Medicare & medicaid research review最新文献

{"title":"Utilization of dental services among Medicaid-enrolled children.","authors":"Ellen Bouchery","doi":"10.5600/mmrr.003.03.b04","DOIUrl":"https://doi.org/10.5600/mmrr.003.03.b04","url":null,"abstract":"<p><strong>Objective: </strong>To assess what characteristics of children and their communities are associated with lower dental service use rates, to support development of strategies to target subgroups of children with lower utilization.</p><p><strong>Data source: </strong>The Medicaid Analytic Extract (MAX) 5-percent sample file, known as Mini- MAX 2008.</p><p><strong>Methods: </strong>Multivariate logistic regression was used to assess the association between enrollee and county characteristics and dental preventive and treatment service utilization.</p><p><strong>Principal findings: </strong>There is substantial variation in service use by age. Relative to a 9-year-old, a 2-year-old is 28 percentage points less likely, and a 15-year-old is 15 percentage points less likely, to receive a preventive dental service. Children enrolled in Medicaid for only part of the year were significantly less likely to receive a preventive or a treatment service relative to children covered by Medicaid for the full year. For preventive care, children enrolled for nine months were 15 percentage points less likely to have a service. Those enrolled for six months were 30 points less likely; those enrolled for three months were 41 points less likely. Children eligible for Medicaid based on disability were 9 and 6 percentage points less likely to receive a preventive or treatment service, respectively, than their counterparts who were eligible based on income alone.</p><p><strong>Conclusions: </strong>This study identifies some subgroups of children who are particularly underserved and for whom states may need to devote more attention.</p>","PeriodicalId":89601,"journal":{"name":"Medicare & medicaid research review","volume":"3 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983737/pdf/mmrr2013-003-03-b04.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32279964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Episode-based payment: evaluating the impact on chronic conditions.","authors":"Thomas J O'Byrne,&nbsp;Nilay D Shah,&nbsp;Douglas Wood,&nbsp;Robert E Nesse,&nbsp;Patrick J F Killinger,&nbsp;William J Litchy,&nbsp;Robert J Stroebel,&nbsp;Amy E Wagie,&nbsp;James M Naessens","doi":"10.5600/mmrr.003.03.a07","DOIUrl":"https://doi.org/10.5600/mmrr.003.03.a07","url":null,"abstract":"<p><strong>Background: </strong>Policy makers are interested in aggregating fee-for-service reimbursement into episode-based bundle payments, hoping it will lead to greater efficiency in the provision of care. The focus of bundled payment initiatives has been upon surgical or discrete procedures. Relatively little is known about calculating and implementing episode-based payments for chronic conditions.</p><p><strong>Objective: </strong>Compare the differences in two different episode-creation algorithms for two common chronic conditions: diabetes and coronary artery disease (CAD).</p><p><strong>Study design: </strong>We conducted a retrospective evaluation using enrollees with continuous coverage in a self-funded plan from 2003 to 2006, meeting Healthcare Effectiveness Data and Information Set (HEDIS) criteria for diabetes or CAD. For each condition, an annual episode-based payment was assessed using two algorithms: Episode Treatment Groups (ETGs) and the Prometheus model.</p><p><strong>Principal findings: </strong>We began with 1,580 diabetes patients with a 4-year total payment mean of $67,280. ETGs identified 1,447 (92%) as having diabetes with 4-year episode-based mean payments of $12,731; while the Prometheus model identified 1,512 (96%) as having diabetes, but included only 1,195 of them in the Prometheus model with mean diabetes payments of $23,250. Beginning with 1,644 CAD patients with a 4-year total payment mean of $65,661, ETGs identified 983 patients (60%) with a 4-year episode-based mean of $24,362. The Prometheus model identified 1,135 (69%) as CAD patients with 948 CAD patients having a mean of $26,536.</p><p><strong>Conclusions: </strong>The two episode-based methods identify different patients with these two chronic conditions. In addition, there are significant differences in the episode-based payment estimates for diabetes, but similar estimates for CAD. Implementing episode-based payments for chronic conditions is challenging, and thoughtful discussions are needed to determine appropriate payments.</p>","PeriodicalId":89601,"journal":{"name":"Medicare & medicaid research review","volume":"3 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983732/pdf/mmrr2013-003-03-a07.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32281983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Standardizing Medicare payment information to support examining geographic variation in costs.","authors":"Brian E O'Donnell,&nbsp;Kathleen M Schneider,&nbsp;John M Brooks,&nbsp;Gregory Lessman,&nbsp;June Wilwert,&nbsp;Elizabeth Cook,&nbsp;Glenda Martens,&nbsp;Kara Wright,&nbsp;Elizabeth A Chrischilles","doi":"10.5600/mmrr.003.03.a06","DOIUrl":"10.5600/mmrr.003.03.a06","url":null,"abstract":"<p><strong>Objectives: </strong>Examination of efficiency in health care requires that cost information be normalized. Medicare payments include both geographic and policy-based facility type differentials (e.g., wage index and disproportionate share hospital), which can bias cost comparisons of hospitals and averages across geographic areas. Standardizing payment information to remove the area- and policy-based payment differentials should normalize much of the observed geographic variability in payments, allowing for a more accurate comparison of resource use between providers and across geographic regions. Use of standardized payments will ensure that observed payment variation is due to differences in practice patterns and service use, rather than Medicare payment differences over which the providers have no control. This paper describes a method for standardizing claim payments, and demonstrates the difference in actual versus standardized payments by geographic region.</p><p><strong>Study design and methods: </strong>We used a nationwide cohort of Medicare patients hospitalized with an acute myocardial infarction (AMI) in 2007, then limited our study to those with Medicare Part A and Part B fee-for-service (FFS), and Part D coverage (n = 143,123). Standardized payment amounts were calculated for each Part A and Part B claim; standardized and actual payments were summed for all services for each patient beginning with the index hospitalization through 12 months post discharge.</p><p><strong>Principal findings: </strong>Without standardization of payments, certain areas of the country are mischaracterized as either high or low healthcare resource-consuming areas. The difference between actual and standardized payments varies by care setting.</p><p><strong>Conclusions: </strong>Standardized payment amounts should be calculated when comparing Medicare resource use across geographic areas.</p>","PeriodicalId":89601,"journal":{"name":"Medicare & medicaid research review","volume":"3 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983731/pdf/mmrr2013-003-03-a06.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32281982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measuring prevention more broadly: an empirical assessment of CHIPRA core measures.","authors":"Nir Menachemi,&nbsp;Justin Blackburn,&nbsp;David J Becker,&nbsp;Michael A Morrisey,&nbsp;Bisakha Sen,&nbsp;Cathy Caldwell","doi":"10.5600/mmrr.003.03.a04","DOIUrl":"https://doi.org/10.5600/mmrr.003.03.a04","url":null,"abstract":"<p><strong>Objective: </strong>To assess limitations of using select Children's Health Insurance Program Reauthorization Act (CHIPRA) core claims-based measures in capturing the preventive services that may occur in the clinical setting.</p><p><strong>Methods: </strong>We use claims data from ALL Kids, the Alabama Children's Health Insurance Program (CHIP), to calculate each of four quality measures under two alternative definitions: (1) the formal claims-based guidelines outlined in the CMS Technical Specifications, and (2) a broader definition of appropriate claims for identifying preventive service use. Additionally, we examine the extent to which these two claims-based approaches to measuring quality differ in assessments of disparities in quality of care across subgroups of children.</p><p><strong>Results: </strong>Statistically significant differences in rates were identified when comparing the two definitions for calculating each quality measure. Measure differences ranged from a 1.9 percentage point change for measure #13 (receiving preventive dental services) to a 25.5 percentage point change for measure #12 (adolescent well-care visit). We were able to identify subgroups based upon family income, rural location, and chronic disease status with differences in quality within the core measures. However, some identified disparities were sensitive to the approach used to calculate the quality measure.</p><p><strong>Conclusions: </strong>Differences in CHIP design and structure, across states and over time, may limit the usefulness of select claims-based core measures for detecting disparities accurately. Additional guidance and research may be necessary before reporting of the measures becomes mandatory.</p>","PeriodicalId":89601,"journal":{"name":"Medicare & medicaid research review","volume":"3 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4001808/pdf/mmrr2013-003-03-a04.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32319489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of long-term care use on Medicare and Medicaid expenditures for dual eligible and non-dual eligible elderly beneficiaries.","authors":"Robert L Kane,&nbsp;Andrea Wysocki,&nbsp;Shriram Parashuram,&nbsp;Tetyana Shippee,&nbsp;Terry Lum","doi":"10.5600/mmrr.003.03.a05","DOIUrl":"https://doi.org/10.5600/mmrr.003.03.a05","url":null,"abstract":"<p><strong>Background: </strong>Dual eligible Medicare and Medicaid beneficiaries consume disproportionate shares of both programs.</p><p><strong>Objectives: </strong>To compare Medicare and Medicaid expenditures of elderly dual eligible beneficiaries with non-dual eligible beneficiaries based on their long-term care (LTC) use.</p><p><strong>Research design: </strong>Secondary analysis of linked MAX and Medicare data in seven states.</p><p><strong>Subjects: </strong>Dual eligible adults (65+) receiving LTC in institutions, in the community, or not at all; and Medicare non-dual eligibles.</p><p><strong>Measures: </strong>Medicaid acute medical and LTC expenditures per beneficiary year, Medicare expenditures.</p><p><strong>Results: </strong>Among dual eligibles and non-dual eligibles, the average number of diseases and case mix scores are higher for LTC users. Adjusting for case mix virtually eliminates the difference for medical costs, but not for LTC expenditures. Adjusting for LTC status reduces the difference in LTC costs, but increases the difference in medical costs.</p><p><strong>Conclusions: </strong>Efforts to control costs for dual eligibles should target those in LTC while better coordinating medical and LTC expenditures.</p>","PeriodicalId":89601,"journal":{"name":"Medicare & medicaid research review","volume":"3 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983730/pdf/mmrr2013-003-03-a05.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32281981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bundling post-acute care services into MS-DRG payments.","authors":"James C Vertrees,&nbsp;Richard F Averill,&nbsp;Jon Eisenhandler,&nbsp;Anthony Quain,&nbsp;James Switalski","doi":"10.5600/mmrr.003.03.a03","DOIUrl":"https://doi.org/10.5600/mmrr.003.03.a03","url":null,"abstract":"<p><strong>Objective: </strong>A bundled hospital payment system that encompasses both acute and post-acute care has been proposed as a means of creating financial incentives in the Medicare fee-for-service system to foster care coordination and to improve the current disorganized system of post care. The objective of this study was to evaluate the statistical stability of alternative designs of a hospital payment system that includes post-acute care services to determine the feasibility of using a combined hospital and post-acute care bundle as a unit of payment.</p><p><strong>Methods: </strong>The Medicare Severity-Diagnosis Related Groups (MS-DRGs) were subdivided into clinical subclasses that measured a patient's chronic illness burden to test whether a patient's chronic illness burden had a substantial impact on post-acute care expenditures. Using Medicare data the statistical performance of the MS-DRGs with and without the chronic illness subclasses was evaluated across a wide range of post-acute care windows and combinations of post-acute care service bundles using both submitted charges and Medicare payments.</p><p><strong>Results: </strong>The statistical performance of the MS-DRGs as measured by R(2) was consistently better when the chronic illness subclasses are included indicating that MS-DRGs by themselves are an inadequate unit of payment for post-acute care payment bundles. In general, R(2) values increased as the post-acute care window length increased and decreased as more services were added to the post-acute care bundle.</p><p><strong>Discussion: </strong>The study results suggest that it is feasible to develop a payment system that incorporates significant post-acute care services into the MS-DRG inpatient payment bundle. This expansion of the basic DRG payment approach can provide a strong financial incentive for providers to better coordinate care potentially leading to improved efficiency and outcome quality.</p>","PeriodicalId":89601,"journal":{"name":"Medicare & medicaid research review","volume":"3 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983729/pdf/mmrr2013-003-03-a03.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32281980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using the National Provider Identifier for health care workforce evaluation.","authors":"Andrew B Bindman","doi":"10.5600/mmrr.003.03.b03","DOIUrl":"https://doi.org/10.5600/mmrr.003.03.b03","url":null,"abstract":"<p><p>The establishment in recent years of a National Provider Identifier (NPI) offers a new method for counting and categorizing physicians and other health care professionals involved in clinical care. In this paper, I describe how the NPI is assigned, the information collected in association with assigning the NPI, potential ways to enhance information on health professionals through data linkages using the NPI, and how the assessment of the health care workforce could be improved by requiring health care professionals to update their information as a part of maintaining their NPI. </p>","PeriodicalId":89601,"journal":{"name":"Medicare & medicaid research review","volume":"3 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983736/pdf/mmrr2013-003-03-b03.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32279963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiple chronic conditions among Medicare beneficiaries: state-level variations in prevalence, utilization, and cost, 2011.","authors":"Kimberly A Lochner,&nbsp;Richard A Goodman,&nbsp;Samual Posner,&nbsp;Anand Parekh","doi":"10.5600/mmrr.003.03.b02","DOIUrl":"https://doi.org/10.5600/mmrr.003.03.b02","url":null,"abstract":"<p><strong>Objectives: </strong>Individuals with multiple (>2) chronic conditions (MCC) present many challenges to the health care system, such as effective coordination of care and cost containment. To assist health policy makers and to fill research gaps on MCC, we describe state-level variation of MCC among Medicare beneficiaries, with a focus on those with six or more conditions.</p><p><strong>Methods: </strong>Using Centers for Medicare & Medicaid Services administrative data for 2011, we characterized a beneficiary as having MCC by counting the number of conditions from a set of fifteen conditions, which were identified using diagnosis codes on the claims. The study population included fee-for-service beneficiaries residing in the 50 U.S. states and Washington, DC.</p><p><strong>Results: </strong>Among beneficiaries with six or more chronic conditions, prevalence rates were lowest in Alaska and Wyoming (7%) and highest in Florida and New Jersey (18%); readmission rates were lowest in Utah (19%) and highest in Washington, DC (31%); the number of emergency department visits per beneficiary were lowest in New York and Florida (1.6) and highest in Washington, DC (2.7); and Medicare spending per beneficiary was lowest in Hawaii ($24,086) and highest in Maryland, Washington, DC, and Louisiana (over $37,000).</p><p><strong>Conclusion: </strong>These findings expand upon prior research on MCC among Medicare beneficiaries at the national level and demonstrate considerable state-level variation in the prevalence, health care utilization, and Medicare spending for beneficiaries with MCC. State-level data on MCC is important for decision making aimed at improved program planning, financing, and delivery of care for individuals with MCC.</p>","PeriodicalId":89601,"journal":{"name":"Medicare & medicaid research review","volume":"3 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983735/pdf/mmrr2013-003-03-b02.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32279962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"State variability in children's Medicaid/CHIP crowd-out estimates.","authors":"David B Muhlestein,&nbsp;Eric E Seiber","doi":"10.5600/mmrr.003.03.a01","DOIUrl":"https://doi.org/10.5600/mmrr.003.03.a01","url":null,"abstract":"<p><strong>Background: </strong>Health insurance crowd-out occurs when individuals enrolled in a public health insurance plan would have enrolled in a private plan but for the public option. The crowding-out of private insurance is often used to criticize state Medicaid and Children's Health Insurance Program (CHIP) expansion, as already insured children move their coverage to the states at the public's expense. A difficulty in discussing crowd-out comes from inconsistent estimates. Previous work focusing on the expansion of public programs has led to estimates ranging from 0% to 50% of the children newly insured on public plans being crowded-out.</p><p><strong>Methods: </strong>We apply a regression discontinuity approach to estimate how many children near the state Medicaid/CHIP threshold are crowded-out of private insurance. This approach allows estimates of crowd-out near the eligibility threshold independent of any expansion. Data from the American Community Survey's yearly survey of American households allows for state-level estimates of crowd-out.</p><p><strong>Results: </strong>We find considerable heterogeneity in the crowd-out that occurs in each state, ranging from no crowd-out to over 18% in states with similar eligibility thresholds. Additionally, we found that as state eligibility thresholds increase, children are less likely to be crowded-out.</p><p><strong>Discussion: </strong>This research indicates that national estimates of crowd-out are inappropriate, as state-specific Medicaid and CHIP programs have state-specific crowd-out. Additionally, it indicates that wealthier families that are eligible for public insurance are less likely to switch from private to public coverage than families earning less. Future work should identify reasons for the heterogeneity among states.</p>","PeriodicalId":89601,"journal":{"name":"Medicare & medicaid research review","volume":"3 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983728/pdf/mmrr2013-003-03-a01.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32281979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increased use of dental services by children covered by Medicaid: 2000-2010.","authors":"Leighton Ku, Jessica Sharac, Brian Bruen, Megan Thomas, Laurie Norris","doi":"10.5600/mmrr.003.03.b01","DOIUrl":"10.5600/mmrr.003.03.b01","url":null,"abstract":"<p><p>This report analyzes the use of dental services by children enrolled in Medicaid from federal fiscal years (FFY) 2000 to 2010. The number and percent of children receiving dental services under Medicaid climbed continuously over the decade. In FFY 2000, 6.3 million children ages 1 to 20 were reported to receive some form of dental care (either preventive or treatment); the number more than doubled to 15.4 million by FFY 2010. Part of the increase was because the overall number of children covered by Medicaid rose by 12 million (50%), but the percentage of children who received dental care climbed appreciably from 29.3% in FFY 2000 to 46.4% in FFY 2010. In that same time period, the number of children ages 1 to 20 receiving preventive dental services climbed from a reported 5.0 million to 13.6 million, while the percentage of children receiving preventive dental services rose from 23.2% to 40.8%. For children ages 1 to 20 who received dental treatment services, the reported number rose from 3.3 million in FFY 2000 to 7.6 million in FFY 2010. The percentage of children who obtained dental treatment services increased from 15.3% to 22.9%. In FFY 2010, about one sixth of children covered by Medicaid (15.7%) ages 6-14 had a dental sealant placed on a permanent molar. While most states have made steady progress in improving children's access to dental care in Medicaid over the past decade, there is still substantial variation across states and more remains to be done. </p>","PeriodicalId":89601,"journal":{"name":"Medicare & medicaid research review","volume":"3 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983734/pdf/mmrr2013-003-03-b01.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32279961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}