Visual management system to improve care planning and controlling: the case of intensive care unit

Health Lean Management (HLM) is usually implemented to enhance the operational performance in health care; nevertheless, scant attention is devoted to visual control and daily accountability processes. This paper aims at investigating how to adopt a visual management system to: plan and control patient journey in health care operations and perform a continuous improvement process. Conducting in-depth interviews and observations, participating in meetings and collecting documentation, the patient journey board and daily briefings of an Intensive Care Unit were studied and improved. In the patient journey board, the Plan, Do and Check phases were reported, distinguishing between actual and planned actions for the patient care. The daily meetings were organised and a continuous improvement board was also developed to solve specific issues (Act phase), by creating ad-hoc teams, involving the staff and reporting transparently on the board. Operational and sociotechnical performance, before and after the adoption of HLM, were assessed demonstrating the effectiveness and efficiency of visual management tools.     

Using a benchmarking system to improve patient care and assist in technology assessment

Clinical benchmarking is a tool of CQI that can be used to improve outcomes in areas of strategic importance. While it is a simple tool, benchmarking requires a long-term commitment from the entire organization involved in its use to be successful. Benchmarking is a means of setting goals or targets. As a tool used for continuous quality management, benchmarking is an ongoing activity of comparing an organization's service, product, or process with similar ones outside the organization that are known to be the best. In attempting to emulate or surpass "best practice," an organization must set challenging but attainable goals and reach them with a plan of realistic and efficient actions.     

Evaluating correlated outcomes and sources of new information

This paper considers the difficulties associated with evaluating the expected value of additional information when the outcomes of various decision alternatives may be correlated. Such correlation is explained in terms of dependence of outcomes on common exogenous factors and it is argued that decisions regarding what, if any, additional information to collect should take such dependencies into account. A model-based ‘fixed-parameter’ approach to evaluating EVPI in such a context is developed and compared to the traditional ‘fixed-correlation’ approach. The results suggest that different assumptions about the issue of correlation can produce different, sometimes contradictory, conclusions about the expected value of additional information and bence, should be explicitly stated as part of any pre-posterior analysis. A hybrid model encompassing both approaches and rooted in the theory of psychology of inference is then proposed and illustrated.     

Twelve questions to ask about your outcomes monitoring system--Part I

Outcomes monitoring is an integral part of any decision maker's information resources--the cornerstone of a provider's commitment to quality improvement or of a purchaser's strategy for seeking value. In their eagerness to obtain useful information about provider performance, purchasers and consumers naively may accept flawed evaluations and thereby create perverse incentives for providers that undermine the very qualities they wish to foster. Inaccurate or misleading information about provider performance will lead managers to reward the wrong behavior and so induce more of it. Inaccurate information also can discourage better providers whose performances are not recognized and can lead all providers to distrust and denounce clinical monitoring in general. When these things happen, the great value of outcomes monitoring systems as a tool for quality improvement is lost.     

Twelve questions to ask about your outcomes monitoring system--Part II

Commercial and customized outcomes monitoring systems designed to assess the results of care, whether clinical outcomes or resource use, are not all of equal value or equally appropriate for every use. In creating each system, its developers had to make critical decisions about such matters as definitions of outcomes for study, selection of patients, selection of data elements, methods and timing of data collection, and method of analysis and reporting. Each system represents a unique set of choices that were made. This series of two articles presents answers to 12 questions that will help users understand the basic workings of an outcomes monitoring system--to be able to distinguish good systems from the mediocre and the bad, and to make wise use of a system already in operation. In addition to the six questions presented in the April 1994 issue of Physician Executive, the following six questions are of critical importance in determining a system's value to you and your organization.     

The high point of efforts to improve access to health care by "documentation"

The set of articles of which this article is a part has documented the tension between the advocates and the opponents of government intervention in the American health care system. This article will focus on a chapter of American health care history that is almost forgotten and has still never been told in its entirety. The story of the Committee on the Costs of Medical Care (CCMC), which existed from 1927 to 1933, represents the apogee of the factual approach effort to changing health care delivery in America.     

Combining analytical hierarchy process and Choquet integral within non-additive robust ordinal regression

We consider multiple criteria decision aiding in the case of interaction between criteria. In this case the usual weighted sum cannot be used to aggregate evaluations on different criteria and other value functions with a more complex formulation have to be considered. The Choquet integral is the most used technique and also the most widespread in the literature. However, the application of the Choquet integral presents two main problems being the necessity to determine the capacity, which is the function that assigns a weight not only to all single criteria but also to all subset of criteria, and the necessity to express on the same scale evaluations on different criteria. While with respect to the first problem we adopt the recently introduced Non-Additive Robust Ordinal Regression (NAROR) taking into account all the capacities compatible with the preference information provided by the DM, with respect to the second one we build the common scale for the considered criteria using the Analytic Hierarchy Process (AHP). We propose to use AHP on a set of reference points in the scale of each criterion and to use an interpolation to obtain the other values. This permits to reduce considerably the number of pairwise comparisons usually required by the DM when applying AHP. An illustrative example details the application of the proposed methodology.     

An approximate summarization method of process data for acquiring knowledge to improve product quality

This paper describes a machine learning approach for a manufacturing database. The method is presented in the Nb-Ti superconducting wire domain. A Nb-Ti superconducting wire is produced by iterating the drawing and heat treatment operations. The purpose is to obtain approximate summarization of process data that describes how a production schedule can be improved for better product quality. The method consists of the following steps: First, define a ranking function for a production schedule. Then, generate 'positive' and 'negative' instances for improving a production schedule by comparing a pair of schedules and their ranking values in the database. Using a machine learning technique, called 'ID3', a 'modification patterns' are obtained that generalize the data for better production quality. The final step is to extract approximate information from the induced patterns, which is both desirable for easier understanding by human experts and necessary to avoid being too much influenced by excessive details or disturbances. Two criteria are proposed, correctness and applicability indices, for this approximation.     

Using Lean Six Sigma to improve mobile order fulfilment process in a telecom service sector

This study proposes and follows a specific and systematic framework for implementing Lean Six Sigma (LSS) methodology in a telecom company in order to improve customer satisfaction by minimizing the company’s response time to customer requirements. The goal of this study was achieved by utilizing several LSS tools under five phases of the DMAIC methodology. Unlike previous studies in the telecom sector that used only qualitative method, in this study, both qualitative and quantitative methods were utilized to draw meaningful conclusions. As a result of the implementation of the LSS methodology, the average order fulfilment lead time for sales orders (SO) and value-added service (VAS) orders was reduced from 10.3 to 5.9 days and from 1.5 to 0.5 days, respectively. The reduction in lead time resulted in an increase in the sigma level for SO and VAS orders from 0.44 to 1.26 and from 0.73 to 2.66, respectively. These improvements were expected to lead to a financial benefit in savings of over $600,000 per year in operational costs, enhancements to customer experience and an increase in revenue generating opportunities. Moreover, this article enriches the existing literature on the application of LSS concept in the service industry, and helps the company to speed up the response to customer requirements.     

Institutional factors affecting offshore business process and information technology outsourcing

Micro and macro level impacts of offshore outsourcing are far from clear. Thus there are some well-founded rationales for and against offshore outsourcing as well as a number of misinformed and ill guided viewpoints. Using institutional theory as a lens, this paper analyzes the drivers of offshore business process and information technology outsourcing. We examine the mechanisms by which regulative rules, social rules, culturally supported habits and subconsciously accepted rules and customs influence assessment, selection as well as continuation of outsourcing projects. Managerial and policy implications are discussed and directions for future research have been suggested.     

The need to improve communication about scope changes: frustration as an indicator of operational inefficiencies

Early and timely sharing of information can provide a sustainable competitive advantage. However, even if lean information management aims to improve this information flow, it has mainly been investigated in ‘operations-based’ companies. This paper fills this gap, drawing upon the experience of the authors working within a large project-based company engaged in the ‘engineer and manufacture to order’ of a complex piece of equipment costing millions of dollars, for its strategic long-term client, both working in the same industrial field, i.e. nuclear decommissioning. This research investigates the information flow regarding scope changes between the project-based company and the long-term client adapting and applying a five-step framework to highlight operational inefficiencies, reduce the corresponding transaction costs and increase the overall company’s competitiveness. This is exemplified through a particular case, but can be applied to other project-based companies dealing with strategic clients involved in long-term relationships.     

Combining QMRA and Epidemiology to Estimate Campylobacteriosis Incidence

The disease burden of pathogens as estimated by QMRA (quantitative microbial risk assessment) and EA (epidemiological analysis) often differs considerably. This is an unsatisfactory situation for policymakers and scientists. We explored methods to obtain a unified estimate using campylobacteriosis in the Netherlands as an example, where previous work resulted in estimates of 4.9 million (QMRA) and 90,600 (EA) cases per year. Using the maximum likelihood approach and considering EA the gold standard, the QMRA model could produce the original EA estimate by adjusting mainly the dose‐infection relationship. Considering QMRA the gold standard, the EA model could produce the original QMRA estimate by adjusting mainly the probability that a gastroenteritis case is caused by Campylobacter. A joint analysis of QMRA and EA data and models assuming identical outcomes, using a frequentist or Bayesian approach (using vague priors), resulted in estimates of 102,000 or 123,000 campylobacteriosis cases per year, respectively. These were close to the original EA estimate, and this will be related to the dissimilarity in data availability. The Bayesian approach further showed that attenuating the condition of equal outcomes immediately resulted in very different estimates of the number of campylobacteriosis cases per year and that using more informative priors had little effect on the results. In conclusion, EA was dominant in estimating the burden of campylobacteriosis in the Netherlands. However, it must be noted that only statistical uncertainties were taken into account here. Taking all, usually difficult to quantify, uncertainties into account might lead to a different conclusion.     

Value-based health care, Part 2. The physician imperative: define, measure, and improve health care quality

Health care is the only major industry that lacks agreed-upon metrics to objectively define the quality of its products and services. The fundamental deficiency has led to the use of price as the de facto metric for patient contracting. Provider selection defaults to price because quality is assumed to be equal across all physicians and hospitals. This assumption is erroneous and now obsolete. Health care quality can be accurately measured using sophisticated illness modeling techniques that objectively risk-adjust patients level data. Providers' clinical data can be correlated with patient self-assessed outcomes for all episodes of inpatient and outpatient care. Physicians and their hospitals currently managing financial risks and those positioning themselves for these opportunities find such tools and techniques to be invaluable. Credible information creates a power shift away from price-based contracting to a true competitive marketplace that rewards quality of care. Purchasers and patients seek providers who objectively demonstrate their value on both quality and price. Part I of this article appeared in the January/February issue of The Physician Executive.     

结合RSM和田口方法改进产品/过程质量

对产品/过程参数进行优化时,响应曲面方法(RSM)和田口方法各有优缺点.本文在对两种方法的优缺点分析比较的基础上,提出了运用双响应曲面方法将RSM和田口方法结合起来,实现优势互补,以期能更有效地改进产品/过程质量.     

Combining Judgmental and Statistical Forecasts: An Application to Earnings Forecasts

This study investigated the accuracy of combinations of statistical and judgmental forecasts of annual accounting earnings. Combined forecasts were generated as equally weighted (i.e., simple averages) and unequally weighted combinations of individual forecasts from time-series models of quarterly and annual earnings (statistical forecasts) and security analysts' forecasts of quarterly and annual earnings (judgmental forecasts). The effect of the number of individual forecasts combined on the accuracy of the combined forecasts was also examined. The empirical results indicated that, on the average, combined forecasts were more accurate than individual forecasts. The results also indicated that although analysts' forecasts are based on a wider information set, the accuracy of their forecasts could be improved by combining them with forecasts generated from statistical models. Even if the best individual forecast could be identified in advance, gains in accuracy could be achieved by using combinations of two other forecasting methods. Several of the combined forecasts were superior to the most accurate individual forecast. Forecasts combined by using unequal weights derived from a regression model proved more accurate than equally weighted combinations. Forecasting accuracy improved and the variability of accuracy across different combinations decreased as the number of forecasts in the combination increased.     

New information and social trust: asymmetry and perseverance of attributions about hazard managers.

It has been argued that news about negative events has a much stronger effect on decreasing social trust than does news about positive events on increasing it. This asymmetry principle of trust was investigated in two surveys that also investigated the perseverance of trust. The possibility that established trust attributions persevere in the face of new information raises questions about the limits of trust asymmetry. The two studies yielded evidence that both type of news (good versus bad) and initial general trust in the nuclear power industry or the food supply industry affected level of trust. Compared to individuals trusting the industry, those distrusting the industry exhibited less trust following both bad and good news events. Study I also found that judged informativeness and judged positiveness of news events were affected by type of news and general trust of the industry. Individuals low in general trust of the nuclear power industry judged both bad news and good news as less positive than did those high in general trust. Those low in general trust judged bad news as more informative than good news and than did those high in general trust. An important implication of the perseverance of trust is to focus attention on including not only the effects of information about specific events and actions, but also on the judgment processes underlying social trust. The Salient Value Similarity model is suggested as one way of accounting for these psychological processes.     

Integrating management judgment and statistical methods to improve short-term forecasts

The complementary strengths that management judgment and statistical methods can bring to the forecasting process have been widely discussed. This paper reviews research on the effectiveness of methods that are designed to allow judgment and statistical methods to be integrated when short-term point forecasts are required. The application of both voluntary and mechanical integration methods are considered and conditions identified where the use of particular methods is appropriate, according to current research. While acknowledging the power of mechanical integration methods that exclude the judgmental forecaster from the integration process, the paper suggests that future research effort should focus on the design of forecasting support systems that facilitate voluntary integration.     

Combining Occurrence and Toxicity Information to Identify Priorities for Drinking-Water Mixture Research

Characterizing all possible chemical mixtures in drinking water is a potentially overwhelming project, and the task of assessing each mixture's net toxicity even more daunting. We propose that analyzing occurrence information on mixtures in drinking water may help to narrow the priorities and inform the approaches taken by researchers in mixture toxicology. To illustrate the utility of environmental data for refining the mixtures problem, we use a recent compilation of national ground-water-quality data to examine proposed U.S. Environmental Protection Agency (EPA) and Agency for Toxic Substances and Disease Registry (ATSDR) models of noncancer mixture toxicity. We use data on the occurrence of binary and ternary mixtures of arsenic, cadmium, and manganese to parameterize an additive model and compute hazard index scores for each drinking-water source in the data set. We also use partially parameterized interaction models to perform a bounding analysis estimating the interaction potential of several binary and ternary mixtures for which the toxicological literature is limited. From these results, we estimate a relative value of additional toxicological information for each mixture. For example, we find that according to the U.S. EPA's interaction model, the levels of arsenic and cadmium found in U.S. drinking water are unlikely to have synergistic cardiovascular effects, but the same mixture's potential for synergistic neurological effects merits further study. Similar analysis could in future be used to prioritize toxicological studies based on their potential to reduce scientific and regulatory uncertainty. Environmental data may also provide a means to explore the implications of alternative risk models for the toxicity and interaction of complex mixtures.     

Centralized nurse scheduling to simultaneously improve schedule cost and nurse satisfaction

Nursing managers are faced with rising turnover and shortages of qualified nursing staff. At the same time they are under increased pressure to simultaneously increase patient care and satisfaction while reducing costs. In this study, we examine the impact of centralizing scheduling decisions across departments in a hospital. By pooling nurses from multiple units and scheduling them in one model, improved costs and reduced overtime result. Reduced overtime improves schedules for nurses. Improved satisfaction levels can positively impact turnover rates among nurses. Our results show that by using a centralized model, nursing managers in hospitals can improve the desirability of nurse schedules by approximately 34% and reduce overtime by approximately 80% while simultaneously reducing costs by just under 11%.