Health Care Management Science 

About: Health Care Management Science is an academic journal published by Springer Science+Business Media. The journal publishes majorly in the area(s): Health administration & Health care. It has an ISSN identifier of 1386-9620. Over the lifetime, 877 publications have been published receiving 30531 citations. The journal is also known as: HCMS.

Optimization of surgery sequencing and scheduling decisions under uncertainty.

Abstract: Operating rooms (ORs) are simultaneously the largest cost center and greatest source of revenues for most hospitals. Due to significant uncertainty in surgery durations, scheduling of ORs can be very challenging. Longer than average surgery durations result in late starts not only for the next surgery in the schedule, but potentially for the rest of the surgeries in the day as well. Late starts also result in direct costs associated with overtime staffing when the last surgery of the day finishes later than the scheduled shift end time. In this article we describe a stochastic optimization model and some practical heuristics for computing OR schedules that hedge against the uncertainty in surgery durations. We focus on the simultaneous effects of sequencing surgeries and scheduling start times. We show that a simple sequencing rule based on surgery duration variance can be used to generate substantial reductions in total surgeon and OR team waiting, OR idling, and overtime costs. We illustrate this with results of a case study that uses real data to compare actual schedules at a particular hospital to those recommended by our model.

Non-parametric and parametric applications measuring efficiency in health care.

Abstract: This paper reviews 188 published papers on frontier efficiency measurement. The techniques used are mainly based on non-parametric data envelopment analysis, but there is increasing use of parametric techniques, such as stochastic frontier analysis. Applications both to hospitals and wider health care areas are reviewed and summarised, and some meta-type analysis undertaken. Results appear to confirm earlier findings that public provision demonstrates less variability than private. The paper is meant as a resource in itself, but also points to the future in terms of possible directions for research in efficiency measurement in health care and health.

Operational research in the management of the operating theatre: a survey.

Abstract: Operating theatre represents one of the most critical and expensive hospital resources since a high percentage of the hospital admissions is due to surgical interventions. The main objectives are to guarantee the optimal utilization of medical resources, the delivery of surgery at the right time, the maximisation of profitability (i.e., patient flow) without incurring additional costs or excessive patient waiting time. The operating theatre management is a process very complex: the use of mathematical and simulation models, and quantitative techniques plays, thus a crucial role. The main aim of this paper is to provide a structured literature review on how Operational Research can be applied to the surgical planning and scheduling processes. A particular attention is on the published papers that present the most interesting mathematical (optimization and simulation) models and solution approaches developed to address the problems arising in operating theatres. Directions for future researches are also highlighted.

Efficiency measurement of health care: a review of non-parametric methods and applications.

Abstract: There has been increasing interest in measuring the productive performance of health care services, since the mid-1980s. This paper reviews this literature and, in particular, the concept and measurement of efficiency and productivity. Concerning measurement, we focus on the use of Data Envelopment Analysis (DEA), a technique particularly appropriate when multiple outputs are produced from multiple inputs. Applications to hospitals and to the wider context of general health care are reviewed and the empirical evidence from both the USA and Europe (EU) is that public rather than private provision is more efficient.

Alternative methods to examine hospital efficiency: data envelopment analysis and stochastic frontier analysis.

Abstract: There has been increasing interest in the ability of different methods to rank efficient hospitals over their inefficient counterparts. The UK Department of Health has used three cost indices to benchmark NHS hospitals (Trusts). This study uses the same dataset and compares the efficiency rankings from the cost indices with those obtained using Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA). The paper concludes that the methods each have particular strengths and weaknesses and potentially measure different aspects of efficiency. Several specifications should be used to develop ranges of inefficiency to act as signalling devices rather than point estimates. It is argued that differences in efficiency scores across different methods may be due to random "noise" and reflect data deficiencies. The conclusions concur with previous findings that there are not truly large efficiency differences between Trusts and savings from bringing up poorer performers would in fact be quite modest.