Appointment scheduling with customer impatience based on operating cost model

An appointment scheduling problem is studied with the consideration of customer impatience.On the assumption that both the time of leaving queue and the time of service are exponentially distributed,in order to minimize the joint cost,the optimal appointment schedule of the fixed number of customers is studied.The joint cost function is composed of customers expected delay time and service availability time.The expected delay time of each customer in the queue is recursively computed in terms of customer interarrival time.Furthermore,the effect of impatience on the optimal schedule as well as the total operating cost is studied.The results show that as the impatience rate increases,the optimal interarrival time becomes shorter and the interarrival time of the last few customers gradually approaches that of the customers in the middle.In addition,impatient behaviors can increase the joint cost.

Machine learning-based prediction models for patients no-show in online outpatient appointments

With the development of information and communication technologies,all public tertiary hospitals in China began to use online outpatient appointment systems.However,the phenomenon of patient no-shows in online outpatient appointments is becoming more serious.The objective of this study is to design a prediction model for patient no-shows,thereby assisting hospitals in making relevant decisions,and reducing the probability of patient no-show behavior.We used 382,004 original online outpatient appointment records,and divided the data set into a training set(N_(1)=286,503),and a validation set(N_(2)=95,501).We used machine learning algorithms such as logistic regression,k-nearest neighbor(KNN),boosting,decision tree(DT),random forest(RF)and bagging to design prediction models for patient no-show in online outpatient appointments.The patient no-show rate of online outpatient appointment was 11.1%(N=42,224).From the validation set,bagging had the highest area under the ROC curve and AUC value,which was 0.990,followed by random forest and boosting models,which were 0.987 and 0.976,respectively.In contrast,compared with the previous prediction models,the area under ROC and AUC values of the logistic regression,decision tree,and k-nearest neighbors were lower at 0.597,0.499 and 0.843,respectively.This study demonstrates the possibility of using data from multiple sources to predict patient no-shows.The prediction model results can provide decision basis for hospitals to reduce medical resource waste,develop effective outpatient appointment policies,and optimize operations.

Design and Implementation of Clinic Appointment Registration System

Clinic Appointment Registration System is an important way to see a doctor, and it’s also a preliminary tool for storage and management of clinic medical records. This new system was developed using Visual Studio 2008 and C#.NET as the development environment and tools and Microsoft Access 2003 as the database to store the medical data based on Browse/Server (B/S) model. The system consists of several data operation functions including appointment registration, data management (e.g. addition, deletion and searching), data backup and recovery, etc., thus, achieve key research ob-jectives.

Appointment of Dr. Xue-Long JIANG as the Associate Editor-in-Chief of Zoological Research

We are very pleased to announce that we have invited Dr. Xue-Long JIANG to serve as the Associate Editor-in-Chief for Zoological Research （ZR）, effective from 1 March, 2016. Dr. JIANG, Professor and principle investigator from the Laboratory of Mammal Ecology and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, has worked with ZR since 2006 as a member of the editorial board and has played an active and important role in maintaining ZR as a respected academic publishing platform. Currently, he also works as the Associate Editor-in-Chief of Acta Thefiologica Sinica, Mammal Research and as a senior editorial board member of Biodiversity Science.

Appointment of Dr. Wai-Yee Chan as the Associate Editor-in-Chief of Zoological Research

We are very pleased to announce that we have invited Dr. Wai-Yee Chan, Professor and Director of School of Biomedical Sciences, The Chinese University of Hong Kong, to serve as the Associate Editor- in-Chief for Zoological Research （ZR）, effective 1 September, 2016.

Quantum Algorithm for Appointment Scheduling

Suppose a practical scene that when two or more parties want to schedule anappointment, they need to share their calendars with each other in order to make itpossible. According to the present result the whole communication cost to solve thisproblem should be their calendars’ length by using a classical algorithm. In this work, weinvestigate the appointment schedule issue made by N users and try to accomplish it inquantum information case. Our study shows that the total communication cost will bequadratic times smaller than the conventional case if we apply a quantum algorithm in theappointment-scheduling problem.

The impact of out-of-pocket expenditures on missed appointments at HIV r care and treatment centers in Northern Tanzania

Background:Missed clinic appointments negatively impact clinic patient flow and health outcomes of people living with HIV(PLHIV).PLHIV likelihood of missing clinic appointments is associated with direct and indirect expenditures made while accessing HIV care.The objective of this study was to examine the relationship between out-of-pocket(OOP)health expenditures and the likelihood of missing appointments.Method:Totally 618 PLHIV older than 18 years attending two HIV care and treatment centres(CTC)in Northern Tanzania were enrolled in the study.Clinic attendance and clinical characteristics were abstracted from medical records.Information on OOP health expenditures,demographics,and socio-economic factors were self-reported by the participants.We used a hurdle model.The first part of the hurdle model assessed the marginal effect of a one Tanzanian Shillings(TZS)increase in OOP health expenditure on the probability of having a missed appointment and the second part assessed the probability of having missed appointments for those who had missed an appointment over the study period.Results:Among these 618 participants,242(39%)had at least one missed clinic appointment in the past year.OOP expenditure was not significantly associated with the number of missed clinic appointments.The median amount of OOP paid was 5100 TZS per visit,about 7%of the median monthly income.Participants who were separated from their partners(adjusted odds ratio[AOR]=1.83,95%confidence interval[CZ]:1.11-8.03)and those aged above 50 years(AOR=2.85,95%CI:1.01-8.03)were significantly associated with missing an appointment.For those who had at least one missed appointment over the study period,the probability of missing a clinic appointment was significantly associated with seeking care in a public CTC(P=0.49,95%CI:0.88-0.09)and aged between>25-35 years(P=0.90,95%CI:0.11-1.69).Conclusion:Interventions focused on improving compliance to clinic appointments should target public CTCs,PLHIV aged between>25-35 years,above 50 years of age and those who are separated from their partners.

An Extended Bailey-welch Rule with No-show and Walk-in For Outpatient Appointment Scheduling

In clinic＇s appointment scheduling system no-shows have been a significant and confirmed issue with a bad influence on patient accessibility and clinic efficiency. The problem of walk-in has often been seen as the opposite of no-show problem. In this work we revisit a walk-in admitting based approach to mitigate the bad influence of no-show without overbooking. First we establish a model which utilizes marginal benefit objective function to balance the interests of the clinic, the patient and the doctor, we prove that no-show and walk-in cancels out each other straightly has a bad property. Then we propose a new rule which is an extension of the well-known Bailey - Welch rule, the simulation results show that our rule has an improvement comparing with the common rule that cancels them out straightly.

Understanding the antecedents of patients’missed appointments:the perspective of attribution theory

The occurrence of missed appointments from online outpatient bookings significantly hinders the operational efficiency of outpatient services.This study aimed to investigate various factors influencing patients’missed appointments from online outpatient bookings.Drawing on attribution theory,an empirical analysis was conducted using 382,004 authentic online outpatient appointments.The empirical findings revealed that appointment lead-time,appointment time,weekday appointments,online doctor rating,appointment doctor’s expertise,patient distance,and previous outpatient visit experience significantly influenced patients’missed appointment behaviors from online outpatient bookings.Importantly,previous outpatient experience positively moderated the relationship between the appointment doctor’s expertise and patients’missed-appointment behavior.This study provides insights into the factors influencing patients’missed-appointment behavior from online outpatient bookings.It further offers a theoretical foundation for medical institutions in China to mitigate the likelihood and adverse effects of patients’missed-appointment behavior from online outpatient bookings.

Visual analysis of shared medical appointments based on CiteSpace

Objective:Analyze the research hotspots and frontiers of shared outpatient service,and provide a reference for researchers in this field to carry out follow-up research.Methods:Search the Web of Science core collection database until 2022 and visually analyzekeywords in this field through CiteSpace5.8.R3 software,Results:A total of 261 iteratures were included.The research focuses mainly on advanced care planning,diabetes care,andgroup prenatal care,The research trend tends to be telemedicine and nursing provided by specialized nurses.Conclusion:Scholars can learn from the research hotspots of foreign shared medical appointments,pay attention to the research trend,expand its application scope in combination with China's national conditions,and further promote thedevelopment of shared medical appointments in China.

Making an Appointment

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Can Real-Name Registration Clean Up Micro-Blogs?

Beijing Municipal Public Security Bureau and related departments have issued a regulation to strengthen the management of Twitter-like micro-blogs.The regulation,issued on December 16,2011,requires Internet companies registered in the city and offering micro-blogging services to have their users register with their real names and personal information.Users＇ identity information must be validated before they begin blogging.Starting March 16,2012,microbloggers without real-name registration will not be allowed to blog.

Keeping an Appointment With Death The Final Contribution of a Woman Doct

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Evaluation of the Effectiveness of the Competency Model for Nursing Managers in the Training of Newly Appointed Head Nurses

Objective:To explore the effectiveness of the competency model for nursing managers in the training of newly appointed head nurses.Methods:Eighteen newly appointed head nurses from Yichang Central People’s Hospital,selected between August 2023 and July 2024,were chosen as the research subjects.Based on the nursing manager competency model,corresponding training programs were developed,and these 18 head nurses were trained accordingly.Results:After the training,all newly appointed head nurses passed the theoretical assessments,with a pass rate of 100.00%.The pass rates for two rounds of assessment were 100.00%and 94.54%,respectively.There was no significant difference in the performance evaluation scores between new and senior head nurses in terms of standardized services,nursing quality,nursing research and teaching,and patient satisfaction(P>0.05).Conclusion:The competency model for nursing managers has a significant effect on the training of newly appointed head nurses.It effectively enhances management awareness,facilitates role transition,and,to some extent,improves the management and leadership capabilities of head nurses.It holds high value for broader implementation.

清华简与《古文尚书》中的傅说形象

传统上所熟知的傅说是一个“王者师”的圣贤,这一形象由孔传本《说命》三篇塑造。结合清华简《傅说之命》以及孔传本《说命》的文本研究,可知孔传本《说命》绝非魏晋时人所能伪造,其成篇年代当在战国初年前后。新出清华简《傅说之命》上、中两篇的成篇年代在春秋初年前后,上篇将傅说塑造成一个人神参半的上帝使臣。《傅说之命》下篇的成篇年代约在西周中晚期,将傅说塑造成一个蜷缩在森严王权下的人臣,这是最接近真实傅说的人物形象。傅说作为“王者师”的圣贤形象是春秋战国之际以儒家为代表的士人为实现自身理想与抱负而塑造的历史范例,对后世产生了深远的影响。

一体化门诊手术管理系统的设计与应用

目的解决医院门诊手术信息化程度低、尚未形成统一的全流程闭环管理体系的问题,以提高患者就医效率,提高医护人员工作效率。方法深入分析门诊手术业务需求,设计一体化门诊手术管理系统。系统设计采用模块化与微服务架构,并融合前沿开发技术,实现手术预约、排程、术前准备、术中记录、费用补收等各环节的有机整合,形成闭环管理。实现手术预约、项目审核、文书记录、费用补收及查询统计等系统功能。结果该系统的引入极大地提升了门诊手术效率,患者就诊平均时间由(12.82±0.88)min降低至(10.97±0.53)min,门诊手术补收费用的漏收率由13.22%降低至5.86%,且差异均有统计学意义(P<0.05)。结论该系统可满足门诊手术医护人员的工作需要,可显著提高医护人员工作效率、患者门诊就诊效率,提升患者就诊满意度。

潮水洞岩溶系统中有机氯农药的时空分布特征,来源与迁移

为研究岩溶地下水易受地表污染物影响的问题,选取了湖北宜昌一典型岩溶泉域——潮水洞为研究对象,采集了一年四季的水体.土壤和沉积物样品,分析了有机氯农药(OCPs)在岩溶泉系统中的污染特征,来源及迁移过程.结果表明,潮水洞地表水和泉水中OCPs的平均浓度为8.25ng/L和5.11ng/L,土壤及沉积物中OCPs的平均浓度分别为15.9ng/g和12.6ng/g.与其他地区相比,潮水洞岩溶泉域中OCPs的污染处于较低水平,其季节性变化特点与当地水文地质条件及OCPs迁移过程密切相关.HCHs和DDTs的特征比值溯源结果显示,水体和沉积物中的HCHs主要来源于林丹(γ-HCH)的输入,土壤中的HCHs则主要来源于工业HCHs的输入;DDTs在水体,土壤和沉积物3种介质中都是属于混合来源,即来源于工业DDT和三氯杀螨醇.研究表明,补给区土壤中OCPs对上游地表水中OCPs的贡献率为87.8%,对泉水的贡献率为58.3%,排泄区泉水中OCPs对泉沉积物中OCPs的贡献率为64.2%.OCPs可通过地表迁移和地下迁移两种方式从补给区迁移至排泄区污染水体.

实施性研究利益相关方偏好评估——优劣尺度法的应用

在医疗卫生服务领域,结合健康服务供方和需方(即利益相关方)的偏好优化医疗创新服务至关重要。优劣尺度法(best-worst scaling,BWS)是一种新型陈述性偏好评估方法,具有独特优势。但目前国内尚缺乏此方法评估利益相关方偏好的详细介绍,限制其应用与推广。本文重点介绍应用BWS评估服务供方对医防融合服务——糖尿病共享门诊的偏好以及相关注意事项,旨在为研究者提供参考,促进BWS在实施性研究中的应用。

基于正定矩阵因子分解模型的污染源解析研究进展及应用前景

通过对最近10年间(2012—2022年)国内外文献资料检索分析,对正定矩阵因子分解(PMF)模型在环境污染源解析中的研究进行了全面梳理归纳,通过对PMF模型在不同受体和研究对象的污染源解析中应用结果的比较分析,提出了该模型应用存在的缺陷及其未来应用前景展望,可为将来更精准的环境污染源解析研究提供科学依据。当前,PMF模型在国内主要应用于大气和土壤等介质中的颗粒物、重金属和有机物等污染源解析,而国外则相对更多集中应用于大气颗粒物源解析。分析发现PMF模型获得的源分析结果与主成分分析法(PCA)、化学质量平衡法(CMB)和Unmix等方法不同,主要区别是对不确定性参数采用了不同取值方法,其次是对原始数据中的不确定性的反映存在不同。综上所述,PMF模型已经在大气颗粒物、土壤重金属和多环芳烃(PAHs)等的应用中相对广泛,但其在其他环境介质中的除上述讨论污染物以外的源解析中仍需要进一步深入探究。