Taxonomic classification of planning decisions in health care: a review of the state of the art in OR/MS

We provide a structured overview of the typical decisions to be made in resource capacity planning and control in health care, and a review of relevant OR/MS articles for each planning decision. The contribution of this paper is twofold. First, to position the planning decisions, a taxonomy is presented. This taxonomy provides health care managers and OR/MS researchers with a method to identify, break down and classify planning and control decisions. Second, following the taxonomy, for six health care services, we provide an exhaustive specification of planning and control decisions in resource capacity planning and control. For each planning and control decision, we structurally review the key OR/MS articles and the OR/MS methods and techniques that are applied in the literature to support decision making

Inferring Hospital Quality from Patient Discharge Records Using a Bayesian Selection Model

This paper develops new econometric methods to estimate hospital quality and other models with discrete dependent variables and non-random selection. Mortality rates in patient discharge records are widely used to infer hospital quality. However, hospital admission is not random and some hospitals may attract patients with greater unobserved severity of illness than others. In this situation the assumption of random admission leads to spurious inference about hospital quality. This study controls for hospital selection using a model in which distance between the patient's residence and alternative hospitals are key exogenous variables. Bayesian inference in this model is feasible using a Markov chain Monte Carlo posterior simulator, and attaches posterior probabilities to quality comparisons between individual hospitals and groups of hospitals. The study uses data on 77.937 Medicare patients admitted to 117 hospitals in Los Angeles County from 1989 through 1992 with a diagnosis of pneumonia. It finds higher quality in smaller hospitals than larger, and in private for-profit hospitals than in hospitals in other ownership categories. Variations in unobserved severity of illness across hospitals is at least a great as variation in hospital quality. Consequently a conventional probit model leads to inferences about quality markedly different than those in this study's selection model.

Outcomes Assessment and Health Care Reform

Argues for the use of outcomes assessment in measuring cost-effectiveness and quality to capture the overall impact of multi-dimensional treatment strategies and to identify healthcare systems that both adopt appropriate technologies and perform well

Applying the real options theory for identifying flexibility in project delivery of health organisations

Healthcare is influenced by many uncertainties. Uncertainties affecting health organisations also influence real estate since this facilitates the primary process. Within real estate management, decisions have to be made today while there is little knowledge about the future. Therefore, flexibility is needed in the process of designing, constructing and operating real estate. A case study has been done to gain insight about how health organisations deal with flexibility. The real options approach is used to show what types of flexibility have been used, and that uncertainty can also generate opportunities. Of the five types of flexibility, only in two types real options were identified in the case study. These were stage, abandon, defer and scale within process flexibility and the options growth and switch within product flexibility. This is partly a result of the fact that the project in the case study is not further advanced than the preliminary design phase. Nevertheless it can be concluded that project managers already act as using real options. Consciously using this concept might create even more real options to be used in project management

Randomized controlled trial of a coordinated care intervention to improve risk factor control after stroke or transient ischemic attack in the safety net: Secondary stroke prevention by Uniting Community and Chronic care model teams Early to End Disparities (SUCCEED).

BackgroundRecurrent strokes are preventable through awareness and control of risk factors such as hypertension, and through lifestyle changes such as healthier diets, greater physical activity, and smoking cessation. However, vascular risk factor control is frequently poor among stroke survivors, particularly among socio-economically disadvantaged blacks, Latinos and other people of color. The Chronic Care Model (CCM) is an effective framework for multi-component interventions aimed at improving care processes and outcomes for individuals with chronic disease. In addition, community health workers (CHWs) have played an integral role in reducing health disparities; however, their effectiveness in reducing vascular risk among stroke survivors remains unknown. Our objectives are to develop, test, and assess the economic value of a CCM-based intervention using an Advanced Practice Clinician (APC)-CHW team to improve risk factor control after stroke in an under-resourced, racially/ethnically diverse population.Methods/designIn this single-blind randomized controlled trial, 516 adults (≥40 years) with an ischemic stroke, transient ischemic attack or intracerebral hemorrhage within the prior 90 days are being enrolled at five sites within the Los Angeles County safety-net setting and randomized 1:1 to intervention vs usual care. Participants are excluded if they do not speak English, Spanish, Cantonese, Mandarin, or Korean or if they are unable to consent. The intervention includes a minimum of three clinic visits in the healthcare setting, three home visits, and Chronic Disease Self-Management Program group workshops in community venues. The primary outcome is blood pressure (BP) control (systolic BP <130 mmHg) at 1 year. Secondary outcomes include: (1) mean change in systolic BP; (2) control of other vascular risk factors including lipids and hemoglobin A1c, (3) inflammation (C reactive protein [CRP]), (4) medication adherence, (5) lifestyle factors (smoking, diet, and physical activity), (6) estimated relative reduction in risk for recurrent stroke or myocardial infarction (MI), and (7) cost-effectiveness of the intervention versus usual care.DiscussionIf this multi-component interdisciplinary intervention is shown to be effective in improving risk factor control after stroke, it may serve as a model that can be used internationally to reduce race/ethnic and socioeconomic disparities in stroke in resource-constrained settings.Trial registrationClinicalTrials.gov Identifier NCT01763203

Making Medical Homes Work: Moving From Concept to Practice

Explores practical considerations for implementing a medical home program of physician practices committed to coordinating and integrating care based on patient needs and priorities, such as how to qualify medical homes and how to match patients to them

Identification with Latent Choice Sets

In a common experimental format, individuals are randomly assigned to either a treatment group with access to a program or a control group without access. In such experiments, analyzing the average effects of the treatment of program access may be hindered by the problem that some control individuals do not comply with their assigned status and receive program access from outside the experiment. Available tools to account for such a problem typically require the researcher to observe the receipt of program access for every individual. However, in many experiments, this is not the case as data is not collected on where any individual received access. In this paper, I develop a framework to show how data on only each individual's treatment assignment status, program participation decision and outcome can be exploited to learn about the average effects of program access. I propose a nonparametric selection model with latent choice sets to relate where access was received to the treatment assignment status, participation decision and outcome, and a linear programming procedure to compute the identified set for parameters evaluating the average effects of program access in this model. I illustrate the framework by analyzing the average effects of Head Start preschool access using the Head Start Impact Study. I find that the provision of Head Start access induces parents to enroll their child into Head Start and also positively impacts test scores, and that these effects heterogeneously depend on the availability of access to an alternative preschool.Comment: 23 pages, plus 32 pages of supplemental appendi

Probability and Common-Sense: Tandem Towards Robust Robotic Object Recognition in Ambient Assisted Living

The suitable operation of mobile robots when providing Ambient Assisted Living (AAL) services calls for robust object recognition capabilities. Probabilistic Graphical Models (PGMs) have become the de-facto choice in recognition systems aiming to e ciently exploit contextual relations among objects, also dealing with the uncertainty inherent to the robot workspace. However, these models can perform in an inco herent way when operating in a long-term fashion out of the laboratory, e.g. while recognizing objects in peculiar con gurations or belonging to new types. In this work we propose a recognition system that resorts to PGMs and common-sense knowledge, represented in the form of an ontology, to detect those inconsistencies and learn from them. The utilization of the ontology carries additional advantages, e.g. the possibility to verbalize the robot's knowledge. A primary demonstration of the system capabilities has been carried out with very promising results.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Fiscal Federalism as Risk-Sharing: The Insurance Role of Redistributive Taxation

In addition to funding government and redistributing income, a redistributive tax-and-transfer system, and a progressive income tax in particular, provides insurance against the risk of uncertain future income. By providing for high taxes for high incomes, and low taxes, exemptions, and transfers for low incomes, a progressive income tax lowers the volatility of potential after-tax income relative to a lump-sum tax. This insurance function is distinct from the redistributive function of the system, since it provides a direct risk-mitigation benefit to the taxpayer himself, rather than simply redistributing income from one taxpayer to another. This article analyzes the question of at what level of government to assign the income tax role in a federal system, given both its redistributive and insurance functions. The standard view in the literature is that redistribution is best done centrally, and thus that an income tax is best used by the federal government, rather than by state governments. Yet recent work suggests that states can effectively have some role in redistribution. Income insurance, however, can be more effectively done by the federal government, because of its larger risk pool and better ability to handle revenue volatility. This article argues that states will, and likely should, use progressive income taxes as a tool of greater redistribution. At the same time, the insurance function of a progressive income tax can still be nationalized through policies that resemble re-insurance. In particular, this article looks at the idea of a multi-state rainy-day fund as a form of pooled state revenue insurance, as well as federal policies that may achieve some of the same benefits