003cp\u003eDDDs\u0026thinsp;=\u0026thinsp;total drug usage / DDD value of the drug\u003c/p\u003e \u003cp\u003eAccording to the Chinese COVID-19 infection diagnosis and treatment guidelines [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], the national essential drug catalog [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and the first and second batches of the national key monitoring and rational use drug catalogs [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], a statistical analysis was conducted on the use of guideline-recommended drugs, the national essential drugs, and the key monitoring drugs, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRationality of medication use\u003c/h2\u003e \u003cp\u003eBasic prescription details and medication status were consolidated in the FC database, and an assessment of the clinical medication's rationality was conducted according to the \"Prescription Management Measures\" and \"Prescription Evaluation Quality Management Standards\" [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The rational utilization of the drugs was then summarized according to hospital grade, and an analysis of the influencing factors was performed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed using SPSS 28.0 software. Measurement data were subjected to a normality test. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (\u0026#119909;̅\u0026plusmn; \u0026#119878;\u0026#119863;) if they conform to a normal distribution. Otherwise, they are represented by the median and interquartile [IQR]. For intergroup comparisons, if the normal distribution and homogeneity of variance were met, the t-test or analysis of variance was used for the difference analysis; if not, the rank sum test was used. The count data are presented as the constituent or relative ratios, and the comparisons between groups were made using the χ\u003csup\u003e2\u003c/sup\u003e test. Statistical tests were performed using bilateral tests, with a significance level (α) set at 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDemographic characteristics of patients\u003c/h2\u003e \u003cp\u003eFrom September 1 to December 31, 2022, 41,445 patients attended FCs in 11 hospitals. This comprised 22,991 males (55.5%) and 18,454 females (44.5%), resulting in a male-to-female ratio of 1.25:1. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the distribution of daily patient visits and the weekly growth rate during the study period. Between September 1 and December 6, 2022, China implemented stringent epidemic prevention and control measures, leading to relatively stable daily patient visits. However, following the relaxation of national epidemic prevention and control measures on December 7, 2022, there was a rapid surge in the number of patients seeking medical treatment. The maximum daily patient visits to FCs sampled exceeded 1,000, with a maximum weekly growth rate of 158.8%.\u003c/p\u003e \u003cp\u003eThe age distribution of the patients and the sampling morbidity rate for each age group are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e. As is evident from the figure, the number of cases per age group was highest among children under 6 years of age. When comparing the age composition of the Chinese mainland population at 0:00 on November 1, 2020, as calculated by the seventh national population census, the sampling morbidity rate was highest among individuals 85 years and older in the 11 hospitals sampled. The morbidity rate exceeded 100 cases per million people, with those aged 98 years having a morbidity rate of 904 cases per million people. The second-highest morbidity rate was observed in children, with the morbidity rate for each age group under 6 years ranging between 60 and 94 cases per million people. To minimize possible sample errors in individual age groups, age was divided into 5-year intervals, and a graph was generated illustrating the relationship between patients and the population base in each age group. The equation of the fitted relationship between the sampling morbidity rate (\u003cem\u003ey\u003c/em\u003e) and age (\u003cem\u003ex\u003c/em\u003e) is \u003cem\u003ey\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.4961\u003cem\u003ex\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e \u0026minus;\u0026thinsp;24.657\u003cem\u003ex\u003c/em\u003e\u0026thinsp;+\u0026thinsp;101.25 (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.9008).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDisease distribution of patients seeking medical treatment\u003c/h2\u003e \u003cp\u003eThe distribution of diseases among patients seeking medical treatment is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The prescriptions involved 64,565 disease diagnoses, involving 1,013 types of disease diagnoses. Most patients (24,420) had a single diagnosis, and 2,261 and 3,093 individuals experienced two and three diseases simultaneously, respectively. Nine individuals were diagnosed with a maximum of seven diseases simultaneously. Regarding organ systems, the highest morbidity rate was observed in the respiratory system (39,295 person-times), followed by the digestive system, infectious diseases, the central nervous system, endocrine/metabolic diseases, and the circulatory system. When considering specific diseases, the highest morbidity rates were for respiratory system infections (21,201 person-times) and fever (15,132 person-times), followed by gastrointestinal dysfunction, sepsis, electrolyte disorders, cough, COVID-19 infection, epilepsy/convulsion, and gastrointestinal bleeding, all exceeding 1,000 person-times.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of disease among patients seeking medical treatment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003esystems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ediseases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003enumber of cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003esystems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ediseases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003enumber of cases\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003erespiratory system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003ecirculatory system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2487\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erespiratory system infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ehypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e906\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efever/febrile convulsion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eshock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e344\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ecoronary heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e327\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edyspnea/asthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eheart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e326\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esore throat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emyocardial damage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erespiratory and cardiac arrest/respiratory failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003earrhythmias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eacute exacerbation of COPD/COPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ehypotension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003echest tightness/chest pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003econgenital heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epulmonary heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epleural effusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eurinary system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e956\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eemphysema\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eurinary system infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e378\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003erenal insufficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003edigestive system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003enephritis/nephrotic syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003egastrointestinal dysfunction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eabnormal urination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003egastrointestinal bleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eurinary system stones\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003egastrointestinal inflammation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eliver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003esurgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e951\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ebiliary diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ejoint/muscle disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e294\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epancreatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003einfect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e223\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epeptic ulcer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003edehydration/edema\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eintestinal obstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003etrauma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003evascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003einfectious diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eblood system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e921\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCOVID-19 infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eabnormal coagulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eatypical pathogen infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eanemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ebacterial infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eleukemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evaricella\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eagranulocytosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ecentral nervous system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eleukopenia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eepilepsy/convulsion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ebone marrow suppression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edizziness/dizziness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003edermatology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e680\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecentral nervous system infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003erash/dermatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e531\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003econsciousness disorders/loss/coma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eskin infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esleep disorders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eallergy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emental disorders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecerebral edema\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eother system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eweakness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003etumour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eoral diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eendocrine/metabolic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eobstetrics and gynecology diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eelectrolyte disorders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003enasal diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eabnormal blood sugar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eeye diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehypoalbuminemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eear diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehyperlipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eimmune diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evitamin and trace element deficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e273\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ethyroid disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehyperuricemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64565\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePrescription analysis\u003c/h2\u003e \u003cp\u003eThe number of patient visits and medication items in different hospital grades is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In particular, three tertiary teaching hospitals accounted for more than 70% of the medical treatment tasks for fever patients. The predominant type of prescriptions in FCs was regular prescriptions (30,978, 74.7%), with a relatively high proportion of pediatric prescriptions (9,734, 23.5%). There were fewer prescriptions for psychotropic drugs (708, 1.7%) and anesthetic drugs (25, 0.1%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumber of patient visits and prescription items in hospital of different grades\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eclassification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003enumber of hospitals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003enumber of visits\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eproportion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003enumber of prescription items\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eproportion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etertiary teaching hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etertiary general hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esecondary general hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA total of 635 types of drugs were used by patients, with national essential drugs accounting for 34.3% in terms of variety and 73.1% in frequency of use. Guideline-recommended medications constituted only 6.1% of the total number of drugs but had a high proportion in terms of frequency of the medication, reaching 43.2%. The proportion of the first and second batches of nationally key monitored drugs was notably small, as illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e The use of national essential drugs, guideline-recommended drugs, and key monitored drugs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eclassification\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003enumber of drug varieties\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eproportion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eusage count\u003c/p\u003e\u003cp\u003e/times\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eproportion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003esum of money\u003c/p\u003e\u003cp\u003e/thousand yuan\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eproportion\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003etotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e635\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63630\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3211.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003enational essential drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e218\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46487\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e73.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e581.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e18.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eguideline drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27512\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e43.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1955.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e60.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ekey monitored drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5222\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e428.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the 20 main drugs according to the number of prescriptions, DDDs, and cost of the drug. The drugs prescribed most frequently included sodium chloride, ibuprofen, and acetaminophen (including compound formulations). Regarding DDDs, ibuprofen, acetaminophen (including compound preparations), and \u003cem\u003eLianhua Qingwen\u003c/em\u003e were ranked highest, excluding the sodium chloride solvent. Regarding the medication cost, the top three were immunoglobulin, zidovudine, and cefoperazone sulbactam. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the rankings of the number and cost for various drug categories. The most commonly used drugs belonged to water-electrolyte balancing drugs, respiratory system drugs, and antiinfective drugs. Regarding cost, the top three were immunomodulators, anti-infective drugs, and traditional Chinese patent medicines.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 20 drugs with prescription frequency, DDDs, and medication cost\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eorders\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eprescription frequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eDDDs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003esum of medication cost\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003edrug name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003enumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003edrug name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDDDs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003edrug name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ecost/ thousand yuan\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esodium chloride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eibuprofen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eimmunoglobulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1374.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eibuprofen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eacetaminophen/compound\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eazvudine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e309.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eacetaminophen/compound\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003elianhua qingwen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ecefoperazone and sulbactam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e218.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elianhua qingwen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eazvudine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003elianhua qingwen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e70.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epotassium chloride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eambroxol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eomeprazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e57.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eglucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ecefixime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ecyclic ester erythromycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e57.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eambroxol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eomeprazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003epiperacillin tazobactam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e52.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eceftriaxone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ebudesonide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eostavir\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e46.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eglucose sodium chloride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edexamethasone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003euladil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003einsulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003epudi lan anti-inflammatory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2585\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003esodium chloride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e35.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecefoperazone and sulbactam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eantiviral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003epudi lan anti-inflammatory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecefixime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003epotassium chloride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eabidor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eazvudine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eceftriaxone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ebutylphthalide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elysine aspirin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emethylprednisolone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1977\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ebudesonide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elevofloxacin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ecompound liquorice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003enorepinephrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ebudesonide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eazithromycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003evalproic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epiperacillin tazobactam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emoxifloxacin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ephenobarbital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edexamethasone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003elevofloxacin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003enamatvir/litonavir\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emoxifloxacin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ecyclic ester erythromycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003elevofloxacin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003einjection water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ecefadinib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003exiaoer chiqiaoqingre\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eostavir\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSorting of medication frequency and amount of medication for various drugs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eclassification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003esorting of medication frequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003enumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eamount of medication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003emoney/ thousand yuan\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ewater-electrolyte balance regulator drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003erespiratory system drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e132.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-infective drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e902.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etraditional Chinese patent drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e244.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edigestive system drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e107.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eendocrine/metabolic drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1828\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecirculatory system drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e129.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecentral nervous system drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1549\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e121.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehormonal drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003evitamin trace elements\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehematological drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esurgical medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eantiallergic drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eurinary system drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eimmunomodulatory drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1378.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edermatological medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emedication for facial features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enutritional drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eantitumor drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eobstetrics and gynecology medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003econtrast agent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eantidote\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3212.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRationality of medication use\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrate the distribution of the reasons for unreasonable drug use between hospitals of different grades. Tertiary teaching hospitals exhibited the highest rational drug use rate, while tertiary general hospitals had the lowest rate, only 67.5%. A comparative analysis of the factors that influence irrational drug use in the three hospital grades revealed significant differences (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in both overall and pairwise comparisons between the groups. The elevated proportion of unreasonable drug use in tertiary teaching hospitals was attributed to inappropriate drug usage and dosage. In contrast, tertiary and secondary general hospitals showed higher rates of improper drug selection, followed by incorrect usage and dosage. Furthermore, some prescription formats in these hospitals were not standardized.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEvaluation results of rational use of medications\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehospital grade\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eirrational\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eproportion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eformat not standardized\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eimproper drug selection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003einappropriate route of administration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eincorrect dosage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eimproper combination of medication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etertiary teaching hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.81%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.05%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.06%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etertiary general hospital\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.58%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11.65%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.17%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esecondary general hospital\u003csup\u003e**##\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.47%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.63%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.83%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.06%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eNote: ** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, compared to tertiary teaching hospitals; \u003csup\u003e##\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, compared to tertiary general hospitals\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDuring the COVID-19 pandemic, infected patients received treatment primarily in outpatient clinics. The effective management of patients by FCs has proven instrumental in reducing hospitalization rates, particularly among vulnerable populations such as older patients, who face an elevated risk of severe outcomes, and individuals with underlying conditions such as obesity, cardiovascular disease, and diabetes [\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. FCs operate as specialized facilities within large general hospitals, playing a crucial role in the screening, diagnosing, and treating COVID-19 cases and curbing the spread of the epidemic. An essential component of this effort involves analyzing the spectrum of the disease and the medication status of patients seeking treatment.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eDemographic characteristics of patients seeking medical treatment\u003c/h2\u003e \u003cp\u003eThe time distribution chart of the patients indicates a notable increase in the number of individuals seeking medical treatment after the relaxation of the epidemic prevention and control measures in China on December 7, 2022. This increase is evident compared to the period of stringent control, and the numbers gradually stabilized after that. The global impact of the COVID-19 pandemic has resulted in a substantial disease burden [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In the context of a vast country with a population exceeding 1.4\u0026nbsp;billion, implementing rigorous epidemic control measures during the initial wave of the outbreak in China played a pivotal role in effectively managing the infection morbidity rate.\u003c/p\u003e \u003cp\u003e Analysis of the age distribution of the patients attending FCs and the sampling morbidity rate in 11 hospitals reveals that the highest morbidity rate was observed among individuals over 85 years, and children were closely followed. Among children, those under 6 years of age had the highest morbidity, consistent with findings from previous studies [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. After fitting, the morbidity rate shows a quadratic equation relationship with age. The fitted relationship equation exhibits good correlation, providing a reference for infection prediction across various age groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePatient disease spectrum\u003c/h2\u003e \u003cp\u003eThere were 1,013 different diagnoses of the disease among the patients, highlighting the complexity of the types of disease observed in individuals seeking medical treatment in FCs. Examining the distribution of diseases reveals a concentration of cases within the respiratory system, where respiratory infections and fever rank highest. These conditions serve as primary indicators and common accompanying diagnoses of COVID-19 infection [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], aligning with the diagnostic and therapeutic functions of FCs. Additionally, symptoms such as coughing, gastrointestinal dysfunction, and epilepsy/convulsions, which are commonly associated with COVID-19 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], also exhibit a high morbidity rate. Furthermore, the diagnosis of sepsis, electrolyte disorders, gastrointestinal bleeding, and other diseases with elevated morbidity rates suggests the presence of severe and critical cases of COVID-19 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Regarding drug use, drugs to regulate the water-electrolyte balance are the most commonly prescribed. Other commonly used medications include cefoperazone/sulbactam, piperacillin-tazobactam, and immunoglobulin, thus confirming the aforementioned results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of medications\u003c/h2\u003e \u003cp\u003eA total of 635 different medications were prescribed for FC patients. Based on the ranking of the number of drugs used, DDDs, and costs of medications, the selection of prescription drugs for FCs aligns well with the types of disease observed in patients. This includes antipyretic and analgesic, antiviral, and respiratory system medications. Among medications, drugs in the essential national formulary account for 34.3% of the variety and 73.1% of the total frequency of use. This indicates that physicians in FCs frequently recommend safe, effective, and cost-efficient national essential drugs to patients, thus alleviating the economic burden on patients. The proportion of guideline-recommended drugs is relatively low, reflecting the limited number of drugs recommended in the national COVID-19 diagnosis and treatment guidelines [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, the frequency of drugs recommended by the guideline is 43.2%. This indicates that physicians effectively followed the recommended treatment protocols for diagnosing and treating COVID-19 patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eThe role of traditional Chinese medicine\u003c/h2\u003e \u003cp\u003eThe findings of this study underscore the significant role of TCM in managing COVID-19. Among the medications administered to patients, 148 types of TCM are identified. TCM ranks fourth in terms of medication frequency and third in terms of medication cost. In particular, \u003cem\u003eLianhua Qingwen\u003c/em\u003e emerges as the most commonly used drug within TCM, securing the third position in both medication frequency and DDDs, and the fourth position in medication cost. Clinical studies have shown that \u003cem\u003eLianhua Qingwen\u003c/em\u003e can alleviate the clinical symptoms associated with COVID-19, substantially improve overall treatment efficacy, and reduce hospitalization and treatment duration [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Molecular biology research and network pharmacology predictions suggest that the active components of \u003cem\u003eLianhua Qingwen\u003c/em\u003e may exert therapeutic effects on COVID-19 infection by targeting angiotensin-converting enzyme 2 (ACE2), 3C-like protease (3CLpro), and interleukin (IL)-6 [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Additionally, six components within their formulation have the potential to interact with the active sites of the Akt1 gene, implicated in lung injury, pulmonary fibrosis, and viral infection, indicating a prospective therapeutic role in COVID-19 infection [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnalysis of medication rationality reveals a comparatively lower rate of medication rationality of 83.68% in FCs, significantly below that observed in outpatient, emergency, or inpatient services [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. This suggests that the medical staff in the FCs experienced increased work pressure, compounded by the challenges of epidemic control and patient care, leading to an increased likelihood of medical errors. Studies indicate that physicians are more susceptible to input errors in emergencies, and the time taken to complete prescription tasks is inversely correlated with the error rate [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Inappropriate prescriptions can lead to medication errors, elevated morbidity rates, or increased hospitalization rates, imposing economic burdens on patients [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Consequently, it is imperative to implement measures to mitigate prescription errors in FCs. This may include establishing standardized drug charts based on error analysis and system improvement evaluations and enhancing practical prescription education and training programs.\u003c/p\u003e \u003cp\u003eAnalysis of the number of prescriptions from 11 hospitals indicates the distinct roles that different grades of hospitals played during COVID-19, with tertiary teaching hospitals assuming primary reception tasks. In particular, there are significant variations in the distribution of the reasons for irrational medication use between hospitals of different grades. Tertiary teaching hospitals exhibit the highest rate of rational drug use. Reasons for unreasonable drug use are attributed to inappropriate drug use and dosage, representing a technical error in drug use. In contrast, the reason for irrational medication use in tertiary and secondary general hospitals was inappropriate drug selection, indicating a significant and unreasonable use of drugs. The second most common issue is incorrect usage and dosage, coupled with a notable prevalence of non-standardized prescription formats. Differences in the quality of drug utilization levels are observed between hospitals of different grades, and tertiary teaching hospitals demonstrate higher quality levels of drug use, consistent with findings in the existing literature [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Research suggests that, compared to other hospital grades, teaching hospitals possess robust teaching resources and advantages in talent development within universities, boasting a higher proportion of clinical experts. Consequently, they can provide more extensive and higher-quality medical services to the public [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The contemporary academic medical model of university hospitals, originating in the late 18th century, plays a pivotal role in present-day medical activities and is expected to be instrumental in driving future medical advancements.\u003c/p\u003e \u003cp\u003eThis study has several limitations. Research subjects are patients from FCs; assessing the patient's prognosis is impossible, and treatment outcomes remain unknown. Additionally, access to electronic prescription information is restricted due to the incomplete nature of the Hospital Information System in grassroots hospitals, such as community health centers and township health centers. As a result, this information was not included.\u003c/p\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe can share the raw data of this manuscript, the datasets generated are not publicly available due the reasons for patient privacy protection, but can be obtained from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Hebei Pharmaceutical Association Hospital Pharmacy Special Research Project (2022-HBsyxhqjyxzd01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the contributions from other members of the team including Zhenzhen Yang, Kai Wang, Jie Dong, and Yang Gao who provided data review, cleaning and proofreading.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the research team, Yaru Zang, Jingyi Yang, Kaining Yang, Yue Zhao, Wei Zhang, Shuanghu Guo, Chaoxu Han, Chaoxing Liu, Xiangzheng Mi, and Xiaoli Wang participated in data extraction and preliminary review, Zhiqing Zhang and Chuanping Wang conducted data validation. All authors read and approved the final version of the manuscript, had full access to all the data in the study, and had final responsibility for the decision to submit for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe agree to publish this paper by the BMC Department of Public Health.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHO coronavirus (COVID-19) dashboard. Geneva: World Health Organization. (https //covid19. who. int/table). \u003c/li\u003e\n\u003cli\u003eGottlieb RL, Vaca CE, Paredes R, et al. Early remdesivir to prevent progression to severe Covid-19 in outpatients. N Engl J Med. 2022 Jan 27; 386(4): 305-315. doi: 10. 1056/NEJMoa2116846.\u003c/li\u003e\n\u003cli\u003eWu Z, McGoogan JM. 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PLoS One. 2020 Sep 11;15(9): e0238828. doi: 10.1371/journal.pone.0238828. eCollection 2020.\u003c/li\u003e\n\u003cli\u003eHuang K, Zhang P, Zhang Z, Y et al. Traditional Chinese Medicine (TCM) in the treatment of COVID-19 and other viral infections: Efficacies and mechanisms. Pharmacol Ther. 2021 Sep; 225:107843. doi: 10.1016/j.pharmthera.2021.107843. Epub 2021 Mar 31.\u003c/li\u003e\n\u003cli\u003eXia QD, Xun Y, Lu JL, et al. Network pharmacology and molecular docking analyses on Lianhua Qingwen capsule indicate Akt1 is a potential target to treat and prevent COVID-19. Cell Prolif. 2020 Dec;53(12): e12949. doi: 10.1111/cpr.12949. Epub 2020 Nov 3.\u003c/li\u003e\n\u003cli\u003eDevarajan V, Nadeau NL, Creedon JK, et al. Reducing Pediatric Emergency Department Prescription Errors. Pediatrics. 2022 Jun 1;149(6): e2020014696. doi: 10.1542/peds.2020-014696.\u003c/li\u003e\n\u003cli\u003eFajreldines A, Bazzano M, Pellizzari M. 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Lancet. 2010 Feb 6;375(9713):462. doi: 10.1016/S0140-6736(10)60197-3.\u003c/li\u003e\n\u003cli\u003eBurke LG, Frakt AB, Khullar D, et al. Association between teaching status and mortality in US hospitals. JAMA. 2017 May 23;317(20):2105-2113. doi: 10.1001/jama.2017.5702.\u003c/li\u003e\n\u003cli\u003eNiedzwiecki MJ, Machta RM, Reschovsky JD, et al. Characteristics of academic-affiliated health systems. Acad Med. 2020 Apr; 95(4):559-566. doi: 10.1097/ACM.0000000000003149.\u003c/li\u003e\n\u003cli\u003eLai PM, Lin N, Du R. Effect of teaching hospital status on outcome of aneurysm treatment. World Neurosurg. 2014 Sep-Oct;82(3-4):380-385.e6. doi: 10.1016/j.wneu.2013.07.015.\u003c/li\u003e\n\u003cli\u003eRaus K, Mortier E, Eeckloo K. Past, present and future of university hospitals. Acta Clin Belg. 2020 Jun;75(3):177-184. doi: 10.1080/17843286.2019.1590024.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, Fever Clinics Isolated Area, Demographic Characteristics, Medication Use, Multicenter Study","lastPublishedDoi":"10.21203/rs.3.rs-3908849/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3908849/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eTo analyze the demographic characteristics and patterns of medication use among patients in fever clinics (FCs) during the COVID-19 outbreak in China and provide information for COVID-19 treatment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e: Various-grade general hospitals in China were selected, and patient information was extracted during the initial wave of the COVID-19 epidemic. Demographic characteristics were analyzed, including visit time, age, sampling morbidity rate, and disease distribution. Prescription information from the FC database was extracted to analyze drug use and the rationality of the medication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResult: \u003c/strong\u003eBetween September 1 and December 31, 2022, 41,445 patients received treatment at FCs in 11 included hospitals. After the relaxation of COVID-19 control measures, there was a rapid increase in the number of daily patient visits (peaking \u0026gt;1,000 people/day, with a growth rate of 158.8%). The highest sampling morbidity rate was observed among individuals over 85 years old (\u0026gt;100 person-times/million population), followed by children (60-94 person-times/million population). Respiratory system diseases (39,295 cases) were the most diagnosed, with respiratory system infections (21,201 cases) and fever (15,132 cases) the most common. The proportion and frequency of use of essential national drugs were 34.3% and 73.1%, respectively, while those for the drugs recommended in the national COVID-19 treatment guidelines were 6.1% and 43.2%, respectively. Ibuprofen, acetaminophen, and \u003cem\u003eLianhua Qingwen\u003c/em\u003e had the highest frequency of drug use. The most prescribed drugs by cost were immunoglobulin, azivudine, and cefoperazone sulbactam. The water-electrolyte balance regulator drugs, respiratory system drugs, anti-infective drugs, and traditional Chinese patent drugs were the most frequently used. In contrast, immunomodulators, anti-infectives, and Chinese patent drugs had the largest monetary amounts. There was a significant difference in medication rationality between different hospital grades (P\u0026lt;0.001), with tertiary teaching hospitals having the highest rate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eStrict epidemic control measures and the role of FCs played a crucial role in controlling the spread of the COVID-19 epidemic. Patients treated in FCs predominantly suffered from respiratory diseases, with older patients and children identified as high-risk populations. Physicians often choose national guidelines, essential drugs, and traditional Chinese for COVID-19 treatment. Tertiary teaching hospitals played a crucial role during the epidemic outbreak.\u003c/p\u003e","manuscriptTitle":"Analysis of Medication Utilization in Isolated Areas of Fever Clinics During the COVID-19 Epidemic Outbreak: A Multicenter Study in General Hospitals in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-09 17:08:48","doi":"10.21203/rs.3.rs-3908849/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a8529395-a8f0-4ad7-b624-089922b9449f","owner":[],"postedDate":"February 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-16T03:53:20+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-09 17:08:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3908849","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3908849","identity":"rs-3908849","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}