Purpose There is uncertainty about when personalized medicine tests provide economic value. We assessed evidence on the economic value of personalized medicine tests and gaps in the evidence base. Methods We created a unique evidence base by linking data on published cost–utility analyses from the Tufts Cost-Effectiveness Analysis Registry with data measuring test characteristics and reflecting where value analyses may be most needed: (i) tests currently available or in advanced development, (ii) tests for drugs with Food and Drug Administration labels with genetic information, (iii) tests with demonstrated or likely clinical utility, (iv) tests for conditions with high mortality, and (v) tests for conditions with high expenditures. Results We identified 59 cost–utility analyses studies that examined personalized medicine tests (1998–2011). A majority (72%) of the cost/quality-adjusted life year ratios indicate that testing provides better health although at higher cost, with almost half of the ratios falling below $50,000 per quality-adjusted life year gained. One-fifth of the results indicate that tests may save money. Conclusion Many personalized medicine tests have been found to be relatively cost-effective, although fewer have been found to be cost saving, and many available or emerging medicine tests have not been evaluated. More evidence on value will be needed to inform decision making and assessment of genomic priorities.

No abstract

Billing and insurance-related functions have been reported to consume 14 percent of medical group revenue, but little is known about the costs associated with performing specific activities. We conducted semistructured interviews, observed work flows, analyzed department budgets, and surveyed clinicians to evaluate these activities at a large multispecialty medical group. We identified 0.67 nonclinical full-time-equivalent (FTE) staff working on billing and insurance functions per FTE physician. In addition, clinicians spent more than thirty-five minutes per day performing these tasks. The cost to medical groups, including clinicians' time, was at least $85,276 per FTE physician (10 percent of revenue).

Objective. There is widespread debate over whether health plans should require enrollees to use ''gatekeepers,'' which are primary care providers that coordinate care and control access to specialists. However, little is known about whether health plan gatekeeper requirements improve or reduce quality-of-care. Our objective was to examine whether gatekeeper requirements are associated with the utilization of cancer screening for breast, cervical, and prostate cancer. Data Sources. Three linked sources (N 5 13,534): (1) 1996 Medical Expenditure Panel Survey (MEPS) Household Survey, a nationally representative, ongoing survey sponsored by the Agency for Healthcare Research and Quality; (2) 1996 MEPS Health Insurance Plan Abstraction, which codes data from health plan booklets obtained from privately insured respondents, and (3) 1995 National Health Interview Survey. Study Design/Data Collection. Cross-sectional, multivariate logistic regression analysis using secondary data. Principal Findings. We found in multivariate analyses that women in gatekeeper plans were significantly more likely to obtain mammography screening (Odds Ratio [OR] 5 1.22, 95 percent Confidence Interval [CI] 1.07-1.40), clinical breast examinations (OR 5 1.39, 95 percent CI 1.23-1.57), and Pap smears (OR 5 1.33, 95 percent CI 1.16-1.52) than women not in gatekeeper plans. In contrast, gatekeeper requirements were not associated with prostate cancer screening (OR 5 1.11, 95 percent CI 0.93-1.33). We found no association between screening utilization and aggregate plan types (HMO, POS, PPO, FFS). Conclusions. Gatekeeper requirements are associated with higher utilization of widely recommended cancer screening procedures, but not with utilization of a less uniformly recommended cancer screening procedure. Researchers should consider the analysis of specific plan characteristics rather than aggregate plan types in conducting future research, and insurers and policymakers should consider the potential benefits of gatekeepers with respect to preventive care when designing health plans and legislation.

Objective: To conduct a cost-effectiveness analysis of genetic testing in the management of patients who have or are suspected to have familial long QT syndrome (LQTS).Background: Genetic testing for LQTS has been available in a research setting for the past

The majority of medication administration errors detected by a BCMA system were judged to be benign and pose minimal safety risks; however, the numbers and severity of medication administration errors that occur despite the use of a BCMA system suggest that there are opportunities to improve these systems and how the information they generate is used.

Methods of economic evaluation, especially cost-effectiveness analysis and cost-benefit analysis, are widely used to examine new healthcare technologies. However, few economic evaluations of pharmacogenomics have been conducted, and pharmacogenomic researchers may be unfamiliar with how to review or conduct these analyses. This review provides an overview of the methods of economic evaluation and examples of where they have been applied to pharmacogenomics. We discuss the steps in conducting a cost-effectiveness or cost-benefit analysis, demonstrating these steps using specific examples from the pharmacogenomics literature.

The appointment of a nurse case manager trained in anticoagulation and the development of an automated VTE-risk-assessment tool to identify patients at high risk of VTE were associated with improved adherence to best-practice guidelines for VTE risk assessment and prevention.