BACKGROUND: Less than one third of the 65 million Americans with hypertension have adequate blood pressure (BP) control. This study examined the effectiveness of 2 interventions for improving patient BP control. METHODS: This was a 2-level (primary care provider and patient) cluster randomized trial with 2-year follow-up occurring among patients with hypertension enrolled from a Veterans Affairs Medical Center primary care clinic. Primary care providers (n = 17) in the intervention received computer-generated decision support designed to improve guideline concordant medical therapy at each visit; control providers (n = 15) received a reminder at each visit. Patients received usual care or a bimonthly tailored nurse-delivered behavioral telephone intervention to improve hypertension treatment. The primary outcome was proportion of patients who achieved a BP <140/90 mm Hg (<130/85 for diabetic patients) over the 24-month intervention. RESULTS: Of the 816 eligible patients contacted, 190 refused and 38 were excluded. The 588 enrolled patients had a mean age of 63 years, 43% had adequate baseline BP control, and 482 (82%) completed the 24-month follow-up. There were no significant differences in amount of change in BP control in the 3 intervention groups as compared to the hypertension reminder control group. In secondary analyses, rates of BP control for all patients receiving the patient behavioral intervention (n = 294) improved from 40.1% to 54.4% at 24 months (P = .03); patients in the nonbehavioral intervention group improved from 38.2% to 43.9% (P = .38), but there was no between-group differences at the end of the study. CONCLUSION: The brief behavioral intervention showed improved outcomes over time, but there were not significant between group differences.

Objective: To investigate coronary heart disease (CHD) morbidity and mortality and their patterning by socioeconomic status among diabetic and nondiabetic individuals in Finland.

Methods: All diabetic persons aged 35-74 years entitled to free anti-diabetic medication were drawn from the 1991-1996 national health insurance files along with nondiabetic referents. Outcome events for up to 6 years of follow-up, corresponding to 418,987 and 867,813 person-years in diabetic and nondiabetic people, respectively, were identified from national health insurance, hospital discharge and causes of death registers using personal identification codes.

Results: The annual CHD incidence for diabetic women and men was 2.7% and 3.7%, respectively, corresponding to relative risks of 3.55 (95% CI: 3.43-3.67) and 2.64 (95% CI: 2.56-2.72) compared to nondiabetic persons. The impact of diabetes on CHD mortality was greater, with relative death rates of 6.04 and 3.42 for women and men, respectively. CHD mortality and incidence displayed systematic socioeconomic trends with higher rates among worse-off diabetic and nondiabetic people, although gradients were generally steeper for nondiabetics. In the diabetic population, socioeconomic differences were rather similar for sudden CHD deaths and nonfatal CHD incident cases. For both genders, socioeconomic differences in mortality after CHD diagnosis were small in both diabetic and nondiabetic persons, except for the lowest compared to the highest income quintile.

Conclusions: Socioeconomic CHD mortality differences among diabetic people in Finland were mainly explained by higher CHD incidence and particularly sudden deaths without prior CHD diagnosis. No systematic socioeconomic differences were found in long-term prognosis after CHD diagnosis.

BACKGROUND: Diabetes mellitus is common, costly, and increasingly prevalent. Despite innovations in therapy, little is known about patterns and costs of drug treatment.

METHODS: We used the National Disease and Therapeutic Index to analyze medications prescribed between 1994 and 2007 for all US office visits among patients 35 years and older with type 2 diabetes. We used the National Prescription Audit to assess medication costs between 2001 and 2007.

RESULTS: The estimated number of patient visits for treated diabetes increased from 25 million (95% confidence interval [CI], 23 million to 27 million) in 1994 to 36 million (95% CI, 34 million to 38 million) by 2007. The mean number of diabetes medications per treated patient increased from 1.14 (95% CI, 1.06-1.22) in 1994 to 1.63 (1.54-1.72) in 2007. Monotherapy declined from 82% (95% CI, 75%-89%) of visits during which a treatment was used in 1994 to 47% (43%-51%) in 2007. Insulin use decreased from 38% of treatment visits in 1994 to a nadir of 25% in 2000 and then increased to 28% in 2007. Sulfonylurea use decreased from 67% of treatment visits in 1994 to 34% in 2007. By 2007, biguanides (54% of treatment visits) and glitazones (thiazolidinediones) (28%) were leading therapeutic classes. Increasing use of glitazones, newer insulins, sitagliptin phosphate, and exenatide largely accounted for recent increases in the mean cost per prescription ($56 in 2001 to $76 in 2007) and aggregate drug expenditures ($6.7 billion in 2001 to $12.5 billion in 2007).

CONCLUSIONS: Increasingly complex and costly diabetes treatments are being applied to an increasing population. The magnitude of these rapid changes raises concerns about whether these more costly therapies will result in proportionately improved outcomes.

OBJECTIVES: With >6 million hospital stays, costing almost $50 billion annually, hospitalized children represent an important population for which most inpatient quality indicators are not applicable. Our aim was to develop indicators using inpatient administrative data to assess aspects of the quality of inpatient pediatric care and access to quality outpatient care.

METHODS: We adapted the Agency for Healthcare Research and Quality quality indicators, a publicly available set of measurement tools refined previously by our team, for a pediatric population. We systematically reviewed the literature for evidence regarding coding and construct validity specific to children. We then convened 4 expert panels to review and discuss the evidence and asked them to rate each indicator through a 2-stage modified Delphi process. From the 2000 and 2003 Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project Kids' Inpatient Database, we generated national estimates for provider level indicators and for area level indicators.

RESULTS: Panelists recommended 18 indicators for inclusion in the pediatric quality indicator set based on overall usefulness for quality improvement efforts. The indicators included 13 hospital-level indicators, including 11 based on complications, 1 based on mortality, and 1 based on volume, as well as 5 area-level potentially preventable hospitalization indicators. National rates for all 18 of the indicators varied minimally between years. Rates in high-risk strata are notably higher than in the overall groups: in 2003 the decubitus ulcer pediatric quality indicator rate was 3.12 per 1000, whereas patients with limited mobility experienced a rate of 22.83. Trends in rates by age varied across pediatric quality indicators: short-term complications of diabetes increased with age, whereas admissions for gastroenteritis decreased with age.

CONCLUSIONS: Tracking potentially preventable complications and hospitalizations has the potential to help prioritize quality improvement efforts at both local and national levels, although additional validation research is needed to confirm the accuracy of coding.

Biotechnology (or biotech) has impacted almost every aspect of human life. It has reorganized industries, drastically changed healthcare, helped to improve the environment, and led to important changes in laws and ethical norms.

Among the various biotech fields, medical biotech has been by far the most influential, beneficial, and controversial. It has generated not only superlative discoveries to improve the lifespan and quality of human life, but also the greatest amount of wealth for all the players involved, and the greatest volume of public debate.

Several important trends are shaping the future of the pharmaceutical (or pharma) and biotech industries. The biotech industry is characterized by the presence of strong clusters in all countries. The pharma and biotech industries are experiencing an outsourcing phenomenon, mainly due to a lack of in-house expertise and efficiencies. Diagnostics and therapeutics are increasingly converging, a trend that will lead to predictive and precise diagnostics and personalized and preventive medicine. The first few years of the twenty-first century have witnessed significant changes in the pharma/biotech alliance landscape. Today we are seeing the “omic”-ization of the biotech industry: most of the emerging technologies are genomics, proteomics, cellomics, and pharmacogenomics. In addition, the biotech industry faces uphill ethical issues, including excessive marketing, third-world drug availability, genetic engineering, stem cells, and cloning.

The medical biotech industry faces several challenges. First, science, the human body, and disease are, essentially, complex. Second, unlike other high-technology industries, the biotech product development cycle is very long, even after proof of concept. Biotech projects take between ten and twenty years to become successful and cost over $200–300 million before a product reaches the market. Third, delivery of most biotech products and therapies is complex and can be painful, often involving intravenous delivery. Fourth, the preceding three factors pose significant challenges for research and development (R&D) financing. In addition, there are certain outside determinants that influence the biotech industry, including regulation, demography, reimbursement climate, and big pharma companies.

Stem cell research is one of the most fascinating areas of biology, but it raises questions as rapidly as it generates new discoveries. The greatest potential application of this research is the generation of cells and tissues that can be used for cell-based therapies. A stem cell is a special kind of cell that has a unique capacity to renew itself and to give rise to specialized cell types. Through the process of differentiation, stem cells form various tissues and organs, and the combination of these differentiated materials develops into the whole human body. This class of human stem cell holds the promise of being able to repair or replace cells or tissues that are damaged or destroyed by many of our most devastating diseases.

Diabetes mellitus is a group of diseases characterized by high levels of blood glucose resulting from defects in insulin production, insulin action, or both. Diabetes mellitus is a type I diabetes—also called juvenile-onset diabetes or insulin-dependent diabetes—and develops when the body’s immune system destroys pancreatic beta cells, the only cells in the body that make the insulin that regulates blood glucose. Type II diabetes, also called adult-onset diabetes or noninsulin-dependent diabetes, may account for 90–95 percent of all diagnosed cases of diabetes. There are more than 194 million diabetics worldwide, with this number expected to exceed 333 million by 2025.

Insulin is currently the most effective drug for controlling hyperglycemia and is widely accepted as the gold standard for treating type I diabetes and even late-stage type II diabetes. However, physicians and patients are reluctant to use insulin until other less effective drugs have been attempted. This is mainly because insulin therapy is invasive and painful: patients must take insulin intravenously.

One of the most promising ways to cure diabetes is to restore the function of islet cells biologically, either through islet cell transplantation or by engineering cells to restore the insulin secreting function. Islet transplantation, a procedure that can restore insulin production in patients, is a highly promising area of research.

Based on analysis of stem cell research, diabetes market opportunities, and the development of stem cell therapies, it is possible to place a value on a company in the early (preclinical) development stage of a stem cell therapy for diabetes. Such an exercise involves valuing a company based on three different approaches—(1) the discounted cashflow model, (2) the royalty or licensing model, and (3) the comparables valuation model. Sensitivity analysis based on market, pricing, costing, R&D, and development stage can further lead to precise valuation range for a given company.

For biotechnology companies, various drivers play a critical role in company valuation, including people (management team), alliances and partnerships, intellectual property rights, R&D and technology, funding and financing, market opportunity, and therapeutic area.

Abstract:

Context: Without detailed evidence of their effectiveness, pedometers have recently become popular as a tool for motivating physical activity.

Objective: To evaluate the association of pedometer use with physical activity and health outcomes among outpatient adults.

Data Sources: English-language articles from MEDLINE, EMBASE, Sport Discus, PsychINFO, Cochrane Library, Thompson Scientific (formerly known as Thompson ISI), and ERIC (1966-2007); bibliographies of retrieved articles; and conference proceedings.

Study Selection: Studies were eligible for inclusion if they reported an assessment of pedometer use among adult outpatients, reported a change in steps per day, and included more than 5 participants.

Data Extraction and Data Synthesis: Two investigators independently abstracted data about the intervention; participants; number of steps per day; and presence or absence of obesity, diabetes, hypertension, or hyperlipidemia. Data were pooled using random-effects calculations, and meta-regression was performed.

Results: Our searches identified 2246 citations; 26 studies with a total of 2767 participants met inclusion criteria (8 randomized controlled trials [RCTs] and 18 observational studies). The participants' mean (SD) age was 49 (9) years and 85% were women. The mean intervention duration was 18 weeks. In the RCTs, pedometer users significantly increased their physical activity by 2491 steps per day more than control participants (95% confidence interval [CI], 1098-3885 steps per day, P .001). Among the observational studies, pedometer users significantly increased their physical activity by 2183 steps per day over baseline (95% CI, 1571-2796 steps per day, P .0001). Overall, pedometer users increased their physical activity by 26.9% over baseline. An important predictor of increased physical activity was having a step goal such as 10,000 steps per day (P = .001). When data from all studies were combined, pedometer users significantly decreased their body mass index by 0.38 (95% CI, 0.05-0.72; P = .03). This decrease was associated with older age (P = .001) and having a step goal (P = .04). Intervention participants significantly decreased their systolic blood pressure by 3.8 mm Hg (95% CI, 1.7-5.9 mm Hg, P .001). This decrease was associated with greater baseline systolic blood pressure (P = .009) and change in steps per day (P = .08).

Conclusions: The results suggest that the use of a pedometer is associated with significant increases in physical activity and significant decreases in body mass index and blood pressure. Whether these changes are durable over the long term is undetermined.