Cost-effectiveness of the tubeless automated insulin delivery system vs standard of care in the management of type 1 diabetes in the United States.

BACKGROUND: A tubeless, on-body automated insulin delivery (AID) system (Omnipod 5 Automated Insulin Delivery System) demonstrated improved glycated hemoglobin A1c levels and increased time in range (70 mg/dL to 180 mg/dL) for both adults and children with type 1 diabetes in a 13-week multicenter, single-arm study. OBJECTIVE: To assess the cost-effectiveness of the tubeless AID system compared with standard of care (SoC) in the management of type 1 diabetes (T1D) in the United States. METHODS: Cost-effectiveness analyses were conducted from a US payer's perspective, using the IQVIA Core Diabetes Model (version 9.5), with a time horizon of 60 years and an annual discount of 3.0% on both costs and effects. Simulated patients received either tubeless AID or SoC, the latter being defined as either continuous subcutaneous insulin infusion (86% of patients) or multiple daily injections. Two cohorts (children: <18 years; adults: ≥18 years) of patients with T1D and 2 thresholds for nonsevere hypoglycemia (nonsevere hypoglycemia event [NSHE] <54 mg/dL and <70 mg/dL) were considered. Baseline cohort characteristics and treatment effects of different risk factors for tubeless AID were sourced from the clinical trial. Utilities and cost of diabetes-related complications were obtained from published sources. Treatment costs were derived from US national database sources. Scenario analyses and probabilistic sensitivity analyses were performed to test the robustness of the results. RESULTS: Treating children with T1D with tubeless AID, considering an NSHE threshold of less than 54 mg/dL, brings incremental life-years (1.375) and quality-adjusted life-years (QALYs) (1.521) at an incremental cost of $15,099 compared with SoC, resulting in an incremental cost-effectiveness ratio of $9,927 per QALY gained. Similar results were obtained for adults with T1D assuming an NSHE threshold of less than 54 mg/dL (incremental cost-effectiveness ratio = $10,310 per QALY gained). Furthermore, tubeless AID is a dominant treatment option for children and adults with T1D assuming an NSHE threshold of less than 70 mg/dL compared with SoC. The probabilistic sensitivity analyses results showed that compared with SoC, in both children and adults with T1D, tubeless AID was cost-effective in more than 90% of simulations, assuming a willingness-to-pay threshold of $100,000 per QALY gained. The key drivers of the model were the cost of ketoacidosis, duration of treatment effect, threshold of NSHE, and definition of severe hypoglycemia. CONCLUSIONS: The current analyses suggest that the tubeless AID system can be considered a cost-effective treatment compared with SoC in people with T1D from a US payer's perspective. DISCLOSURES: This research was funded by Insulet. Mr Hopley, Ms Boyd, and Mr Swift are full-time Insulet employees and own stock in Insulet Corporation. IQVIA, the employer of Ms Ramos and Dr Lamotte, received consulting fees for this work. Dr Biskupiak is receiving research support and consulting fees from Insulet. Dr Brixner has received consulting fees from Insulet. The University of Utah has received research funding from Insulet. Dr Levy is a consultant with Dexcom and Eli Lilly and has received grant/research support from Insulet, Tandem, Dexcom, and Abbott Diabetes. Dr Forlenza conducted research sponsored by Medtronic, Dexcom, Abbott, Tandem, Insulet, Beta Bionics, and Lilly. He has been speaker/consultant/advisory board member for Medtronic, Dexcom, Abbott, Tandem, Insulet, Beta Bionics, and Lilly.

Can Cost-effectiveness Analysis Inform Genotype-Guided Aspirin Use for Primary Colorectal Cancer Prevention?

BACKGROUND: Inherited genetic variants can modify the cancer-chemopreventive effect of aspirin. We evaluated the clinical and economic value of genotype-guided aspirin use for colorectal cancer chemoprevention in average-risk individuals. METHODS: A decision analytical model compared genotype-guided aspirin use versus no genetic testing, no aspirin. The model simulated 100,000 adults ≥50 years of age with average colorectal cancer and cardiovascular disease risk. Low-dose aspirin daily starting at age 50 years was recommended only for those with a genetic test result indicating a greater reduction in colorectal cancer risk with aspirin use. The primary outcomes were quality-adjusted life-years (QALY), costs, and incremental cost-effectiveness ratio (ICER). RESULTS: The mean cost of using genotype-guided aspirin was $187,109 with 19.922 mean QALYs compared with $186,464 with 19.912 QALYs for no genetic testing, no aspirin. Genotype-guided aspirin yielded an ICER of $66,243 per QALY gained, and was cost-effective in 58% of simulations at the $100,000 willingness-to-pay threshold. Genotype-guided aspirin was associated with 1,461 fewer polyps developed, 510 fewer colorectal cancer cases, and 181 fewer colorectal cancer-related deaths. This strategy prevented 1,078 myocardial infarctions with 1,430 gastrointestinal bleeding events, and 323 intracranial hemorrhage cases compared with no genetic testing, no aspirin. CONCLUSIONS: Genotype-guided aspirin use for colorectal cancer chemoprevention may offer a cost-effective approach for the future management of average-risk individuals. IMPACT: A genotype-guided aspirin strategy may prevent colorectal cancer, colorectal cancer-related deaths, and myocardial infarctions, while minimizing bleeding adverse events. This model establishes a framework for genetically-guided aspirin use for targeted chemoprevention of colorectal cancer with application toward commercial testing in this population.

Cost-effectiveness of early cancer surveillance for patients with Li-Fraumeni syndrome.

INTRODUCTION: Patients with germline TP53 pathogenic variants (Li-Fraumeni syndrome [LFS]) are at extremely high lifetime risk of developing cancer. Recent data suggest that tumor surveillance for patients with LFS may improve survival through early cancer detection. The objective of this study was to assess the cost-effectiveness of a cancer surveillance strategy for patients with LFS compared with those whose tumors present clinically. METHODS: A Markov decision analytic model was developed from a third-party payer perspective to estimate cost-effectiveness of routine cancer surveillance over a patient's lifetime. The model consisted of four possible health states: no cancer, cancer, post-cancer survivorship, and death. Model outcomes were costs (2015 United States Dollars [USD]), effectiveness (life years [LY] gained), and incremental cost-effectiveness ratio (ICER; change in cost/LY gained). One-way sensitivity analyses and probabilistic sensitivity analyses examined parameter uncertainty. RESULTS: The model showed a mean cost of $46 496 and $117 102 and yielded 23 and 27 LY for the nonsurveillance and surveillance strategies, respectively. The ICER for early cancer surveillance versus no surveillance was $17 125 per additional LY gained. At the commonly accepted willingness to pay threshold of $100 000/life-year gained, surveillance had a 98% probability of being the most cost-effective strategy for early cancer detection in this high-risk population. CONCLUSIONS: Presymptomatic cancer surveillance is cost-effective for patients with germline pathogenic variants in TP53. Lack of insurance coverage or reimbursement in this population may have significant consequences and leads to undetected cancers presenting in later stages of disease with worse clinical outcomes.

Clinical Utility of Pharmacogenetic Testing and a Clinical Decision Support Tool to Enhance the Identification of Drug Therapy Problems Through Medication Therapy Management in Polypharmacy Patients.

BACKGROUND: In polypharmacy patients, medication therapy management (MTM) services provide a comprehensive review of current medications and future treatment goals. Pharmacogenetics (PGx) may further optimize the identification of potential drug therapy problems (DTPs); however, the clinical utility of PGx information with a clinical decision support tool (CDST) in an MTM setting in identifying DTPs has not been systematically assessed. OBJECTIVE: To assess the clinical utility of an MTM service enhanced by pharmacogenetic test results and a clinical decision support tool. METHODS: This study was a post hoc analysis of the data obtained from an open-label, randomized, observational trial. Polypharmacy patients eligible for MTM service were randomly assigned to 3 intervention arms: standard MTM (SMTM), MTM incorporating CDST (CMTM), and CMTM further enhanced by PGx test results of CYP450 and VKORC1 enzymes (PGxMTM). Allocation for this post hoc analysis was based on patient adherence to the research protocol and completion of a PGx test. The number of DTPs per patient was compared across the 3 arms using analysis of variance. In addition, the frequency of serious DTPs as a categorical variable (grade 3 or above vs. lower grade) was compared across the 3 arms between PGx driven and non-PGx driven DTP recommendations. Statistical significance was tested using the chi-square test. The level of agreement between the DTP seriousness and the acceptance made by prescribers was presented as Cohen's kappa coefficient. RESULTS: Numbers of patients after cohort reallocation based on completion of PGx testing were 104, 180, and 58 for the SMTM, CMTM, and PGxMTM arms, respectively. On average, 3.08 DTPs were identified for each patient, which was nearly identical across all 3 arms. Blinded clinical pharmacists considered seriousness (grade 3 or 4) in 31% of the PGx-related DTPs in comparison with 4.9% of the non-PGx DTPs (P < 0.001). The more serious (i.e., grade 3 or above) DTP recommendations were more likely to be accepted by prescribers with the odds ratios of 1.95 (P = 0.05) and 2.39 (P = 0.15), when the analysis was performed for all DTPs and DTPs from the PGxMTM arm only, respectively. CONCLUSIONS: MTM enhanced by PGx testing and the clinical decision support tool did not increase the number of DTPs identified. However, PGx testing and the decision support software helps pharmacists determine more serious DTPs, and resulting subsequent recommendations were more readily accepted by a prescriber. Future study of the patient safety outcomes and overall health care costs associated with the utility of the decision support is warranted. DISCLOSURES: No funding was received for conducting the post hoc analysis presented in this study. Magness is employed by Magellan Health, which received funding from Genelex for costs to administrate the medication management program. The open-label randomized trial was sponsored by Genelex (Clinicaltrials.gov ID number NCT02428660). PGx tests were provided and laboratory analysis was performed by Genelex. Valerie Baron is an employee of YouScript, which created the clinical decision support tool used in this study and formerly was part of Genelex. The other authors have nothing to disclose.

The potential impact of monitoring disease activity biomarkers on rheumatoid arthritis outcomes and costs.

Rheumatoid arthritis (RA) management requires monitoring of disease activity to determine course of treatment. Global assessments are used in clinical practice to determine RA disease activity. Monitoring disease activity via biomarkers may also help providers optimize biologic and nonbiologic drug use while decreasing overall drug spend by delaying use of expensive biologic therapies. By testing multiple biologic domains at the same time, a multibiomarker disease activity test may have utility in RA patient management, through improved intra- and inter-rater reliability. This report provides a comprehensive review of studies of objective measures, single biomarkers and multibiomarker disease activity tests as disease activity measures to decrease uncertainty in treatment decisions, and of biomarkers' potential impact on economic and clinical outcomes of treatment choices.

Impact of a genetic counseling requirement prior to genetic testing.

BACKGROUND: Genetic counseling by a Genetic Counselor (GC) is a requirement prior to genetic testing for cancer susceptibility genes (GC-mandate policy) for some insurers. This study evaluated the impact of this policy from the patient perspective. METHODS: Surveys were sent to individuals for whom their insurer ordered genetic testing for the cancer susceptibility genes BCRA1 and BRCA2 over a 1 year time period that spanned the introduction of a GC-mandate policy. Responses were assessed by time period (before/after policy introduction) and genetic test completion. RESULTS: The surveys were completed by 1247/4950 (25.7%) eligible individuals. After policy introduction, there was no change in the proportion of respondents who completed genetic testing (p = 0.13) or had a mutation (p = 0.55). Overall decisional conflict (uncertainty or feeling uninformed) around genetic testing did not change after policy introduction (p = 0.16), but was significantly higher among respondents who did not complete genetic testing (p < 0.01). Although a larger proportion of respondents saw a GC after policy introduction (p < 0.01), fewer did so to better understand their test results (p < 0.01). The proportion of respondents who did not see a GC due to insurance issues/requirements and time restraints was higher among those tested after policy introduction or who did not complete genetic testing (p < 0.01). In multivariate analysis, respondents with a household income of $25,000 or greater were 3-times more likely to complete testing. CONCLUSIONS: A GC-mandate policy did not improve decisional conflict or increase the number of deleterious mutations identified and low-income respondents were less likely to complete testing. On the contrary, insurance requirements and time constraints may be preventing individuals at risk from receiving appropriate testing.

Nine years of comparative effectiveness research education and training: initiative supported by the PhRMA Foundation.

The term comparative effectiveness research (CER) took center stage with passage of the American Recovery and Reinvestment Act (2009). The companion US$1.1 billion in funding prompted the launch of initiatives to train the scientific workforce capable of conducting and using CER. Passage of the Patient Protection and Affordable Care Act (2010) focused these initiatives on patients, coining the term 'patient-centered outcomes research' (PCOR). Educational and training initiatives were soon launched. This report describes the initiative of the Pharmaceutical Research and Manufacturers Association of America (PhRMA) Foundation. Through provision of grant funding to six academic Centers of Excellence, to spearheading and sponsoring three national conferences, the PhRMA Foundation has made significant contributions to creation of the scientific workforce that conducts and uses CER/PCOR.

Identification of Patients with Statin Intolerance in a Managed Care Plan: A Comparison of 2 Claims-Based Algorithms.

BACKGROUND: While statins are safe and efficacious, some patients may experience statin intolerance or treatment-limiting adverse events. Identifying patients with statin intolerance may allow optimal management of cardiovascular event risk through other strategies. Recently, an administrative claims data (ACD) algorithm was developed to identify patients with statin intolerance and validated against electronic medical records. However, how this algorithm compared with perceptions of statin intolerance by integrated delivery networks remains largely unknown. OBJECTIVE: To determine the concurrent validity of an algorithm developed by a regional integrated delivery network multidisciplinary panel (MP) and a published ACD algorithm in identifying patients with statin intolerance. METHODS: The MP consisted of 3 physicians and 2 pharmacists with expertise in cardiology, internal medicine, and formulary management. The MP algorithm used pharmacy and medical claims to identify patients with statin intolerance, classifying them as having statin intolerance if they met any of the following criteria: (a) medical claim for rhabdomyolysis, (b) medical claim for muscle weakness, (c) an outpatient medical claim for creatinine kinase assay, (d) fills for ≥ 2 different statins excluding dose increases, (e) decrease in statin dose, or (f) discontinuation of a statin with a subsequent fill for a nonstatin lipid-lowering therapy. The validated ACD algorithm identified statin intolerance as absolute intolerance with rhabdomyolysis; absolute intolerance without rhabdomyolysis (i.e., other adverse events); or as dose titration intolerance. Adult patients (aged ≥ 18 years) from the integrated delivery network with at least 1 prescription fill for a statin between January 1, 2011, and December 31, 2012 (first fill defined the index date) were identified. Patients with ≥ 1 year pre- and ≥ 2 years post-index continuous enrollment and no statin prescription fills in the pre-index period were included. The MP and ACD algorithms were applied to the population, and concordance was examined using individual (i.e., sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV]) and overall performance measures (i.e., accuracy, Cohen's kappa coefficient, balanced accuracy, F-1 score, and phi coefficient). RESULTS: After applying the inclusion criteria, 7,490 patients were evaluated for statin intolerance. The mean (SD) age of the population was 51.1 (8.5) years, and 55.7% were male. The MP and ACD algorithms classified 11.3% and 5.4% of patients as having statin intolerance, respectively. The concordance of the MP algorithm was mixed, with negative classification of statin intolerance measures having high concordance (specificity 0.91, NPV 0.97) and positive classification of statin intolerance measures having poor concordance (sensitivity 0.45, PPV 0.21). Overall performance measures showed mixed agreement between the algorithms. CONCLUSIONS: Both algorithms used a mix of pharmacy and medical claims and may be useful for organizations interested in identifying patients with statin intolerance. By identifying patients with statin intolerance, organizations may consider a variety of options, including using nonstatin lipid-lowering therapies, to manage cardiovascular event risk in these patients. DISCLOSURES: This study was funded by Regeneron Pharmaceuticals and Sanofi US. Boklage is employed by, and owns stock in, Regeneron, and Charland is employed by Sanofi. Bellows has received fees from Avenir for advisory board membership and grants from Myriad Genetics, Biogen, Janssen, and National Institutes of Health. Brixner reports advisory board and consultancy fees and grants from Sanofi. Mitchell reports consultancy fees from Sanofi. Study concept and design were contributed by Bellows, Boklage, Charland, and Brixner. Bellows, Sainski-Nguyen, and Olsen took the lead in data collection, along with Mitchell. Data interpretation was performed by Mitchell, along with the other authors. The manuscript was written by Bellows, Sainski-Nguyen, and Olsen and revised by all the authors.

Cost-Utility of a Prognostic Test Guiding Adjuvant Chemotherapy Decisions in Early-Stage Non-Small Cell Lung Cancer.

BACKGROUND: A prognostic test was developed to guide adjuvant chemotherapy (ACT) decisions in early-stage non-small cell lung cancer (NSCLC) adenocarcinomas. The objective of this study was to compare the cost-utility of the prognostic test to the current standard of care (SoC) in patients with early-stage NSCLC. MATERIALS AND METHODS: Lifetime costs (2014 U.S. dollars) and effectiveness (quality-adjusted life-years [QALYs]) of ACT treatment decisions were examined using a Markov microsimulation model from a U.S. third-party payer perspective. Cancer stage distribution and probability of receiving ACT with the SoC were based on data from an academic cancer center. The probability of receiving ACT with the prognostic test was estimated from a physician survey. Risk classification was based on the 5-year predicted NSCLC-related mortality. Treatment benefit with ACT was based on the prognostic score. Discounting at a 3% annual rate was applied to costs and QALYs. Deterministic one-way and probabilistic sensitivity analyses examined parameter uncertainty. RESULTS: Lifetime costs and effectiveness were $137,403 and 5.45 QALYs with the prognostic test and $127,359 and 5.17 QALYs with the SoC. The resulting incremental cost-effectiveness ratio for the prognostic test versus the SoC was $35,867/QALY gained. One-way sensitivity analyses indicated the model was most sensitive to the utility of patients without recurrence after ACT and the ACT treatment benefit. Probabilistic sensitivity analysis indicated the prognostic test was cost-effective in 65.5% of simulations at a willingness to pay of $50,000/QALY. CONCLUSION: The study suggests using a prognostic test to guide ACT decisions in early-stage NSCLC is potentially cost-effective compared with using the SoC based on globally accepted willingness-to-pay thresholds. IMPLICATIONS FOR PRACTICE: Providing prognostic information to decision makers may help some patients with high-risk early stage non-small cell lung cancer receive appropriate adjuvant chemotherapy while avoiding the associated toxicities and costs in patients with low-risk disease. This study used an economic model to assess the effectiveness and costs associated with using a prognostic test to guide adjuvant chemotherapy decisions compared with the current standard of care in patients with non-small cell lung cancer. When compared with current standard care, the prognostic test was potentially cost effective at commonly accepted thresholds in the U.S. This study can be used to help inform decision makers who are considering using prognostic tests.

Assessment of HER2 testing patterns, HER2+ disease, and the utilization of HER2-directed therapy in early breast cancer.

CONTEXT: Determining human epidermal growth factor receptor 2 (HER2) status is critical for the management of early-stage breast cancer (ESBC). An understanding of HER2 testing practices can provide insight into how test results influence the use of HER2-directed therapy. OBJECTIVE: To assess HER2 testing, HER2+ disease, and HER2-directed therapy in ESBC at the Huntsman Cancer Institute before and after the 2007 American Society of Clinical Oncology and College of American Pathologist (ASCO/CAP) guidelines on HER2 testing were published. METHODS: Patients were identified from an institutional tumor registry. HER2 testing patterns and results were examined using a chart review of pathology and clinical notes. Patient characteristics, HER2+ rate, and trastuzumab use were evaluated descriptively. Discordance rate with reflex testing (immunohistochemistry [IHC]2+ retested by fluorescence in situ hybridization [FISH]) was also evaluated. RESULTS: A total of 1,459 women were included (mean age: 57 years). The rate of HER2+ disease was 17% (number [N] =245). The discordance rate between IHC2+ and FISH was 10%. After the 2007 ASCO/CAP guidelines, fewer tumors were classified as IHC3+ (16% post- versus 21.9% pre-2007), more tumors were characterized as IHC2+ (26.4% post- versus 20.7% pre-2007), and the overall HER2+ rate was decreased (18.7% versus 21.9%), but this was not statistically significant (P=0.519). Most patients with HER2+ ESBC received HER2-targeted therapy (N=185). CONCLUSION: The HER2+ rate was 17% and within the range of the reported rates in the literature. Reflex testing identified additional HER2+ tumors by approximately 10%, and should be considered a potential quality indicator. ASCO/CAP HER2 testing guidelines in 2007 appeared to impact the interpretation and classification of HER2+ tumors.

Impact of adherence and weight loss on glycemic control in patients with type 2 diabetes: cohort analyses of integrated medical record, pharmacy claims, and patient-reported data.

BACKGROUND: Managed care organizations put great effort into managing the population of patients with type 2 diabetes mellitus (T2DM) because of the health and economic burden of this disease. In patients with T2DM, weight loss and glycemic control are primary treatment aims to help improve patient outcomes, but these goals are not easily achieved. While achieving these aims requires a multifaceted approach of drug therapy management and lifestyle modification, truly understanding the role of medication adherence in achieving these outcomes is important for both patient and population management. This study expands on existing evidence that weight loss is associated with improved glycemic control by examining the role of medication adherence in achieving these goals in a managed care setting. This study is unique in that these associations are evaluated using multiple sources of data, including medical records for treatment outcomes, pharmacy claims, and patient-reported data to assess medication adherence. These data sources represent those typically available to payers or providers.  OBJECTIVE: To describe the relationships between medication and adherence, weight change, and glycemic control in patients with T2DM. METHODS: This historical cohort study included adult patients with T2DM in a large integrated health system and was based on electronic health record and pharmacy claims data from November 1, 2010, through October 31, 2011, as well as data from a self-reported adherence survey conducted in March 2012. Included patients received a diabetes medication from a therapeutic class not previously received, between November 1, 2010, and April 30, 2011 (index date), who had blood glucose (HbA1c) and weight values at index date and 6 months follow-up, participated in an adherence survey, and had ≥ 1 prescription claim for the index-date drug. Associations between the dual outcomes of weight loss (≥ 3%) and HbA1c control ( less than 7.0%), while controlling for medication adherence and other demographic, treatment, and clinical variables, were evaluated using structural equation models (SEM). Separate models adjusted for different measures of medication adherence-self-reported using the 5-item Medication Adherence Rating Scale (MARS-5) and a modified medication possession ratio (mMPR) from pharmacy claims data. RESULTS: The study included 166 patients with a mean age of 61.1 (standard deviation = 12.1) years; 56.0% were female. Medication adherence was high, with 72.2% adherent using MARS-5 and 77.1% using mMPR measures. The SEMs found that only self-reported medication adherence is associated with weight loss (MARS-5: OR = 1.70, 95% CI = 1.11-2.60), while both self-reported and claims-based medication adherence were associated with HbA1c less than 7.0% (MARS-5: OR = 1.59, 95% CI = 1.09-2.34; mMPR: OR 2.71, 95% CI = 1.22-5.98). Further, weight loss is significantly associated with HbA1c less than 7.0% (MARS-5: OR = 3.60, 95% CI = 2.39-5.46; mMPR: OR 2.99, 95% CI = 1.45-6.17). CONCLUSIONS: This study has provided additional evidence in a managed, integrated setting that in patients treated for T2DM, weight loss is associated with good glycemic control. Adherence is associated with weight loss according to self-report, but not claims-based adherence measures. Adherence is also associated with glycemic control as measured by the 2 different methods. This study adds to the body of literature highlighting the importance of adherence as well as weight loss in achieving good glycemic control. The fact that the association of weight loss and adherence on glycemic control outcomes was significant regardless of medication adherence method is important in payer-provider collaborations, where access to data sources to evaluate adherence may vary. This study also supports continued investment in weight loss and adherence programs in the management of patients with T2DM.

Can CER be an effective tool for change in the development and assessment of new drugs and technologies?

BACKGROUND: Comparative effectiveness research (CER) has been proposed in the United States as a way to compare new drugs and technologies with established alternatives and determine not just whether a therapy works, but how well it works compared to other options. OBJECTIVES: To define the current use of CER in the development of new drugs and technologies and explore what is needed for this research approach to reduce or stabilize health care costs in the United States. SUMMARY: In 2010, the Patient-Centered Outcomes Research Institute (PCORI) was established by the Patient Protection and Affordable Care Act (PPACA) to coordinate federally funded CER and recommend research priorities. Hochman and McCormick's (2010) evaluation of 328 randomized trials, observational studies, and meta-analyses involving medications published between June 2008 and September 2009 in 6 key journals showed that most published research did not fulfill the criteria of CER (defined as comparison to active treatment) and that most study design is driven by FDA requirements rather than the need to develop evidence to facilitates election of the most effective therapy. Since PPACA provides alternative funding for CER, it could encourage funding more studies to help determine which treatment delivers the best value per unit of investment from clinical, humanistic, and economic perspectives. Manufacturers may avoid CER because it increases product development costs, but a drug proven more effective is more likely to be accepted by formulary committees, increasing the drug's market share, whereas payers may reject or limit use of a new drug that performs less effectively in comparative studies. CONCLUSIONS: CER may not directly reduce expenditures for drugs and medical technologies. The results may vary widely from case to case; however, despite often significantly higher prices for new drugs, it is important to look beyond product costs to the overall impact on health care costs, including medical cost offsets that may occur through improved health or decreased morbidity. To truly decrease cost and improve quality, cost-effectiveness will have to be integrated into CER with the objective of prioritizing efficient therapies in the real-world health care system. If the methods and output of CER improve, the resulting cost-effectiveness ratios will also be more useful to the payer. CER should ultimately, therefore, be a useful tool to help patients, providers, and decision makers provide the most effective and most cost-effective interventions.

All-cause and bleeding-related health care costs in warfarin-treated patients with atrial fibrillation.

BACKGROUND: Bleeding is a major complication of warfarin therapy. Assessing the cost of warfarin-associated bleeding may more fully describe the costs associated with warfarin use. OBJECTIVE: To assess health care costs related to warfarin-associated bleeding in patients with newly diagnosed atrial fibrillation (AF). METHODS: Medical and pharmacy claims were analyzed for patients with AF (ICD-9-CM code 427.31) in the Medstat MarketScan database from January 2003 to December 2007. Eligible patients had no warfarin pharmacy claim or AF diagnosis in the 4 months prior to AF index date, a warfarin pharmacy claim within 30 days of AF diagnosis, and 12 months follow-up data after the index warfarin claim. Subjects were categorized based on the first type of bleeding event observed during follow-up, and only bleeding events occurring within 30 days following a warfarin claim were considered. Intracranial hemorrhage (ICH) and gastrointestinal (GI) events were assessed based on primary or secondary ICD-9-CM codes, and major GI bleeding was defined as a GI bleed associated with hospitalization. Annual total all-cause allowed charges in patients with and without bleeding events after the index warfarin claim were compared using generalized linear model (GLM) regression with gamma distribution and log link, controlling for demographics, insurance status, and comorbidities. Costs for claims with a primary or secondary diagnosis of bleeding were calculated separately. RESULTS: Of the 47,437 patients who were analyzed, 194 (0.4%) had an ICH, 919 (1.9%) had a major GI bleed, and 1,804 (3.8%) had a minor GI bleed within 30 days after a warfarin claim during follow-up. Compared with patients who had no bleeding events after a warfarin claim (n = 44,520, 93.9%) during the study period, patients with at least 1 bleeding event were older and had more comorbidities (P < 0.01). Patients with at least 1 ICH or major GI bleed had more all-cause hospitalizations (P < 0.05) and hospital days (P < 0.01) than patients without bleeding events. Patients with at least 1 ICH, major GI bleed, or minor GI bleed had more all-cause emergency room visits (P < 0.01) than patients without bleeding events. Mean (SD) unadjusted all-cause health care costs in the 12 months after the warfarin index claim were $41,903 ($56,654), $40,586 ($65,164), and $24,347 ($56,488) for patients with at least 1 ICH, major GI bleed, and minor GI bleed, respectively, compared with $24,129 ($36,425) for patients with no bleeding events. Claims with a primary or secondary diagnosis of bleeding accounted for 49.6%, 30.2%, and 2.6% of annual cost in patients with ICH, major GI bleeding, and minor GI bleeding, respectively. On average, 50.9%, 33.5%, and 10.8% of annual all-cause costs occurred within 30 days after the first ICH, major GI bleeding event, and minor GI bleeding event, respectively. GLM regression showed that annual all-cause costs were 64.4% and 49.0% higher (P? less than ?0.001) for patients with ICH and major GI bleeding, respectively, than for patients with no bleeding events. CONCLUSION: ICH and major GI bleeding associated with warfarin therapy are rare but costly.

All-cause and incremental per patient per year cost associated with chronic hepatitis C virus and associated liver complications in the United States: a managed care perspective.

BACKGROUND: Approximately 3.2-3.9 million U.S. residents are infected with the hepatitis C virus (HCV). Total annual costs (direct and indirect) in the United States for HCV were estimated to be $5.46 billion in 1997, and direct medical costs have been predicted to increase to $10.7 billion for the 10-year period from 2010 through 2019, due in part to the increasing number of HCV patients developing advanced liver disease (AdvLD). OBJECTIVE: To quantify in a sample of commercially insured enrollees (a) total per patient per year (PPPY) all-cause costs to the payer, overall and by the stage of liver disease, for patients diagnosed with HCV; and (b) incremental all-cause costs for patients diagnosed with HCV relative to a matched non-HCV cohort. METHODS: This retrospective, matched cohort study included patients aged at least 18 years and with at least 6 months of continuous enrollment in a large managed care organization (MCO) claims database from July 1, 2001, through March 31, 2010. Patients with a diagnosis of HCV (ICD-9-CM codes 070.54, 070.70) were identified and stratified into those with and without AdvLD, defined as decompensated cirrhosis (ICD-9-CM codes 070.44, 070.71, 348.3x, 456.0, 456.1, 456.2x, 572.2, 572.3, 572.4, 782.4, 789.59); hepatocellular carcinoma (HCC, ICD-9-CM code 155); or liver transplant (ICD-9-CM codes V42.7, 50.5 or CPT codes 47135, 47136). For patients without AdvLD, the index date was the first HCV diagnosis date observed at least 6 months after the first enrollment date, and at least 6 months of continuous enrollment after the index date were required. HCV patients without AdvLD were stratified into those with and without compensated cirrhosis (ICD-9-CM codes 571.2, 571.5, 571.6). For patients with AdvLD, the index date was the date of the first AdvLD diagnosis observed at least 6 months after the first enrollment date, and at least 1 day of enrollment after the index date was required. Cases were matched in an approximate 1:10 ratio to comparison patients without an HCV diagnosis or AdvLD diagnosis who met all other inclusion criteria based on gender, age, hospital referral region state, pre-index health care costs, alcoholism, human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS), and a modified Charlson Comorbidity Index. For the HCV and comparison patient cohorts, PPPY all-cause costs to the payer were calculated as total allowed charges summed across all patients divided by total patient-days of follow-up for the cohort, multiplied by 365, inflation-normalized to 2009 dollars. Because the calculation of PPPY cost generated a single value for each cohort, bootstrapping was used to generate descriptive statistics. Incremental PPPY costs for HCV patients relative to non-HCV patients were calculated as between-group differences in PPPY costs. T-tests for independent samples were used to compare costs between case and comparison cohorts. RESULTS: A total of 34,597 patients diagnosed with HCV, 78.0% with HCV without AdvLD, 4.4% with compensated cirrhosis, 12.3% with decompensated cirrhosis, 2.8% with HCC, and 2.6% with liver transplant, were matched to 330,435 comparison patients. Mean (SD) age of all HCV cases was 49.9 (8.5) years; 61.7% were male. Incremental mean (SD) PPPY costs in 2009 dollars for all HCV patients relative to comparison patients were $ 9,681 ($176) PPPY. Incremental PPPY costs were $5,870 ($157) and $5,330 ($491) for HCV patients without liver disease and with compensated cirrhosis, respectively. Incremental PPPY costs for patients with AdvLD were $27,845 ($ 965) for decompensated cirrhosis, $43,671 ($2,588) for HCC, and $ 93,609 ($4,482) for transplant. Incremental prescription drug costs, including the cost of antiviral drugs, were $2,739 ($37) for HCV patients overall, $2,659 ($41) for HCV without liver involvement, and $3,102 ($157) for HCV with compensated cirrhosis. These between-group differences were statistically significant at P<0.001. CONCLUSIONS: Based on a retrospective analysis of data from a large, MCO claims database, patients diagnosed with HCV had annual all-cause medical costs that were almost twice as high as those of enrollees without a diagnosis of HCV. Health care costs increased dramatically with AdvLD. Data from this study may help MCOs project future HCV costs and facilitate planning for HCV patient management efforts.

Cost effectiveness of pharmacotherapy for the prevention of migraine: a Markov model application.

BACKGROUND: There are few data about the cost effectiveness of prophylactic medications for migraine. Clinical trials have shown several preventive agents to be useful in reducing the frequency of migraine attack while having tolerable side effects. OBJECTIVE: To compare the cost effectiveness of adding preventive treatment to abortive therapy for acute migraine with abortive therapy for acute migraine alone in the primary care setting. METHODS: A Markov decision analytic model with a cycle length of 1 day, a time horizon of 365 days and three health states was used to perform an analysis comparing the cost effectiveness and utility of five treatments for migraine prophylaxis (amitriptyline 75 mg/day, topiramate 100 and 200 mg/day, timolol 20 mg/day, divalproex sodium 1000 mg/day or propranolol 160 mg/day) with treatment of acute migraine alone for the management of migraine in the primary care setting. One-way and probabilistic sensitivity analyses were performed to test the robustness of the results. RESULTS: The expected total annual cost for the use of preventive agents ranged from $US2932 to $US3887, compared with $US3960 for the use of abortive medications only. In the baseline analysis, use of each of the five preventive agents generated more quality-adjusted life-years (QALYs) and incurred lower costs compared with abortive medications only. Monte Carlo Simulation suggested that amitriptyline 75 mg/day was most likely to be considered a cost-effective option versus the other five therapies, followed by timolol 20 mg/day, topiramate 200 mg/day, topiramate 100 mg/day, divalproex sodium 1000 mg/day and propranolol 160 mg/day when the willingness-to-pay (WTP) for society is <$US18 000 per QALY gained. CONCLUSIONS: Preventive medications appear to be a cost-effective approach to the management of migraine in the primary care setting compared with the approach of abortive treatment only. Among those preventive agents, probabilistic sensitivity analysis suggests that, when the societal WTP is <$US18 000 per QALY gained, amitriptyline 75 mg/day is most likely to be considered a cost-effective option.

Assessment of time to follow-up visits in newly-treated hypertensive patients using an electronic medical record database.

OBJECTIVE: Use of electronic medical record (EMR) data for evaluating healthcare processes and outcomes is relatively new. Using EMR data, this study evaluated the time from antihypertensive initiation to the first follow-up office visit controlling for adverse events (AEs) and other factors that could influence follow-up timing. Findings were compared to treatment guidelines which recommend monthly follow-up in treatment naive patients until blood pressure (BP) levels are controlled. RESEARCH DESIGN AND METHODS: Treatment-naïve hypertensive adult patients in the General Electric Centricity EMR database (1996-2006) with a new antihypertensive prescription were evaluated. Time from treatment initiation to first office visit was identified and stratified by occurrence of AEs and therapy change. BP was assessed at 120 +/- 30 days. RESULTS: The mean +/- SD time from first antihypertensive prescription (index date) to the first office visit was 96.2 +/- 160.6 days; 38% returned within a month of treatment initiation. Controlling for baseline demographic and clinical characteristics, the adjusted time until first office visit was shorter for those with an AE and therapy change than for those with neither event (61 vs. 158 days). Of the patients with follow-up BP data for analysis (n = 27,875), more of those seen within a month of treatment initiation achieved BP goal at 120 days (<140/90 mmHg) than those who were not seen within a month (64.3 vs. 61.7% respectively; p < 0.001). CONCLUSIONS: This study demonstrates that EMR data can be used to assess quality measures which in turn can inform efforts to improve treatment outcomes. Specifically, this study evaluated mean time to first office visit after antihypertensive therapy initiation controlling for clinical factors that could influence office visit intervals based on data available in a national EMR dataset. A key limitation of this study is that the EMR may not represent patient care delivered by other providers, thus, use of antihypertensives, changes in therapy, and office visits may be underreported.