Specialty Costs in English Hospitals — A Statistical Approach Based upon a Cost Component Model

A previous paper in this Journal compared various regression models designed to relate hospital recurrent expenditure to corresponding measures of hospital activity and services provided. The paper concluded by discussing briefly an alternative approach designed to avoid some of the criticisms raised and to reconcile the differing viewpoints inherent in the existing models. The objective of the present paper is to describe this alternative approach in more detail. The model introduced is concerned with the separate modelling of a number of broad components of hospital inpatient expenditure, rather than with the total expenditure in isolation. A system of simultaneous regression models is proposed, each related to a particular area of expenditure, the structure of each being determined by means of empirical analyses based upon data from some 1505 English hospitals. It is shown that when the total costs generated by aggregating the cost components are considered, the models provide a better representation of the cost structure of English hospitals than the models based upon total costs published in the recent literature. Various applications of the models in the management and planning of hospital services involving the use of micro- or other computers are discussed.     

Modelling the size and skill-mix of hospital nursing teams

Previously published work has described the development of a hospital capacity simulation tool, PROMPT. PROMPT has now been adopted by a number of hospitals in the UK and is used for both strategic and operational planning and management of key hospital resources. The work, as presented here, extends the PROMPT functionality to consider in more detail workforce issues. In particular, working with some of the current hospital users, the research has focussed on detailed planning for calculating the size and skill-mix of inpatient nursing teams. The chosen methodology utilizes both simulation and optimization. Outputs from the PROMPT three-phase discrete event simulation are fed into a stochastic programme which suggests the optimal number of nurses to employ (whole time equivalents) by skill-mix and the corresponding numbers by shift. A novel feature of the tool is the ability to predict and compare nursing needs based on different methods of capturing patient-to-nurse ratios as currently adopted across the UK National Health Service. Illustrative results from one hospital demonstrate that although the overall sizes of nursing teams on different wards are of an acceptable level and comparable to the outputs from the simulation phase of the work, often the number of nurses employed at different grades is not well matched to patient needs and the skill-mix should be reconsidered. Results from the optimization phase of the work suggest that it is cost beneficial to increase the number of permanently employed nurses to account for fluctuations in demand and corresponding high costs of temporary (agency) nurses. The scenario functionality of the tool permits for the study of changing size and skill-mix as a consequence of changes in patient volumes, patient case-mix, numbers of beds and length of stay.     

A system dynamics-based simulation study for managing clinical governance and pathways in a hospital

This paper examines the development of clinical pathways (CP) in a hospital in Australia based on empirical clinical data of patient episodes. A system dynamics (SD)-based decision support system is developed and analysed for this purpose. The study highlights the scenarios that will help hospital administrators to redistribute caseloads among admitting clinicians with a focus on multiple diagnostic-related groups (DRGs) as the means to improve the patient turnaround and hospital throughput without compromising quality patient care. DRGs are the best known classification system used in a casemix funding model. Casemix is a DRG-based government funding model for hospitals with a mix of performance measures aiming to reward initiatives that increase efficiencies in hospitals. The classification system groups inpatient stays into clinically meaningful categories of similar levels of complexity that consume similar amounts of resources. Policy explorations reveal various combinations of the dominant policies that hospital management can adopt. With the use of visual interfaces, executives can manipulate the DSS to test various scenarios. Experimental evidence based on focus groups demonstrated that it can enhance group learning processes and improve decision making. The findings are supported by other recent studies of CP implementation on various DRGs. These showed substantial reduction in length of stay, costs and resource utilization.     

Modelling the requirement for supplementary nurses in an intensive care unit

The intensive care unit (ICU) of a hospital is an essential yet costly resource. Consequently, intensive care modelling has become increasingly prevalent in recent years in attempts to increase efficiency and reduce costs. Previous models have usually assumed that the numbers of beds available are restricted; when all beds are occupied, any additional patients are referred elsewhere or elective surgeries are cancelled. In this study, activities at the ICU at a large teaching hospital were modelled using data relating to all admissions to the ICU during the year 2000—a total of 1084 admissions. The unit is unusual in that the majority of patients referred for intensive care therapy are admitted. Bed numbers are increased when necessary to cope with demand. However, nurses are a restricted resource. In order to maintain the required nurse:patient ratio of at least one:one, supplementary nurses are employed during busy periods. Supplementary nurse costs are substantial and so nurse utilization must be closely monitored. The development of a model that calculates the required number of supplementary nurses per shift, and also encapsulates the time-dependent nature of elective surgery admissions and complex duration-of-stay profiles, is presented in this paper. In particular, the model is used to determine the number of rostered nurses that are required to minimize overall nursing staff costs.     

A multi-objective model to determine efficient resource levels in a medical assessment unit

This paper details models that determine the efficient allocation of resources on a medical assessment unit (MAU) of a general hospital belonging to the National Health Service (NHS) UK. The MAU was established to improve the quality of care given to acute medical patients on admission, and also provide the organizational means of rapid assessment and investigation in order to avoid unnecessary admissions. To analyse the performance of the MAU, doctors, nurses and beds are considered as the three main resources. Then a model is developed using the goal programming approach in multiobjective decision making and solved to deal with MAU performance. The developed model is solved under three different sets of patient admissions with the same resource levels using past data from the MAU. The results of the model are used to analyse the needed resource levels. Conclusions as to the appropriate staffing levels and functions of the MAU are drawn.     

A network model for nursing staff scheduling

The staffing of hospital nurses has become critical in recent years. As a means of containing skyrocketing costs, many hospitals are reducing nursing staff to a bare minimum. At the same time, the hospitals must maintain some minimal staffing level as insufficient staff could lead to a life threatening situation possibly with detrimental social, economic, and legal consequences. This article will present a model which can be used to determine the optimal scheduling of nursing staff under varying conditions. A typical problem will illustrate its use.     

医疗资源影响下具有潜伏期的一类传染病模型建立及性态分析

建立了医疗资源影响下的考虑疾病具有潜伏期的一类传染病模型,并分析了模型的动力学性态.发现疾病流行与否由基本再生数和医院病床数共同决定,并得到了病床数的阈值条件.当基本再生数R_0大于1时,系统只存在惟一正平衡点,且通过构造Dulac函数证明了正平衡点只要存在一定是全局渐近稳定的;当R_01,我们得到系统存在两个正平衡点及无正平衡点的条件,且只有当医院的病床数小于阈值时,系统会经历后向分支.因此,可根据实际情况使医院病床的投入量不低于阈值条件,不仅有利于疾病的控制而且不会出现医疗资源过剩的现象.     

Locating specialized service capacity in a multi-hospital network

Multi-hospital systems have become very common in today’s healthcare environment. However, there has been limited published research examining the opportunities and challenges of pooling specialized services to a subset of hospitals in the network. Therefore, this paper considers how hospital networks with multiple locations can leverage pooling benefits when deciding where to position specialized services, such as magnetic resonance imaging (MRI), transplants, or neonatal intensive care. Specifically, we develop an optimization model to determine how many and which of a hospital network’s hospitals should be set up to deliver a specialized service. Importantly, this model takes into account both financial considerations and patient service levels. Computational results illustrate the value of optimally pooling resources across a subset of hospitals in the network versus two alternate approaches: (1) delivering the service at all locations and requiring each site to handle its own demand, or (2) locating the service at one hospital that handles all network demand.     

DEA与DRF法的整合

本文针对利用DEA模型进行有效性评价时碰到问题，提出了用因子分析法（简称DRF法）与DEA法相结合来进行评价，这是对DEA法的一种改进。并在此基础上对医院绩效进行了评价，为财政部门科学制定《医疗单位财政支出效益评价实施办法》提供依据。     

Health network mergers and hospital re-planning

This paper presents an integer programming formulation for the hospital re-planning problem which arises after hospital network mergers. The model finds the best re-allocation of resources among hospitals, the assignment of patients to hospitals and the service portfolio to minimize the system costs subject to quality and capacity constraints. An application in the Turkish hospital networks case is illustrated to show the implications of consolidation of health insurance funds on resource allocations and flow of patients in the system.     

普通高中教育投入绩效评估实证研究——基于江门市47所高中调查的多层数据

基于江门市47所高中调查的多层数据,运用多层统计分析模型,进行普通高中教育投入绩效评估的实证研究,结果表明:中考成绩与学校绩效之间呈负相关态势;高考成绩最重要的决定因素是学生先前的知识储备和起始能力水平;教育经费投入对高考成绩有显著正影响;学校师资质量对提高学生学业成就有正影响;在47所学校中,有18所学校教育绩效较好,有27所学校教育绩效还有待进一步提高,相应的教育资源的配置需要进一步优化等,并提出相应的政策建议.     

基于物联网的医用耗材智能屋管理系统

针对医用高值耗材种类繁多、管理难度大的问题,为减少人力成本、提高医用高值耗材的智能化管理水平。本文提出了基于物联网的高值医用耗材智能屋的管理系统,介绍了智能屋的整体架构、系统功能、核心业务及流程设计,主要分为结构模块、RFID模块、数据库模块、控制系统模块四大模块,具体有用户管理、出入库管理、综合查询、预警管理四大业务,通过GM(1,1)模型对2022年全年高值医用耗材的月消耗量进行预测分析,并且检验得该预测模型的精度等级为一级,模型预测效果很好,能够为医院采购人员采购提供了一个参考,避免因过度的主观估计而造成的耗材浪费。该系统能够有效地提高医院对于高值医用耗材的管理水平,减少人力、物力和财力的消耗,为广大患者提供更加优质的医疗服务。本文所提的高值医用耗材智能屋管理系统解决了传统的高值医用耗材管理的诸多难题。     

Estimating bed requirements for an intermediate care facility

Concern has been expressed in the United Kingdom regarding the proportion of beds intended for acute care that are occupied by patients who do not require acute care. One solution to this problem that is being investigated by some hospitals is the establishment of an intermediate care facility devoted to non-acute care. A key question faced by hospital planners is how many beds such an intermediate care facility should have. We report on a study consisting of a bed use survey and a stochastic analysis exercise that was conducted at the Whittington Hospital NHS Trust in London in order to address this question. Rather than focus on the whether patients in acute beds required acute care throughout their stay in hospital, the study concentrated on identifying periods in patients’ stays when they would have been transferred to an intermediate care facility if one had been available.     

A derivative-free approach for a simulation-based optimization problem in healthcare

Hospitals have been challenged in recent years to deliver high quality care with limited resources. Given the pressure to contain costs, developing procedures for optimal resource allocation becomes more and more critical in this context. Indeed, under/overutilization of emergency room and ward resources can either compromise a hospital’s ability to provide the best possible care, or result in precious funding going toward underutilized resources. Simulation-based optimization tools then help facilitating the planning and management of hospital services, by maximizing/minimizing some specific indices (e.g. net profit) subject to given clinical and economical constraints. In this work, we develop a simulation-based optimization approach for the resource planning of a specific hospital ward. At each step, we first consider a suitably chosen resource setting and evaluate both efficiency and satisfaction of the restrictions by means of a discrete-event simulation model. Then, taking into account the information obtained by the simulation process, we use a derivative-free optimization algorithm to modify the given setting. We report results for a real-world problem coming from the obstetrics ward of an Italian hospital showing both the effectiveness and the efficiency of the proposed approach.     

A goal programming approach to strategic resource allocation in acute care hospitals

This paper describes a methodology for allocating resources in hospitals. The methodology uses two linear goal-programming models. One model sets case mix and volume for physicians, while holding service costs fixed; the other translates case mix decisions into a commensurate set of practice changes for physicians. The models allow decision makers to set case mix and case costs in such a way that the institution is able to break even, while preserving physician income and minimizing disturbance to practice. The models also permit investigation of trade-offs between case mix and physician practice parameters. Results are presented from a decision-making scenario facing the surgical division of Toronto's Mount Sinai Hospital after the announcement of a 3-year, 18% reduction in funding.     

Modelling hospital costs to produce evidence for policies that promote equity and efficiency

Third party payers for health care, when introducing policies to promote equity, through formulas for resource allocation by capitation, and efficiency, through prospective payment by case-mix, have sought to make adjustments for “unavoidable” hospital costs, which are caused by structural characteristics and are beyond the scope of local hospital management. To date, however, most published studies of such estimates have been inadequate. This paper reports the development of a generalisable model that aims to produce sound estimates of “unavoidable” hospital costs and shows how this stochastic multilevel model can be used to estimate unavoidable costs per unit of measurable output, identify sources of allocative inefficiency, and capture systematic variations in costs between different types of hospitals, through prospective payment by case-mix or formulas for resource allocation by capitation The application of the model to Portuguese hospitals has identified various causes of allocative inefficiencies: centrally-determined distributions of beds and doctors, a lack of local flexibility, systems with perverse incentives, and the existence of diseconomies of scale.     

Patient flow-based allocation of inpatient resources: A case study

The paper considers the allocation of inpatient resources such as beds, operating theatres and nursing staff to specialties within a hospital setting. It describes an allocation procedure that takes patient flows as its starting point and enables an evaluation of combined impacts on the different resources involved. The paper is written in the format of a case study, dealing with a hospital that had serious problems with the utilization of beds and was faced with many admission-stops. However, the method can be used to a wide range of resource management problems in hospitals and can contribute to improving flexibility in the use of hospital resources.     

Hospital management games: a taxonomy and extensive review

Hospital management games have gained importance in better planning for scarce resources in times of growing health care demand and increasing technology costs. We classify and investigate the main characteristics of these games from an Operations Research (OR) perspective. Hospital management games model the complex decision making process of internal resource, process, and financial management all influenced by the external hospital environment (e.g., purchasing markets, job markets, legal/political conditions, competition) and simulate situations of the real world. We also highlight the potential of these games for teaching OR in the classroom. Experiencing the advantages of OR may reduce the reservations policy makers have and could make them increasingly open to promoting OR applications in practice. We also disclose potential for new applications.     

Development of a Financial Performance Index for Hospitals: DEA Approach

This paper presents an innovative method of measuring and assessing financial performance for hospitals using data envelopment analysis (DEA). A 6% national sample of acute care hospitals was used to compare conventional ratio analysis with the financial performance index (FPI), an aggregate measure of financial performance, developed in this study. The results showed that FPI has captured what various financial ratios indicate independently. The development of a FPI across many financial ratios eases the comparison of an individual hospital with its peers. Development and uses of a FPI can also be applied to other industries.     

Competition under different reimbursement systems: The concept of an internet-based hospital management game

We have developed an internet-based management game to illustrate the economic and organisational decision-making process in a hospital by using discrete event simulation. Up to six hospitals compete against each other for inpatients with different disease categories and budget depending on hospital mission, regional health policy, inpatient reimbursement system (day-, case- and global-budget based) as well as labour and radiology technology market for 12 decision periods. Players can evaluate alternative actions for capacity planning as well as patient scheduling and control problems depending on different game situations. The uniqueness of COREmain hospital game consists of the internet-based framework, the combination of resource, process and financial result management, the competition of hospitals within a region and the consideration of different inpatient reimbursement systems. The deployment of this game in teaching, policy and research might improve policy making both at a hospital, regional and national level and also induce further research in these fields.