Workforce staffing and scheduling: Hospital nursing specific models

Decisions relating to hospital nurse staffing and scheduling are among the most important decisions made in hospitals today. Staffing and scheduling choices must be made which will result in timely and high-quality care to patients. These choices are complicated by the requirement for round-the-clock staffing in many hospital nursing units, a severe nursing shortage, and an outcry from many quarters to cut costs of health care. In general, patients today are kept in hospitals only if they are in need of highly skilled nursing care. In this paper we present a review of some of the issues in health care currently influencing the hospital nurse staffing and scheduling environment. In addition, we review the literature that illustrates nurse manager's concerns, and approaches taken in the past by operations researchers to address those concerns. We present some data from a recent study of nurse managers in 31 hospitals that illustrates the complexity of the issues. We conclude with a discussion of future research directions in hospital nurse staffing and scheduling.     

Managing the overflow of intensive care patients

Many hospitals in the Netherlands are confronted with capacity problems at their intensive care units (ICUs) resulting in cancelling operations, overloading the staff with extra patients, or rejecting emergency patients. In practice, the last option is a common choice because for legal reasons, as well as for hospital logistics, rejecting emergency patients has minimal consequences for the hospital. As a result, emergency patients occasionally have to be transported to hospitals far away. In this work, we propose a cooperative solution for the ICU capacity problem. In our model, several hospitals in a region jointly reserve a small number of beds for regional emergency patients. We present a mathematical method for computing the number of regional beds for any given acceptance rate. The analytic approach is inspired by overflow models in telecommunication systems with multiple streams of telephone calls. Simulation studies show that our model is quite accurate. We conclude that cooperation between hospitals helps to achieve a high acceptance level with a smaller number of beds resulting in improved service for all patients.     

Multi-Level Strategic Evaluation of Hospital Plans and Decisions

Strategic decision making in hospitals involves the assessment of linkages between decisions that are typically made in a hierarchical fashion. In hospitals, as in most large organizations, overall system performance is a function of how well the critical decisions are integrated. This paper focuses on the multi-level nature of the decisions and policies that typically need to be evaluated in hospital planning, highlighting that both optimization and simulation approaches may be required. An application involving a large general purpose urban hospital is used to illustrate the interdependency between the levels in the planning hierarchy. An optimization model is formulated to deal with facility layout and capacity allocation while a simulation model is proposed to capture the complexities of hospital operations. The linkages and information feedback between the models are shown to be critical in the design of a system that performs well and facilitates strategic hospital planning.     

A comparison of shadow prices and reimbursement rates of hospital services

The purpose of this paper is to calculate shadow prices of hospital services and compare them to the reimbursement rates those hospitals receive. These shadow prices are calculated by estimating a multiple-output distance function and applying a dual Shephard's lemma, a technique suggested by Färe and Grosskopf [8]. In contrast to cost functions, distance functions require no price data and do not presume cost minimization. We apply this technique to a sample of California hospitals operating in 1986. We find that hospitals engaged in selective contracting for Medi-Cal patients exhibit closer agreement between relative shadow prices and relative reimbursement rates (Medi-Cal relative to private patients) than noncontracting hospitals.Contact author.     

Nash equilibria in the two-player kidney exchange game

Kidney exchange programs have been set in several countries within national, regional or hospital frameworks, to increase the possibility of kidney patients being transplanted. For the case of hospital programs, it has been claimed that hospitals would benefit if they collaborated with each other, sharing their internal pools and allowing transplants involving patients of different hospitals. This claim led to the study of multi-hospital exchange markets. We propose a novel direction in this setting by modeling the exchange market as an integer programming game. The analysis of the strategic behavior of the entities participating in the kidney exchange game allowed us to prove that the most rational game outcome maximizes the social welfare and that it can be computed in polynomial time.     

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.     

政府监管下的医院医疗信息分享演化博弈分析

在分析政府监管下医院间医疗信息分享特征的基础上,结合我国当前正在推行的医联体医院间信息分享运作模式,引入梅特卡夫定律并考虑患者评价的影响,分析了监管部门与医院各自的利益组成,建立了监管部门与医院两者之间的演化博弈模型,并采用复制动态方程研究了不同情形下医院间信息分享的演化博弈轨迹。研究表明,政府通过监管并建立激励惩罚机制等引导措施对医院最终达到的演化稳定态具有极大影响;降低医院主体信息分享的风险成本、规范提高医院分享信息的质量、引导患者增强对医院信息分享的关注、制定有吸引力和威慑力的奖惩政策,是促进医院医疗信息分享的关键。研究结果可为政府监管部门预测医院间的信息分享趋势和制定精准化政策以促进分享提供参考。     

Using system dynamics principles for conceptual modelling of publicly funded hospitals

This paper examines the long-standing operational issue of patients boarding in the emergency department (ED), who have been admitted to hospital (inpatient ‘boarders’). From this analysis we design a conceptual model that provides a roadmap to create sustainable improvements in ED waiting times. The conceptual model is built using system dynamics methodology, and illustrates the use of system archetypes, a set of common causal feedback loops that illustrate how well-intended decisions have unintentional side effects. This paper outlines the journey taken by one large academic health centre to address these issues, and highlights the larger implications and recommendations that are applicable to other publicly funded hospitals.     

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.     

Literature review on multi-appointment scheduling problems in hospitals

This paper presents a review of the literature on multi-appointment scheduling problems in hospitals. In these problems, patients need to sequentially visit multiple resource types in a hospital setting so they can receive treatment or be diagnosed. Therefore, each patient is assigned a specific path over a subset of the considered resources and each step needs to be scheduled. The main aim of these problems is to let each patient visit the resources in his or her subset within the allotted time to receive timely care. This is important because a delayed diagnosis or treatment may result in adverse health effects. Additionally, with multi-appointment scheduling, hospitals have the opportunity to augment patient satisfaction, allowing the patient to visit the hospital less frequently. To structure the growing body of literature in this field and aid researchers in the field, a classification scheme is proposed and used to classify the scientific work on multi-appointment scheduling in hospitals published before the end of 2017. The results show that multi-appointment scheduling problems are becoming increasingly popular. In fact, multi-appointment scheduling problems in hospitals are currently gaining progressively more momentum in the academic literature.     

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.     

考虑患者止步行为的动态入院接收决策模型

大型公立医院病床供需矛盾日益突出,医院作为服务系统有必要考虑由于病床需求响应速度不及时而引起的患者策略性行为。针对患者到达时间的随机性与住院时长的不确定性,本文提出考虑患者止步行为的动态入院接收决策问题,制定了适用于可等待慢性病患者的入院接收决策方法,旨在提高患者的就医满意度,有效权衡多类患者的接收数量,降低由于科室响应速度过慢引发的患者止步频率。首先,本文对考虑患者止步行为的动态入院接收决策问题进行数学描述及符号定义;然后,对患者止步行为的影响因素进行分析并构建止步概率函数;进一步地,构建考虑患者止步行为的动态入院接收马尔可夫决策过程(MDP)模型,并针对模型特点设计值迭代算法,最后通过数值算例验证本文所提方法的可行性与有效性。     

Incorporating health outcomes in Pennsylvania hospital efficiency: an additive super-efficiency DEA approach

The health care sector is one of the fastest growing sectors in the United States. Researchers are interested in conducting studies in the area of health economics in order to propose solutions to curb the rapid increase in health care spending and to improve the efficiency of the health care system in the United States. Specifically, hospital efficiency is one important research area in health economics. In this paper, data envelopment analysis (DEA) is used to assess hospital efficiency. An additive super-efficiency model is presented and applied to a sample of general acute care hospitals in Pennsylvania. In addition to the conventional choice of input and output variables, we include the survival rate as a quality measure of health outcome in the set of output variables. Thus our model takes both the quantity and the quality of the output into account. With the results obtained from our proposed DEA model, inefficiencies can be identified for hospitals to address without sacrificing the quality of care.     

Trends in labor efficiency among American hospital markets

The health care sector is one of the most labor intensive sectors of the economy. As a major player in health service delivery, hospitals must closely examine their largest cost — labor expenses. This study evaluates trends in the efficiency of health care labor among urban hospital markets. More specifically, it assesses the hypothesis that technological changes and market and regulatory pressures have increased aggregate labor efficiency. Using data envelopment analysis (DEA), this study evaluates labor efficiency in 1989 and 1993 in 298 metropolitan statistical areas (MSAs) with two or more hospitals. Results of this study suggest that between 1989 and 1993, hospital markets generally demonstrated higher labor inefficiencies. The U.S. health care system could save approximately $16.6 billion in 1993 by eliminating hospitals' excessive use of health care provider labor.     

Efficiency and productivity change in Taiwan’s hospitals: a non-radial quality-adjusted measurement

This study measures the quality-adjusted hospital efficiency and productivity index of a production unit. We propose a non-radial output-oriented directional distance function approach to analyze Taiwan’s hospital productivity, which embeds the quality of care and environment variables simultaneously. There are two major advantages of this model. First, it considers all the radial and non-radial slacks that the model can identify, and hence is able to provide a more accurate performance measure and improve the discriminating power of the analysis. Second, it allows us to identify the source of the inefficiency. Our results show that the productivity indices of most of Taiwan’s hospitals got worse during the 2002–2004 period, during which both technology and efficiency performance deteriorated, but divergence appeared among different types of hospitals. We confirmed the need to incorporate quality factors while measuring a hospital’s efficiency and productivity. Nevertheless, there is no evidence to support the idea that healthcare quality is undermined by the cost-saving efforts by the care providers after the implantation of a global budget system.     

The Impact of Teaching on Hospital Costs: A Budgetary Approach to Non-market Institutions

NHS hospitals contribute to medical education, training nurses and research, as well as to the care of patients. In the past they have been funded largely on the basis of resources employed, with additional funding for medical education and training nurses. The intellectual basis for the funding of medical education is a single econometric study of English hospitals in the financial year 1969-70. The methodology used has since been criticized, and it has been suggested that actual expenditure has been very much less than that earmarked by the health departments. New estimates are obtained using Scottish data for the financial year 1985-86. The method used is to proceed in a two-stage fashion, identifying via regression techniques variables measuring hospital activity and resources which contribute significantly to hospital costs. We then assess the significance of medical education, nurse training and hospitals' teaching status against this background. Our conclusions include: (1) actual expenditure on medical education was probably less than the funding formula allowed, but the error of margin is too large to suggest overfunding; (2) training nurses incurs significant financial costs, even after the explicit allowances made; and (3), major teaching hospitals tended to cost more, but not significantly more than their non-teaching counterparts. These financial implications for NHS hospitals should be borne in mind given the current NHS review.     

基于分级诊疗体系的转诊与政府投资决策研究

针对我国分级诊疗实施过程中,由于基层医疗机构服务能力不足所造成的“上转容易下转难”的困境,研究了政府部门对社区医院服务能力进行投资以促进病人下转的问题.通过构建四阶段的博弈模型,探讨了为实现医疗系统总病人效用最大化的政府资金均衡投入策略,为实现三甲医院期望效益最大化的病人下转策略,病人效用最大化下的社区医院服务能力规划以及基于期望效益最大化下的病人选择.研究发现：1)三甲医院的期望效益受到政府投资金额的影响,当政府投资金额不足时,三甲医院的期望效益仅能达到次优;2)三甲医院病人的均衡转诊率受到三甲医院的治疗价格和政府的资金投入量的影响;3)在实现整个医疗系统总病人效用最大化上,虽然总病人效用随政府投入金额的增加而增加,但从政府角度来讲,政府投资金额不宜过大.     

An alterative method for hospital partition determination using hierarchical cluster analysis.

The classification of short-term hospitals into homogeneous groups has become an integral part of many systems designed to abate continuing cost inflation in the hospital industry. This paper describes one approach which was developed to identify homogeneous groups of short-term hospitals. The approach, based on hierarchical cluster analysis, defines an objective measure (called expected distinctiveness) to evaluate any group of hospitals identified by a hierarchical grouping structure or dendrogram. Using this measure, an efficient algorithm is developed which finds the hospital partition from the identified groups which maximizes total expected distinctiveness. A numerical example illustrates the application and extensions.     

A multiobjective stochastic program for hospital bed planning

In this paper, we study hospital bed capacity management for a set of existing hospitals when the demand for beds is random. We propose a multiobjective stochastic program model to assign beds to hospital departments. We consider three objective functions to be minimized, which are the cost of creation and management of new beds and the number of nurses and physicians working in these hospitals, subject to demand satisfaction of three kinds of health-care specialities. A certainty equivalent program was derived based on a mixture between the chance constrained approach, the recourse approach and the goal programming approach. Empirical results using real data from 157 Tunisian national hospitals are reported.     

Do mergers improve hospital productivity?

This paper complements the existing literature on hospital mergers by using data envelopment analysis (DEA) to generate both efficiency and productivity measures to ascertain whether hospital mergers, at least in the short run, result in performance gains. Using data over the period 1996–1998, we apply DEA, both pre-merger and post-merger, to set of hospitals that merged in 1997 as well as to a matching control group of non-merging hospitals over the same timeframe. A comparison of DEA efficiency scores and the Malmquist index values across the case and control hospitals allow us to assess whether any increase in productivity is the result of a merger rather than simply and randomly adding two hospitals' inputs and outputs together.