Toward a Framework for Benefit-Risk Assessment in Diagnostic Imaging: Identifying Scenario-specific Criteria.

RATIONALE AND OBJECTIVES: Diagnostic imaging has many effects and there is no common definition of value in diagnostic radiology. As benefit-risk trade-offs are rarely made explicit, it is not clear which framework is used in clinical guideline development. We describe initial steps toward the creation of a benefit-risk framework for diagnostic radiology. MATERIALS AND METHODS: We performed a literature search and an online survey of physicians to identify and collect benefit-risk criteria (BRC) relevant to diagnostic imaging tests. We operationalized a process for selection of BRC with the use of four clinical use case scenarios that vary by diagnostic alternatives and clinical indication. Respondent BRC selections were compared across clinical scenarios and between radiologists and nonradiologists. RESULTS: Thirty-six BRC were identified and organized into three domains: (1) those that account for differences attributable only to the test or device (n = 17); (2) those that account for clinical management and provider experiences (n = 12); and (3) those that capture patient experience (n = 7). Forty-eight survey participants selected 22 criteria from the initial list in the survey (9-11 per case). Engaging ordering physicians increased the number of criteria selected in each of the four clinical scenarios presented. We developed a process for standardizing selection of BRC in guideline development. CONCLUSION: These results suggest that a process relying on elements of comparative effectiveness and the use of standardized BRC may ensure consistent examination of differences among alternatives by way of making explicit implicit trade-offs that otherwise enter the decision-making space and detract from consistency and transparency. These findings also highlight the need for multidisciplinary teams that include input from ordering physicians.

A proposed approach for quantitative benefit-risk assessment in diagnostic radiology guideline development: the American College of Radiology Appropriateness Criteria Example.

The American College of Radiology develops evidence-based practice guidelines to aid appropriate utilization of radiological procedures. Panel members use expert opinion to weight trade-offs and consensus methods to rate appropriateness of imaging tests. These ratings include an equivocal range, assigned when there is disagreement about a technology's appropriateness and the evidence base is weak or for special circumstances. It is not clear how expert consensus merges with the evidence base to arrive at an equivocal rating. Quantitative benefit-risk assessment (QBRA) methods may assist decision makers in this capacity. However, many methods exist and it is not clear which methods are best suited for this application. We perform a critical appraisal of QBRA methods and propose several steps that may aid in making transparent areas of weak evidence and barriers to consensus in guideline development. We identify QBRA methods with potential to facilitate decision making in guideline development and build a decision aid for selecting among these methods. This study identified 2 families of QBRA methods suited to guideline development when expert opinion is expected to contribute substantially to decision making. Key steps to deciding among QBRA methods involve identifying specific benefit-risk criteria and developing a state-of-evidence matrix. For equivocal ratings assigned for reasons other than disagreement or weak evidence base, QBRA may not be needed. In the presence of disagreement but the absence of a weak evidence base, multicriteria decision analysis approaches are recommended; and in the presence of weak evidence base and the absence of disagreement, incremental net health benefit alone or combined with multicriteria decision analysis is recommended. Our critical appraisal further extends investigation of the strengths and limitations of select QBRA methods in facilitating diagnostic radiology clinical guideline development. The process of using the decision aid exposes and makes transparent areas of weak evidence and barriers to consensus.

Transforming Healthcare Delivery: Integrating Dynamic Simulation Modelling and Big Data in Health Economics and Outcomes Research.

In the era of the Information Age and personalized medicine, healthcare delivery systems need to be efficient and patient-centred. The health system must be responsive to individual patient choices and preferences about their care, while considering the system consequences. While dynamic simulation modelling (DSM) and big data share characteristics, they present distinct and complementary value in healthcare. Big data and DSM are synergistic-big data offer support to enhance the application of dynamic models, but DSM also can greatly enhance the value conferred by big data. Big data can inform patient-centred care with its high velocity, volume, and variety (the three Vs) over traditional data analytics; however, big data are not sufficient to extract meaningful insights to inform approaches to improve healthcare delivery. DSM can serve as a natural bridge between the wealth of evidence offered by big data and informed decision making as a means of faster, deeper, more consistent learning from that evidence. We discuss the synergies between big data and DSM, practical considerations and challenges, and how integrating big data and DSM can be useful to decision makers to address complex, systemic health economics and outcomes questions and to transform healthcare delivery.

Applying dynamic simulation modeling methods in health care delivery research-the SIMULATE checklist: report of the ISPOR simulation modeling emerging good practices task force.

Health care delivery systems are inherently complex, consisting of multiple tiers of interdependent subsystems and processes that are adaptive to changes in the environment and behave in a nonlinear fashion. Traditional health technology assessment and modeling methods often neglect the wider health system impacts that can be critical for achieving desired health system goals and are often of limited usefulness when applied to complex health systems. Researchers and health care decision makers can either underestimate or fail to consider the interactions among the people, processes, technology, and facility designs. Health care delivery system interventions need to incorporate the dynamics and complexities of the health care system context in which the intervention is delivered. This report provides an overview of common dynamic simulation modeling methods and examples of health care system interventions in which such methods could be useful. Three dynamic simulation modeling methods are presented to evaluate system interventions for health care delivery: system dynamics, discrete event simulation, and agent-based modeling. In contrast to conventional evaluations, a dynamic systems approach incorporates the complexity of the system and anticipates the upstream and downstream consequences of changes in complex health care delivery systems. This report assists researchers and decision makers in deciding whether these simulation methods are appropriate to address specific health system problems through an eight-point checklist referred to as the SIMULATE (System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence) tool. It is a primer for researchers and decision makers working in health care delivery and implementation sciences who face complex challenges in delivering effective and efficient care that can be addressed with system interventions. On reviewing this report, the readers should be able to identify whether these simulation modeling methods are appropriate to answer the problem they are addressing and to recognize the differences of these methods from other modeling approaches used typically in health technology assessment applications.

Innovation in diagnostic imaging services: assessing the potential for value-based reimbursement.

Innovation in the field of diagnostic imaging is based primarily on the availability of new and improved equipment that opens the door for new clinical applications. Payments for these imaging procedures are subject to complex Medicare price control schemes, affecting incentives for appropriate use and innovation. Achieving a "dynamically efficient" health care system-one that elicits a socially optimal amount of innovation-requires that innovators be rewarded in relation to the value they add and can demonstrate with evidence. The authors examine how and whether value-based reimbursement for diagnostic imaging services might better reward innovation explicitly for expected improvements in health and economic outcomes.

Optimizing CAD diagnosis in China with CT angiography.

BACKGROUND: Diagnosis of coronary artery disease (CAD) in China with coronary angiography (CA) can be challenging because of high disease prevalence and limited resources. Coronary computed tomography angiography (CTA) may provide an opportunity to minimize invasive diagnostic procedures among intermediate-risk patients indicated for CA and increase patient access to diagnosis of CAD in a cost-effective manner. OBJECTIVE: This study was conducted to evaluate the potential costs and efficiency of using CTA in combination with CA to optimize diagnosis and care of patients with suspected CAD in China. METHODS: We conducted a cost-consequences analysis from the perspective of Fuwai Hospital in Beijing. We developed a decision-analytic model that compared a diagnostic strategy of CA only with a strategy of CTA in combination with CA for patients with intermediate pretest probability of significant CAD and indicated for CA. RESULTS: In the base-case analysis, use of CTA in combination with CA led to a cost-savings of US $597 per patient evaluated compared with the CA-only diagnostic strategy. The hospital cost per angiography-confirmed diagnosis of CAD was US $8,103 for CTA followed by CA compared with US $9,148 for CA only. The unit cost of CA, and CTA sensitivity were the most influential parameters on the results. The range of cost savings associated with use of CTA followed by CA was US $768 - US $461 per patient over a CAD prevalence range of 14% - 59%. CONCLUSION: The results of our study suggest that CTA implementation in China for intermediate-risk patients indicated for CA may optimize the patient population that undergoes invasive CA procedures and may provide cost savings for Chinese hospitals.

A cost-effectiveness analysis of antibiotic therapy in macrolide-resistant community-acquired pneumonia.

Successful treatment of community-acquired pneumonia (CAP) can have substantial implications. As rates of antibiotic resistance of Streptococcus pneumoniae--the most common pathogen of CAP-increase, so does the likelihood that first-line pharmacotherapy will fail. Thus, the cost effectiveness and budgetary effects of treating CAP with amoxicillin/ clavulanate (AMX/CLA) extended-release (ER) and clarithromycin ER were analyzed. The model considers incidence of macrolide and AMX/ CLA-susceptible and nonsusceptible S. pneumoniae in empiric therapy. Clinical cure rates from multicenter clinical trials and published literature were used to calculate average treatment costs and success. Amoxicillin/ clavulanate ER resulted in a higher percentage of patients cured compared with clarithromycin ER (88.7% vs. 82.4%, respectively) and lower average per-patient treatment costs (dollar 437.70 vs. dollar 548.14, respectively).

Health economic evaluation of non-melanoma skin cancer and actinic keratosis.

Non-melanoma skin cancer (NMSC) and actinic keratosis are becoming an increasingly important healthcare problem. There are approximately 1 million cases of NMSC in the US each year, primarily basal cell carcinomas, and the incidence is increasing. Although NMSC is significant in terms of both health risk and the resource implications for treatment within healthcare systems, our understanding of the health economics of NMSC is limited. The purpose of this article was to systematically review and assess published health economic studies of the treatment of NMSC and actinic keratosis, taking into consideration key aspects of guidelines set by drug purchasers and key reimbursement agencies, and to provide recommendations for appropriate modelling approaches and data collection for health economic studies of NMSC and actinic keratosis. We systematically reviewed the published literature from 1965 to 2003 for health economic evaluations of treatments of NMSC and actinic keratosis using the search terms: ('skin cancer' or 'non melanoma skin cancer' or 'basal cell carcinoma' or 'actinic keratosis') and ('decision model' or 'decision theoretic' or 'decision analytic' or 'health economic' or 'cost effective'). Studies using one of the following methodologies were included: cost-effectiveness, cost-benefit, cost-utility, cost-minimisation, cost-of-illness, cost-consequence, and treatment cost analysis. We identified eight studies evaluating NMSC. One of these studies also evaluated actinic keratosis. Although several studies satisfied some of the basic requirements of health economic evaluations, the majority had serious shortcomings that limit their usefulness. There are a few high-quality health economic evaluations assessing treatments for NMSC or actinic keratosis. However, our analysis suggests that additional data on treatment practice patterns and epidemiology need to be collected, and incorporated with efficacy and safety data in a formal decision-analytic framework to assist decision makers in allocating scarce healthcare resources.

The workplace impact of acute exacerbations of chronic bronchitis (AECB); A literature review.

Acute exacerbations of chronic bronchitis (AECB) are known to have a substantial economic burden in terms of medical care costs. The objective of this study was to assess workplace-based costs associated with AECB, including absenteeism and decreased productivity, based on a review of published literature. A secondary goal was to identify factors related to workplace-based costs in AECB. A literature search was conducted to identify relevant articles assessing one or more aspects of work loss or workplace costs among patients with chronic bronchitis. A review of the identified literature indicates that patients with chronic bronchitis had more days off work; patients whose exacerbations were treated were less likely to have additional exacerbations and had comparatively less work loss. Findings suggest that clinical outcomes and workplace costs are related. While this relationship is clearer in terms of work loss, further exploration is needed to assess decreased productivity and to evaluate this relationship using objective indicators of absenteeism and productivity rather than recall.

The economic impact of acute exacerbations of chronic bronchitis in the United States and Canada: a literature review.

BACKGROUND: Acute exacerbations of chronic bronchitis (AECB) are recurrent and potentially severe medical events for the 13 million people in the United States who have chronic bronchitis. Medical resource use associated with AECB can have a substantial economic impact on the patients, health care system, and society overall. OBJECTIVE: To evaluate literature on the economic impact of AECB in terms of cost of illness, cost of treatments, and cost-effectiveness. METHODS: A MEDLINE literature search was conducted for studies of chronic bronchitis and costs. Reference lists of identified articles were also retrieved for review. RESULTS: Eight published studies were identified: 2 cost-of-illness studies, 1 comparative cost study, and 5 cost-effectiveness studies. Important drivers of costs associated with AECB include hospitalization and choice of antibiotics. In mild to moderate AECB, patient adherence with therapy is essential to consider when selecting treatment. The antibiotic with the lowest acquisition cost has not been shown to be the most cost effective, as adherence and clinical outcomes, particularly rehospitalization rates, differ. CONCLUSION: Further research in these areas is needed to guide clinical decision making and the conduct of disease management programs.

Managed care in the genomics era: assessing the cost effectiveness of genetic tests.

BACKGROUND: Despite the fact that the Human Genome Project was completed only recently, genetic tests already have entered the marketplace, some with few or no long-term data to support their use. Managed care organizations will face reimbursement decisions for genetic tests on a growing scale, and they should have a framework in place to evaluate the clinical and economic outcomes of this new class of diagnostics. OBJECTIVE: To develop a set of criteria that could assist decision makers in evaluating the cost effectiveness of genetic testing. METHODS: A literature review was conducted of marketed genetic tests and criteria used to evaluate the clinical and economic benefits of genetic testing. Criteria were developed and pilot-tested on currently available genetic tests in colon cancer, periodontitis, acute lymphoblastic leukemia, and anticoagulation. RESULTS: A robust cost-effectiveness analysis requires data demonstrating (1) genotype-phenotype association; (2) genetic variant prevalence; (3) clinical outcome severity and incidence; (4) interventions for the variant group; and (5) sensitivity, specificity, and timing of the assay result. In addition, calculating the number of patients who need to be screened based on the above factors is useful for evaluating genetic tests. CONCLUSIONS: When evaluating a genetic test for reimbursement, these criteria can help to: (1) quantify the potential clinical benefit and economic savings; (2) assess the robustness of a cost-effectiveness analysis; and (3) clarify areas where data are deficient. These criteria should be used to inform the decision-making process in the context of ethical, legal, and social issues related to genetic testing.

The cost-effectiveness of interleukin-1 genetic testing for periodontal disease.

BACKGROUND: A genetic test for a composite interleukin-1 (IL-1) genotype is being marketed to predict risk for progression of periodontal disease. The objective of this study was to determine the clinical scenario required to produce cost-effective results with the use of IL-1 testing to identify high-risk patients. METHODS: A disease simulation model was developed using decision-analytic techniques and a 30-year time frame. RESULTS: Using different modeling scenarios, the genetic test produced results ranging from cost savings of $830,140 and 52.8 fewer cases of severe periodontitis to increased costs of $300,430 and 3.6 additional cases of severe periodontitis (per 1,000 patients). Three parameters in the analysis were highly influential: 1) the compliance rate for maintenance therapy in test positive versus non-tested patients; 2) the effectiveness of non-surgical therapy; and 3) the relative risk of disease progression for test positive patients. CONCLUSION: The model produced a wide range of outcomes reflecting our incomplete understanding of the biology, optimal treatment, and genetic susceptibility of periodontal diseases. However, the model demonstrates that three clinical parameters are highly influential in determining if IL-1 testing can be implemented in a primary care setting in a cost-effective manner.