Automated symptom and treatment side effect monitoring for improved quality of life among adults with diabetic peripheral neuropathy in primary care: a pragmatic, cluster, randomized, controlled trial.

AIMS: To evaluate the effectiveness of automated symptom and side effect monitoring on quality of life among individuals with symptomatic diabetic peripheral neuropathy. METHODS: We conducted a pragmatic, cluster randomized controlled trial (July 2014 to July 2016) within a large healthcare system. We randomized 1834 primary care physicians and prospectively recruited from their lists 1270 individuals with neuropathy who were newly prescribed medications for their symptoms. Intervention participants received automated telephone-based symptom and side effect monitoring with physician feedback over 6 months. The control group received usual care plus three non-interactive diabetes educational calls. Our primary outcomes were quality of life (EQ-5D) and select symptoms (e.g. pain) measured 4-8 weeks after starting medication and again 8 months after baseline. Process outcomes included receiving a clinically effective dose and communication between individuals with neuropathy and their primary care provider over 12 months. Interviewers collecting outcome data were blinded to intervention assignment. RESULTS: Some 1252 participants completed the baseline measures [mean age (sd): 67 (11.7), 53% female, 57% white, 8% Asian, 13% black, 20% Hispanic]. In total, 1179 participants (93%) completed follow-up (619 control, 560 intervention). Quality of life scores (intervention: 0.658 ± 0.094; control: 0.653 ± 0.092) and symptom severity were similar at baseline. The intervention had no effect on primary [EQ-5D: -0.002 (95% CI -0.01, 0.01), P = 0.623; pain: 0.295 (-0.75, 1.34), P = 0.579; sleep disruption: 0.342 (-0.18, 0.86), P = 0.196; lower extremity functioning: -0.079 (-1.27, 1.11), P = 0.896; depression: -0.462 (-1.24, 0.32); P = 0.247] or process outcomes. CONCLUSIONS: Automated telephone monitoring and feedback alone were not effective at improving quality of life or symptoms for people with symptomatic diabetic peripheral neuropathy. TRIAL REGISTRATION: ClinicalTrials.gov (NCT02056431).

Determining the optimal strategy for the live-attenuated herpes zoster vaccine in adults.

The optimal strategy for the vaccinating against herpes zoster (HZ) vaccine remains unknown. Cost-effectiveness analyses provide insight to the most cost-effective age groups but results vary across studies. The optimal strategy is important given that vaccine efficacy and duration vary depending on vaccination age. Therefore, small changes from the optimal age can affect long-term outcomes and produce sub-optimal results. The objective of this research was to determine the optimal timing policy for HZ vaccination. We simulated cohorts of men and women and use stochastic dynamic programming to evaluate the decision to vaccinate or defer each year from age 50 to 100. If the decision was to defer, the cohort risked developing HZ. If HZ occurred, the cohort was subjected to cost and quality-adjusted life year (QALY) loss for a typical HZ infection (including complications) at that age. If HZ did not occur, the decision was evaluated at the next age. Then, we extend the model to consider the case in which a booster vaccine is available. A set of probabilistic sensitivity analyses were conducted to check model robustness. Results show the optimal policy for women is to vaccinate between ages 66 and 77, and for men between ages 66 and 74, assuming a willingness to pay (WTP) of $100,000 per QALY. It becomes optimal to vaccinate earlier if a booster vaccine is available, and women have a wider range of ages than men. This research is the first to examine exactly when the HZ vaccine should be administered. It is also the first study, to our knowledge, that used stochastic dynamic programming to examine the question of a second dose for any vaccine. This research provides the first simple policy on when to vaccinate and re-vaccinate against HZ.

Estimated morbidity and mortality in adolescents and young adults diagnosed with Type 2 diabetes mellitus.

AIMS: To estimate remaining life expectancy (RLE), quality-adjusted life expectancy (QALE), causes of death and lifetime cumulative incidence of microvascular/macrovascular complications of diabetes for youths diagnosed with Type 2 diabetes. METHODS: A Markov-like computer model simulated the life course for a hypothetical cohort of adolescents/young adults in the USA, aged 15-24 years, newly diagnosed with Type 2 diabetes following either conventional or intensive treatment based on the UK Prospective Diabetes Study. Outcomes included RLE, discounted QALE in quality-adjusted life years (QALYs), cumulative incidence of microvascular/macrovascular complications and causes of death. RESULTS: Compared with a mean RLE of 58.6 years for a 20-year-old in the USA without diabetes, conventional treatment produced an average RLE of 43.09 years and 22.44 discounted QALYs. Intensive treatment afforded an incremental 0.98 years and 0.44 discounted QALYs. Intensive treatment led to lower lifetime cumulative incidence of all microvascular complications and lower mortality from microvascular complications (e.g. end-stage renal disease (ESRD) death 19.4% vs. 25.2%). Approximately 5% with both treatments had ESRD within 25 years. Lifetime cumulative incidence of coronary heart disease (CHD) increased with longer RLE and greater severity of CHD risk factors. Incorporating disutility (loss in health-related quality of life) of intensive treatment resulted in net loss of QALYs. CONCLUSIONS: Adolescents/young adults with Type 2 diabetes lose approximately 15 years from average RLE and may experience severe, chronic complications of Type 2 diabetes by their 40s. The net clinical benefit of intensive treatment may be sensitive to preferences for treatment. A comprehensive management plan that includes early and aggressive control of cardiovascular risk factors is likely needed to reduce lifetime risk of CHD.

Barriers to using cost-effectiveness analysis in managed care decision making.

Managed care organizations would appear to be natural advocates for, and users of, cost-effectiveness analysis (CEA) as a tool for maximizing health outcomes for their covered populations within fixed budgets. There is, however, little evidence that CEA plays a major role in managed care decision making. The purpose of this paper is to identify barriers to both conducting and using CEA in managed care decision making. Lack of understanding about the value and applicability of CEA, and incentives that do not align with a lifetime perspective on either health outcomes or costs may be at least as important as perceived or real methodological limitations of the methodology. Research focused on ways to overcome these barriers, and thereby improve resource allocations, is recommended.

Cost-effectiveness of cholesterol-lowering therapies according to selected patient characteristics.

BACKGROUND: The National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel II) recommends treatment guidelines based on cholesterol level and number of risk factors. OBJECTIVE: To evaluate how the cost-effectiveness ratios of cholesterol-lowering therapies vary according to different risk factors. DESIGN: Cost-effectiveness analysis. DATA SOURCES: Published data. TARGET POPULATION: Women and men 35 to 84 years of age with low-density lipoprotein cholesterol levels of 4.1 mmol/L or greater (> or =160 mg/dL), divided into 240 risk subgroups according to age, sex, and the presence or absence of four coronary heart disease risk factors (smoking status, blood pressure, low-density lipoprotein cholesterol level, and high-density lipoprotein cholesterol level). TIME HORIZON: 30 years. PERSPECTIVE: Societal. INTERVENTIONS: Step I diet, statin therapy, and no preventive treatment for primary and secondary prevention. OUTCOME MEASURES: Incremental cost-effectiveness ratios. RESULTS OF BASE-CASE ANALYSIS: Incremental cost-effectiveness ratios for primary prevention with step I diet ranged from $1900 per quality-adjusted life-year (QALY) gained to $500000 per QALY depending on risk subgroup characteristics. Primary prevention with a statin compared with diet therapy was $54000 per QALY to $1400000 per QALY. Secondary prevention with a statin cost less than $50000 per QALY for all risk subgroups. RESULTS OF SENSITIVITY ANALYSIS: The inclusion of niacin as a primary prevention option resulted in much less favorable incremental cost-effectiveness ratios for primary prevention with a statin (>$500000 per QALY). CONCLUSIONS: Cost-effectiveness of treatment strategies varies significantly when adjusted for age, sex, and the presence or absence of additional risk factors. Primary prevention with a step I diet seems to be cost-effective for most risk subgroups but may not be cost-effective for otherwise healthy young women. Primary prevention with a statin may not be cost-effective for younger men and women with few risk factors, given the option of secondary prevention and of primary prevention in older age ranges. Secondary prevention with a statin seems to be cost-effective for all risk subgroups and is cost-saving in some high-risk subgroups.