The economic burden of depression among adults with rheumatoid arthritis in the United States

Aims: Depression is the most frequent comorbidity reported among patients with rheumatoid arthritis (RA). Comorbid depression negatively impacts RA patients’ health-related quality-of-life, physical function, mental function, mortality, and experience of pain and symptom severity. The objective of this study was to assess healthcare utilization, expenditures, and work productivity among patients with RA with or without depression.

Materials and methods: Data from adult patients who had at least two visits each related to RA and depression over a 1-year period were extracted from the Truven Health MarketScan research databases. Outcomes comprised healthcare resource utilization, work productivity loss, and direct healthcare costs comparing patients with RA with depression (n?=?3,478) vs patients with RA without depression (n?=?43,222).

Results: Patients with RA and depression had a significantly greater relative risk of hospitalization and number of all-cause and RA-related hospitalizations, utilization of emergency services, days spent in the hospital, physician visits, and RA-related surgeries compared with RA patients without depression. Patients with RA and depression had a higher risk of and experienced more events and days of short-term disability compared with patients without depression. The incremental adjusted annual all-cause and RA-related direct costs were $8,488 (95% CI = $6,793–$10,223) and $578 (95% CI = –$98–$1,243), respectively, when comparing patients with RA and depression vs RA only.

Limitations: The current analysis is subject to the known limitations of retrospective studies based on administrative claims data.

Conclusions: This study suggested increased healthcare utilization, work productivity loss, and economic burden among RA patients due to comorbid depression. These findings emphasize the importance of managing depression and including depression as a factor when devising treatment algorithms for patients with RA.     

Sources, uses, and forms of data in the new product development process

This paper presents qualitative and exploratory research investigating the role that managing knowledge and information plays in new product development (NPD). A set of 20 in-depth interviews uncovered eight basic types of information used throughout the NPD process and three general approaches to managing information needed in the NPD process. Although some exemplary companies seem to do an outstanding job of collecting and disseminating information, the majority of firms struggle. NPD process automation solutions tackle part of the problem, ignoring nonquantitative data forms and the full picture of information use throughout the entire development process.     

Day-of-the-Week Effects in the Long-Run Performance of Initial Public Offerings

This study examines the influence of day-of-the-week patterns in security returns on long-run IPO underperformance. Comparisons are made between the IPOs in Ritter's [20] database, and a constructed set of matching firms based on SIC code and size, using NYSE, AMEX, and NASDAQ securities. It is found that virtually all of the IPO underperformance occurs on Mondays and Tuesdays and that the degree of underperformance significantly differs from other days. Thus, a common explanation may exist for the general day-of-the-week pattern in security returns and IPO long-run underperformance.     

The “swing of the pendulum” from public to market support for science and technology: Is the U.S. leading the way?

The structure and financing of science and technology activities are undergoing a slow, but profound, change. This change can be briefly characterized as a shift from relying and supporting public science to a stronger emphasis on “market-based” incentives for science and technology. In this paper we analyze this shift in a historical perspective, discussing both the theoretical explanations and the empirical trends of the ongoing change. While we do not claim to provide a comprehensive and exhaustive identification of the causes of this shift, we argue that it is largely driven by the perception of a shift of the U.S. policy towards market-based, rather than publicly supported, incentives for science and technology. This, in turn—given the strong economic performance of the United States over the 1990s—has influenced policies in most OECD countries, especially in Europe.We conclude by analyzing the evolution of research in U.S. higher education and find two major trends: an increasing diversity in the number of institutions of different types other than universities and a steady and continuous public funding of the leading U.S. universities. This has allowed the construction of an infrastructure now used largely by the private sector, but it also noted that the United States has not compromised public support for core areas or in those fields in which there is a clear perception that market incentives are not sufficient for meeting the strategic targets of the U.S. policy. The implication is that there is a considerable policy diversity in the U.S. practice and that all aspects of this diversity should be considered when using the United States as a reference.     

The application of Operation and Technology Roadmapping to aid Singaporean SMEs identify and select emerging technologies

In order to aid Singaporean SMEs identify and select emerging technologies for business benefit, a modified process of the Cambridge T-Plan methodology has been introduced and applied to a pilot sample of 30 companies in a variety of manufacturing sectors. This fast and simple process takes the company through five key steps to enable them to create their first Operation and Technology Roadmap (OTR). The paper explains the background to the approach and focuses on the initial benefits identified by a survey of the pilot companies.     

A note on “Bed allocation techniques based on census data”

Capacity planning and resource allocation are crucial to the cost-effective delivery of health care services. In this paper, we present an analytic approach based on a modified version of the Holt-Winters multiplicative seasonality forecasting model to determine the frequency distribution associated with a hospital care unit's census. This paper is a follow-up to the census frequency distribution simulation model described in Lapierre et al. (Socio Econ. Plan. Sci. 33 (1999) 25). We demonstrate that our model can provide census frequency distributions equivalent to the simulation model of Lapierre et al. [1], but without the computational effort common to simulation models.     

Strategizing through analyzing and influencing the network horizon

How does a firm keep on being valuable in a network? One requirement is that the firm has a sufficient overview of the network and its dynamics. In other words, a firm's strategy depends on the firm's overview of the network—its network horizon. How comprehensive or limited should its network horizon be? Is it necessary to know the network beyond the direct counterparts? Such issues have not received much attention. In this article, we discuss network horizons and argue that limited network horizons are both inevitable and useful. However, such myopia requires that a firm's counterparts effectively and efficiently mediate between the firm and the rest of the network. Based on a case study, we introduce and discuss three mediating functions of counterparts: a joining, a relating, and an insulating function, and we claim that in order to support a firm's strategizing, managers need to analyze and influence counterparts' mediating functions and thereby the firm's network horizon.     

Multiple generation product life cycle predictions using a novel two-stage fuzzy piecewise regression analysis method

Product life cycle (PLC) prediction plays a crucial role in strategic planning and policy definition for high-technology products. Forecast methodologies which can predict PLCs accurately can help to achieve successful strategic decision-making, forecasting, and foresight activities in high-technology firms, research institutes, governments, and universities. Over the past few decades, even though analytic framework strategies have been proposed for production, marketing, R&D (research and development), and finance, aiming at each stage of PLCs, forecast methodologies with which to predict PLCs are few. The purpose of this research is to develop a novel forecast methodology to allow for predictions of product life time (PLT) and the annual shipment of products during the entire PLC of multiple generation products. A novel two-stage fuzzy piecewise regression analysis method is proposed in this paper. In the first stage, the product life-time of the specific generation to be analyzed will be predicted by the fuzzy piecewise regression line that is derived based upon the product life-time of earlier generations. In the second stage of the forecast methodology, the annual shipment of products of the specified generation will be predicted by deriving annual fuzzy regression lines for each generation, based upon the historical data on the earlier generations' products. An empirical study predicting the life-time and the annual shipment of the 16 Mb (Mega bit) DRAM (Dynamic Random Access Memory) PLC is illustrated to validate the analytical process. The results demonstrate that two-stage fuzzy piecewise regression analysis can predict multiple generation PLT and PLC precisely, thereby serving as a foundation for future strategic planning, policy definitions and foresights.