Unaddressed Uncertainties When Scaling Regional Aircraft Emission Surveys to Basin Emission Estimates.

Wide-area aerial methods provide comprehensive screening of methane emissions from oil and gas (O & G) facilities in production basins. Emission detections ("plumes") from these studies are also frequently scaled to the basin level, but little is known regarding the uncertainties during scaling. This study analyzed an aircraft field study in the Denver-Julesburg basin to quantify how often plumes identified maintenance events, using a geospatial inventory of 12,629 O & G facilities. Study partners (7 midstream and production operators) provided the timing and location of 5910 maintenance events during the 6 week study period. Results indicated three substantial uncertainties with potential bias that were unaddressed in prior studies. First, plumes often detect maintenance events, which are large, short-duration, and poorly estimated by aircraft methods: 9.2 to 46% (38 to 52%) of plumes on production were likely known maintenance events. Second, plumes on midstream facilities were both infrequent and unpredictable, calling into question whether these estimates were representative of midstream emissions. Finally, 4 plumes attributed to O & G (19% of emissions detected by aircraft) were not aligned with any O & G location, indicating that the emissions had drifted downwind of some source. It is unclear how accurately aircraft methods estimate this type of plume; in this study, it had material impact on emission estimates. While aircraft surveys remain a powerful tool for identifying methane emissions on O & G facilities, this study indicates that additional data inputs, e.g., detailed GIS data, a more nuanced analysis of emission persistence and frequency, and improved sampling strategies are required to accurately scale plume estimates to basin emissions.

AirPen: A Wearable Monitor for Characterizing Exposures to Particulate Matter and Volatile Organic Compounds.

Exposure to air pollution is a leading risk factor for disease and premature death, but technologies for assessing personal exposure to particulate and gaseous air pollutants, including the timing and location of such exposures, are limited. We developed a small, quiet, wearable monitor, called the AirPen, to quantify personal exposures to fine particulate matter (PM2.5) and volatile organic compounds (VOCs). The AirPen combines physical sample collection (PM onto a filter and VOCs onto a sorbent tube) with a suite of low-cost sensors (for PM, VOCs, temperature, pressure, humidity, light intensity, location, and motion). We validated the AirPen against conventional personal sampling equipment in the laboratory and then conducted a field study to measure at-work and away-from-work exposures to PM2.5 and VOCs among employees at an agricultural facility in Colorado, USA. The resultant sampling and sensor data indicated that personal exposures to benzene, toluene, ethylbenzene, and xylenes were dominated by a specific workplace location. These results illustrate how the AirPen can be used to advance our understanding of personal exposure to air pollution as a function of time, location, source, and activity, even in the absence of detailed activity diary data.

Effects of household and participant characteristics on personal exposure and kitchen concentration of fine particulate matter and black carbon in rural Honduras.

Traditional cooking with solid fuels (biomass, animal dung, charcoals, coal) creates household air pollution that leads to millions of premature deaths and disability worldwide each year. Exposure to household air pollution is highest in low- and middle-income countries. Using data from a stepped-wedge randomized controlled trial of a cookstove intervention among 230 households in Honduras, we analyzed the impact of household and personal variables on repeated 24-h measurements of fine particulate matter (PM2.5) and black carbon (BC) exposure. Six measurements were collected approximately six-months apart over the course of the three-year study. Multivariable mixed models explained 37% of variation in personal PM2.5 exposure and 49% of variation in kitchen PM2.5 concentrations. Additionally, multivariable models explained 37% and 47% of variation in personal and kitchen BC concentrations, respectively. Stove type, season, presence of electricity, primary stove location, kitchen enclosure type, stove use time, and presence of kerosene for lighting were all associated with differences in geometric mean exposures. Stove type explained the most variability of the included variables. In future studies of household air pollution, tracking the cooking behaviors and daily activities of participants, including outdoor exposures, may explain exposure variation beyond the household and personal variables considered here.

Design and Testing of a Low-Cost Sensor and Sampling Platform for Indoor Air Quality.

Americans spend most of their time indoors at home, but comprehensive characterization of in-home air pollution is limited by the cost and size of reference-quality monitors. We assembled small "Home Health Boxes" (HHBs) to measure indoor PM2.5, PM10, CO2, CO, NO2, and O3 concentrations using filter samplers and low-cost sensors. Nine HHBs were collocated with reference monitors in the kitchen of an occupied home in Fort Collins, Colorado, USA for 168 h while wildfire smoke impacted local air quality. When HHB data were interpreted using gas sensor manufacturers' calibrations, HHBs and reference monitors (a) categorized the level of each gaseous pollutant similarly (as either low, elevated, or high relative to air quality standards) and (b) both indicated that gas cooking burners were the dominant source of CO and NO2 pollution; however, HHB and reference O3 data were not correlated. When HHB gas sensor data were interpreted using linear mixed calibration models derived via collocation with reference monitors, root-mean-square error decreased for CO2 (from 408 to 58 ppm), CO (645 to 572 ppb), NO2 (22 to 14 ppb), and O3 (21 to 7 ppb); additionally, correlation between HHB and reference O3 data improved (Pearson's r increased from 0.02 to 0.75). Mean 168-h PM2.5 and PM10 concentrations derived from nine filter samples were 19.4 µg m-3 (6.1% relative standard deviation [RSD]) and 40.1 µg m-3 (7.6% RSD). The 168-h PM2.5 concentration was overestimated by PMS5003 sensors (median sensor/filter ratio = 1.7) and underestimated slightly by SPS30 sensors (median sensor/filter ratio = 0.91).

Estimating the Clinical Pipeline of Cell and Gene Therapies and Their Potential Economic Impact on the US Healthcare System.

OBJECTIVES: To estimate, at the indication level, durable gene and cellular therapy new product launches in the United States through 2030, and the number of treated patients. METHODS: A statistical analysis of clinical trials pipeline data and disease incidence and prevalence was conducted to estimate the impact of new cell and gene therapies. We used Citeline's® Pharmaprojects® database to estimate the rates and timing of new product launches, on the basis of the phase of development, duration in phase, and probability of progression. Disease incidence and prevalence data were combined with estimates of market adoption to project the size of reimbursed patient populations. RESULTS: We project that about 350 000 patients will have been treated with 30 to 60 products by 2030. About half the launches are expected to be in B-cell (CD-19) lymphomas and leukemias. CONCLUSIONS: Cell and gene therapies promise durable clinical benefit from a single treatment course. High upfront reimbursement for these products means that the total costs could exceed what the healthcare system can manage. This creates a need for precision financing solutions and new reimbursement models that can ensure appropriate patient access to needed treatments, increase affordability for payers, and sustain private investment in innovation.

Estimating Years of Life Lost Due to Cardiovascular Disease in Japan.

BACKGROUND: In Japan, the burden associated with myocardial infarction (MI) and ischemic stroke as well as atherosclerotic cardiovascular disease (ASCVD) generally is high. One key element in measuring disease burden is years of life lost (YLL). The aim of this study was to understand the burden of these diseases by estimating YLL at an overall disease level and average person-YLL (PYLL), a measure of disease burden also used in prior studies. Methods and Results: Because calculation of YLL and PYLL involves inputs such as disease prevalence, disease-related mortality by age, and general population mortality by age and sex, we searched public databases of disease surveillance to identify comprehensive Japanese-specific inputs. For our reference analysis, disease-specific prevalence and mortality were taken from the Institute for Health Metrics and Evaluation Global Disease Burden study, and background mortality data were from the Japanese life tables published by the Ministry of Health, Labour and Welfare. The average age of patients with MI or stroke was 74 and 70 years, respectively. On average, men comprised 59% and 54% of the MI and stroke population, respectively. The disease-level burden of ASCVD (inclusive of MI, stroke, and peripheral artery disease) was 2,703,711 YLL in 2017. The patient-level burden was 11.99 PYLL for MI and 9.39 PYLL for stroke. CONCLUSIONS: The burden of ASCVD, MI, and stroke in terms of premature mortality is substantial in Japan, both on a population disease level and an individual patient level.

Study protocol for a stepped-wedge randomized cookstove intervention in rural Honduras: household air pollution and cardiometabolic health.

BACKGROUND: Growing evidence links household air pollution exposure from biomass-burning cookstoves to cardiometabolic disease risk. Few randomized controlled interventions of cookstoves (biomass or otherwise) have quantitatively characterized changes in exposure and indicators of cardiometabolic health, a growing and understudied burden in low- and middle-income countries (LMICs). Ideally, the solution is to transition households to clean cooking, such as with electric or liquefied petroleum gas stoves; however, those unable to afford or to access these options will continue to burn biomass for the foreseeable future. Wood-burning cookstove designs such as the Justa (incorporating an engineered combustion zone and chimney) have the potential to substantially reduce air pollution exposures. Previous cookstove intervention studies have been limited by stove types that did not substantially reduce exposures and/or by low cookstove adoption and sustained use, and few studies have incorporated community-engaged approaches to enhance the intervention. METHODS/DESIGN: We conducted an individual-level, stepped-wedge randomized controlled trial with the Justa cookstove intervention in rural Honduras. We enrolled 230 female primary cooks who were not pregnant, non-smoking, aged 24-59 years old, and used traditional wood-burning cookstoves at baseline. A community advisory board guided survey development and communication with participants, including recruitment and retention strategies. Over a 3-year study period, participants completed 6 study visits approximately 6 months apart. Half of the women received the Justa after visit 2 and half after visit 4. At each visit, we measured 24-h gravimetric personal and kitchen fine particulate matter (PM2.5) concentrations, qualitative and quantitative cookstove use and adoption metrics, and indicators of cardiometabolic health. The primary health endpoints were blood pressure, C-reactive protein, and glycated hemoglobin. Overall study goals are to explore barriers and enablers of new cookstove adoption and sustained use, compare health endpoints by assigned cookstove type, and explore the exposure-response associations between PM2.5 and indicators of cardiometabolic health. DISCUSSION: This trial, utilizing an economically feasible, community-vetted cookstove and evaluating endpoints relevant for the major causes of morbidity and mortality in LMICs, will provide critical information for household air pollution stakeholders globally. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT02658383 , posted January 18, 2016, field work completed May 2018. Official title, "Community-Based Participatory Research: A Tool to Advance Cookstove Interventions." Principal Investigator Maggie L. Clark, Ph.D. Last update posted July 12, 2018.

Solid-Phase Extraction Coupled to a Paper-Based Technique for Trace Copper Detection in Drinking Water.

Metal contamination of natural and drinking water systems poses hazards to public and environmental health. Quantifying metal concentrations in water typically requires sample collection in the field followed by expensive laboratory analysis that can take days to weeks to obtain results. The objective of this work was to develop a low-cost, field-deployable method to quantify trace levels of copper in drinking water by coupling solid-phase extraction/preconcentration with a microfluidic paper-based analytical device. This method has the advantages of being hand-powered (instrument-free) and using a simple "read by eye" quantification motif (based on color distance). Tap water samples collected across Fort Collins, CO, were tested with this method and validated against ICP-MS. We demonstrate the ability to quantify the copper content of tap water within 30% of a reference technique at levels ranging from 20 to 500 000 ppb. The application of this technology, which should be sufficient as a rapid screening tool, can lead to faster, more cost-effective detection of soluble metals in water systems.

Personal Exposure to PM2.5 Black Carbon and Aerosol Oxidative Potential using an Automated Microenvironmental Aerosol Sampler (AMAS).

Traditional methods for measuring personal exposure to fine particulate matter (PM2.5) are cumbersome and lack spatiotemporal resolution; methods that are time-resolved are limited to a single species/component of PM. To address these limitations, we developed an automated microenvironmental aerosol sampler (AMAS), capable of resolving personal exposure by microenvironment. The AMAS is a wearable device that uses a GPS sensor algorithm in conjunction with a custom valve manifold to sample PM2.5 onto distinct filter channels to evaluate home, school, and other (e.g., outdoors, in transit, etc.) exposures. Pilot testing was conducted in Fresno, CA where 25 high-school participants ( n = 37 sampling events) wore an AMAS for 48-h periods in November 2016. Data from 20 (54%) of the 48-h samples collected by participants were deemed valid and the filters were analyzed for PM2.5 black carbon (BC) using light transmissometry and aerosol oxidative potential (OP) using the dithiothreitol (DTT) assay. The amount of inhaled PM2.5 was calculated for each microenvironment to evaluate the health risks associated with exposure. On average, the estimated amount of inhaled PM2.5 BC (µg day-1) and OP [(µM min-1) day-1] was greatest at home, owing to the proportion of time spent within that microenvironment. Validation of the AMAS demonstrated good relative precision (8.7% among collocated instruments) and a mean absolute error of 22% for BC and 33% for OP when compared to a traditional personal sampling instrument. This work demonstrates the feasibility of new technology designed to quantify personal exposure to PM2.5 species within distinct microenvironments.

Paper-based analytical devices for environmental analysis.

The field of paper-based microfluidics has experienced rapid growth over the past decade. Microfluidic paper-based analytical devices (µPADs), originally developed for point-of-care medical diagnostics in resource-limited settings, are now being applied in new areas, such as environmental analyses. Low-cost paper sensors show great promise for on-site environmental analysis; the theme of ongoing research complements existing instrumental techniques by providing high spatial and temporal resolution for environmental monitoring. This review highlights recent applications of µPADs for environmental analysis along with technical advances that may enable µPADs to be more widely implemented in field testing.

Methane Emissions from the Natural Gas Transmission and Storage System in the United States.

The recent growth in production and utilization of natural gas offers potential climate benefits, but those benefits depend on lifecycle emissions of methane, the primary component of natural gas and a potent greenhouse gas. This study estimates methane emissions from the transmission and storage (T&S) sector of the United States natural gas industry using new data collected during 2012, including 2,292 onsite measurements, additional emissions data from 677 facilities and activity data from 922 facilities. The largest emission sources were fugitive emissions from certain compressor-related equipment and "super-emitter" facilities. We estimate total methane emissions from the T&S sector at 1,503 [1,220 to 1,950] Gg/yr (95% confidence interval) compared to the 2012 Environmental Protection Agency's Greenhouse Gas Inventory (GHGI) estimate of 2,071 [1,680 to 2,690] Gg/yr. While the overlap in confidence intervals indicates that the difference is not statistically significant, this is the result of several significant, but offsetting, factors. Factors which reduce the study estimate include a lower estimated facility count, a shift away from engines toward lower-emitting turbine and electric compressor drivers, and reductions in the usage of gas-driven pneumatic devices. Factors that increase the study estimate relative to the GHGI include updated emission rates in certain emission categories and explicit treatment of skewed emissions at both component and facility levels. For T&S stations that are required to report to the EPA's Greenhouse Gas Reporting Program (GHGRP), this study estimates total emissions to be 260% [215% to 330%] of the reportable emissions for these stations, primarily due to the inclusion of emission sources that are not reported under the GHGRP rules, updated emission factors, and super-emitter emissions.

Population preference values for health states in relapsed or refractory B-precursor acute lymphoblastic leukemia in the United Kingdom.

BACKGROUND: To date, reliable and comprehensive health-related quality of life data for patients with relapsed or refractory B-precursor acute lymphoblastic leukemia (ALL) have not been collected in clinical trials of the disease, and no utility studies have been published. The purpose of this study was to define and validate health states experienced by adults with relapsed/refractory B-precursor ALL, and to assign utility values to these health states using time-trade off methodology. METHODS: This study was conducted in the UK in three phases. In the first phase, five health state descriptions were developed based on a recent clinical trial. The second phase validated the health state descriptions with clinicians and patients with experience of relapsed/refractory B-precursor ALL. The third phase involved prospective health state valuation using time-trade off methodology in a sample of the general public. The study was approved by the UK National Health Service Research Ethics Committee. RESULTS: In total, 123 participants were recruited and included in the final analysis; all participants gave written, informed consent. Complete remission was the most preferred health state (mean utility [SEM], 0.86 [0.01]), followed by complete remission with partial hematological recovery (with minimal risk of bleeding or developing infection) (0.75 [0.02]); aplastic bone marrow (0.59 [0.02]); partial remission (0.50 [0.03]); and progressive disease (0.30 [0.04]). CONCLUSIONS: This is the first study to report utility values for health states associated with relapsed/refractory B-precursor ALL. It was designed and conducted to align with NICE guidance on alternative methods for generating health state utility values when EQ-5D data are either unavailable or inappropriate. These utilities can be applied in future cost-effectiveness analyses of treatment for relapsed/refractory B-precursor ALL.

Metadata Correction: Internet Search and Krokodil in the Russian Federation: An Infoveillance Study.

[This corrects the article DOI: .].

Internet search and krokodil in the Russian Federation: an infoveillance study.

BACKGROUND: Krokodil is an informal term for a cheap injectable illicit drug domestically prepared from codeine-containing medication (CCM). The method of krokodil preparation may produce desomorphine as well as toxic reactants that cause extensive tissue necrosis. The first confirmed report of krokodil use in Russia took place in 2004. In 2012, reports of krokodil-related injection injuries began to appear beyond Russia in Western Europe and the United States. OBJECTIVE: This exploratory study had two main objectives: (1) to determine if Internet search patterns could detect regularities in behavioral responses to Russian CCM policy at the population level, and (2) to determine if complementary data sources could explain the regularities we observed. METHODS: First, we obtained krokodil-related search pattern data for each Russia subregion (oblast) between 2011 and 2012. Second, we analyzed several complementary data sources included krokodil-related court cases, and related search terms on both Google and Yandex to evaluate the characteristics of terms accompanying krokodil-related search queries. RESULTS: In the 6 months preceding CCM sales restrictions, 21 of Russia's 83 oblasts had search rates higher than the national average (mean) of 16.67 searches per 100,000 population for terms associated with krokodil. In the 6 months following restrictions, mean national searches dropped to 9.65 per 100,000. Further, the number of oblasts recording a higher than average search rate dropped from 30 to 16. Second, we found krokodil-related court appearances were moderately positively correlated (Spearman correlation=.506, P≤.001) with behaviors consistent with an interest in the production and use of krokodil across Russia. Finally, Google Trends and Google and Yandex related terms suggested consistent public interest in the production and use of krokodil as well as for CCM as analgesic medication during the date range covered by this study. CONCLUSIONS: Illicit drug use data are generally regarded as difficult to obtain through traditional survey methods. Our analysis suggests it is plausible that Yandex search behavior served as a proxy for patterns of krokodil production and use during the date range we investigated. More generally, this study demonstrates the application of novel methods recently used by policy makers to both monitor illicit drug use and influence drug policy decision making.

Association of ambient air pollution and pesticide mixtures on respiratory inflammatory markers in agricultural communities.

Air pollution exposure is associated with adverse respiratory health outcomes. Evidence from occupational and community-based studies also suggests agricultural pesticides have negative health impacts on respiratory health. Although populations are exposed to multiple inhalation hazards simultaneously, multidomain mixtures (e.g. environmental and chemical pollutants of different classes) are rarely studied. We investigated the association of ambient air pollution-pesticide exposure mixtures with urinary leukotriene E4 (LTE4), a respiratory inflammation biomarker, for 75 participants in four Central California communities over two seasons. Exposures included three criteria air pollutants estimated via the Community Multiscale Air Quality model (fine particulate matter, ozone, and nitrogen dioxide) and urinary metabolites of organophosphate (OP) pesticides (total dialkyl phosphates (DAPs), total diethyl phosphates (DE), and total dimethyl phosphates (DM)). We implemented multiple linear regression models to examine associations in single pollutant models adjusted for age, sex, asthma status, occupational status, household member occupational status, temperature, and relative humidity, and evaluated whether associations changed seasonally. We then implemented Bayesian kernel machine regression (BKMR) to analyse these criteria air pollutants, DE, and DM as a mixture. Our multiple linear regression models indicated an interquartile range (IQR) increase in total DAPs was associated with an increase in urinary LTE4 in winter (ß: 0.04, 95% CI: [0.01, 0.07]). Similarly, an IQR increase in total DM was associated with an increase in urinary LTE4 in winter (ß:0.03, 95% CI: [0.004, 0.06]). Confidence intervals for all criteria air pollutant effect estimates included the null value. BKMR analysis revealed potential non-linear interactions between exposures in our air pollution-pesticide mixture, but all confidence intervals contained the null value. Our analysis demonstrated a positive association between OP pesticide metabolites and urinary LTE4 in a low asthma prevalence population and adds to the limited research on the joint effects of ambient air pollution and pesticides mixtures on respiratory health.

Impact of randomly assigned "pay-as-you-go" liquefied petroleum gas prices on energy use for cooking: Experimental pilot evidence from rural Rwanda.

The disease burden related to air pollution from traditional solid-fuel cooking practices in low- and middle-income countries impacts millions of people globally. Although the use of liquefied petroleum gas (LPG) fuel for cooking can meaningfully reduce household air pollution concentrations, major barriers, including affordability and accessibility, have limited widespread adoption. Using a randomized controlled trial, our objective was to evaluate the association between the cost and use of LPG among 23 rural Rwandan households. We provided a 2-burner LPG stove with accessories and incorporated a "pay-as-you-go" (PAYG) LPG service model that included fuel delivery. PAYG services remove the large up-front cost of cylinder refills by integrating "smart meter" technology that allows participants to pay in incremental amounts, as needed. We assigned three randomized discounted prices for LPG to each household at ~4-week intervals over a 12-week period. We modeled the relationship between randomized PAYG LPG price and use (standardized to monthly periods), analyzing effect modification by relative household wealth. A 1000 Rwandan Franc (about 1 USD at the time of the study) increase in LPG price/kg was associated with a 4.1 kg/month decrease in use (95% confidence interval [CI]: -6.7, -1.6; n=69 observations). Wealth modified this association; we observed a 9.7 kg/month reduction (95% CI: -14.8, -4.5) among wealthier households and a 2.5 kg/month reduction (95% CI: -5.3, 0.3) among lower-wealth households (p-interaction=0.01). The difference in price sensitivity was driven by higher LPG use among wealthier households at more heavily discounted prices; from an 80% to 10% discount, wealthy households used 17.5 to 5.3 kg/month and less wealthy households used 6.2 to 3.1 kg/month. Our pilot-level experimental evidence of PAYG LPG in a rural low-resource setting suggests that further exploration of subsidized pricing varied by household wealth is needed to ensure future policy initiatives can achieve targets without exacerbating inequities.

Internet search patterns of human immunodeficiency virus and the digital divide in the Russian Federation: infoveillance study.

BACKGROUND: Human immunodeficiency virus (HIV) is a serious health problem in the Russian Federation. However, the true scale of HIV in Russia has long been the subject of considerable debate. Using digital surveillance to monitor diseases has become increasingly popular in high income countries. But Internet users may not be representative of overall populations, and the characteristics of the Internet-using population cannot be directly ascertained from search pattern data. This exploratory infoveillance study examined if Internet search patterns can be used for disease surveillance in a large middle-income country with a dispersed population. OBJECTIVE: This study had two main objectives: (1) to validate Internet search patterns against national HIV prevalence data, and (2) to investigate the relationship between search patterns and the determinants of Internet access. METHODS: We first assessed whether online surveillance is a valid and reliable method for monitoring HIV in the Russian Federation. Yandex and Google both provided tools to study search patterns in the Russian Federation. We evaluated the relationship between both Yandex and Google aggregated search patterns and HIV prevalence in 2011 at national and regional tiers. Second, we analyzed the determinants of Internet access to determine the extent to which they explained regional variations in searches for the Russian terms for "HIV" and "AIDS". We sought to extend understanding of the characteristics of Internet searching populations by data matching the determinants of Internet access (age, education, income, broadband access price, and urbanization ratios) and searches for the term "HIV" using principal component analysis (PCA). RESULTS: We found generally strong correlations between HIV prevalence and searches for the terms "HIV" and "AIDS". National correlations for Yandex searches for "HIV" were very strongly correlated with HIV prevalence (Spearman rank-order coefficient [rs]=.881, P ≤ .001) and strongly correlated for "AIDS" (rs = .714, P ≤ .001). The strength of correlations varied across Russian regions. National correlations in Google for the term "HIV" (rs = .672, P = .004) and "AIDS" (rs = .584, P ≤ .001) were weaker than for Yandex. Second, we examined the relationship between the determinants of Internet access and search patterns for the term "HIV" across Russia using PCA. At the national level, we found Principal Component 1 loadings, including age (-0.56), HIV search (-0.533), and education (-0.479) contributed 32% of the variance. Principal Component 2 contributed 22% of national variance (income, -0.652 and broadband price, -0.460). CONCLUSIONS: This study contributes to the methodological literature on search patterns in public health. Based on our preliminary research, we suggest that PCA may be used to evaluate the relationship between the determinants of Internet access and searches for health problems beyond high-income countries. We believe it is in middle-income countries that search methods can make the greatest contribution to public health.

A new tool for system building.

A hybrid deal is an innovative type of joint venture between for-profit and not-for-profit entities designed for the purpose of improving healthcare delivery in a mutually accretive manner. Not-for-profit health systems, in particular, find hybrid deals attractive because these systems typically take a minority stake in the venture, requiring significantly less capital investment from not-for-profits than an outright acquisition. Hybrid deals allow not-for-profits to preserve capital for other needs while often maintaining some level of governance.

Medicaid best price reforms to enable innovative payment models for cell and gene therapies.

BACKGROUND: Cell and gene therapies promise durable benefits but face financial challenges from the uncertainty in their performance. Value-based purchasing arrangements (VBPAs) can address uncertainty but have been inhibited in the US by the Medicaid Drug Rebate Program (MDRP) approach to determining Medicaid Best Price (MBP) rebates. The likely effectiveness of MDRP reform proposals enabling VBPAs is examined in this study for durable cell and gene therapies. METHODS: Monte Carlo simulations examined three potential reforms (Multiple Best Prices, Bundled Sales, and National Pooling) to determine the impact on payment misalignment, the required payer size to participate, and the percentage of total lives covered by a VBPA. RESULTS: Simulation results suggest that 11% to 54% of commercial US lives would be feasibly covered by a VBPA depending on reform type and condition size. MPB reform achieved the highest commercial contracted percentage and lowest misalignment for commercial payers compared to National Pooling and Bundled Sales. State Medicaid plan results suggest lower extreme misalignment across all successfully contracted instances than commercial payers. CONCLUSIONS: The Multiple Best Prices will likely enable VBPAs for many durable cell and gene therapies and larger payers. Further reforms may be needed to extend VBPAs to ultra-orphan conditions.

Value-based performance arrangements for chronic conditions: an economic simulation of Medicaid Drug Rebate Program reforms.

OBJECTIVE: Changes to the Medicaid Drug Rebate Program (MDRP) determination of Medicaid Best Price (MBP) enables Value-based purchasing arrangements (VBPAs) to address financial uncertainty. This study estimates the likely effectiveness of MDRP-enabled VBPAs for chronically dosed medicines. METHODS: Monte Carlo simulations examined: Multiple Best Prices and Bundled Sales MBP approaches authorized under MDRP and a third National Pooling approach using payment misalignment; needed payer size for practical participation; and the resulting potential number of covered lives under a VBPA as evaluation metrics. RESULTS: Both Multiple Best Prices and National Pooling enable VBPAs for 95% of scenarios (including all 5i chronic products with ≥1,000 treated patients per year), with 75% of those with payment misalignment ≤9%. National pooling for retail drugs has less participation and worse misalignment (5i: 95% contracted, 75% ≤9% misalignment; retail: 71%, 66%). Bundled Sales performed worst (5i: 40%, 75% ≤9%; retail: 31%, 88%) due to rebate volatility risk of breaking best price and Average Manufacturer Price impact. Medicaid sees worse misalignment for the 60% drug performance scenarios because of comparison to the statutory rebate (23.1%). CONCLUSION: The Multiple Best Prices approach has the lowest misalignment and could be applied to most chronic therapies, even rare ones.