Cost-effectiveness analysis of exenatide once-weekly versus dulaglutide,liraglutide, and lixisenatide for the treatment of type 2 diabetes mellitus: an analysis from the UK NHS perspective

Objective: To assess the cost-effectiveness of exenatide 2?mg once-weekly (EQW) compared to dulaglutide 1.5?mg QW, liraglutide 1.2?mg and 1.8?mg once-daily (QD), and lixisenatide 20?μg QD for the treatment of adult patients with type 2 diabetes mellitus (T2DM) not adequately controlled on metformin.

Methods: The Cardiff Diabetes Model was applied to evaluate cost-effectiveness, with treatment effects sourced from a network meta-analysis. Quality-adjusted life years (QALYs) were calculated with health-state utilities applied to T2DM-related complications, weight changes, hypoglycemia, and nausea. Costs (GBP £) included drug treatment, T2DM-related complications, severe hypoglycemia, nausea, and treatment discontinuation due to adverse events. A 40-year time horizon was used.

Results: In all base-case comparisons, EQW was associated with a QALY gain per patient; 0.046 vs dulaglutide 1.5?mg; 0.102 vs liraglutide 1.2?mg; 0.043 vs liraglutide 1.8?mg; and 0.074 vs lixisenatide 20?μg. Cost per patient was lower for EQW than for liraglutide 1.8?mg (?£2,085); therefore, EQW dominated liraglutide 1.8?mg. The cost difference per patient between EQW and dulaglutide 1.5?mg, EQW and liraglutide 1.2?mg, and EQW and lixisenatide 20?μg was £27, £103, and £738, respectively. Cost per QALY gained with EQW vs dulaglutide 1.5?mg, EQW vs liraglutide 1.2?mg, and EQW vs lixisenatide 20?μg was £596, £1,004, and £10,002, respectively. In the probabilistic sensitivity analysis, the probability that EQW is cost-effective ranged from 76–99%.

Conclusion: Results suggest that exenatide 2?mg once-weekly is cost-effective over a lifetime horizon compared to dulaglutide 1.5?mg QW, liraglutide 1.2?mg QD, liraglutide 1.8?mg QD, and lixisenatide 20?μg QD for the treatment of T2DM in adults not adequately controlled on metformin alone.     

Mapping your innovation strategy

In the complex sport of American football, teams rely on playbooks as thick as the Manhattan phone directory. But when it comes to creating innovative growth businesses-which is at least as complicated as professional football--most companies have not developed detailed game plans. Indeed, many managers have concluded that a fog enshrouds the world of innovation, obscuring high-potential opportunities. The authors believe that companies can penetrate that fog by developing growth strategies based on disruptive innovations, as defined by Clayton Christensen. Such innovations conform to a pattern: They offer an entirely new solution; they perform adequately along traditional dimensions and much better along other dimensions that matter more to target customers; and they are not initially appealing to powerful incumbents. Companies can develop customized checklists, or playbooks, by combining this basic pattern with analysis of major innovations in their markets. The key early on is to focus not on detailed financial estimates--which will always guide companies toward the markets most hostile to disruptive innovations--but on how well the innovation fits the pattern of success. It's also crucial to encourage flexibility: Companies must be willing to kill projects that are going nowhere, exempt innovations from standard development processes, and avoid burdening project teams with extra financing, which can keep them heading in the wrong direction. Companies can create competitive advantage by becoming champions at defining the pattern of successful innovations and executing against it. But as that pattern becomes obvious--and others emerge-building a sustainable advantage on innovation competencies will again prove elusive.     

On the Predictability of the Stock Market Volatility: Does History Matter?

This study compares the performance of the ISD, the GARCH (1,1) , the historical volatility estimates and of two lagged trading volume measures for predicting the Swiss Stock Market Index's (SMI) volatility. The ISD has a superior daily informational content than the GARCH (1,1) estimate and retains unbiased but decreasing explanatory power over up to 20 days ahead horizons. Mean and spread daily volume measures play a significant correcting role when forecasting stock market volatility over daily and longer intervals respectively and clearly dominate the GARCH (1,1) forecasts. Their significance emphasises heterogeneous horizon traders' influence on the SMI volatility time series properties     

Ethical decision making in the medical profession: An application of the theory of planned behavior

The present study applied Ajzen's (1985) theory of planned behavior to the explanation of ethical decision making. Nurses in three hospitals were provided with scenarios that depicted inadequate patient care and asked if they would report health professionals responsible for the situation. Study results suggest that the theory of planned behavior can explain a significant amount of variation in the intent to report a colleague. Attitude toward performing the behavior explained a large portion of the variance; subjective norms explained a moderate amount of the variance; and, perceived behavioral control added little to the explanation of variance. Implications for research and practice are discussed. Donna M. Randall is an Associate Professor in Management and Systems at Washington State University. Her research interests include organizational commitment, media coverage of elite crime, and ethical issues in management. Her publications have appeared in such journals as Decision Sciences, Academy of Management Review, and Journal of Business Ethics. Annetta M. Gibson is a doctoral student in the Department of Accounting and Business Law at Washington State University and a CPA. Her research interests lie in the area of behavioral accounting and ethical issues in auditing, accounting, and management. She has published in the Journal of Business Ethics.     

Economics and Restaurant Gratuities: Determining Tip Rates

Abstract IS tipping in restaurants simply a social norm where people tip on the basis of some rule of thumb (15% of bill size for example)? Using evidence gathered from surveys of nearly 700 diners in 7 Minnesota restaurants, it is argued that tipping is both a social norm and a means of rewarding good service. Survey evidence suggests that diners use rules of thumb as starting points and then vary gratuities on the basis of service just received, expected future service, whether they dine alone or with a group, alcohol consumption and location of the restaurant. Tipping may be viewed as a game played indirectly between diners in which each diner contemplates tipping, or not tipping, based on expectations of future service and the tipping behavior of other diners. Tipping is commonplace as long as people expect better service when they tip more and the expected payoff to tipping rises when more people tip, but rare otherwise. Neo-classical economics is quite successful in predicting tip size as long as diners view tipping as a pecuniary cost of buying service.