Large General Hospitals In China Research Articles

Exploring the problems and coping strategies of pharmacy internship in large general hospitals in China: from the perspective of preceptors

ObjectiveThe role of the Hospital Pharmacy Preceptor (HPP) is pivotal in upholding the excellence of experiential training and fostering the professional growth of pharmacy interns. However, there is a lack of studies that provide an overview of pharmacy internships from the perspective of HPP. This study explores the experience and expectations of HPPs regarding existing problems and possible coping strategies in intern teaching. MethodsThis is a qualitative study that was conducted through individual interviews and focus group discussions. HPPs were invited as participants from large-scale tertiary hospitals in representative provinces of mainland China. Interview and focus group discussion data were analyzed using thematic analysis to see emerging themes from the data. Nvivo 12 was utilized for data management and processing.ResultsEight individual interviews and two focus group discussions were conducted, involving 14 HPPs as participants. Upon the examination of the interviews and focus group data, four themes were summarized regarding HPPs’ perceptions: 1) current presenting problems; 2) possible coping strategies; 3) something HPPs should do; 4) something interns should do.ConclusionThis study found that from the HPPs’ perspective, the hospital-based pharmacy internship still has some problems from policy to practice, which need to be addressed by the joint efforts of the state, schools, internship bases, pharmacy preceptors, and students.

Exploring Acute Pancreatitis Clinical Pathways Using a Novel Process Mining Method.

Mining process models of medical behavior from electronic medical records is an effective way to optimize clinical pathways. However, clinical medical behavior is an extremely complex field with high nonlinearity and variability, and thus we need to adopt a more effective method. In this study, we developed a fuzzy process mining method for complex clinical pathways. Firstly, we designed a multi-level expert classification system with fuzzy values to preserve finer details. Secondly, we categorized medical events into long-term and temporary events for more specific data processing. Subsequently, we utilized electronic medical record (EMR) data of acute pancreatitis spanning 9 years, collected from a large general hospital in China, to evaluate the effectiveness of our method. The results demonstrated that our modeling process was simple and understandable, allowing for a more comprehensive representation of medical intricacies. Moreover, our method exhibited high patient coverage (>0.94) and discrimination (>0.838). These findings were corroborated by clinicians, affirming the accuracy and effectiveness of our approach.

A reinforcement learning-based optimal control approach for managing an elective surgery backlog after pandemic disruption.

Contagious disease pandemics, such as COVID-19, can cause hospitals around the world to delay nonemergent elective surgeries, which results in a large surgery backlog. To develop an operational solution for providing patients timely surgical care with limited health care resources, this study proposes a stochastic control process-based method that helps hospitals make operational recovery plans to clear their surgery backlog and restore surgical activity safely. The elective surgery backlog recovery process is modeled by a general discrete-time queueing network system, which is formulated by a Markov decision process. A scheduling optimization algorithm based on the piecewise decaying [Formula: see text]-greedy reinforcement learning algorithm is proposed to make dynamic daily surgery scheduling plans considering newly arrived patients, waiting time and clinical urgency. The proposed method is tested through a set of simulated dataset, and implemented on an elective surgery backlog that built up in one large general hospital in China after the outbreak of COVID-19. The results show that, compared with the current policy, the proposed method can effectively and rapidly clear the surgery backlog caused by a pandemic while ensuring that all patients receive timely surgical care. These results encourage the wider adoption of the proposed method to manage surgery scheduling during all phases of a public health crisis.

Analysis of risk factors associated with healthcare-associated carbapenem-resistant Klebsiella pneumoniae infection in a large general hospital: a case-case-control study.

Carbapenem-resistant Klebsiella pneumoniae (CRKP) infection is a major public health threat in the world. To inform the prevention and control of CRKP infection in hospitals, this study analyzed the factors associated with CRKP infection and resistance to carbapenems in K. pneumoniae. This case-case-control study was carried out in a large general hospital in China from January 2016 to December 2018, comprising 494 hospitalized patients infected with CRKP (case group 1) and 2429 hospitalized patients infected with carbapenem-susceptible K. pneumoniae (CSKP, case group 2). We selected control groups from hospitalized patients without K. pneumoniae infections for the two case groups separately, with a 1:3 case-control ratio, to analyze the risk factors of the two case groups using the conditional logistic regression. Multivariate analysis showed that the risk factors of CRKP infection were intensive care unit (ICU) admission (odds ratio [OR], 6.85; 95% confidence interval [CI], 4.90-9.58; P < 0.001), respiratory failure (OR, 1.93; 95% CI, 1.34-2.77; P < 0.001), age-adjusted Charlson comorbidity index (aCCI; OR, 1.08; 95% CI, 1.02-1.15; P = 0.007), admission from the Emergency (OR, 1.37; 95% CI, 1.02-1.85; P = 0.036), and imipenem use (OR, 1.80; 95% CI, 1.30-2.49; P < 0.001). Among the aforementioned five risk factors, aCCI (OR, 1.09; 95% CI, 1.06-1.13; P < 0.001) was also identified as a risk factor of CSKP infections in multivariate analysis. The risk factors for resistance to carbapenems in K. pneumoniae were ICU admission, respiratory failure, admission from the Emergency, and imipenem use.

Clonal Spread of Carbapenem-Resistant Klebsiella pneumoniae Sequence Type 11 in Chinese Pediatric Patients.

Klebsiella pneumoniae often causes life-threatening infections in patients globally. Despite its notability, little is known about potential nosocomial outbreak and spread of K. pneumoniae among pediatric patients in low- and middle-income countries. Ninety-eight K. pneumoniae strains isolated from pediatric patients in a large general hospital in China between February 2018 and May 2019 were subjected to nanopore and Illumina sequencing and genomic analysis to elucidate transmission and genetic diversity. The temporal distribution patterns of K. pneumoniae revealed a cluster of sequence type 11 (ST11) strains comprising two clades. Most inferred transmissions were of clade 1, which could be traced to a common ancestor dating to mid-2017. An infant in the coronary care unit played a central role, potentially seeding transmission clusters in other wards. Major genomic changes during the outbreak included chromosomal mutations associated with virulence and gains and losses of plasmids encoding resistance. In summary, we report a nosocomial outbreak among pediatric patients caused by clonal dissemination of KPC-2-producing ST11 K. pneumoniae. Our findings highlight the value of whole-genome sequencing during outbreak investigations and illustrate that transmission chains can be identified during hospital stays. IMPORTANCE We report a nosocomial outbreak among pediatric patients caused by clonal dissemination of blaKPC-2-carrying ST11 K. pneumoniae. Strains of various sequence types coexist in the complex hospital environment; the quick emergence and spread of ST11 strains were mainly due to the plasmid-mediated acquisition of resistance genes. The spread of hospital infection was highly associated with several specific wards, suggesting the importance of genomic surveillance on wards at high risk of infection.

Early Warning of Infectious Diseases in Hospitals Based on Multi-Self-Regression Deep Neural Network.

Objective Infectious diseases usually spread rapidly. This study aims to develop a model that can provide fine-grained early warnings of infectious diseases using real hospital data combined with disease transmission characteristics, weather, and other multi-source data. Methods Based on daily data reported for infectious diseases collected from several large general hospitals in China between 2012 and 2020, seven common infectious diseases in medical institutions were screened and a multi self-regression deep (MSRD) neural network was constructed. Using a recurrent neural network as the basic structure, the model can effectively model the epidemiological trend of infectious diseases by considering the current influencing conditions while taking into account the historical development characteristics in time-series data. The fitting and prediction accuracy of the model were evaluated using mean absolute error (MAE) and root mean squared error. Results The proposed approach is significantly better than the existing infectious disease dynamics model, susceptible-exposed-infected-removed (SEIR), as it addresses the concerns of difficult-to-obtain quantitative data such as latent population, overfitting of long time series, and considering only a single series of the number of sick people without considering the epidemiological characteristics of infectious diseases. We also compare certain machine learning methods in this study. Experimental results demonstrate that the proposed approach achieves an MAE of 0.6928 and 1.3782 for hand, foot, and mouth disease and influenza, respectively. Conclusion The MRSD-based infectious disease prediction model proposed in this paper can provide daily and instantaneous updates and accurate predictions for epidemic trends.

Exploring the experiences and expectations of pharmacist interns in large general hospitals in China: from the perspective of interns

BackgroundHospital-based pharmacy internship (HBPI) is critical for the transition from “pharmacy students” to “professional pharmacists”. This study explores the pharmacist interns’ experiences and expectations for HBPI from their personal experiences intending to provide references for future hospital pharmacy education reform and policy development.MethodsThis is a multicenter qualitative study applying focus group discussions. Pharmacist interns were invited as participants from large teaching hospitals in Henan, China. A thematic analysis was conducted to qualitatively analyze this data. Nvivo 12 was utilized for data management and processing.ResultsThree focus group discussions were conducted, involving 16 interns as participants. Three themes were summarized regarding interns’ expectations and experiences: (1) positive experiences of the HBPI; (2) negative experiences of the HBPI; (3) expectations and suggestions for the HBPI.ConclusionThis study finds that the HBPI improves the professional knowledge, professional skills, and core competencies of interns. Therefore, the HBPI is an important preparation and transition stage for pharmacy students. However, the current pharmacy internship in China still has imperfections such as the insufficient ability of clinical teachers, unreasonable internship models, and unscientific internship content.

Spatial distribution of patient traffic volume in outpatient buildings of large general hospitals in China

ABSTRACT The spatial distribution of patient traffic is important for hospital building design, but there is still insufficient targeted discussion for Chinese outpatient buildings. To obtain reliable evidence, this study examined the outpatient traffic spatial distribution in a large Chinese general hospital by describing it as a set of inter-department patient traffic frequencies (q), which means the ratio of the number of patient trips within a pair of department units to the hospital’s total outpatient visits. Through three hospital samples and 2443 patient samples, three main findings were obtained: (1) The “q” value sets of each hospital sample and their average value set were obtained, and the idea of using them as evidence in outpatient building design was presented; (2) Outpatient traffic distribution was similar among hospitals and was characterized by clustering among certain departments: 38 out of 150 traffic sections created 90% of outpatient traffic, and four public departments’ outpatient traffic presented directivity; (3) There was an indicated slight variation among the samples; therefore, more precise evidence for specific cases required “q” values generated by themselves, which could be obtained conveniently through methods presented in this study. Subsequently, both evidence and methods are provided.

The Demand for Specialization and Its Influence on the Design of Inpatient Nursing Units: Can Standardized Design Be Done Once and for All?

This study explores the specialized nursing requirements of different clinical departments and their influence on the design of nursing units, which ultimately improves the nursing staff's efficiency and work experience. Specialization of nursing work is important in the provision of quality of healthcare. Most of the research related to nursing units has focuses on general medical-surgical nursing units and has not differentiated between clinical departments. This study was conducted in one inpatient building at a large general hospital in China. Survey data were collected from 11 clinical departments via questionnaire, and interviews were conducted in 10 of the clinical departments. All 11 clinical departments had significant differences in their evaluations of and requirements for the arrangement of their physical space. Specialized requirements were found in three areas: nursing work processes, arrangement and needs of clinical spaces, and allocation of facilities and equipment. Evaluation of the specialized requirements of different clinical departments would contribute to the body of knowledge on nursing unit design and has a positive effect on the development and improvement of design theory. Suggestions for how the design of nursing units could be improved to support the specialized demands of different departments are provided.

Modeling clinical activities based on multi-perspective declarative process mining with openEHR\u2019s characteristic

BackgroundIt is significant to model clinical activities for process mining, which assists in improving medical service quality. However, current process mining studies in healthcare pay more attention to the control flow of events, while the data properties and the time perspective are generally ignored. Moreover, classifying event attributes from the view of computers usually are difficult for medical experts. There are also problems of model sharing and reusing after it is generated.MethodsIn this paper, we presented a constraint-based method using multi-perspective declarative process mining, supporting healthcare personnel to model clinical processes by themselves. Inspired by openEHR, we classified event attributes into seven types, and each relationship between these types is represented in a Constrained Relationship Matrix. Finally, a conformance checking algorithm is designed.ResultsThe method was verified in a retrospective observational case study, which consists of Electronic Medical Record (EMR) of 358 patients from a large general hospital in China. We take the ischemic stroke treatment process as an example to check compliance with clinical guidelines. Conformance checking results are analyzed and confirmed by medical experts.ConclusionsThis representation approach was applicable with the characteristic of easily understandable and expandable for modeling clinical activities, supporting to share the models created across different medical facilities.

Nurse staffing in large general hospitals in China: an observational study

BackgroundThe appropriate staffing of nurses not only reflects the situation of nursing management of human resource, but also is related to the nursing quality in hospitals. This study investigated the staffing of nurses in large general hospitals in China.MethodsIn this study, a database established by the National Centre for Nursing Care Quality Control, which conducted a national survey of the staffing of nurses in China mainland in 2017, was analysed. The time-point survey data of 20 375 departments in 668 large general hospitals in China were obtained, including the information of nurses and patients during the day (10:00 am) and at night (10:00 pm). Then, the staffing of nurses was evaluated by calculating the nurse to patient ratio (the average number of patients assigned to a nurse, NTP ratio). The Kruskal-Wallis test was performed to compare the NTP ratios during the day and at night among different regions and departments.ResultsIn large general hospitals, a nurse takes care of eight patients (NTP ratio = 1:8.0) during the day and 23 patients at night (NTP ratio = 1:23) on average. There were significant differences between day and night. In terms of different regions, a nurse in the hospitals in the western region takes care of 7.8 patients during the day (NTP ratio = 1:7.8) on average, and the nursing resource in the western region is more adequate than that in the eastern (1:8.0) and central (1:8.0) regions. At night, the eastern region has a higher level of NTP (1:23.0). In terms of departments, a nurse working in the ICU takes care of two patients during the day (NTP ratio = 1:2.0) and 2.9 patients at night (NTP ratio = 1:2.9). The level of NTP in the oncology department is relatively higher: 9.3 during the day and 34.0 at night. Other departments including internal medicine, surgery, obstetrics and gynaecology, paediatrics, and geriatrics have NTP ratios of 1:7–8 during the day and 1:18–25 at night.ConclusionsIn China, the nurse staffing of large general hospitals has some regional and departmental patterns. The low level of nurse staffing at night may be a problem worthy of attention; the Chinese government needs to establish standards for different periods and departments to improve efficiency and quality of nursing.

Demographic Characteristics, Etiology, and Comorbidities of Patients with Cushing's Syndrome: A 10-Year Retrospective Study at a Large General Hospital in China.

Purpose To investigate the demographic characteristics, etiology, and comorbidities of Cushing's syndrome (CS) patients at a large medical center in China. Methods Records on CS patients discharged from 2008 to 2017 were retrieved from the hospital discharge abstract database (DAD) using ICD-10 codes. Demographic characteristics, etiology, and comorbidity data were analyzed. Results Cushing's disease (CD) accounted for 63.0% of CS patients, followed by adrenocortical adenoma (ACA) (20.9%), primary bilateral macronodular adrenal hyperplasia (BMAH) (6.2%), ectopic ACTH syndrome (EAS) (5.9%), primary pigmented nodular adrenocortical disease (PPNAD) (1.8%), and adrenocortical carcinoma (ACC) (1.0%). CD, ACA, ACC, and PPNAD presented marked preponderances in women (4.1 : 1, 10.5 : 1, 4.3 : 1, and 2.3 : 1, respectively), while BMAH (59.8%) and EAS (51.0%) showed slightly higher preponderances in men. CD patients were younger than ACA and EAS patients (36.1 ± 12.9 years vs. 39.4 ± 12.7 years and 36.1 ± 12.9 years vs. 41.0 ± 15.8, P < 0.001); PPNAD patients were the youngest (24.2 ± 10.8 years, P < 0.001), and BMAH patients were the oldest (51.3 ± 9.9 years, P < 0.001). Hypertension, diabetes mellitus, osteoporosis without fractures, osteoporotic fractures, dyslipidemia, and fatty liver occurred more frequently in CD patients than in ACA patients (P < 0.001 for all). Osteoporotic fractures were observed more frequently in PPAND than in ACA (26.7% vs. 9.0%, P < 0.001) and BMAH (26.7% vs. 4.9%, P < 0.001) patients. EAS patients had more severe and diverse comorbidities, with higher prevalences of hypokalemia (52.0%), diabetes mellitus (61.2%), and osteoporotic fractures (28.6%). When adjusted for age, male CD patients were associated with hypertension (OR = 2.266, 95% CI: 1.524–3.371, and P < 0.001), osteoporotic fractures (OR = 2.274, 95% CI: 1.568–3.298, and P < 0.001), fatty liver (OR = 1.435, 95% CI: 1.028–2.003, and P = 0.034), and hypokalemia (OR = 1.944, 95% CI: 1.280–2.951, and P = 0.002). Conclusions The proposed method efficiently evaluates CS patients' epidemiological profiles using hospital DADs with ICD-10 codes and thus may enrich the limited epidemiological data and contribute to clinical practice for CS.

Assessment of the Risk of Venous Thromboembolism in Medical Inpatients using the Padua Prediction Score and Caprini Risk Assessment Model.

Aim: The optimal risk assessment model (RAM) to stratify the risk of venous thromboembolism (VTE) in medical inpatients is not known. We examined and compared how well the Padua Prediction Score (PPS) and the Caprini RAM stratify VTE risk in medical inpatients.Methods: We undertook a retrospective case-control study among medical inpatients admitted to a large general hospital in China during a 4-year period. In total, 902 cases were confirmed to have VTE during hospitalization and 902 controls were selected randomly to match cases by medical service.Results: The VTE risk increased significantly with an increase of the cumulative PPS or Caprini RAM score. A PPS and Caprini RAM “high risk” classification was, respectively, associated with a 5.01-fold and 4.10-fold increased VTE risk. However, the Caprini RAM could identify 84.3% of the VTE cases to receive prophylaxis according to American College of Chest Physicians guidelines, whereas the PPS could only identify 49.1% of the VTE cases. In the medical inpatients studied, five risk factors seen more frequently in VTE cases than in controls in the Caprini RAM were not included in the PPS. The Caprini RAM risk levels were linked almost perfectly to in-hospital and 6-month mortality.Conclusions: Both the PPS and Caprini RAM can be used to stratify the VTE risk in medical inpatients effectively, but the Caprini RAM may be considered as the first choice in a general hospital because of its incorporation of comprehensive risk factors, higher sensitivity to identify patients who may benefit from prophylaxis, and potential for prediction of mortality.

Research on the Influence of Doctor-Patient Relationship on Physicians’ Citizenship Behavior

Although the doctor-patient relationship (DPR) is a predictor of organizational citizenship behavior (OCB), the relations between DPR and OCB is not well understood. This study was designed to investigate the specific dimensions of OCB among physicians in China and determine the effects of DPR on OCB. The subjects were physicians at five large general hospitals in China, who were selected by random sampling methodology. Then, using empirical study methods, factor analysis and regression analysis for data collecting from 958 samples were made. Finally, we find that OCB consists of four dimensions including civic virtue, sportsmanship, altruism, and conscientiousness. DPR has significant negative impact on the civic virtue, sportsmanship, altruism, and conscientiousness behaviors, respectively. This finding suggests that effective strategies should be applied to promote physicians’ OCB by improving DPR, which can enhance their job performances and improve the quality of health care delivery.

Suicidal ideation among Chinese cancer inpatients of general hospitals: prevalence and correlates.

Cancer patients are at high risk for suicide, particularly when they are informed about the cancer diagnosis or hospitalized for cancer treatment. Therefore, oncology healthcare settings such as large general hospitals in China, may represent an ideal setting to identify and treat suicidality in cancer patients. However, the clinical epidemiology of suicidality of Chinese cancer patients remains largely unknown. This study examined the prevalence and correlates of suicidal ideation among Chinese cancer inpatients of large general hospitals. A total of 517 cancer inpatients were consecutively recruited from two tertiary general hospitals of a metropolitan city in northern China, and administered with standardized questionnaires to collect data on sociodemographics, mental health, and cancer-related clinical characteristics. Suicidal ideation and mental health were measured with a single self-report question “In the past month, did you think about ending your life?” and Hospital Anxiety and Depression Scale, respectively. The one-month prevalence of suicidal ideation was 15.3% in Chinese cancer inpatients. In multivariable Logistic regression, depression, anxiety, moderate-to-severe pain, metastatic cancer, poor performance status, surgery, and palliative care were significantly associated with suicidal ideation. Cancer inpatients of large Chinese general hospitals have high prevalence of suicidal ideation and therefore potentially at high risk for suicide. Suicide prevention efforts for cancer inpatients should include periodic evaluation of suicidality, effective pain management, psychooncological supports, and, when necessary, psychiatric treatment and crisis intervention.

The Sensitivity of Pap Cytology and HPV Testing to Detect Cervical Cancer: Prior Testing Results in 178 Patients with Invasive Cervical Cancer at a Large General Hospital in China

The Sensitivity of Pap Cytology and HPV Testing to Detect Cervical Cancer: Prior Testing Results in 178 Patients with Invasive Cervical Cancer at a Large General Hospital in China

The sensitivity of Pap cytology and HPV testing to detect incident cervical cancer: prior testing results in 178 patients with invasive cervical cancer at a large general hospital in China

Prior screening results in women diagnosed with cervical carcinoma are only reported in the literature in small numbers. We wish to examine a larger number of prior testing results in women with cervical carcinoma from China to better understand the strengths and weaknesses of Pap (Papanicolaou) cytology and human papillomavirus (HPV) testing. In our study, 178 patients with histologically diagnosed cervical carcinoma and Pap cytology and/or HPV testing in the year prior to diagnosis were retrospectively studied. Pap cytology was performed using liquid-based preparations and HPV testing was done with mostly Hybrid Capture 2 but also included other methods. In our study, 82.0% of women were symptomatic at presentation with vaginal bleeding or abnormal vaginal discharge. HPV testing was negative in 9.8% of women in the short period before diagnosis of cervical cancer and Pap cytology had a higher rate of false negative results at 16.7%. Adenocarcinoma showed a higher negative testing rate than squamous cell carcinoma did with both cytology and HPV testing. Only 1 of 78 patients (1.3%) having both tests showed a double negative result. Negative high-risk HPV testing was noted in 2 of 9 squamous cell carcinoma patients with routine gynecological examination. Both Pap cytology and HPV testing have higher rates of prior negative results in women with cervical carcinoma. When testing is performed using both methods, the greatest number of cervical carcinomas can be detected. These results should also be considered when making screening recommendations with the understanding that HPV testing alone will miss at least a proportion of women with incident cervical carcinoma.

Sound Environment of Waiting Areas in Large General Hospitals in China

Sound Environment of Waiting Areas in Large General Hospitals in China

A novel SHV-type β-lactamase variant (SHV-89) in clinical isolates in China

Two clinical strains of Klebsiella pneumoniae (K. pneumoniae) and one isolate of Escherichia coli (E. coli) were collected from two large general hospitals in China. Conjugation experiment, susceptibility testing, isoelectric focusing, PCR, and sequencing techniques as well as clone, expression, purification and kinetics were carried out to describe the characterization of the novel SHV-tpye enzyme. The analysis of plasmid profiling and pulsed-field gel electrophoresis of the novel enzyme were performed to investigate epidemiology. These isolates had CTX-M-14 and SHV-89 beta-lactamases. SHV-89 beta-lactamase of pI 7.6 is a novel variant with two substitutions compared with the sequence of SHV-1: Leu35Gln and Met129Val. Its gene also had two silent mutations at positions 369 and 774, respectively. The results of substrate profiles and MIC determinations showed the activity of the novel enzyme was insufficient for the enzyme to count as an extended-spectrum beta-lactamase (ESBL). The substrates of the enzyme were also characterized. Furthermore, the three novel SHV enzyme-producing strains were epidemiologically unrelated. The emergence of a novel SHV-type beta-lactamase is rarely described in other areas. This study illustrates the importance of molecular survelliance in tracking SHV-producing strains in large teaching hospitals and emphasizes the need for epidemiological monitoring.

User Acceptance of Computerized Physician Order Entry

Computerized physician order entry (CPOE) holds potential of reducing medical errors, improving care quality, and cutting healthcare costs. Yet, its success largely depends on physicians’ acceptance and subsequent usage. This study examines whether Technology Acceptance Model (TAM) can be applied to explain physician acceptance of CPOE. A survey was conducted in a large general hospital in China, and 103 data were collected from 200 physicians. The data analysis provided support for all relationships predicted by TAM but failed to support the relationship between ease of use and attitude. A follow-up analysis showed that this relationship is moderated by CPOE experience. Under the condition of high CPOE experience, perceived ease of use has no effect on attitude, whereas under the condition of low CPOE experience, perceived ease of use positively affects attitude. Implications for healthcare informatics are discussed.