The Impact of Free Trial Acceptance on Demand for Alternative Nicotine Products: Evidence from Experimental Auctions

Objectives: This study explored the relationship between product trials and consumer demand for alternative nicotine products (ANP). Methods: An experimental auction was conducted with 258 adult smokers, wherein participants were randomly assigned to one of four experimental conditions. The participants received the opportunity to try, but did not have to accept, one of three relatively novel ST products (i.e., snus, dissolvable tobacco, or medicinal nicotine), or they were placed into a control group (i.e., no trial). All the participants then bid on all three of these products, as well as on cigarettes. We assessed interest in using ANP based on both trial of the product and bids placed for the products in the experimental auction. Results: Fewer smokers were willing to try snus (44 %) than dissolvable tobacco (64 %) or medicine nicotine (68 %). For snus, we find modest evidence suggesting that willingness to try is associated with greater demand for the product. For dissolvable tobacco or medicinal nicotine, we find no evidence that those who accept the product trial have higher demand for the product. Conclusions: Free trials of a novel ANP were not strongly associated with product demand, as assessed by willingness to pay. Given the debate over the potential for ANP to reduce the harm from smoking, these results are important in understanding the impact of free trial offers on adoption of ST product as a strategy to reduce harm from tobacco use

Comparison of Organizational Context Across HMORN Members

Background/Aims: Organizational context is an important element in implementation science and comparative effectiveness research (CER). Contextual factors include practice, hospital, system and environmental factors that may influence care delivery. For multisystem research networks such as the HMORN, awareness and inclusion of contextual factors can strengthen research design and interpretation of findings. Similarly, consideration of local contextual factors can enhance dissemination and implementation of interventions across systems. To our knowledge a comparative analysis of system-level contextual factors reflecting recent market and policy changes has not been performed for HMORN members. The aim of this study is to describe differences and similarities in seven system-level contextual factors across HMORN delivery systems and discuss their implications for CER and implementation research. Methods: We performed a review of system-level contextual factors representing major policy, market or operational changes from 2004 to 2014. Contextual factors were: 1) accountable care organization (ACO) participation; 2) patient-centered medical home (PCMH) implementation; 3) CMS-CMMI program participation; 4) market consolidation (Mergers & Acquisitions); 5) systemwide adoption of Lean or continuous quality improvement (CQI) programs; 6) Beacon Community Grants; and 7) systemwide population health management program. A manual review of several data sources including HMORN member websites, CMS website, National Committee for Quality Assurance website and Office of the National Coordinator for Health Information technology website. Additional data was attained using a keyword search in industry journals. For each contextual factor we determined a system’s level of participation, start and end dates, and program or consolidation characteristics as applicable. Results: Preliminary results indicate a wide variation across HMORN members in adoption of new models of care and market consolidation. Four members belonged to Beacon communities (health information exchanges). While most systems participated in an ACO, the funding mechanisms varied (Medicare-shared savings or Pioneer program). Systems underwent considerable consolidation, with the largest merger increasing a HMORN member size from 12 to 43 hospitals. Further results are pending. Discussion: System-level contextual factors differ across HMORN members. Our findings draw attention to the relevance of contextual factors and may inform interpretation of results and implementation

Analysis of an Integrated Diabetes Care Program and Impact on Health Outcomes and Utilization

Background/Aims: For the past decade, Geisinger Health System has coordinated care for patients with diabetes using an integrated diabetes care model. This model utilizes the electronic health record to coordinate a program to improve physician adherence to nationally recommended diabetes measures. The aim of this study is to assess which patient level factors are associated with improved health outcomes for patients who receive care in this integrated diabetes program compared to patients with diabetes who receive nonintegrated diabetes care. Methods: Study population consists of Geisinger Health Plan members with diabetes in the year 2013. Geisinger Health Plan is a private nonprofit insurance provider in Pennsylvania. The study examined 1,692 patients with diabetes (866 in the intervention group, 826 in the control group). This cross-sectional study uses survey data matched to administrative claims data to assess factors associated with health outcomes and costs. Chi-squared tests were used to determine whether there is a significant difference between patients with diabetes in an integrated program compared to patients in nonintegrated programs. Results: Mean age of the study population was 67.8 years, and 45.4% were female. There were no significant differences between study cohorts regarding demographic characteristics including smoking and exercise habits. Subjects in the intervention group (i.e. received care in the integrated diabetes program) had statistically significantly higher scores for patient activation and for follow-up care coordination from their respective primary care provider. Subjects in the treatment group were more likely to feel that their doctor listens attentively to them (P = 0.019) as well as more likely to be referred to a diabetes education class (P = 0.001). There were no significant differences on emergency department use by each group. Cost results are pending. Conclusion: Preliminary results show that patients who received care in the integrated diabetes care program score higher on patient activation measures as well as goal setting and follow-up coordination compared to patients who are not within the integrated diabetes program. Subsequent analyses will be conducted to study the relationship between outcomes and health care utilization

A Real-World Approach to a Value-Based Decision-Making Framework for Genetic Testing

Background/Aims: Relatively few genetic tests have been formally evaluated for cost-effectiveness, and many lack widely accepted evidence of clinical utility. Pragmatic approaches are needed to support real-world, value-based decision-making for genomic-based screening and treatment strategies, including patient selection criteria to identify those with greater potential to benefit. The lack of evidentiary standards for clinical implementation as well as evidence gaps are barriers to decision-making for implementation and reimbursement. Value-improving technology impacts clinical decisions by improving patient care without a disproportionate increase in overall costs. Available knowledge about genomic testing and potential concerns can be integrated and applied using a process to assess value for patient care. The objective of this research is to develop a decision-making framework to support implementation of value-improving technology. Satisfying this objective should avoid premature use of tests that provide little benefit or pose significant health risks compared to usual care. Methods: Multicriteria decision analysis (MCDA) provides structure and transparency in evaluating options by considering the relative importance of different criteria using a weighting scheme and information on each option’s performance. The results of the review of health care MCDA methods are synthesized and applied to systematically identify and structure elements of value. We then integrate and evaluate clinical, epidemiological and economic evidence to assess the value of genetic and pharmacogenomic testing to support real-world decision-making. Results: A model with relative weighting for all elements of measured value is developed and applied to facilitate aggregating measures to support real-world decision-making. Current knowledge about genetic and pharmacogenomic testing is integrated and applied to move from the concept of value to making a decision. This is done by measuring and gathering evidence on each of the elements and aggregating the combined elements, with uncertainty of an outcome treated as an element of value. Discussion: Assuming a continuing shortage of formal and direct evidence for genetic testing, transparent consideration of available, including indirect, evidence can be used to assess whether outcomes relative to cost are likely to offer sufficient value in a comprehensible and actionable decision-making framework. This framework offers the potential to reduce barriers to widespread implementation

High-Risk Breast Cancer Clinic –– A New Risk-Stratified, Evidence-Based, and Efficient Patient Care Model

Background/Aims: There is considerable variation in adherence to available evidence-based recommendations for risk assessment, screening, genetic counseling and testing, surveillance and preventive care for women at risk for breast cancer. To improve adherence and patient outcomes and to facilitate appropriate referral to genetic testing, Geisinger implemented a new care model in February 2015 to systematically and efficiently deliver appropriate risk assessment and management services using midlevel providers. This “high-risk breast cancer clinic” provides any interested woman with a personal risk assessment and care plan. Validated risk assessment approaches are used to stratify women into differing risk levels. This new approach focuses on the large moderate-risk (5-year risk ≥ 1.7% and/or lifetime risk ≥ 20%) and average-risk (5-year risk ≤ 1.7%) populations, who comprise the majority of women and who are typically underserved with usual care. It provides them with evidence-based counseling, surveillance and chemoprevention care services. This clinic also serves women with dense breasts (density \u3e 50%, which includes about half of all women) who also are known to be at increased risk for breast cancer. Methods: For women at moderate risk of developing breast cancer, a decision-analysis model compares care, outcomes and costs for the high-risk breast cancer clinic’s approach to usual care. Assumptions for the model are based on Geisinger patient data, literature and expert opinion to develop estimates for clinical and economic outcomes. Results: A decision-analysis model comparing Geisinger’s high-risk breast cancer clinic to usual care is used for a budget impact analysis to show the estimated effects of differences in patient care on outcomes and costs, including benefits of delivering risk-based prevention and treatment at earlier stages to moderate-risk patients. This analysis is used to make a business case for this new care model in an integrated health system. Conclusion: A new targeted care model providing evidence-based evaluation and services to women at moderate and average risk for developing breast cancer offers the potential to improve delivery of appropriate care, patient experience and health outcomes with a favorable impact on cost

Chronic Care Model Strategies In The United States And Germany Deliver Patient-Centered, High-Quality Diabetes Care

Improving the quality of care for chronic diseases is an important issue for most health care systems in industrialized nations. One widely adopted approach is the Chronic Care Model (CCM), which was first developed in the late 1990s. In this article we present the results from two large surveys in the United States and Germany that report patients' experiences in different models of patient-centered diabetes care, compared to the experiences of patients who received routine diabetes care in the same systems. The study populations were enrolled in either Geisinger Health System in Pennsylvania or Barmer, a German sickness fund that provides medical insurance nationwide. Our findings suggest that patients with type 2 diabetes who were enrolled in the care models that exhibited key features of the CCM were more likely to receive care that was patient-centered, high quality, and collaborative, compared to patients who received routine care. This study demonstrates that quality improvement can be realized through the application of the Chronic Care Model, regardless of the setting or distinct characteristics of the program

Using Systematic Review and Decision Modeling to Fill Gaps in Evidence: Application to Positron Emission Tomography Scan Use in Posttreatment Squamous Cell Carcinoma of the Oropharynx

Background/Aims: There is a general lack of cost-effectiveness evidence for positron emission tomography (PET) scan use in cancer suitable to support decision-making, and specifically for post-nonsurgical treatment of squamous cell carcinoma of the oropharynx (SCOOP). The value of effectiveness research is greatest when there are considerable data challenges and uncertainty due to early adoption of new technology and/or emerging serious high-growth disease. New expensive technology commonly becomes the standard of care without adequate evidence to support its value, including whether its performance does more good than harm to patients compared to the previous standard or alternatives. An example is the lack of evidence-informed standards for postchemoradiation imaging of SCOOP for patient management. The standard of care is posttreatment physical examination with imaging at 8–12 weeks using PET scan, computed tomography scan or ultrasound. Due to limits in the sensitivity and negative predictive value of these alternatives, patients may be over- or undertreated. A particular concern is PET scans are routinely used in practice although they have a high false-positive rate, which often result in unnecessary procedures. Methods: A recommended efficient and evidence-based approach to providing needed information addressing health care cost and quality research gaps is decision and simulation modeling informed by a systematic review of the literature to obtain relevant information for model assumptions and parameter values augmented by expert input and consensus review. This approach will be applied to three posttreatment imaging alternatives for human papillomavirus (HPV)-positive SCOOP patients, and supplemented by Cancer Research Network (CRN) virtual data warehouse (VDW) patient data from HMORN participants and a technical expert panel from the newly formed CRN Head and Neck Cancer Scientific Interest Group. Results: The results presented are a decision-analysis model with assumptions, parameters and input values documented from the systematic review, CRN VDW data and input provided by the CRN Head and Neck Cancer Scientific Interest Group. Discussion: The finalized decision-analysis model will support simulations to estimate comparative effectiveness outcomes and cost-effectiveness of the HPV-positive SCOOP post-nonsurgical treatment imaging alternatives to provide much needed evidence to evaluate and improve clinical decision-making and patient outcomes and to identify future research needs