Recognition & management of varicella infections and accuracy of antimicrobial recommendations: Case vignettes study in the US.

BACKGROUND: In 1995, the CDC recommended one-dose routine varicella immunization for children <12 years of age, expanding its recommendation to two doses in 2006. Today, with widespread varicella vaccination coverage, an estimated 3.5 million cases of varicella, 9,000 hospitalizations, and 100 deaths are prevented annually in the United States. Since varicella infections are now uncommon, health care providers (HCPs) may not recognize varicella infections and may prescribe inappropriate treatment. METHODS: An online survey of HCPs was conducted to assess recognition and management of varicella infections. Responses to eight varicella vignettes describing patients with varying varicella symptoms were analyzed and descriptive analyses performed. Stratified analysis comparing responses of those licensed before and in/after 1996 was also performed. RESULTS: 153 HCPs (50 nurse practitioners, 103 doctors) completed the survey. Mean age of respondents was 44 years. 62% were female, and 82% were licensed before 1996. Varicella infection was correctly diagnosed 79% of the time. HCPs correctly recognized uncomplicated varicella vignettes 85% of the time versus 61% of the time for complicated varicella vignettes. Antibiotics were recommended 17% of the time and antivirals 18% of the time, of which 25% and 69% (respectively) were not appropriate per guidelines. HCPs licensed before 1996 were better able to recognize varicella compared to those licensed later, but prescribed more antimicrobials medications to treat varicella. CONCLUSIONS: Although most HCPs recognized varicella infection, a sizable proportion could not recognize cases with complications, and some of the varicella cases were inappropriately treated with antibiotics and/or antivirals. Additional HCP training and high vaccination coverage are important strategies to avoid inaccurate diagnoses and minimize unnecessary exposure to antimicrobial/antiviral therapies.

Economic value of transcatheter valve replacement for inoperable aortic stenosis.

OBJECTIVES: To project the social value of transcatheter aortic valve replacement (TAVR) for inoperable patients with severe, symptomatic aortic stenosis (SSAS). STUDY DESIGN: This study used an economic model with parameters obtained from the literature and from US Census Bureau population projections. METHODS: Our model estimated the economic value that will accrue to inoperable patients with SSAS and to device manufacturers as a result of TAVR utilization. We estimated individual patient value as the monetized gain in quality-adjusted life-years as estimated in the cost-effectiveness literature, net of device costs and cost offsets. We estimated manufacturer value by applying an assumed profit margin to revenue from device sales. We created population-level estimates by combining these individual-level estimates with age-stratified Census Bureau population projections and estimates of the incidence of AS. We assessed model uncertainty through the use of probabilistic sensitivity analyses. RESULTS: Between 2018 and 2028, approximately 465,000 inoperable Americans with SSAS will be treated with TAVR. These procedures will yield a cumulative social benefit of up to $48 billion, with roughly 80% of that benefit accruing to patients and 20% accruing to device manufacturers. CONCLUSIONS: Policy makers and payers should take this social value into account when considering decisions related to the care of inoperable patients with SSAS.

Value-Based Payments and Incentives to Improve Care: A Case Study of Patients with Type 2 Diabetes in Medicare Advantage.

OBJECTIVES: To estimate the impact of increased glycated hemoglobin (A1C) monitoring and treatment intensification for patients with type 2 diabetes (T2D) on quality measures and reimbursement within the Medicare Advantage Star (MA Star) program. METHODS: The primary endpoint was the share of patients with T2D with adequate A1C control (A1C ≤ 9%). We conducted a simulation of how increased A1C monitoring and treatment intensification affected this end point using data from the National Health and Nutrition Examination Survey and clinical trials. Using the estimated changes in measured A1C levels, we calculated corresponding changes in the plan-level A1C quality measure, overall star rating, and reimbursement. RESULTS: At baseline, 24.4% of patients with T2D in the average plan had poor A1C control. The share of plans receiving the highest A1C rating increased from 27% at baseline to 49.5% (increased monitoring), 36.2% (intensification), and 57.1% (joint implementation of both interventions). However, overall star ratings increased for only 3.6%, 1.3%, and 4.8% of plans, respectively, by intervention. Projected per-member per-year rebate increases under the MA Star program were $7.71 (monitoring), $2.66 (intensification), and $10.55 (joint implementation). CONCLUSIONS: The simulation showed that increased monitoring and treatment intensification would improve A1C levels; however, the resulting average increases in reimbursement would be small.

Patient Versus Physician Valuation of Durable Survival Gains: Implications for Value Framework Assessments.

BACKGROUND: Previous research indicates that patients value therapies that provide durable or tail-of-the-curve survival gains, but it is unclear whether physicians share these preferences. OBJECTIVE: To compare patient and physician preferences for treatments with a positive probability of durable survival gains relative to those with fixed survival gains. METHODS: Patients with advanced stage melanoma or lung cancer and the oncologists who treated these patients were surveyed. The primary end point was the share of respondents who selected a therapy with a variable survival profile, with some patients experiencing long-term durable survival and others experiencing much shorter survival, compared to a therapy with a fixed survival duration. Parameter estimation by sequential testing was applied to calculate the length of nonvarying survival that would make respondents indifferent between that survival and therapy with durable survival. RESULTS: The sample comprised 165 patients (lung = 84, melanoma = 81) and 98 physicians. For lung cancer, 65.5% of patients preferred the therapy with a variable survival profile, compared with 40.8% of physicians (Δ = 24.7%; P < 0.001). For melanoma, these figures were 63.0% for patients and 29.7% for physicians (Δ = 33.3%; P < 0.001). Patients' indifference point implied that therapies with a variable survival profile are preferred unless the treatment with fixed survival had 13.6 months (melanoma) or 11.6 months (lung) longer mean survival; physicians would prescribe treatments with a fixed survival if the treatment had 7.5 months (melanoma) or 1.0 month (lung) shorter survival than the variable survival profile. CONCLUSIONS: Patients place a high value on therapies that provide a chance of durable or "tail-of-the-curve" survival, whereas physicians do not. Value frameworks should incorporate measures of tail-of-the-curve survival gains into their methodologies.

Estimating the Value of New Technologies That Provide More Accurate Drug Adherence Information to Providers for Their Patients with Schizophrenia.

BACKGROUND: Nonadherence to antipsychotic medication among patients with schizophrenia results in poor symptom management and increased health care and other costs. Despite its health impact, medication adherence remains difficult to accurately assess. New technologies offer the possibility of real-time patient monitoring data on adherence, which may in turn improve clinical decision making. However, the economic benefit of accurate patient drug adherence information (PDAI) has yet to be evaluated. OBJECTIVE: To quantify how more accurate PDAI can generate value to payers by improving health care provider decision making in the treatment of patients with schizophrenia. METHODS: A 3-step decision tree modeling framework was used to measure the effect of PDAI on annual costs (2016 U.S. dollars) for patients with schizophrenia who initiated therapy with an atypical antipsychotic. The first step classified patients using 3 attributes: adherence to antipsychotic medication, medication tolerance, and response to therapy conditional on medication adherence. The prevalence of each characteristic was determined from claims database analysis and literature reviews. The second step modeled the effect of PDAI on provider treatment decisions based on health care providers' survey responses to schizophrenia case vignettes. In the survey, providers were randomized to vignettes with access to PDAI and with no access. In the third step, the economic implications of alternative provider decisions were identified from published peer-reviewed studies. The simulation model calculated the total economic value of PDAI as the difference between expected annual patient total cost corresponding to provider decisions made with or without PDAI. RESULTS: In claims data, 75.3% of patients with schizophrenia were found to be nonadherent to their antipsychotic medications. Review of the literature revealed that 7% of patients cannot tolerate medication, and 72.9% would respond to antipsychotic medication if adherent. Survey responses by providers (n = 219) showed that access to PDAI would significantly alter treatment decisions for nonadherent or adherent/poorly controlled patients (P < 0.001). Payers can expect to save $3,560 annually per nonadherent patient who would respond to therapy if adherent. Savings increased to $9,107 per nonadherent patient when PDAI was given to providers who frequently augmented therapy for these patients. Among all poorly controlled patients (i.e., the nonadherent or those who were adherent but unresponsive to therapy), access to PDAI decreased annual patient cost by $2,232. Savings for this group increased to $7,124 per patient when PDAI was given to providers who frequently augmented therapy. CONCLUSIONS: Access to PDAI significantly improved provider decision making, leading to lower annual health care costs for patients who were nonadherent or adherent but poorly controlled. Additional research is warranted to evaluate how new technologies that accurately monitor adherence would affect health and economic outcomes among patients with serious mental illness. DISCLOSURES: This study and medical writing assistance was funded by Otsuka Pharmaceutical Development & Commercialization. Shafrin and Schwartz are employees of Precision Health Economics, which received funding from Otsuka Pharmaceutical Development & Commercialization in support of this study. Lakdawalla is Chief Scientific Officer and a founding partner of Precision Health Economics. Schwartz is a consultant for Otsuka Pharmaceutical Development & Commercialization, and Forma is an employee of Otsuka Pharmaceutical Development & Commercialization. The authors presented the abstract for this study as a poster presentation at the AMCP Managed Care & Specialty Pharmacy Annual Meeting, April 19-22, 2016, San Francisco, California. All authors contributed equally to the study design, data collection and analysis, and the writing and revision of the manuscript.