Paying For Value From Costly Medical Technologies: A Framework For Applying Value-Based Payment Reforms.

Innovative medical products offer significant and potentially transformative impacts on health, but they create concerns about rising spending and whether this rise is translating into higher value. The result is increasing pressure to pay for therapies in a way that is tied to their value to stakeholders through improving outcomes, reducing disease complications, and addressing concerns about affordability. Policy responses include the growing application of health technology assessments based on available evidence to determine unit prices, as well as alternatives to volume-based payment that adjust product payments based on predictors or measures of value. Building on existing frameworks for value-based payment for health care providers, we developed an analogous framework for medical products, including drugs, devices, and diagnostic tools. We illustrate each of these types of alternative payment mechanisms and describe the conditions under which each may be useful. We discuss how the use of this framework can help track reforms, improve evidence, and advance policy analysis involving medical product payment.

Value-based arrangements may be more prevalent than assumed.

OBJECTIVES: To better understand the prevalence of US value-based payment arrangements (VBAs), their characteristics, and the factors that facilitate their success or act as barriers to their implementation. STUDY DESIGN: Surveys were administered to a convenience sample of subject matter experts who were senior representatives from payer organizations and biopharmaceutical manufacturers. These data were supplemented with qualitative interviews in a subsample of survey respondents. METHODS: Descriptive statistics, including percentages for categorical values and mean (SD) and median (interquartile range) for continuous variables, were assessed for quantitative questions. Trained reviewers collated responses to free-text survey questions and the qualitative interviews to identify themes. RESULTS: Of the 25 respondents, 1 manufacturer and 4 payers reported not having explored or negotiated any VBAs. Subsequently, questionnaire results from 11 biopharmaceutical manufacturers and 9 payers who had experience with VBAs were analyzed. More than 70% of VBAs implemented between 2014 and 2017 were not publicly disclosed. Furthermore, although consideration of VBAs as a coverage and payment tool is increasing, VBA implementation is relatively low, with manufacturers and payers reporting that approximately 33% and 60% of early dialogues translate into signed VBA contracts, respectively. Respondents' reasoning for VBA negotiation process breakdowns generally differed by sector and reflected each sector's respective priorities. CONCLUSIONS: This study reveals that the majority of VBAs are not publicly disclosed, which could underestimate their true prevalence and impact. Given the effort required to implement a VBA, future arrangements would likely benefit from a framework or other evaluative tool to help assess VBA pursuit desirability and guide the negotiation and implementation process.

Implementation of a Market Entry Reward within the United States.

As part of a multifactorial approach to address weak incentives for innovative antimicrobial drug development, market entry rewards (MERs) are an emerging solution. Recently, the Duke-Margolis Center for Health Policy released the Priority Antimicrobial Value and Entry (PAVE) Award proposal, which combines a MER with payment reforms, transitioning from volume-based to "value-based" payments for antimicrobials. Here, the PAVE Award and similar MERs are reviewed, focusing on further refinement and avenues for implementation.

Repairing the broken market for antibiotic innovation.

Multidrug-resistant bacterial diseases pose serious and growing threats to human health. While innovation is important to all areas of health research, it is uniquely important in antibiotics. Resistance destroys the fruit of prior research, making it necessary to constantly innovate to avoid falling back into a pre-antibiotic era. But investment is declining in antibiotics, driven by competition from older antibiotics, the cost and uncertainty of the development process, and limited reimbursement incentives. Good public health practices curb inappropriate antibiotic use, making return on investment challenging in payment systems based on sales volume. We assess the impact of recent initiatives to improve antibiotic innovation, reflecting experience with all sixty-seven new molecular entity antibiotics approved by the Food and Drug Administration since 1980. Our analysis incorporates data and insights derived from several multistakeholder initiatives under way involving governments and the private sector on both sides of the Atlantic. We propose three specific reforms that could revitalize innovations that protect public health, while promoting long-term sustainability: increased incentives for antibiotic research and development, surveillance, and stewardship; greater targeting of incentives to high-priority public health needs, including reimbursement that is delinked from volume of drug use; and enhanced global collaboration, including a global treaty.

Improving pharmaceutical innovation by building a more comprehensive database on drug development and use.

New drugs and biologics have had a tremendous impact on the treatment of many diseases. However, available measures suggest that pharmaceutical innovation has remained relatively flat, despite substantial growth in research and development spending. We review recent literature on pharmaceutical innovation to identify limitations in measuring and assessing innovation, and we describe the framework and collaborative approach we are using to develop more comprehensive, publicly available metrics for innovation. Our research teams at the Brookings Institution and Deerfield Institute are collaborating with experts from multiple areas of drug development and regulatory review to identify and collect comprehensive data elements related to key development and regulatory characteristics for each new molecular entity approved over the past several decades in the United States and the European Union. Subsequent phases of our effort will add data on downstream product use and patient outcomes and will also include drugs that have failed or been abandoned in development. Such a database will enable researchers to better analyze the drivers of drug innovation, trends in the output of new medicines, and the effect of policy efforts designed to improve innovation.

Utilizing data consortia to monitor safety and effectiveness of biosimilars and their innovator products.

BACKGROUND: The Biologics Price Competition and Innovation Act, introduced as part of the Affordable Care Act, directed the FDA to create an approval pathway for biologic products shown to be biosimilar or interchangeable with an FDA-approved innovator drug. These biosimilars will not be chemically identical to the reference agent. Investigational studies conducted with biosimilar agents will likely provide limited real-world evidence of their effectiveness and safety. How do we best monitor effectiveness and safety of biosimilar products once approved by the FDA and used more extensively by patients? OBJECTIVE: To determine the feasibility of developing a distributed research network that will use health insurance plan and health delivery system data to detect biosimilar safety and effectiveness signals early and be able to answer important managed care pharmacy questions from both the government and managed care organizations. METHODS: Twenty-one members of the AMCP Task Force on Biosimilar Collective Intelligence Systems met November 12, 2013, to discuss issues involved in designing this consortium and to explore next steps. RESULTS: The task force concluded that a managed care biosimilars research consortium would be of significant value. Task force members agreed that it is best to use a distributed research network structurally similar to existing DARTNet, HMO Research Network, and Mini-Sentinel consortia. However, for some surveillance projects that it undertakes, the task force recognizes it may need supplemental data from managed care and other sources (i.e., a "hybrid" structure model). CONCLUSIONS: The task force believes that AMCP is well positioned to lead the biosimilar-monitoring effort and that the next step to developing a biosimilar-innovator collective intelligence system is to convene an advisory council to address organizational governance.

Near-real-time monitoring of new drugs: an application comparing prasugrel versus clopidogrel.

BACKGROUND: Methods for near-real-time monitoring of new drugs in electronic healthcare data are needed. OBJECTIVE: In a novel application, we prospectively monitored ischemic, bleeding, and mortality outcomes among patients initiating prasugrel versus clopidogrel in routine care during the first 2 years following the approval of prasugrel. METHODS: Using the HealthCore Integrated Research Database, we conducted a prospective cohort study comparing prasugrel and clopidogrel initiators in the 6 months following the introduction of prasugrel and every 2 months thereafter. We identified patients who initiated antiplatelets within 14 days following discharge from hospitalizations for myocardial infarction (MI) or acute coronary syndrome. We matched patients using high-dimensional propensity scores (hd-PSs) and followed them for ischemic (i.e., MI and ischemic stroke) events, bleed (i.e., hemorrhagic stroke and gastrointestinal bleed) events, and all-cause mortality. For each outcome, we applied sequential alerting algorithms. RESULTS: We identified 1,282 eligible new users of prasugrel and 8,263 eligible new users of clopidogrel between September 2009 and August 2011. In hd-PS matched cohorts, the overall MI rate difference (RD) comparing prasugrel with clopidogrel was -23.1 (95 % confidence interval [CI] -62.8-16.7) events per 1,000 person-years and RDs were -0.5 (-12.9-11.9) and -2.8 (-13.2-7.6) for a composite bleed event outcome and death from any cause, respectively. No algorithms generated alerts for any outcomes. CONCLUSIONS: Near-real-time monitoring was feasible and, in contrast to the key pre-marketing trial that demonstrated the efficacy of prasugrel, did not suggest that prasugrel compared with clopidogrel was associated with an increased risk of gastrointestinal and intracranial bleeding.

Validity of diagnostic codes to identify cases of severe acute liver injury in the US Food and Drug Administration's Mini-Sentinel Distributed Database.

PURPOSE: The validity of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes to identify diagnoses of severe acute liver injury (SALI) is not well known. We examined the positive predictive values (PPVs) of hospital ICD-9-CM diagnoses in identifying SALI among health plan members in the Mini-Sentinel Distributed Database (MSDD) for patients without liver/biliary disease and for those with chronic liver disease (CLD). METHODS: We selected random samples of members (149 without liver/biliary disease; 75 with CLD) with a principal hospital diagnosis suggestive of SALI (ICD-9-CM 570, 572.2, 572.4, 572.8, 573.3, 573.8, or V42.7) in the MSDD (2009-2010). Medical records were reviewed by hepatologists to confirm SALI events. PPVs of codes and code combinations for confirmed SALI were determined by CLD status. RESULTS: Among 105 members with available records and no liver/biliary disease, SALI was confirmed in 26 (PPV, 24.7%; 95%CI, 16.9-34.1%). Combined hospital diagnoses of acute hepatic necrosis (570) and liver disease sequelae (572.8) had high PPV (100%; 95%CI, 59.0-100%) and identified 7/26 (26.9%) events. Among 46 CLD members with available records, SALI was confirmed in 19 (PPV, 41.3%; 95%CI, 27.0-56.8%). Acute hepatic necrosis (570) or hepatorenal syndrome (572.4) plus any other SALI code had a PPV of 83.3% (95%CI, 51.6-97.9%) and identified 10/19 (52.6%) events. CONCLUSIONS: Most individual hospital ICD-9-CM diagnoses had low PPV for confirmed SALI events. Select code combinations had high PPV but did not capture all events.

Amphetamines, atomoxetine and the risk of serious cardiovascular events in adults.

MAIN OBJECTIVE: To compare the incidence rates of serious cardiovascular events in adult initiators of amphetamines or atomoxetine to rates in non-users. METHODS: This was a retrospective cohort study of new amphetamines (n=38,586) or atomoxetine (n=20,995) users. Each medication user was matched to up to four non-users on age, gender, data source, and state (n=238,183). The following events were primary outcomes of interest 1) sudden death or ventricular arrhythmia, 2) stroke, 3) myocardial infarction, 4) a composite endpoint of stroke or myocardial infarction. Cox proportional hazard regression was used to calculate propensity-adjusted hazard ratios for amphetamines versus matched non-users and atomoxetine versus matched non-users, with intracluster dependence within matched sets accounted for using a robust sandwich estimator. RESULTS: The propensity-score adjusted hazard ratio for amphetamines use versus non-use was 1.18 (95% CI: 0.55-2.54) for sudden death/ventricular arrhythmia, 0.80 (95% CI: 0.44-1.47) for stroke, 0.75 (95% CI: 0.42-1.35) for myocardial infarction, and 0.78 (95% CI: 0.51-1.19) for stroke/myocardial infarction. The propensity-score adjusted hazard ratio for atomoxetine use versus non-use was 0.41 (95% CI: 0.10-1.75) for sudden death/ventricular arrhythmia, 1.30 (95% CI: 0.52-3.29) for stroke, 0.56 (95% CI: 0.16-2.00) for myocardial infarction, and 0.92 (95% CI: 0.44-1.92) for stroke/myocardial infarction. CONCLUSIONS: Initiation of amphetamines or atomoxetine was not associated with an elevated risk of serious cardiovascular events. However, some of the confidence intervals do not exclude modest elevated risks, e.g. for sudden death/ventricular arrhythmia.

Validation of acute myocardial infarction in the Food and Drug Administration's Mini-Sentinel program.

PURPOSE: To validate an algorithm based upon International Classification of Diseases, 9(th) revision, Clinical Modification (ICD-9-CM) codes for acute myocardial infarction (AMI) documented within the Mini-Sentinel Distributed Database (MSDD). METHODS: Using an ICD-9-CM-based algorithm (hospitalized patients with 410.x0 or 410.x1 in primary position), we identified a random sample of potential cases of AMI in 2009 from four Data Partners participating in the Mini-Sentinel Program. Cardiologist reviewers used information abstracted from hospital records to assess the likelihood of an AMI diagnosis based on criteria from the Joint European Society of Cardiology and American College of Cardiology Global Task Force. Positive predictive values (PPVs) of the ICD-9-based algorithm were calculated. RESULTS: Of the 153 potential cases of AMI identified, hospital records for 143 (93%) were retrieved and abstracted. Overall, the PPV was 86.0% (95% confidence interval; 79.2%, 91.2%). PPVs ranged from 76.3% to 94.3% across the four Data Partners. CONCLUSIONS: The overall PPV of potential AMI cases, as identified using an ICD-9-CM-based algorithm, may be acceptable for safety surveillance; however, PPVs do vary across Data Partners. This validation effort provides a contemporary estimate of the reliability of this algorithm for use in future surveillance efforts conducted using the Food and Drug Administration's MSDD.

Supplementing claims data with outpatient laboratory test results to improve confounding adjustment in effectiveness studies of lipid-lowering treatments.

BACKGROUND: Adjusting for laboratory test results may result in better confounding control when added to administrative claims data in the study of treatment effects. However, missing values can arise through several mechanisms. METHODS: We studied the relationship between availability of outpatient lab test results, lab values, and patient and system characteristics in a large healthcare database using LDL, HDL, and HbA1c in a cohort of initiators of statins or Vytorin (ezetimibe & simvastatin) as examples. RESULTS: Among 703,484 patients 68% had at least one lab test performed in the 6 months before treatment. Performing an LDL test was negatively associated with several patient characteristics, including recent hospitalization (OR = 0.32, 95% CI: 0.29-0.34), MI (OR = 0.77, 95% CI: 0.69-0.85), or carotid revascularization (OR = 0.37, 95% CI: 0.25-0.53). Patient demographics, diagnoses, and procedures predicted well who would have a lab test performed (AUC = 0.89 to 0.93). Among those with test results available claims data explained only 14% of variation. CONCLUSIONS: In a claims database linked with outpatient lab test results, we found that lab tests are performed selectively corresponding to current treatment guidelines. Poor ability to predict lab values and the high proportion of missingness reduces the added value of lab tests for effectiveness research in this setting.

Characterizing vaccine-associated risks using cubic smoothing splines.

Estimating risks associated with the use of childhood vaccines is challenging. The authors propose a new approach for studying short-term vaccine-related risks. The method uses a cubic smoothing spline to flexibly estimate the daily risk of an event after vaccination. The predicted incidence rates from the spline regression are then compared with the expected rates under a log-linear trend that excludes the days surrounding vaccination. The 2 models are then used to estimate the excess cumulative incidence attributable to the vaccination during the 42-day period after vaccination. Confidence intervals are obtained using a model-based bootstrap procedure. The method is applied to a study of known effects (positive controls) and expected noneffects (negative controls) of the measles, mumps, and rubella and measles, mumps, rubella, and varicella vaccines among children who are 1 year of age. The splines revealed well-resolved spikes in fever, rash, and adenopathy diagnoses, with the maximum incidence occurring between 9 and 11 days after vaccination. For the negative control outcomes, the spline model yielded a predicted incidence more consistent with the modeled day-specific risks, although there was evidence of increased risk of diagnoses of congenital malformations after vaccination, possibly because of a "provider visit effect." The proposed approach may be useful for vaccine safety surveillance.

Patterns of bone density evaluation in a community population treated with aromatase inhibitors.

Aromatase inhibitors (AIs) increase the risk of bone loss and fracture. Guidelines recommend routine bone density screening for women on AIs, but there are few data regarding the incorporation of these guidelines into clinical practice. We assessed bone density testing in a community-based cohort of breast cancer patients treated with AIs. By means of encounter and pharmacy data from WellPoint plans in the HealthCore Integrated Research Database, we assessed bone density testing among 9,138 women aged ≥50 years with breast cancer who were treated with AIs between 2002 and 2008. We used multivariable logistic regression to identify factors associated with baseline bone density testing in women initiating an AI, and among a subset of 2,086 women treated with AIs for at least 2 years, with testing during the first 2 years of therapy. Only 41.6 % of women underwent bone density testing when initiating AI therapy. Rates of bone density testing increased over time, but were lower for women who were older, lived in the Northeast (vs. other regions), had been treated with prior proton pump inhibitor or tamoxifen therapy, lived in areas with lower educational attainment, or were enrolled in a health maintenance organization (vs. other insurance types) (all P < 0.05). Among women treated with AIs for at least 2 years, 59.9 % of women underwent bone density testing during the first 2 years of AI therapy. Rates of testing were lower for women living in the Midwest or West (vs. Northeast), living in areas with lower education levels, enrolled in health maintenance organizations (vs. other insurance types), and with prior tamoxifen use. In conclusion, most women initiating AI therapy, and 40 % of those on long-term therapy, did not undergo recommended bone density evaluation in this community-based population. Attention is needed to insure that unnecessary fractures are avoided in breast cancer patients taking AIs.

Validation of a claims-based diagnostic code for Stevens-Johnson syndrome in a commercially insured population.

PURPOSE: To validate the administrative claims identification of a diagnosis of Stevens-Johnson syndrome (SJS) using medical records as the "gold standard" in a large, commercially insured US population. METHODS: Patients with >1 medical claim with the International Classification of Diseases, Ninth Revision, Clinical Modification code 695.1x between 1 July 2000 and 31 May 2007 were queried in the HealthCore Integrated Research Database(SM) , which contains administrative claims data for 14 commercial health insurance plans. Trained nurses and pharmacists abstracted pertinent information from the identified patients' medical records, which were then reviewed by two independent dermatologists to identify criteria to determine SJS diagnosis. Positive predictive values (PPVs) based on the claims and chart data were computed for all the cases. RESULTS: Medical charts for 200 claims-identified cases, with the International Classification of Diseases, Ninth Revision, Clinical Modification code 695.1x, were abstracted and reviewed by the dermatologists. A total of five cases (PPV = 2.50%, 95%CI = 0.8%-5.7%) were determined to be SJS with clinical certainty. PPVs varied with data stratification: PPV for inpatient claims only (PPV = 2.00%, 95%CI = 0.24%-7.04%), inpatient claims with 695.1x in first diagnosis field (PPV = 4.11%, 95%CI = 0.86%-11.54%), and final decisions of either clinical certainty or probable cases of SJS (PPV = 6.00%, 95%CI = 3.14%-10.25%). CONCLUSION: These findings demonstrate the difficulties associated with identifying rare disorders, which lack specific diagnostic criteria, within administrative claims databases. They underscore the challenges of using claims data to monitor ill-defined clinical conditions as well as the need to validate claims-identified cases with information from other sources, such as medical charts. Copyright © 2012 John Wiley & Sons, Ltd.

Early steps in the development of a claims-based targeted healthcare safety monitoring system and application to three empirical examples.

BACKGROUND: Several efforts are under way to develop and test methods for prospective drug safety monitoring using large, electronic claims databases. Prospective monitoring systems must incorporate signalling algorithms and techniques to mitigate confounding in order to minimize false positive and false negative signals due to chance and bias. OBJECTIVE: The aim of the study was to describe a prototypical targeted active safety monitoring system and apply the framework to three empirical examples. METHODS: We performed sequential, targeted safety monitoring in three known drug/adverse event (AE) pairs: (i) paroxetine/upper gastrointestinal (UGI) bleed; (ii) lisinopril/angioedema; (iii) ciprofloxacin/Achilles tendon rupture (ATR). Data on new users of the drugs of interest were extracted from the HealthCore Integrated Research Database. New users were matched by propensity score to new users of comparator drugs in each example. Analyses were conducted sequentially to emulate prospective monitoring. Two signalling rules--a maximum sequential probability ratio test and an effect estimate-based approach--were applied to sequential, matched cohorts to identify signals within the system. RESULTS: Signals were identified for all three examples: paroxetine/UGI bleed in the seventh monitoring cycle, within 2 calendar years of sequential data; lisinopril/angioedema in the second cycle, within the first monitoring year; ciprofloxacin/ATR in the tenth cycle, within the fifth year. CONCLUSION: In this proof of concept, our targeted, active monitoring system provides an alternative to systems currently in the literature. Our system employs a sequential, propensity score-matched framework and signalling rules for prospective drug safety monitoring and identified signals for all three adverse drug reactions evaluated.

Immune globulins and thrombotic adverse events as recorded in a large administrative database in 2008 through 2010.

BACKGROUND: Thrombotic events (TEs) are rare but often serious adverse events that could occur after administration of immune globulin (IG) products. Our study objective was to assess occurrence of recorded TEs after administration of different US-licensed IG products and investigate potential risk factors using a large administrative database. STUDY DESIGN AND METHODS: This is a retrospective claims-based cohort study of individuals exposed to IG products from January 1, 2008, through September 30, 2010, using HealthCore's Integrated Research Database, a longitudinal health care database. IG products were identified by recorded Healthcare Common Procedure Coding System codes. TEs were ascertained via International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for same-day TEs by IG product, while controlling for confounders. RESULTS: Of 11,785 individuals exposed to IG products in the study period, 122 (1%) had TE(s) recorded on the same day as IG administration. TE rates per 1000 persons exposed ranged from 6.1 to 20.5 for different IG product groups. Vivaglobin users had an increased same-day TE risk compared to reference Gammagard Liquid users (OR, 3.56; 95% CI, 1.54-8.23). An increased TE risk was also found with older age (≥ 45 years), prior TE(s), and hypercoagulable state(s). CONCLUSION: The study suggests potentially elevated TE rates for different IG products, including subcutaneous. It also identifies important recipient TE risk factors and suggests that risk-benefit profiles should be weighed before IG administration. The observed differences may be due to various factors such as dosage, administration rates, and product manufacturing processes that warrant further evaluation.