MAPPING CANINE LEPTOSPIROSIS RISK IN THE UNITED STATES

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that most of the framework criteria and their ethical underpinnings reflected their values and processes. Criteria “Comparative effectiveness” (range of normalized weights across methods: 0.09–0.12), “Quality of evidence/uncertainty” (0.10–0.13), “Disease severity” (0.09–0.19) and “Cost of intervention” (0.08-0.11) received the highest weights across all three methods. Elucidating the ethical underpinning of criteria was useful to explore the trade-off inherent to decisions for rare disease, operationalized by adding a quantitative “Priority” criteria.  Conclusions: Holistic MCDA provides a means to make explicit the ethical underpinnings of HTA organizations’ values and processes, including the imperative to help, prioritizing those who are worst off, wise use of resources and uncertainty. It raises awareness of trade-offs that have to be made when prioritizing interventions in the real world, such as for rare diseases, furthering participatory and transparent processes. PRM100 MAPPING CANINE LEPTOSPIROSIS RISK IN THE UNITED STATES Mwacalimba K K 1, Wright A K 2, White A 3, Zambrana-Torrelio C 3, Allen C 3, Rostal M 3, Ball E 4, Husain I 5, Karesh W B 3, Daszak P 3 1Zoetis, Indianapolis, IN, USA, 2Zoetis, Greeley, CO, USA, 3Ecohealth Alliance, New York, NY, USA, 4Zoetis, Florham Park, NJ, USA, 5Celeritas Solutions LLC, New York, NY, USA .

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Objectives: This study aimed to identify the spatial trends of canine leptospirosis, and predict the likelihood of leptospirosis events based on environmental and socioeconomic risk profiles across the United States.  Methods: We analyzed 87,355 serological (hereafter MAT) canine leptospirosis results (2000-2014) from IDEXX Laboratories Inc. with percentage of test-positive data aggregated by county. MAT titers at a dilution of ≥ 1:800 were considered positive. Spatial cluster analyses were calculated using ArcGIS ver.10.2, to identify canine leptospirosis clusters and hotspots. Boosted-regression trees were developed using the dismo package in the statistical software R to identify the probability of a dog testing positive for leptospirosis using 31 selected variables for climate and precipitation, dog ownership, landscape composition, and mammal and rodent diversity. Explanatory variables included climate, land cover type, and socio-economic factors. The upper Midwest and parts of the Southeast were poorly represented in testing data. We focused on climatic and environmental risk factors to understand the dynamics of canine leptospirosis and create a risk profile even in areas where data is sparse.  Results: Statistical analysis highlighted environment (e.g., precipitation and temperature) and land use (e.g., residential areas with houses built on large lots) as influencing the variation of canine leptospirosis risk in different counties of the US. The results of this study are accessible to both veterinarians and pet owners through a dedicated webpage https://www.zoetisus.com/conditions/dogs/leptospirosis/index. aspx.  Conclusions: Given the complexity of the model and the number of variables included, we only described important variables but not the precise relationship between each variable and leptospirosis risk. The outputs allow individuals to identify the likelihood of getting a positive canine leptospirosis case in each county of the contiguous US. This model is intended to help inform veterinary diagnostics and vaccination, and identify areas for increased research and surveillance. PRM101 IMPACT OF IMPLEMENTING INTERNATIONAL REFERENCE PRICING ON PHARMACEUTICAL PRICES FOR UNITED STATES MEDICARE Weiss J , Hakim P , Degun R Navigant Consulting Inc, London, UK .

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Objectives: The ex-factory price of pharmaceutical drug interventions in the United States is generally greater than those in Europe and the rest of world, with some instances of U.S. price differences exceeding 200-250%. As such, the U.S. House of Representatives investigative panel is mounting continuous pressure on manufacturers to review the rising cost of prescription drugs and associated cost to patients. Resulting from a fragmented multi-stakeholder healthcare system consisting of both private and public payers, the U.S. payers have limited negotiating power, although the Affordable Care Act has allowed for the utilization of the Independent Payment Advisory Board (IPAB) to review prices. Given other markets have been successful at employing international reference pricing (IRP) to control their prices, a similar approach may be useful for Medicare in lieu of IPAB.  Methods: Navigant’s ‘Pricing and Revenue Optimization For International Launch Excellence’ (PROFILE) Model has been utilized to illustrate the impact of IRP on U.S. price development, with respect to other global markets. Price development was analyzed for a given therapeutic class, assessing impact of various reference baskets including: (1) EU5, (2) top-5 GDP ex-U.S. and (3) Neighboring markets to U.S. (e.g. Canada). Price evolution was assessed over a 10 year horizon, with IRP assumed after 18 months of baseline price changes.  Results: The model demonstrates the inclusion of IRP within the U.S. controls the ex-factory prices across a 10 year horizon. Baskets containing the lower-priced markets were most successful at managing price. In addition, inclusion of IRP prevented the year-over-year price increases typically seen in the current environment.  Conclusions: Assuming legislative interest in implementing IRP, the U.S. government may reduce the differential pricing existing between U.S. and other markets. However, as the U.S. is typically a first-launched market, price control may only be achieved following re-referencing. PRM102 HOSPITAL PERFORMANCE ON QUALITY MESAURES: APPROACHES TO FAIR CROSS-HOSPITAL COMPARISONS AND VALUE-BASED PAYMENTS Nygren K 1, Suponcic S 2 1Navigant Consulting, Lawrenceville, NJ, USA, 2Navigant Life Sciences, Lawrenceville, NJ, USA .

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Objectives: The ACA mandated development of a national quality strategy (NQS). NQS aligns the nation toward Better Care, Healthy People/Healthy Communities, and Affordable Care. To monitor progress, CMS tracks a number of hospital level quality metrics that provide an understanding of hospital level performance. These increasingly serve as an input to value based payments to hospitals by payers. As hospitals may serve distinctly different patient populations, cross hospital comparisons on quality metrics and informed value based payments by hospital pose challenges.

The objective of this analysis is to examine approaches that can provide for fair cross-hospital comparisons that factor in differences in the underlying hospitals and which in turn can underpin informed value based payments.  Methods: We leverage demographic information, baseline population health metrics, and information on hospital characteristics to segment hospitals into groups of “like” hospitals that can be compared directly on quality metrics. This segmentation leverages a latent class approach incorporating covariates and indicator variables. We also explore approaches that further adjusts hospital quality metrics based on hospital characteristics prior to comparisons (similar to how price levels over time are compared by using market baskets with constant weights). We examine these adjustments both overall as well as by segments for “like” hospitals.  Results: We find that a latent class approach provides an intuitive framework that can be leveraged successfully to compare “like” hospitals on quality metrics without having to scale underlying quality metrics. Further enhancements can be made when information is available to successfully adjust quality metrics within segment.  Conclusions: A latent class approach to hospital segmentation allows for more meaningful cross hospital comparisons on quality metrics and can be leveraged to inform the structure and appropriate level of value based payments for individual hospitals. PRM103 IS EXENATIDE REALLY LINKED TO ACUTE PANCREATITIS: A NOVEL ANALYTIC EXAMINATION? Chen J 1, Hauptman P J 2, Turner J S 3, Burroughs T E 1 Louis University Center for Outcomes Research (SLUCOR), Saint Louis, MO, USA, 2Saint Louis University School of Medicine, Saint Louis, MO, USA, 3Saint Louis University College for Public Health and Social Justice, Saint Louis, MO, USA .

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Objectives: To utilize novel analytic methods to examine the suspected risk of acute pancreatitis associated with use of exenatide as monotherapy and polytherapy among national sample of patients with Type 2 diabetes.  Methods: This study utilized retrospective cohort design and included 5,229,477 patients with healthcare encounters between January 2005 and June 2012 from a nationally representative sample of medical administrative claims data. Patients with no history of acute pancreatitis, cystic fibrosis, primary hyperparathyroidism, alcohol addiction, biliary stone disease, cholestatic liver disease, and pancreatic disease for 18 months prior to initiation of any study drugs were assigned to five drug exposure groups: exenatide monotherapy, metformin monotherapy, sulfonylureas monotherapy, exenatide polytherapy, and non-exenatide polytherapy. Acute pancreatitis was identified by ICD-9-CM diagnosis codes. Patient baseline demographic and clinical characteristics were adjusted using propensity score stratification method. A novel analytic method, counting process modeling as extended proportional hazards regression, was conducted. Compared to more traditional analytic approaches, these analyses were able to account for discontinuous drug intervals and to monitor the impact of on- and off-drug effects on acute pancreatitis.  Results: When compared to metformin monotherapy, this analysis found no association between exenatide treatment and acute pancreatitis (exenatide monotherapy: aHR =  0.98, 95% CI: 0.70-1.38; exenatide polytherapy: aHR =  1.43, 95% CI: 0.95-2.15). The risks of developing acute pancreatitis were approximately 39% higher in sulfonylureas monotherapy (aHR =  1.39, 95% CI: 1.32-1.47) and 32% higher in non-exenatide polytherapy (aHR =  1.32, 95% CI: 1.22-1.42).  Conclusions: Applying the novel analytic method suggested that there was no statistically significant association between use of exenatide and acute pancreatitis compared to metformin monotherapy. However, sulfonylureas were found to be associated with elevated risk of acute pancreatitis. PRM104 AN EXPLORATION OF THE HETEROGENEITY IN A NETWORK META-ANALYSIS EXPLAINED BY DOSING DIFFERENCES Schmitz S 1, Kandala N 2, Senn S 2 College Dublin, Dublin, Ireland, 2Luxembourg Institute of Health, Strassen, Luxembourg .

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Objectives: Heterogeneity in meta-analysis is variation of treatment effects between trials that exceeds within-trial variation. Such variation can have many causes, including differences in trial populations, methodology or interventions. Random effects (RE) models are usually fitted to allow for such variation, including a parameter that quantifies such heterogeneity. In the case of Network Metaanalysis (NMA), a common heterogeneity parameter is typically assumed for the network, making its interpretation less intuitive. Our objective is to investigate the impact of dosing differences on the overall heterogeneity of a network.  Methods: A previous NMA analysed in Senn et al. (2011) was re-examined. Ten treatments for diabetes were compared in 26 studies; the outcome measure was change from baseline HbA1c. We have fitted a Bayesian NMA to the network and compared the level of heterogeneity with an extended network, separating doses, resulting in eighteen treatments. Model fit was based on the sum of squared residuals (SSR). We fitted both fixed effects (FE) and RE for the original and extended networks.  Results: The SSR is reduced from 148 in the FE model of the original network to 40 in the extended network. For the RE model, the SSR is reduced from 5 in the original network to 3 in the extended network. The original RE estimated the heterogeneity to be 0.26 (95%CrI: 0.14, 0.43). In the extended model, this was reduced to 0.22 (95%CrI: 0.09, 0.44).  Conclusions: Distinguishing between different doses of the same drug in a NMA can reduce overall heterogeneity and improve model fit. However, since heterogeneity can have a multitude of sources, the extended network does not necessarily resolve all heterogeneity. The fact that some variability can be resolved by taking account of dosage does not argue against RE models but underlines that the interpretation of a common heterogeneity parameter is difficult. PRM105 COMPARISON OF PROPENSITY SCORE WITH ZIP MODELS IN ANALYZING ZEROINFLATED COUNT DATA IN OBSERVATIONAL STUDIES Tu C 1, Koh W Y 2 1University of New England, Portland, ME, USA, 2University of New England, Biddeford, ME, USA .

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