Benchmarking physician practice patterns with DEA: A multi-stage approach for cost containment

Physician practice patterns in a Health Maintenance Organization (HMO) are analyzed using single and multi-stage applications of Data Envelopment Analysis (DEA). Best practice (BP) patterns are identified, which can serve as benchmark targets for inefficient physicians. Results suggest three health policy — resource utilization control strategies:

1. If managed care organizations could motivate primary care physicians to adopt the practice styles of the best practice primary care physicians, substantial clinical resource savings could be achieved, ranging from 12% to over 30% in the HMO that is the focus of this study;
2. some specialists who practice as primary care physicians (PCPs) provide more efficient care than some general practitioner PCPs, modifying the current perception that reducing specialists is the most effective way to achieve low cost practice patterns; and
3. groups of physicians in the HMO exhibit different resource use patterns, which may present opportunities to manage high cost groups as another path to contain costs.

The results suggest specific new paths which may prove effective at reducing health care costs within managed care organizations, the health care providers most likely to dominate the U.S. health system in the future. A multi-stage DEA technique is used to locate specific types of inefficient physicians. Methods to test the clinical viability of using DEA to realize the potential cost savings and extensions of this research are discussed.     

Efficiency assessment of primary care providers: A conditional nonparametric approach

This paper uses a fully nonparametric approach to estimate efficiency measures for primary care units incorporating the effect of (exogenous) environmental factors. This methodology allows us to account for different types of variables (continuous and discrete) describing the main characteristics of patients served by those providers. In addition, we use an extension of this nonparametric approach to deal with the presence of undesirable outputs in data, represented by the rates of hospitalization for ambulatory care sensitive condition (ACSC). The empirical results show that all the exogenous variables considered have a significant and negative effect on efficiency estimates.     

Data envelopment analysis applied to quality in primary health care

The performance of primary care should ultimately be judged on its effect on the health outcome of individual patients. However, for the foreseeable future, it is inconceivable that the outcome data necessary to come to a judgement on performance will be available. And in any case, specification of the statistical model necessary to analyze outcome is fraught with difficulty. This paper therefore sets out a model of primary care performance which is based on the premise that certain measurable quality indicators can act as proxies for outcome. This being the case, a model of performance can be deduced which takes into account the effect of resources and patient characteristics on outcome. The most appropriate analytic technique to make this model operational is data envelopment analysis (DEA). It is argued that DEA can handle multiple dimensions of performance more comfortably, and is less vulnerable to the misspecification bias that afflicts statistically based models. The issues are illustrated with an example from English Family Health Service Authorities.     

Exploring the use of DEA for formative evaluation in primary diabetes care: An application to compare English practices

Primary care is currently at the heart of the UK National Health Service policy. Primary care trusts have the crucial role of improving the efficiency and equity in primary care delivery. However, few studies have focused on performance assessment in primary care provision. In this paper, we examine the role of data envelopment analysis (DEA) in helping decision makers to understand and improve the performance of primary care practices. We discuss the results from a study of 14 practices in England in terms of their delivery of diabetes services. In order to take into account the multiple values that underlie public services provision, we have considered several different perspectives for evaluation. These were: technical, allocative and cost efficiency, clinical and patient-focused effectiveness, and equity. The approach adopted involved a deep engagement with the practices. The purpose was to understand the structures and processes supporting effective practice using DEA in a formative role rather than the more usual summative role with a large data set. This approach is in the tradition of the developmental engagement approach of operational research.     

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.     

A Markovian queueing model for ambulance offload delays

Ambulance offload delays are a growing concern for health care providers in many countries. Offload delays occur when ambulance paramedics arriving at a hospital Emergency Department (ED) cannot transfer patient care to staff in the ED immediately. This is typically caused by overcrowding in the ED. Using queueing theory, we model the interface between a regional Emergency Medical Services (EMS) provider and multiple EDs that serve both ambulance and walk-in patients. We introduce Markov chain models for the system and solve for the steady state probability distributions of queue lengths and waiting times using matrix-analytic methods. We develop several algorithms for computing performance measures for the system, particularly the offload delays for ambulance patients. Using these algorithms, we analyze several three-hospital systems and assess the impact of system resources on offload delays. In addition, simulation is used to validate model assumptions.     

Modelling the future of the Canadian cardiac surgery workforce using system dynamics

Due to the high costs and lengthy lead times involved with training health human resources such as physicians and surgeons, combined with the serious burden borne by the general population when health care provider shortages occur, advance planning of resource requirements is critical. This is particularly true in light of current demographic trends and Canada’s ageing population, which will potentially increase demand for health care providers in the future while also leading to the retirement of many of the providers currently practicing. The purpose of this research was to develop a model simulating the workforce within a single specialty at a national level, which includes students training to enter the profession, providing a tool that would help to inform future resource planning. We present the details of this model, developed using system dynamics modelling, and demonstrate it using the example of cardiac surgeons in Canada.     

Matching patient and physician preferences in designing a primary care facility network

This paper introduces an integer programming model for planning primary care facility networks, which accounts for the interests of different stakeholders while maximizing access to health care. Physician allocation to health-care facilities is explicitly modelled, which allows consideration of physician incentives in the planning phase. An illustrative case study in the Turkish primary care system is presented to show the implications of focusing on patient or physician preferences in the planning phase. A discussion of trade-offs between the different stakeholder preferences and some recommendations for modelling choices to match these preferences are provided. In the context of this case, we found that using an access measure that decays with distance, and incorporating nearest allocation constraints improves performance for all stakeholders. We also show that increasing the number of physicians may have adverse affects on access measures when physician preferences are addressed.     

First,do no harm? A framework for evaluating new <Emphasis Type="Italic">versus</Emphasis> reprocessed medical devices

More than ever before, health care providers are under intense pressure to control costs. Medical devices represent a significant ‘hard’ cost, with worldwide spending exceeding USD 235 billion. A growing number of health care providers are engaging in the practice of reprocessing—sterilizing and reusing medical devices labelled only for a single use. The ethical and technical dimensions of this practice have received much attention, but its economic aspects remain largely unexamined. This paper presents a Markov decision process framework that a health care provider can use to decide whether to use new or reprocessed devices in a given context. Two cases are studied: completely observable device condition and partially observable device condition. After briefly discussing structural results for the two cases, several examples are presented to illustrate how the model can be applied in practice. Useful results can be computed quickly with minimal data. A key insight of the model is that perfect information regarding the device condition is often not required to make a sound decision.     

Quality competition for screening and treatment services

This paper examines how quality for one type of preventive health care services, screening services are determined under competition and explores its links with the treatment services. A Hotelling type of model is introduced for this purpose. Two providers offer both screening and treatment services, and decide on their quality for both services. The equilibrium quality values are characterized assuming providers are identical and patients are free to choose providers for screening and treatment independently. Screening quality and treatment quality are shown to be strategic complements. The social planner can achieve the desired quality level via appropriate reimbursements for screening and treatment of the disease at early and late stage. A sensitivity analysis investigates the effect of model parameters on the equilibrium quality levels.     

Performance evaluation of university extension providers: A frontier approach for ordered response data

A frontier model is used to evaluate the performance of extension service providers in the US land grant university system when providing assistance to organic producers. Performance efficiency indicates the effectiveness of extension agents in achieving the highest evaluations from their clientele conditioned on the farm level characteristics and environmental resources and constraints of the organic farmers. Mean performance efficiency of the extension agents is above 0.69 for entire sample with top performing extension service experts outperforming the average providers by about 44%. Performance efficiency, or advisory outcomes that are below the best that extension could provide, are not significantly reduced when extension agents deal with difficult evaluation situations.     

Payment models to coordinate healthcare providers: Extension to risk-averse providers

Previous works compared the performance of the bundled and unbundled payment schemes in a referral-based setting where the providers (generalist and specialist) are risk-neutral and health outcomes are partial attributable to the providers. In this work, we extend the results to a setting where the providers are risk-averse. We also show that a bundled scheme has higher referral rates, lower time spent by the specialist, higher specialist utilization relative to an unbundled system in most scenarios.     

Optimising key performance indicator adherence with application to emergency department congestion

Many operational queueing systems must adhere to systems of Key Performance Indicators (KPIs), each comprising a waiting time limit and a level of compliance specifying the minimal fraction of customers that must meet the standard. KPIs are frequently employed as measures of system performance in health care settings. The primary flaw with KPIs is that they represent a system of constraints with no objective function. KPIs say nothing about customers who exceed their limit, so long as such occurrences are sufficiently rare, when in fact customers who miss their time limit in a health care setting are of greater importance, not lesser. We address this flaw by minimising the mean number of customers present who have exceeded their respective limits; we consider also weighted averages of the numbers in excess for each class. We then show that one logical service discipline to achieve this goal is the Accumulating Priority Queueing (APQ) discipline. We carry out numerical examples to investigate the utility of our method. We then apply the optimisation approach to the case of an Emergency Department in Southern Ontario, Canada.     

Laps Care—an operational system for staff planning of home care

The health care system in Sweden and many other countries is facing increasing costs. The major reason is the changing age distribution of the population with more elderly people in need of support. At the same time, health care systems are often very labor and staff intensive. In this paper, we focus on a staff planning problem arising in Sweden where people receive home care from the local authorities. The objective is to develop visiting schedules for care providers that incorporate some restrictions and soft objectives. Each visit has a particular task to be performed, for example: cleaning, washing, personal hygiene and/or nursing activities. Each staff member has skills and each client should, if possible, be visited by the same contact person. The operational situation is continuously changing and planning is done each day. We describe the development of a decision support system Laps Care to aid the planners. The system consists of a number of components including information data bases, maps, optimization routines, and report possibilities. We formulate the problem using a set partitioning model and, for a solution method, we make use of a repeated matching algorithm. The system is currently in operation at a number of home care organizations. We report on the practical impact of the system in the health care organization which was involved in the development. The savings are considerably in terms of saved planning time and in the quality of the routes, as well as the measured quality for the clients. Numerical experiments of the system are presented.     

New formulations and solution procedures for the hop constrained network design problem

Optical fiber provides tremendous advantages in being able to carry a wide range of services including video on demand, video conferencing, distance learning, remote medical imaging, and telecommuting. The high capacities encourage carriers to create networks that are substantially sparser than previous copper based networks. A recent publication by the Telecommunications Industry Association indicated that investment in fiber optics is projected to reach $35 billion in the year 2003. Given the magnitude of investments, the design of networks becomes a very important issue. Most telecommunication companies (telcos), IT consulting companies, network equipment manufacturers and network service providers have extensive network design groups. The primary function of these groups is to design the most efficient networks both in terms of costs and performance and maintain them. These designers need flexible tools to support topological network design decisions. These decisions involve significant levels of investments in transmissions and switching facilities, and impact the resulting networks’ performance fundamentally.In this paper we study a special type of a network design problem called the hop constrained backbone network design problem. We present new mathematical programming formulations of the problem and develop an efficient solution procedure based on the linear programming relaxation. Extensive computational results across a number of networks are reported.     

Practical guide for improving performance

Research has established that health care is not error free. The question facing perioperative units, as well as all health care services, is how to minimize the human factors that impact quality and safety. This two-part series on performance improvement in perioperative services was intended to help answer this question. Achieving performance excellence starts with a supportive work culture. The human issues of teamwork, communication, and leadership are crucial to achieving performance excellence. Next, perioperative caregivers must accept that all people make mistakes so systems and processes can be designed to be more "forgiving" of errors. Last, a planned and systematic approach must be used to measure, analyze, and improve performance. Successful implementation of performance improvement calls for strong partnerships between physicians, managers, and staff members. Performance excellence requires that everyone work together to ensure that perioperative care is safe, effective, appropriate, customer focused, and efficient.     

Primary care network development: the regulator’s perspective

Our research is motivated by the proliferation of primary care models in Ontario, Canada. Currently, primary care is mainly provided by facilities belonging to six models of care. These models are remunerated by various schemes—a mixture of fee-for-service, capitation and salary. In addition, they provide different levels of care and several are better adjusted than others to treat complex health needs. The proposed mixed integer programming model allows the regulator to test the outcomes of locating different types of primary care facilities on the overall cost, accessibility and appropriateness of provided care. The network design is fitted to the heterogeneity of the population residing in a defined geographical area, directly using an index (deprivation index) that was found to correlate with increased health needs and barriers to care. The model capabilities are illustrated on the geographical area of Kingston, Ontario.     

Dynamic overbooking scheduling system to improve patient access

Patient no-show has long been a recognized problem in modern outpatient health-care delivery systems. The common impacts are reduced clinic efficiency and provider productivity, wasted medical resources, increased health-care cost and limited patient access to care. The main goal of this research is to develop an effective dynamic overbooking policy into any scheduling system that accounts for the predictive probability of no-shows for any given patient. This policy increases the quality of patient care in terms of wait time and access to care while minimizing the clinic's costs. This proposed model is also illustrated to be more cost-effective than overbooking patients evenly throughout a clinic session. This paper also suggests that overbooking should be performed at better patient flow and higher no-show rate so that the costs are minimized. Consequently, this research improves the outpatient experience for both patients and medical providers.     

Pricing under quality of service uncertainty: Market segmentation via statistical QoS guarantees

This article examines how performance-contingent pricing schemes with long-term statistical performance guarantees can be applied to many IT services. We study two forms of performance-contingent pricing, with rebate proportional to failure rate and fixed rebate for below-threshold performance. We show that threshold-performance contingency pricing can increase both profits and fairness (customers who receive higher benefits pay higher effective price) relative to standard pricing. But an even better solution is to offer a menu of performance guarantees: this can increase the firm’s profit and segment the market. Only service providers whose performance level is sufficiently better than the industry standard can benefit from this pricing mechanism.     

The effects of asset specificity on maintenance financial performance: An empirical application of Transaction Cost Theory to the medical device maintenance field

This study uses multivariate regression analysis to examine the effects of asset specificity on the financial performance of both external and internal governance structures for medical device maintenance, and investigates how the financial performance of external governance structures differs depending on whether a hospital is private or public. The hypotheses were tested using information on 764 medical devices and 62 maintenance service providers, resulting in 1403 maintenance transactions. As such, our data sample is significantly larger than those used in previous studies in this area. The results empirically support our core theoretical argument that governance financial performance is influenced by assets specificity.