INNOVATION AND NATIONAL BROADBAND POLICIES: FACTS, FICTION AND UNANSWERED QUESTIONS IN THE NET NEUTRALITY DEBATE

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Comparative effectiveness of total population versus disease-specific neural network models in predicting medical costs

The objective of this research was to compare the accuracy of two types of neural networks in identifying individuals at risk for high medical costs for three chronic conditions. Two neural network models—a population model and three disease-specific models—were compared regarding effectiveness predicting high costs. Subjects included 33,908 health plan members with diabetes, 19,264 with asthma, and 2,605 with cardiac conditions. For model development/testing, only members with 24 months of continuous enrollment were included. Models were developed to predict probability of high costs in 2000 (top 15% of distribution) based on 1999 claims factors. After validation, models were applied to 2000 claims factors to predict probability of high 2001 costs. Each member received two scores—population model score applied to cohort and disease model score. Receiver Operating Characteristic (ROC) curves compared sensitivity, specificity, and total performance of population model and three disease models. Diabetes-specific model accuracy, C = 0.786 (95%CI = 0.779–0.794), was greater than that of population model applied to diabetic cohort, C = 0.767 (0.759–0.775). Asthma-specific model accuracy, C = 0.835 (0.825–0.844), was no different from that of population model applied to asthma cohort, C = 0.844 (0.835–0.853). Cardiac-specific model accuracy, C = 0.651 (0.620–0.683), was lower than that of population model applied to cardiac cohort, C = 0.726 (0.697–0.756). The population model predictive power, compared to the disease model predictive power, varied by disease; in general, the larger the cohort, the greater the advantage in predictive power of the disease model compared to the population model. Given these findings, disease management program staff should test multiple approaches before implementing predictive models. (Disease Management 2005;8:277–287

Use of chromium picolinate and biotin in the management of type 2 diabetes: an economic analysis

This paper addresses the potential economic benefits of chromium picolinate plus biotin (Diachrome ®) use in people with Type 2 diabetes (T2DM). The economic model was developed to estimate the impact on health care systems’ costs by improved HbA1C levels with chromium picolinate plus biotin (Diachrome). Lifetimes cost savings were estimated by adjusting a benchmark from the literature, using a price index to adjust for inflation. The cost of diabetes is highly dependent on the HbA1C level with higher initial levels and higher annual increments increasing the cost. Improvement in glycemic control has proven to be cost-effective in delaying the onset and progression of T2DM, reducing the risk for diabetes-associated complications and lowering utilization and cost of care. Chromium picolinate plus biotin (Diachrome) showed greater improvement of glycemic control in poorly controlled T2DM patients (HbA1C \u3e=10%) compared to their better controlled counterparts (HbA1C \u3c 10%). This improvement was additive to that achieved by oral hypoglycemic medications and correlates to calculated levels of cost savings. Average 3-year cost savings for chromium picolinate plus biotin (Diachrome) use could range from $1,636 for a poorly controlled patient with diabetes without heart diseases or hypertension, to$5,435 for a poorly controlled patient with diabetes, heart disease, and hypertension. Average 3-year cost savings was estimated to be between $3.9 billion and$52.9 billion for the 16.3 million existing patients with diabetes. Chromium picolinate plus biotin (Diachrome) use among the 1.17 million newly diagnosed patients with T2DM each year could deliver lifetime cost savings of $42 billion, or$36,000 per T2DM patient. Affordable, safe, and convenient, chromium picolinate plus biotin (Diachrome) could prove to be a cost-effective complement to existing pharmacological therapies for controlling T2DM. (Disease Management 2005;8:265–275

Diagnosing Crohn\u27s Disease: An economic analysis comparing wireless capsule endoscopy with traditional diagnostic procedures

The purpose of this study was to review economic considerations related to establishing a diagnosis of Crohn\u27s disease, and to compare the costs of a diagnostic algorithm incorporating wireless capsule endoscopy (WCE) with the current algorithm for diagnosing Crohn\u27s disease suspected in the small bowel. Published literature, clinical trial data on WCE in comparison to other diagnostic tools, and input from clinical experts were used as data sources for (1) identifying contributors to the costs of diagnosing Crohn\u27s disease; (2) exploring where WCE should be placed within the diagnostic algorithm for Crohn\u27s; and (3) constructing decision tree models with sensitivity analyses to explore costs (from a payor perspective) of diagnosing Crohn\u27s disease using WCE compared to other diagnostic methods. Literature review confirms that Crohn\u27s disease is a significant and growing public health concern from clinical, humanistic and economic perspectives, and results in a long-term burden for patients, their families, providers, insurers, and employers. Common diagnostic procedures include radiologic studies such as small bowel follow through (SBFT), enteroclysis, CT scans, ultrasounds, and MRIs, as well as serologic testing, and various forms of endoscopy. Diagnostic costs for Crohn\u27s disease can be considerable, especially given the cycle of repeat testing due to the low diagnostic yield of certain procedures and the inability of current diagnostic procedures to image the entire small bowel. WCE has a higher average diagnostic yield than comparative procedures due to imaging clarity and the ability to visualize the entire small bowel. Literature review found the average diagnostic yield of SBFT and colonoscopy for work-up of Crohn\u27s disease to be 53.87%, whereas WCE had a diagnostic yield of 69.59%. A simple decision tree model comparing two arms--colonoscopy and SBFT, or WCE--estimates that WCE produces a cost savings of 291dollars for each case presenting for diagnostic work-up for Crohn\u27s. Sensitivity analysis varying diagnostic yields of colonoscopy and SBFT vs. WCE demonstrates that WCE is still less costly than SBFT and colonoscopy even at their highest reported yields, as long as the diagnostic yield of WCE is 64.10% or better. Employing WCE as a first-line diagnostic procedure appears to be less costly, from a payor perspective, than current common procedures for diagnosing suspected Crohn\u27s disease in the small bowel. Although not addressed in this model, earlier diagnosis with WCE (due to higher diagnostic yield) also could lead to earlier management, improved quality of life and workplace productivity for people with Crohn\u27s disease

Vertical Integration, Regulation, & The Shifting Of Economic Profits

A model which shows how a vertically integrated, multiproduct regulated monopolist can shift its monopoly profits to its upstream nonregulated affiliate is developed.  The model is expanded to include a self-imposed constraint on the percentage mark-up of the transfer price which makes the regulatory constraint binding.  The telecommunications industry is examined to determine what empirical evidence exists to support the shifting of profits’ hypothesis.  Competitors are foreclosed from the market based on the desire to shift profits not on an economic efficiency criterion.  How a multiproduct regulated monopolist reacts to competition in one of its product lines is analyzed

Competition In A Regulatory Environment

This paper examines the difficulty which exists in allowing competition in a regulatory environment.  We examine how AT&T formerly was able to use the regulatory process as a barrier to entry in the long distance and terminal equipment market but how presently the regulatory process is putting AT&T at a competitive disadvantage in the long distance market