Incorporating quality of evidence into decision analytic modeling

Empirical Development of a Behavioral Intervention for African American/Black and Latino Persons with Unsuppressed HIV Viral Load Levels: An Application of the Multiphase Optimization Strategy (MOST) Using Cost-Effectiveness as an Optimization Objective

We used results from an optimization randomized controlled trial which tested five behavioral intervention components to support HIV antiretroviral adherence/HIV viral suppression, grounded in the multiphase optimization strategy and using a fractional factorial design to identify intervention components with cost-effectiveness sufficiently favorable for scalability. Results were incorporated into a validated HIV computer simulation to simulate longer-term effects of combinations of components on health and costs. We simulated the 32 corresponding long-term trajectories for viral load suppression, health related quality of life (HRQoL), and costs. The components were designed to be culturally and structurally salient. They were: motivational interviewing counseling sessions (MI), pre-adherence skill building (SB), peer mentorship (PM), focused support groups (SG), and patient navigation (short version [NS], long version [NL]. All participants also received health education on HIV treatment. We examined four scenarios: one-time intervention with and without discounting and continuous interventions with and without discounting. In all four scenarios, interventions that comprise or include SB and NL (and including health education) were cost effective (< $100,000/quality-adjusted life year). Further, with consideration of HRQoL impact, maximal intervention became cost-effective enough to be scalable. Thus, a fractional factorial experiment coupled with cost-effectiveness analysis is a promising approach to optimize multi-component interventions for scalability. The present study can guide service planning efforts for HIV care settings and health departments.

Measuring Population Health in a Large Integrated Health System to Guide Goal Setting and Resource Allocation: A Proof of Concept

In integrated health care systems, techniques that identify successes and opportunities for targeted improvement are needed. The authors propose a new method for estimating population health that provides a more accurate and dynamic assessment of performance and priority setting. Member data from a large integrated health system (n = 96,246, 73.8% female, mean age = 44 ± 0.01 years) were used to develop a mechanistic mathematical simulation, representing the top causes of US mortality in 2014 and their associated risk factors. An age- and sex-matched US cohort served as comparator group. The simulation was recalibrated and retested for validity employing the outcome measure of 5-year mortality. The authors sought to estimate potential population health that could be gained by improving health risk factors in the study population. Potential gains were assessed using both average life years (LY) gained and average quality-adjusted life years (QALYs) gained. The simulation validated well compared to integrated health system data, producing an AUC (area under the curve) of 0.88 for 5-year mortality. Current population health was estimated as a life expectancy of 84.7 years or 69.2 QALYs. Comparing potential health gain in the US cohort to the Kaiser Permanente cohort, eliminating physical inactivity, unhealthy diet, smoking, and uncontrolled diabetes resulted in an increase of 1.5 vs. 1.3 LY, 1.1 vs. 0.8 LY, 0.5 vs. 0.2 LY, and 0.5 vs. 0.5 LY on average per person, respectively. Using mathematical simulations may inform efforts by integrated health systems to target resources most effectively, and may facilitate goal setting.

Betting on the fastest horse: Using computer simulation to design a combination HIV intervention for future projects in Maharashtra, India

Objective

To inform the design of a combination intervention strategy targeting HIV-infected unhealthy alcohol users in Maharashtra, India, that could be tested in future randomized control trials.

Methods

Using probabilistic compartmental simulation modeling we compared intervention strategies targeting HIV-infected unhealthy alcohol users on antiretroviral therapy (ART) in Maharashtra, India. We tested interventions targeting four behaviors (unhealthy alcohol consumption, risky sexual behavior, depression and antiretroviral adherence), in three formats (individual, group based, community) and two durations (shorter versus longer). A total of 5,386 possible intervention combinations were tested across the population for a 20-year time horizon and intervention bundles were narrowed down based on incremental cost-effectiveness analysis using a two-step probabilistic uncertainty analysis approach.

Results

Taking into account uncertainty in transmission variables and intervention cost and effectiveness values, we were able to reduce the number of possible intervention combinations to be used in a randomized control trial from over 5,000 to less than 5. The most robust intervention bundle identified was a combination of three interventions: long individual alcohol counseling; weekly Short Message Service (SMS) adherence counseling; and brief sex risk group counseling.

Conclusions

In addition to guiding policy design, simulation modeling of HIV transmission can be used as a preparatory step to trial design, offering a method for intervention pre-selection at a reduced cost.

Using the multiphase optimization strategy (MOST) to optimize an HIV care continuum intervention for vulnerable populations: a study protocol

BACKGROUND

More than half of persons living with HIV (PLWH) in the United States are insufficiently engaged in HIV primary care and not taking antiretroviral therapy (ART), mainly African Americans/Blacks and Hispanics. In the proposed project, a potent and innovative research methodology, the multiphase optimization strategy (MOST), will be employed to develop a highly efficacious, efficient, scalable, and cost-effective intervention to increase engagement along the HIV care continuum. Whereas randomized controlled trials are valuable for evaluating the efficacy of multi-component interventions as a package, they are not designed to evaluate which specific components contribute to efficacy. MOST, a pioneering, engineering-inspired framework, addresses this problem through highly efficient randomized experimentation to assess the performance of individual intervention components and their interactions. We propose to use MOST to engineer an intervention to increase engagement along the HIV care continuum for African American/Black and Hispanic PLWH not well engaged in care and not taking ART. Further, the intervention will be optimized for cost-effectiveness. A similar set of multi-level factors impede both HIV care and ART initiation for African American/Black and Hispanic PLWH, primary among them individual- (e.g., substance use, distrust, fear), social- (e.g., stigma), and structural-level barriers (e.g., difficulties accessing ancillary services). Guided by a multi-level social cognitive theory, and using the motivational interviewing approach, the study will evaluate five distinct culturally based intervention components (i.e., counseling sessions, pre-adherence preparation, support groups, peer mentorship, and patient navigation), each designed to address a specific barrier to HIV care and ART initiation. These components are well-grounded in the empirical literature and were found acceptable, feasible, and promising with respect to efficacy in a preliminary study.

METHODS/DESIGN

Study aims are: 1) using a highly efficient fractional factorial experimental design, identify which of five intervention components contribute meaningfully to improvement in HIV viral suppression, and secondary outcomes of ART adherence and engagement in HIV primary care; 2) identify mediators and moderators of intervention component efficacy; and 3) using a mathematical modeling approach, build the most cost-effective and efficient intervention package from the efficacious components. A heterogeneous sample of African American/Black and Hispanic PLWH (with respect to age, substance use, and sexual minority status) will be recruited with a proven hybrid sampling method using targeted sampling in community settings and peer recruitment (N = 512).

DISCUSSION

This is the first study to apply the MOST framework in the field of HIV prevention and treatment. This innovative study will produce a culturally based HIV care continuum intervention for the nation's most vulnerable PLWH, optimized for cost-effectiveness, and with exceptional levels of efficacy, efficiency, and scalability.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT02801747 , Registered June 8, 2016.

Methods to construct a step-by-step beginner's guide to decision analytic cost-effectiveness modeling

BACKGROUND

Although guidance on good research practice in health economic modeling is widely available, there is still a need for a simpler instructive resource which could guide a beginner modeler alongside modeling for the first time.

AIM

To develop a beginner's guide to be used as a handheld guide contemporaneous to the model development process.

METHODS

A systematic review of best practice guidelines was used to construct a framework of steps undertaken during the model development process. Focused methods review supplemented this framework. Consensus was obtained among a group of model developers to review and finalize the content of the preliminary beginner's guide. The final beginner's guide was used to develop cost-effectiveness models.

RESULTS

Thirty-two best practice guidelines were data extracted, synthesized, and critically evaluated to identify steps for model development, which formed a framework for the beginner's guide. Within five phases of model development, eight broad submethods were identified and 19 methodological reviews were conducted to develop the content of the draft beginner's guide. Two rounds of consensus agreement were undertaken to reach agreement on the final beginner's guide. To assess fitness for purpose (ease of use and completeness), models were developed independently and by the researcher using the beginner's guide.

CONCLUSION

A combination of systematic review, methods reviews, consensus agreement, and validation was used to construct a step-by-step beginner's guide for developing decision analytical cost-effectiveness models. The final beginner's guide is a step-by-step resource to accompany the model development process from understanding the problem to be modeled, model conceptualization, model implementation, and model checking through to reporting of the model results.

Designing Radiology Outcomes Studies-Essential Principles

Health outcomes research is essential to align radiology with current standards of high-value patient care, through the assessment of end results of diagnostic tests, interventions, or policy on patient health. To bridge studies of diagnostic test accuracy and health outcomes research, key considerations include: (1) how to determine when a diagnostic test merits evaluation of impact on outcomes, (2) when study of intermediate/surrogate outcomes can be useful, (3) how to consider the possible harms as well as potential benefits of a test, and (4) how to integrate evidence of an imaging test's efficacy/effectiveness with clinical data to assess outcomes. Due to challenges in conducting studies of long-term outcomes consequent to imaging use, intermediate health outcomes may capture a test's impact on successful diagnosis and therapy, and can provide readily measurable, incremental insights into the role of imaging in health-care delivery and efficiency. In an era marked by recognition of quality and value of care, outcomes research will provide essential evidence to inform radiologists' guidance of imaging use toward improved patient care, creation of clinical guidelines, and policy decisions.

Cost Effectiveness of HIV Prevention Interventions in the U.S

INTRODUCTION

The purpose of this study was to assess and compare the cost effectiveness of current HIV prevention interventions in the U.S. using a consistent, standardized methodology.

METHODS

The cost effectiveness of common and emerging HIV biomedical and behavioral prevention interventions as delivered to men who have sex with men, injection drug users, and sexually active heterosexuals was estimated. Data on program costs, intervention efficacy, risk behaviors, and per contact transmission probabilities were collected from peer-reviewed papers and health department reports. These data were combined with 2010 national HIV incidence and prevalence surveillance data in a Bernoulli process model to estimate the reduced annual risk of HIV transmission or acquisition associated with these interventions. The cost per prevented case of HIV and the cost per saved quality-adjusted life year were then calculated. Analyses were conducted between 2014 and 2015.

RESULTS

Interventions to diagnose HIV and provide ongoing care and treatment had the lowest cost per prevented case. Among interventions targeted at specific risk groups, interventions for men who have sex with men were the most cost effective. The least cost-effective interventions typically addressed people at risk of acquiring HIV rather than those at risk of transmitting the disease.

CONCLUSIONS

HIV prevention interventions targeted at high-risk populations, those associated with the care continuum, and those that reduce the transmission risk of HIV-infected people are typically the most cost effective. Decision makers can consider these results in planning an efficient allocation of HIV prevention resources.

Depression in working adults: comparing the costs and health outcomes of working when ill

Objective

Working through a depressive illness can improve mental health but also carries risks and costs from reduced concentration, fatigue, and poor on-the-job performance. However, evidence-based recommendations for managing work attendance decisions, which benefit individuals and employers, are lacking. Therefore, this study has compared the costs and health outcomes of short-term absenteeism versus working while ill (“presenteeism”) amongst employed Australians reporting lifetime major depression.

Methods

Cohort simulation using state-transition Markov models simulated movement of a hypothetical cohort of workers, reporting lifetime major depression, between health states over one- and five-years according to probabilities derived from a quality epidemiological data source and existing clinical literature. Model outcomes were health service and employment-related costs, and quality-adjusted-life-years (QALYs), captured for absenteeism relative to presenteeism, and stratified by occupation (blue versus white-collar).

Results

Per employee with depression, absenteeism produced higher mean costs than presenteeism over one- and five-years ($42,573/5-years for absenteeism, $37,791/5-years for presenteeism). However, overlapping confidence intervals rendered differences non-significant. Employment-related costs (lost productive time, job turnover), and antidepressant medication and service use costs of absenteeism and presenteeism were significantly higher for white-collar workers. Health outcomes differed for absenteeism versus presenteeism amongst white-collar workers only.

Conclusions

Costs and health outcomes for absenteeism and presenteeism were not significantly different; service use costs excepted. Significant variation by occupation type was identified. These findings provide the first occupation-specific cost evidence which can be used by clinicians, employees, and employers to review their management of depression-related work attendance, and may suggest encouraging employees to continue working is warranted.

Averting HIV infections in New York City: a modeling approach estimating the future impact of additional behavioral and biomedical HIV prevention strategies

Background

New York City (NYC) remains an epicenter of the HIV epidemic in the United States. Given the variety of evidence-based HIV prevention strategies available and the significant resources required to implement each of them, comparative studies are needed to identify how to maximize the number of HIV cases prevented most economically.

Methods

A new model of HIV disease transmission was developed integrating information from a previously validated micro-simulation HIV disease progression model. Specification and parameterization of the model and its inputs, including the intervention portfolio, intervention effects and costs were conducted through a collaborative process between the academic modeling team and the NYC Department of Health and Mental Hygiene. The model projects the impact of different prevention strategies, or portfolios of prevention strategies, on the HIV epidemic in NYC.

Results

Ten unique interventions were able to provide a prevention benefit at an annual program cost of less than $360,000, the threshold for consideration as a cost-saving intervention (because of offsets by future HIV treatment costs averted). An optimized portfolio of these specific interventions could result in up to a 34% reduction in new HIV infections over the next 20 years. The cost-per-infection averted of the portfolio was estimated to be $106,378; the total cost was in excess of $2 billion (over the 20 year period, or approximately $100 million per year, on average). The cost-savings of prevented infections was estimated at more than $5 billion (or approximately $250 million per year, on average).

Conclusions

Optimal implementation of a portfolio of evidence-based interventions can have a substantial, favorable impact on the ongoing HIV epidemic in NYC and provide future cost-saving despite significant initial costs.

Cost-effectiveness of adherence interventions for highly active antiretroviral therapy: a systematic review

OBJECTIVES

The objective of this systematic review was to evaluate the cost-effectiveness of interventions aiming to increase the adherence to highly active antiretroviral therapy (HAART) in HIV-infected patients in developed countries (WHO stratum A).

METHODS

A systematic search for comparative health economic studies was conducted in the following databases: EMBASE, MEDLINE, NHS Economic Evaluation Database, CINAHL, HEED, and EconLit. The identified publications were selected by two reviewers independently according to predefined inclusion and exclusion criteria. Furthermore, these were evaluated according to a standardized checklist and finally extracted, analyzed, and summarized.

RESULTS

After reviewing the abstracts and full texts four relevant studies were identified. Different educational programs were compared as well as the Directly Observed Therapy (DOT). A critical aspect to be considered in particular was the poor transparency of the cost data. In three cost-utility analyses the costs per quality-adjusted life-year (QALY) in the baseline scenario were each under USD 15,000. The sensitivity analyses with a presumed maximum threshold of USD 50,000/QALY showed a predominantly cost-effective result. In one study that examined DOT the costs add up to over USD 150,000/QALY.

CONCLUSIONS

It seems that adherence interventions for HAART in HIV-infected patients can be cost-effective. Nevertheless, the quality of the included studies is deficient and only a few of the possible adherence interventions are taken into consideration. A final assessment of the cost-effectiveness of adherence interventions in general is, therefore, not possible.

Adding decision models to systematic reviews: informing a framework for deciding when and how to do so

OBJECTIVE

Decision models are sometimes used alongside systematic reviews to synthesize evidence. Clarity, however, is lacking about when and how to conduct modeling studies in tandem with systematic reviews, as well as about how to evaluate and present model results. The objective of this study was to collect and analyze information from various sources to inform the development of a framework for deciding when and how a decision model should be added to a systematic review.

METHODS

We collected data through 1) review and analysis of evidence reports that used decision models; 2) review and synthesis of current best practices for the development of decision models; 3) interviews of Evidence-Based Practice Center directors and selected staff, United States Preventive Services Task Force members, and decision modelers who developed models used by the United States Preventive Services Task Force; and 4) a focus group of expert modelers.

RESULTS

Models are well suited to address gaps in the literature, better suited for certain types of research questions, and essential for determining the value of information relating to future research. Opinions differ regarding whether model outputs constitute evidence, but interviewees expressed concern over the lack of standards and directions in grading and reporting such "evidence." Interviews of stakeholders and modelers revealed the importance of communication and presentation of model results as well as the importance of model literacy and involvement of stakeholders.

CONCLUSIONS

The study demonstrates the need for a framework for deciding when and how to use models alongside systematic reviews and provides information to develop such a framework.

Could media reports include a standardized scale for quality of evidence?

While some media reports offer accurate interpretations of clinical research, other reports are misleading. The uneven accuracy of medical reporting may act in concert with its sheer volume to confuse the lay public about which health messages are most important and evidence-based. I outline one possible step towards a solution: medical journals can embed quality of evidence ratings in article summaries and create incentives for inclusion of these ratings in lay media reports.

Economic implications of 21-gene breast cancer risk assay from the perspective of an Israeli-managed health-care organization

OBJECTIVE

Oncotype DX, a 21-gene assay, was clinically validated as a predictor of 10-year recurrence-free survival and treatment response in patients with early-stage estrogen-receptor-positive, lymph-node negative breast cancer (ER+ LN- ESBC). This study determined "real-life" alteration in treatment decision and economic implications of Oncotype DX use in women with ER+ LN- ESBC.

METHODS

Clalit Health Services (CHS, Tel Aviv, Israel), determined the proportion of women in low, intermediate and high-risk groups in the first 368 Oncotype DX assays performed, the change of adjuvant therapy recommendation following the recurrence (RS) results from Oncotype DX use, and associated chemotherapy costs. The risk of recurrence-free survival was derived from prespecified statistical protocols of NCI-sponsored trials conducted by NSABP (B-14 and B-20). Utilities were literature based. A 3% discount rate was employed.

RESULTS

Oncotype DX altered recommendations of 40% of patients, 84% of whom were changed from hormone + chemotherapy to hormonal therapy alone. Among high-risk women, 8% switched actual treatment from hormonal therapy to hormone + chemotherapy. By reducing the chemotherapy disutility, quality-adjusted life-years (QALY) increased 0.170 years. Use of Oncotype DX costs $10,770 per QALY gained. Sensitivity analyses revealed that risk reduction in the low-risk population, the cost of adverse events, and the relative risk reduction of recurrence were the most influential variables.

CONCLUSION

Oncotype DX resulted in net QALY gain and increased overall costs, with an incremental cost-effectiveness ratio of $10,770. For CHS, Oncotype DX represents an effective and affordable approach to favorably affect the lives of women with ESBC.

Can broader diffusion of value-based insurance design increase benefits from US health care without increasing costs? Evidence from a computer simulation model

BACKGROUND

Evidence suggests that cost sharing (i.e.,copayments and deductibles) decreases health expenditures but also reduces essential care. Value-based insurance design (VBID) has been proposed to encourage essential care while controlling health expenditures. Our objective was to estimate the impact of broader diffusion of VBID on US health care benefits and costs.

METHODS AND FINDINGS

We used a published computer simulation of costs and life expectancy gains from US health care to estimate the impact of broader diffusion of VBID. Two scenarios were analyzed: (1) applying VBID solely to pharmacy benefits and (2) applying VBID to both pharmacy benefits and other health care services (e.g., devices). We assumed that cost sharing would be eliminated for high-value services (<$100,000 per life-year), would remain unchanged for intermediate- or unknown-value services ($100,000-$300,000 per life-year or unknown), and would be increased for low-value services (>$300,000 per life-year). All costs are provided in 2003 US dollars. Our simulation estimated that approximately 60% of health expenditures in the US are spent on low-value services, 20% are spent on intermediate-value services, and 20% are spent on high-value services. Correspondingly, the vast majority (80%) of health expenditures would have cost sharing that is impacted by VBID. With prevailing patterns of cost sharing, health care conferred 4.70 life-years at a per-capita annual expenditure of US$5,688. Broader diffusion of VBID to pharmaceuticals increased the benefit conferred by health care by 0.03 to 0.05 additional life-years, without increasing costs and without increasing out-of-pocket payments. Broader diffusion of VBID to other health care services could increase the benefit conferred by health care by 0.24 to 0.44 additional life-years, also without increasing costs and without increasing overall out-of-pocket payments. Among those without health insurance, using cost saving from VBID to subsidize insurance coverage would increase the benefit conferred by health care by 1.21 life-years, a 31% increase.

CONCLUSION

Broader diffusion of VBID may amplify benefits from US health care without increasing health expenditures.

The policy debate over public investment in comparative effectiveness research

BACKGROUND

Policy makers across the political spectrum, as well as many clinicians and physician professional associations, have proposed that better information on comparative clinical effectiveness should be a key element of any solution to the US health-care cost crisis. This superficial consensus hides intense disagreements over critical issues essential to any new public effort to promote more comparative effectiveness research (CER).

METHODS AND RESULTS

This article reviews the background for these disputes, summarizes the different perspectives represented by policy makers and advocates, and offers a framework to aid both practicing and academic internists in understanding the key elements of the emerging debate. Regarding the fundamental question of "what is CER," disagreements rage over whether value or cost effectiveness should be a consideration, and how specific patient perspectives should be reflected in the development and the use of such research. The question of how to pay for CER invokes controversies over the role of the market in producing such information and the private (e.g., insurers and employers) versus public responsibility for its production. The financing debate further highlights the high stakes of comparative effectiveness research, and the risks of stakeholder interests subverting any public process. Accordingly there are a range of proposals for the federal government's role in prioritization, development, and dissemination of CER.

CONCLUSION

The internal medicine community, with its long history of commitment to scientific medical practice and its leadership in evidence-based medicine, should have a strong interest and play an active role in this debate.

Economic evaluation of rituximab plus cyclophosphamide, vincristine and prednisolone for advanced follicular lymphoma

The addition of rituximab to cyclophosphamide, vincristine and prednisolone (CVP) for advanced follicular lymphoma increases median time to progression by 17 months. A US societal cost-effectiveness of R-CVP versus CVP is estimated for a representative 50-year-old patient. Progression-free survival (PFS) and overall survival are based on a randomized Phase III trial. Costs are estimated using Medicare reimbursement rates and published drug price data, and include drug and administration costs, adverse events, treatment of relapses, and end-of-life care. Utility estimates are derived from the literature and a 3% discount rate is employed. Mean overall survival is projected to be 1.51 years longer for patients assigned to R-CVP versus CVP. The cost per quality-adjusted year of life gained is $28,565. The utility associated with stable or progressive disease and the unit drug cost of rituximab most influence the findings. The cost-effectiveness ratio of R-CVP compared with CVP is projected to be cost-effective in the United States under a range of sensitivity analyses.

Integration of modeling and simulation into hospital-based decision support systems guiding pediatric pharmacotherapy

Background

Decision analysis in hospital-based settings is becoming more common place. The application of modeling and simulation approaches has likewise become more prevalent in order to support decision analytics. With respect to clinical decision making at the level of the patient, modeling and simulation approaches have been used to study and forecast treatment options, examine and rate caregiver performance and assign resources (staffing, beds, patient throughput). There us a great need to facilitate pharmacotherapeutic decision making in pediatrics given the often limited data available to guide dosing and manage patient response. We have employed nonlinear mixed effect models and Bayesian forecasting algorithms coupled with data summary and visualization tools to create drug-specific decision support systems that utilize individualized patient data from our electronic medical records systems.

Methods

Pharmacokinetic and pharmacodynamic nonlinear mixed-effect models of specific drugs are generated based on historical data in relevant pediatric populations or from adults when no pediatric data is available. These models are re-executed with individual patient data allowing for patient-specific guidance via a Bayesian forecasting approach. The models are called and executed in an interactive manner through our web-based dashboard environment which interfaces to the hospital's electronic medical records system.

Results

The methotrexate dashboard utilizes a two-compartment, population-based, PK mixed-effect model to project patient response to specific dosing events. Projected plasma concentrations are viewable against protocol-specific nomograms to provide dosing guidance for potential rescue therapy with leucovorin. These data are also viewable against common biomarkers used to assess patient safety (e.g., vital signs and plasma creatinine levels). As additional data become available via therapeutic drug monitoring, the model is re-executed and projections are revised.

Conclusion

The management of pediatric pharmacotherapy can be greatly enhanced via the immediate feedback provided by decision analytics which incorporate the current, best-available knowledge pertaining to dose-exposure and exposure-response relationships, especially for narrow therapeutic agents that are difficult to manage.

A cost-utility comparison of four first-line medications in painful diabetic neuropathy

BACKGROUND

Painful diabetic neuropathy is common and adversely affects patients' quality of life and function. Several treatment options exist, but their relative efficacy and value are unknown.

OBJECTIVE

To determine the relative efficacy, costs and cost effectiveness of the first-line treatment options for painful diabetic neuropathy.

METHODS

Published and unpublished clinical trial and cross-sectional data were incorporated into a decision analytic model to estimate the net health and cost consequences of treatment for painful diabetic peripheral neuropathy over 3-month (base case), 1-month and 6-month timeframes. Efficacy was measured in QALYs, and costs were measured in $US, year 2006 values, using a US third-party payer perspective. The patients included in the model were outpatients with moderate to severe pain associated with diabetic peripheral neuropathy and no contraindications to treatment with tricyclic antidepressants. Four medications were compared: desipramine 100 mg/day, gabapentin 2400 mg/day, pregabalin 300 mg/day and duloxetine 60 mg/day.

RESULTS

Desipramine and duloxetine were both more effective and less expensive than gabapentin and pregabalin in the base-case analysis and through a wide range of sensitivity analyses. Duloxetine offered borderline value compared with desipramine in the base case ($US47,700 per QALY), but not when incorporating baseline-observation-carried-forward analyses of the clinical trial data ($US867,000 per QALY). The results were also sensitive to the probability of obtaining pain relief with duloxetine.

CONCLUSIONS

Desipramine (100 mg/day) and duloxetine (60 mg/day) appear to be more cost effective than gabapentin or pregabalin for treating painful diabetic neuropathy. The estimated value of duloxetine relative to desipramine depends on the assumptions made in the statistical analyses of clinical trial data.

Evidence-based practice in clinical psychology: What it is, why it matters; what you need to know

The history and meaning of evidence-based practice (EBP) in the health disciplines was described to the Council of University Directors of Clinical Psychology (CUDCP) training programs. Evidence-based practice designates a process of clinical decision-making that integrates research evidence, clinical expertise, and patient preferences and characteristics. Evidence-based practice is a transdisciplinary, idiographic approach that promotes lifelong learning. Empirically supported treatments (ESTs) are an important component of EBP, but EBP cannot be reduced to ESTs. Psychologists need additional skills to act as creators, synthesizers, and consumers of research evidence, who act within their scope of clinical expertise and engage patients in shared decision-making. Training needs are identified in the areas of clinical trial methodology and reporting, systematic reviews, search strategies, measuring patient preferences, and acquisition of clinical skills to perform ESTs.