Medical staff configuration is a critical problem in the management of an emergency department (ED) in Hong Kong (HK). Given the service requirements by HK government, it is imperative for the hospital managers to develop medical staff configuration in a cost-and-time-effective way. In this paper, the medical staff configuration problem in ED is modeled as minimizing the total labor cost while satisfying the service quality requirements. To solve this issue, we propose a highly efficient search method, called random boundary generation with feasibility detection (RBG-FD). The random boundary generation (RBG) is applied to efficiently identify good-quality solutions based on the objective value. The feasibility detection (FD) procedure is used to retain the probability of correct feasibility detection of each sampled solution at the desired level, which intrinsically allocates a reasonable number of simulation replications. To estimate the performance measures of the ED, a discrete-event simulation model is developed to reflect the patient flow. Using these techniques, the efficiency of identifying the optimal staff configuration can be significantly improved. A case study is performed in a public hospital in HK. The numerical results indicate significantly higher practicability and efficiency of the proposed method with different patient arrival rates and service constraints. Note to Practitioners This paper seeks to solve the problem of minimizing the medical staff cost constrained by certain service requirements [i.e., patients’ waiting times for treatment] at an emergency department in Hong Kong. In our formulation, these service requirements are characterized by some stochastic constraints. Most of the existing random search methods concentrate on the computing efforts in the neighborhood of the best-so-far solutions in order to obtain good-quality solutions. Due to the special structure of this problem and ease of computing the objective values, we proposed an efficient random search approach that iteratively identifies a solution with a better objective value than that of the current best solution. Experimental studies demonstrate the significantly higher efficiency of this method. In order to obtain the same solution quality, it is able to reduce the computational time by 90% compared with some existing approaches in the literature.

The Hospital Authority (HA) is a statutory body managing all the public hospitals and institutes in Hong Kong (HK). In recent decades, Hong Kong Hospital Authority (HKHA) has been making efforts to improve the healthcare services, but there still exist some problems like unfair resource allocation and poor management, as reported by the Hong Kong medical legislative committee. One critical consequence of these problems is low healthcare efficiency of hospitals, leading to low satisfaction among patients. Moreover, HKHA also suffers from the conflict between limited resource and growing demand. An effective evaluation of HA is important for resource planning and healthcare decision making. In this paper, we propose a two-phase method to evaluate HA efficiency for reducing healthcare expenditure and improving healthcare service. Specifically, in Phase I, we measure the HKHA efficiency changes from 2000 to 2013 by applying a novel DEA-Malmquist index with undesirable factors. In Phase II, we further explore the impact of some exogenous factors (e.g., population density) on HKHA efficiency by Tobit regression model. Empirical results show that there are significant differences between the efficiencies of different hospitals and clusters. In particular, it is found that the public hospital serving in a richer district has a relatively lower efficiency. To a certain extent, this reflects the socioeconomic reality in HK that people with better economic condition prefers receiving higher quality service from the private hospitals.

CLinical Accounting InforMation (CLAIM) is a standard for the exchange of data between patient accounting systems and electronic medical record (EMR) systems. It uses eXtensible Markup Language (XML) as a meta-language and was developed in Japan. CLAIM is subordinate to the Medical Markup Language (MML) standard, which allows the exchange of medical data between different medical institutions. It has inherited the basic structure of MML 2.x and the current version, version 2.1, contains two modules and nine data definition tables. In China, no data exchange standard yet exists that links EMR systems to accounting systems. Taking advantage of CLAIM's flexibility, we created a localized Chinese version based on CLAIM 2.1. Since Chinese receipt systems differ from those of Japan, some information such as prescription formats, etc. are also different from those in Japan. Two CLAIM modules were re-engineered and six data definition tables were either added or redefined. The Chinese version of CLAIM takes local needs into account, and consequently it is now possible to transfer data between the patient accounting systems and EMR systems of Chinese medical institutions effectively.

Medical Markup Language(MML) is a standard for the exchange of medical data among different medical institutions. It was developed in Japan in 1995. Since version 2.21, MML has used extensible Markup Language(XML) as a meta-language. The latest version, 3.0, conforms to HL7 Clinical Document Architecture(CDA) and contains 14 modules and 36 data definition tables. In china, a standard which structures entire medical records in XML does not yet exist. Taking advantage of MML's flexibility, we created a localized Chinese version based on MML 3.0. Parts of the original specifications have been enhanced; these include a newly developed health insurance information module and 12 additional or redefined data definition tables. The Chinese version takes local needs into account and now makes it possible to exchange medical data among Chinese medical institutions.

Medical Markup Language (MML) is a standard for the exchange of medical data among different medical institutions. It was developed in Japan in 1995. Since version 2.21, MML has used eXtensible Markup Language (XML) as a meta-language. The latest version, 3.0, conforms to HL7 Clinical Document Architecture (CDA) and contains 14 modules and 36 data definition tables. In China, a standard which structures entire medical records in XML does not yet exist. Taking advantage of MML's flexibility, we created a localized Chinese version based on MML 3.0. Parts of the original specifications have been enhanced; these include a newly developed health insurance information module and 12 additional or redefined data definition tables. The Chinese version takes local needs into account and now makes it possible to exchange medical data among Chinese medical institutions.