Simulation of emission reduction path under the path of differentiated energy transformation in China's industrial cities: a case study of Shanghai.

The formulation of long-term step-by-step emission reduction plan is an important step for effective scientific emission reduction. This paper takes Shanghai as the research object, constructs PSO-LSTM model on the basis of STIRPAT model, and further constructs three dynamic policy scenarios combined with China's actual situation and makes short-, medium-, and long-term multivariate predictions for them. The study finds that only the improvement of energy consumption structure has a promotion effect on carbon emission reduction, and urbanization, industrial structure, technology level, population, and economic level all have an increasing effect, and secondly, the carbon emission reduction path of Shanghai basically achieves the core objective of steady decrease under the three scenarios. Secondly, under the three scenarios, Shanghai's carbon emission reduction path basically achieves the core objective of steady decline, but the decline in the GU scenario is more significant. It is recommended that Shanghai further adjusts its industrial structure, optimizes its energy consumption structure, promotes technological innovation and progress, and promotes the development of the circular economy model.

Exploration of potential mechanism of Rougan formula against hepatic fibrosis by network analysis and experimental assessment.

ETHNOPHARMACOLOGICAL RELEVANCE: Rougan Formula (RG) has long been clinically applied to treat hepatic fibrosis in patients with different chronic liver diseases. However, the core active substances and the potential pharmacological mechanisms of RG remain unclear. AIM OF THE STUDY: The purpose of this study is to explore bioactive components, key targets, and potential mechanisms of RG by performing network pharmacological analyses and experimental model validation. MATERIALS AND METHODS: All chemical components in RG extract were identified using ultraperformance liquid chromatography-quadrupole/time-of-flight tandem mass technology. The candidate components and drug targets of RG, as well as disease-related genes, were extracted from TCMSP and GeneCards databases. The potential pathways related to genes were predicted by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. The core bioactive components, key targets, and signaling pathways were ultimately obtained by analyzing protein-protein interaction (PPI) and component-target-pathway (C-T-P) networks. Subsequently, the efficacy and underlying mechanisms of RG on hepatic fibrosis were experimentally validated in transforming growth factor-beta 1 (TGF-ß1)-induced hepatic stellate cell activation model and CCL4-induced hepatic fibrosis mouse model. RESULTS: A total of 52 components in RG extract were obtained, and 22 of them were selected as the core bioactive components. Five hundred and thirty-nine overlapped targets were determined by matching drug targets with disease-related targets. The results of PPI and C-T-P network analyses revealed 100 key targets and 19 signaling pathways associated with RG efficacy. In vitro and in vivo studies further verified that RG exerted a significant anti-hepatic fibrotic effect by suppressing the activation of hepatic stellate cells by downregulating the TGF-ß1/Smads signaling pathway. CONCLUSIONS: These results may provide some evidence for further clinical research and development of RG formula as an effective and safe drug for hepatic fibrosis treatment.

Assessment of the bi-directional relationship between blood mitochondrial DNA copy number and type 2 diabetes mellitus: a multivariable-adjusted regression and Mendelian randomisation study.

AIMS/HYPOTHESIS: Mitochondrial dysfunction, which can be approximated by blood mitochondrial DNA copy number (mtDNA-CN), has been implicated in the pathogenesis of type 2 diabetes mellitus. Thus far, however, insights from prospective cohort studies and Mendelian randomisation (MR) analyses on this relationship are limited. We assessed the association between blood mtDNA-CN and incident type 2 diabetes using multivariable-adjusted regression analyses, and the associations between blood mtDNA-CN and type 2 diabetes and BMI using bi-directional MR. METHODS: Multivariable-adjusted Cox proportional hazard models were used to estimate the association between blood mtDNA-CN and incident type 2 diabetes in 285,967 unrelated European individuals from UK Biobank free of type 2 diabetes at baseline. Additionally, a cross-sectional analysis was performed to investigate the association between blood mtDNA-CN and BMI. We also assessed the potentially causal relationship between blood mtDNA-CN and type 2 diabetes (N=898,130 from DIAGRAM, N=215,654 from FinnGen) and BMI (N=681,275 from GIANT) using bi-directional two-sample MR. RESULTS: During a median follow-up of 11.87 years, 15,111 participants developed type 2 diabetes. Participants with a higher level of blood mtDNA-CN are at lower risk of developing type 2 diabetes (HR 0.90 [95% CI 0.89, 0.92]). After additional adjustment for BMI and other confounders, these results attenuated moderately and remained present. The multivariable-adjusted cross-sectional analyses showed that higher blood mtDNA-CN was associated with lower BMI (-0.12 [95% CI -0.14, -0.10]) kg/m2. In the bi-directional MR analyses, we found no evidence for causal associations between blood mtDNA-CN and type 2 diabetes, and blood mtDNA-CN and BMI in either direction. CONCLUSIONS/INTERPRETATION: The results from the present study indicate that the observed association between low blood mtDNA-CN and higher risk of type 2 diabetes is likely not causal.

Identifying patterns of clinical conditions among high-cost older adult health care users using claims data: a latent class approach.

OBJECTIVES: To identify patterns of clinical conditions among high-cost older adults health care users and explore the associations between characteristics of high-cost older adults and patterns of clinical conditions. METHODS: We analyzed data from the Shanghai Basic Social Medical Insurance Database, China. A total of 2927 older adults aged 60 years and over were included as the analysis sample. We used latent class analysis to identify patterns of clinical conditions among high-cost older adults health care users. Multinomial logistic regression models were also used to determine the associations between demographic characteristics, insurance types, and patterns of clinical conditions. RESULTS: Five clinically distinctive subgroups of high-cost older adults emerged. Classes included "cerebrovascular diseases" (10.6% of high-cost older adults), "malignant tumor" (9.1%), "arthrosis" (8.8%), "ischemic heart disease" (7.4%), and "other sporadic diseases" (64.1%). Age, sex, and type of medical insurance were predictors of high-cost older adult subgroups. CONCLUSIONS: Profiling patterns of clinical conditions among high-cost older adults is potentially useful as a first step to inform the development of tailored management and intervention strategies.

Systematic Assessment of Tumor Purity and Its Clinical Implications.

PURPOSE: The tumor microenvironment is complex, comprising heterogeneous cellular populations. As molecular profiles are frequently generated using bulk tissue sections, they represent an admixture of multiple cell types (including immune, stromal, and cancer cells) interacting with each other. Therefore, these molecular profiles are confounded by signals emanating from many cell types. Accurate assessment of residual cancer cell fraction is crucial for parameterization and interpretation of genomic analyses, as well as for accurately interpreting the clinical properties of the tumor. MATERIALS AND METHODS: To benchmark cancer cell fraction estimation methods, 10 estimators were applied to a clinical cohort of 333 patients with prostate cancer. These methods include gold-standard multiobserver pathology estimates, as well as estimates inferred from genome, epigenome, and transcriptome data. In addition, two methods based on genomic and transcriptomic profiles were used to quantify tumor purity in 4,497 tumors across 12 cancer types. Bulk mRNA and microRNA profiles were subject to in silico deconvolution to estimate cancer cell-specific mRNA and microRNA profiles. RESULTS: We present a systematic comparison of 10 tumor purity estimation methods on a cohort of 333 prostate tumors. We quantify variation among purity estimation methods and demonstrate how this influences interpretation of clinico-genomic analyses. Our data show poor concordance between pathologic and molecular purity estimates, necessitating caution when interpreting molecular results. Limited concordance between DNA- and mRNA-derived purity estimates remained a general pan-cancer phenomenon when tested in an additional 4,497 tumors spanning 12 cancer types. CONCLUSION: The choice of tumor purity estimation method may have a profound impact on the interpretation of genomic assays. Taken together, these data highlight the need for improved assessment of tumor purity and quantitation of its influences on the molecular hallmarks of cancers.

Breastfeeding practices 2008-2009 among Chinese mothers living in Ireland: a mixed methods study.

BACKGROUND: Migration to another country has a potential influence on breastfeeding practices. A significant difference in breastfeeding rates between Irish nationals and non-nationals has been reported. This study was conducted to explore breastfeeding practices of the Chinese in Ireland, one of the largest Irish ethnic groups, and to explore the influence of living in Ireland on breastfeeding practices. This is the first and the only migration study so far on breastfeeding practices among the Chinese in Ireland. METHODS: A sequential explanatory mixed methods approach was adopted. The first phase was a cross-sectional self-administered retrospective mailed survey, to explore breastfeeding practices and determinants of breastfeeding among a convenience sample of Chinese mothers living in Ireland (n = 322). Recruitment was conducted in the Dublin metropolitan area, with the application of the snowball technique to increase sample size. The second phase consisted of seven semi-structured focus groups (n = 33) conducted in Dublin, to explore the influence of living in Ireland on breastfeeding among Chinese mothers who had given birth in Ireland. Quantitative data were analyzed by univariate and multivariate logistic regression analyses, and informed the qualitative data collection. Qualitative data were analyzed by thematic content analyses, to explain and enrich the qualitative results. RESULTS: The breastfeeding initiation rate among Chinese immigrants to Ireland who gave birth in Ireland (CMI) (75.6%) was high and close to that of Chinese immigrant mothers who gave birth in China (CMC) (87.2%). However, giving birth in Ireland was independently associated with a shorter duration of breastfeeding (< 4 months) among Chinese immigrants. Qualitative results explained that a shorter breastfeeding duration among CMI than that of CMC was mainly due to cultural conflicts, a lack of family support, language barriers, immigrants' low socioeconomic status, and mothers' preference for infant formula on the Irish market. Both quantitative and qualitative data revealed a strong cultural belief in the efficacy of the traditional Chinese postpartum diet for breast milk production for both CMC and CMI. Antenatal feeding intention was a strong determinant for breastfeeding initiation and duration among CMI. CONCLUSION: Migration to Ireland was found to be associated with a shorter duration of breastfeeding of the Chinese. Culturally sensitive and language-specific education and support of breastfeeding is needed for the Chinese mothers living in Ireland. The mixed methods design presented here might serve as a template for future migration research on breastfeeding.

The effect of Medicare's Annual Wellness Visit on preventive care for the elderly.

The study aim was to assess the effect of receiving an Annual Wellness Visit (AWV) between 2011 and 2013 on the annual rate of eight preventive services recommended for the Medicare population following the AWV. We used retrospective Medicare claims from 2009 to 2014 for a 5% national sample of fee-for-service beneficiaries in the United States. Propensity score-adjusted logistic regressions were performed to estimate the log odds of the probability of receiving the preventive services between beneficiaries who received AWVs during 2011-13 and those who did not during the same period. The average marginal effect was also reported. Among 845,318 patients who met the inclusion and exclusion criteria, 23% had an AWV in 2011-2013. In a propensity-matched sample of 381,934 patients, AWV participants are more likely to undergo subsequent preventive services within a year (adjusted odds ratio ranges from 1.46 (95% CI, 1.44, 1.49) to 2.43 (95% CI, 2.38, 2.49). The findings are consistent using secondary outcomes or with subgroups defined by baseline primary care provider visits or baseline preventive services. These analyses showed that AWV is associated with a significant increase in all the preventive services examined. As Healthy People 2020 has established a target goal to increase the proportion of older adults who receive a core set of clinical preventive services by 10%, AWV represents a promising opportunity to facilitate the delivery of preventive care for the elderly and to advance our knowledge about effective strategies for healthy aging.

Day of Week, Site of Service, and Patient Complexity Disparities in Musculoskeletal MRI Interpretations by Radiologists Versus Nonradiologists.

OBJECTIVE: Although most musculoskeletal MRI examinations are interpreted by radiologists, some nonradiologists provide interpretations as well. We aimed to study day of week (weekday vs weekend), site of service, and patient complexity differences between radiologists and nonradiologists interpreting lower extremity MRI examinations on Medicare beneficiaries. MATERIALS AND METHODS: Using fee-for-service carrier claims for a 5% sample of Medicare beneficiaries nationally from 2012 through 2014, we identified all lower extremity joint MRI examinations. Services were classified by physician specialty, day of week, and site of service. Charlson comorbidity index (CCI) values were calculated for all patients. Chi-square statistical testing was performed. RESULTS: Of all 125,800 billed lower extremity joint MRI examinations, 118,295 (94.0%) were performed on weekdays and 7505 (6.0%) on weekends. Of the weekday examinations, radiologists interpreted 85,991 (83.3%) and nonradiologists 17,260 (16.7%). Of the weekend examinations, radiologists interpreted 6212 (92.8%) and nonradiologists 485 (7.2%). Of examinations performed in inpatient hospital and emergency department settings, radiologists interpreted 6499 (99.2%) and nonradiologists 51 (0.8%). Of the examinations on the most clinically complex patients (CCI ≥ 3), radiologists interpreted 4228 (90.2%) and nonradiologists 461 (9.8%). All interspecialty differences were statistically significant (p < 0.001). CONCLUSION: In the Medicare population, radiologists interpret most lower extremity joint MRI examinations. Compared with nonradiologists, radiologists disproportionately provide services on weekends, in the highest acuity settings, and on the most clinically complex patients. To promote patient access and minimize disparities, future pay-for-performance metrics should consider temporal, acuity, and complexity parameters.

Day of Week, Site of Service, and Patient Complexity Differences in Venous Ultrasound Interpreted by Radiologists Versus Nonradiologists.

OBJECTIVE: Nationally, nonradiologists interpret an increasing proportion of lower extremity venous duplex ultrasound (LEVDU) examinations. We aimed to study day of week, site of service, and patient complexity differences in LEVDU services interpreted by radiologists versus nonradiologists. MATERIALS AND METHODS: Using carrier claims files for a 5% national sample of Medicare beneficiaries from 2012 to 2015, we retrospectively classified all LEVDU examinations by physician specialty (radiologist versus nonradiologist), day of week (weekday versus weekend), site of service, and patient Charlson Comorbidity Index (CCI) scores. Pearson's χ2 was used to test statistical significance. RESULTS: Of 760,433 LEVDU examinations for which provider specialty could be determined, 439,964 (58%) were interpreted by radiologists and 320,469 (42%) by nonradiologists. On weekends, radiologists interpreted 75% (66,094 of 88,244) and nonradiologists 25% (22,150 of 88,244) (P < .0001). Of LEVDU examinations interpreted by radiologists, 57% were performed in the inpatient or emergency department settings, and 70% of LEVDU examinations interpreted by nonradiologists were performed in the private office or outpatient hospital setting. Radiologists interpreted a slightly larger proportion (17%) of their examinations on patients with more comorbidities (CCI of ≥3) than nonradiologists (15%) (P < .0001). CONCLUSION: Compared with nonradiologists, radiologists interpret a disproportionately larger share of weekend (versus weekday) LEVDU examinations and a considerably larger proportion in higher acuity settings. Additionally, the patients on whom they render services have more comorbidities. To optimize around-the-clock patient access to necessary imaging, emerging quality payment programs should consider the timing and sites of service, as well as patient complexity.

Radiologist Professional Payments After Mitigation of CMS's Multiple-Procedure Payment Reduction Initiatives.

PURPOSE: The aim of this study was to assess the potential impact of ACR evidence-based advocacy on radiologist professional reimbursement from individual-provider CMS multiple-procedure payment reduction (MPPR) initiatives. METHODS: CMS Physician and Other Supplier Public Use Files and 5% research-identifiable file carrier claims files from 2012 through 2014 were used to identify individual-provider MPPR-eligible services for radiologists (group practice linking unavailability in either dataset precluded quantification of different provider discounting) and then compare actual payments to Medicare Physician Fee Schedule national professional reimbursement rates to identify MPPR-discounted services. Payments attributed to MPPR-affected services and average radiologist annual MPPR discounts were calculated to estimate incremental individual radiologist payment restoration as a result of evidence-based advocacy. RESULTS: Between 2012 and 2014, a mean of 803 to 836 advanced imaging services per radiologist were potentially affected by individual-provider MPPR discounting. Approximately 23% of these services were discounted by individual-provider MPPR, resulting in approximately $2,524 to $2,893 lost per radiologist per year. The MPPR rollback from 25% to 5% is thus estimated to return $55 million to $64 million to radiologists each year for the individual component of MPPR alone. CONCLUSIONS: Individual-provider MPPR discounting resulted, on average, in more than $2,500 in lost payments per radiologist per year. Its rollback, associated with ACR evidence-based advocacy efforts, is estimated to return well over $50 million in Medicare professional payments to radiologists each year for individual-component MPPR discounting alone.

A County-Level Analysis of the US Radiologist Workforce: Physician Supply and Subspecialty Characteristics.

PURPOSE: To explore associations between county-level measures of radiologist supply and subspecialization and county structural and health-related characteristics. METHODS: Medicare Physician and Other Supplier Public Use Files were used to subspecialty characterize 32,844 radiologists participating in Medicare between 2012 and 2014. Measures of radiologist supply and subspecialization were computed for 3,143 US counties. Additional county characteristics were identified using the 2014 County Health Rankings database. Mann-Whitney tests and Spearman correlations were performed. RESULTS: Counties with at least one (versus no) Medicare-participating radiologist had significantly (P < .001) larger populations (197,050 ± 457,056 versus 20,253 ± 23,689), lower rural percentages (39.5% ± 26.5% versus 74.6% ± 25.6%), higher household incomes ($47,608 ± $12,493 versus $42,510 ± $9,893), higher mammography screening rates (62.4% ± 7.0% versus 56.6% ± 15.3%), and lower premature deaths (7,581 ± 2,085 versus 7,784 ± 3,409 years of life lost). Counties' radiologists per 100,000 population and percent of subspecialized radiologists showed moderate positive correlations with counties' population (r = +0.505-+0.599) and moderate negative correlations with counties' rural percentage (r = -0.434 to -0.523). Radiologist supply and degree of subspecialization both showed concurrent positive or negative weak associations with counties' percent age 65+ (r = -0.256 to -0.271), percent Hispanic (r = +0.209-+0.234), and income (r = +0.230-+0.316). Radiologists per 100,000 population showed weak positive correlation with mammography screening (r = +0.214); percent of radiologists subspecialized showed weak negative correlation with premature death (r = -0.226). CONCLUSION: Geographic disparities in radiologist supply at the community level are compounded by superimposed variation in the degree of subspecialization of those radiologists. The potential impact of such access disparities on county-level health warrants further investigation.

Double Scan CT Rates: An Opportunity for Facility-Based Radiologist Measures in the Quality Payment Program.

PURPOSE: The Medicare Access and CHIP Reauthorization Act (MACRA) provides CMS flexibility to evaluate radiologists using hospital outpatient quality measures in place of conventional physician measures. We explore radiologist characteristics associated with variation in performance in two such measures: abdomen and chest CT "double scan" rates (percentage of total examinations performed both with and without intravenous contrast). METHODS: Radiologists' claims for abdomen and chest CT examinations in a facility setting were identified using 2014 Medicare Physician and Other Supplier data. Individual radiologist double scan rates were computed. Associations were explored between rates and radiologist characteristics extracted from the CMS public data sets using multivariable regression with cross-validation. RESULTS: Radiologists' double scan rates averaged 5.9% ± 10.0% (0.0% for 52.8% of radiologists) for abdomen CT (19,867 radiologists) and 1.0% ± 4.7% (0.0% for 91.3% of radiologists) for chest CT (18,684). At multivariable analysis, abdomen rates were best predicted by geography (lowest in Northeast, greatest in West), practice size (greatest for small practices), and specialty practice pattern (lowest for general radiologists; greatest for nuclear medicine physicians). Agreement for double scan rates among radiologists within the same practice was moderate, though slightly higher for chest (intraclass correlation = 0.70) than abdomen (0.59). CONCLUSION: Radiologists' facility double scan rates vary systematically based on an array of professional characteristics. MACRA grants CMS the authority to use these measures for evaluating radiologists, thereby aligning Medicare's hospital and physician performance programs and better incentivizing population radiation dose and cost reduction. Greater variation in abdomen CT double scan rates, compared with ubiquitously excellent chest CT performance, supports a particular role for abdomen rates in distinguishing disparities in radiologist performance.

Changing Utilization of Noninvasive Diagnostic Imaging Over 2 Decades: An Examination Family-Focused Analysis of Medicare Claims Using the Neiman Imaging Types of Service Categorization System.

OBJECTIVE: The objective of our study was to use a new modality and body region categorization system to assess changing utilization of noninvasive diagnostic imaging in the Medicare fee-for-service population over a recent 20-year period (1994-2013). MATERIALS AND METHODS: All Medicare Part B Physician Fee Schedule services billed between 1994 and 2013 were identified using Physician/Supplier Procedure Summary master files. Billed codes for diagnostic imaging were classified using the Neiman Imaging Types of Service (NITOS) coding system by both modality and body region. Utilization rates per 1000 beneficiaries were calculated for families of services. RESULTS: Among all diagnostic imaging modalities, growth was greatest for MRI (+312%) and CT (+151%) and was lower for ultrasound, nuclear medicine, and radiography and fluoroscopy (range, +1% to +31%). Among body regions, service growth was greatest for brain (+126%) and spine (+74%) imaging; showed milder growth (range, +18% to +67%) for imaging of the head and neck, breast, abdomen and pelvis, and extremity; and showed slight declines (range, -2% to -7%) for cardiac and chest imaging overall. The following specific imaging service families showed massive (> +100%) growth: cardiac CT, cardiac MRI, and breast MRI. CONCLUSION: NITOS categorization permits identification of temporal shifts in noninvasive diagnostic imaging by specific modality- and region-focused families, providing a granular understanding and reproducible analysis of global changes in imaging overall. Service family-level perspectives may help inform ongoing policy efforts to optimize imaging utilization and appropriateness.

Physician Specialty and Radiologist Characteristics Associated with Higher Medicare Patient Complexity.

RATIONALE AND OBJECTIVES: Meaningfully measuring physician outcomes and resource utilization requires appropriate patient risk adjustment. We aimed to assess Medicare patient complexity by physician specialty and to further identify radiologist characteristics associated with higher patient complexity. MATERIALS AND METHODS: The average beneficiary Hierarchical Condition Category (HCC) risk scores (Medicare's preferred measure of clinical complexity) were identified for all physicians using 2014 Medicare claims data. HCC scores were compared among physician specialties and further stratified for radiologists based on a range of characteristics. Univariable and multivariable analyses were performed. RESULTS: Of 549,194 physicians across 54 specialties, the mean HCC risk score was 1.62 ± 0.75. Of the 54 specialties, interventional radiology ranked 4th (2.60 ± 1.29), nuclear medicine ranked 16th (1.87 ± 0.45), and diagnostic radiology ranked 21st (1.75 ± 0.61). Among 31,175 radiologists, risk scores were higher (P < 0.001) for those with teaching (2.03 ± 0.74) vs nonteaching affiliations (1.72 ± 0.61), practice size ≥100 (1.94 ± 0.70) vs ≤9 (1.59 ± 0.79) members, urban (1.79 ± 0.69) vs rural (1.67 ± 0.59) practices, and subspecialized (1.85 ± 0.81) vs generalized (1.68 ± 0.42) practice patterns. Among noninterventional radiology subspecialties, patient complexity was highest for cardiothoracic (2.09 ± 0.57) and lowest for breast (1.08 ± 0.32) imagers. At multivariable analysis, a teaching affiliation was the strongest independent predictor of patient complexity for both interventional (ß = +0.23, P = 0.005) and noninterventional radiologists (ß = +0.21, P < 0.001). CONCLUSIONS: Radiologists on average serve more clinically complex Medicare patients than most physicians nationally. However, patient complexity varies considerably among radiologists and is particularly high for those with teaching affiliations and interventional radiologists. With patient complexity increasingly recognized as a central predictor of clinical outcomes and resource utilization, ongoing insights into complexity measures may assist radiologists navigating emerging risk-based payment models.

Factors Influencing List Prices for Radiologists' Services.

PURPOSE: To identify factors associated with list price variation for radiologists' services. METHODS: The 2014 Medicare Physician and Other Supplier Public Use File was used to identify submitted charges ("list prices") and payments for radiologists' services (ie, not hospital service charges). Charge-to-payment ratios were computed for individual radiologists as a measure of excess charges. Numerous radiologist-level factors identifiable using publicly available data sets were explored. RESULTS: Among 26,715 radiologists nationally, the mean charge-to-payment ratio was 4.2 ± 2.0. A greater charge-to-payment ratio was most strongly predicted for those serving higher-complexity patients (ratio ranging from 3.8 ± 1.8 to 4.1 ± 1.6 for radiologists in the first through third quartiles in terms of patient complexity, compared with a ratio of 4.8 ± 2.8 for radiologists in the highest quartile in terms of patient complexity). A higher charge-to-payment ratio was also observed among those with, rather than without, a teaching institutional affiliation (4.7 ± 2.8 versus 4.0 ± 1.8, respectively) and among subspecialists rather than generalists (4.4 ± 2.5 versus 3.9 ± 1.5, respectively). Among subspecialties, charge-to-payment ratios ranged from 3.3 ± 1.3 (breast imaging) to 5.7 ± 4.1 (interventional radiology). Charge-to-payment ratios showed weak inverse correlations with total service volume (r = -0.13) and total payments (r = -0.11). CONCLUSION: Distinct from hospital prices and historically considered arbitrary, higher charges for radiologists' services demonstrate consistent patterns of variation and are most strongly seen for those serving higher complexity patients. As price transparency initiatives expand, radiologists should be aware of how and why their list prices compare with local and national benchmarks.

Private Practice Radiologist Subspecialty Classification Using Medicare Claims.

PURPOSE: The aim of this study was to assess both existing Medicare provider code assignments and a new claims-based system for subspecialty classification of private practice radiologists. METHODS: Websites of the 100 largest US radiology private practices were used to identify 1,476 radiologists self-identified with a single subspecialty ([1] abdominal, [2] breast, [3] cardiothoracic, or [4] musculoskeletal imaging; [5] nuclear medicine; [6] interventional radiology; [7] neuroradiology). Concordance of existing Medicare radiology subspecialty provider codes (present only for nuclear medicine and interventional radiology) was first assessed. Next, using a classification approach based on Neiman Imaging Types of Service (NITOS) piloted among academic practices, the percentage of subspecialty work relative value units (wRVUs) from 2012 to 2014 Medicare claims were used to assign each radiologist a unique subspecialty. RESULTS: Existing Medicare provider codes matched only 8.0% of nuclear medicine physicians and 10.7% of interventional radiologists to their self-reported subspecialties. The NITOS-based system mapped a median 51.9% of private practice radiologists' wRVUs to self-identified subspecialties (range, 23.3% [nuclear medicine] to 73.6% [neuroradiology]). The 50% NITOS-based wRVU threshold previously established for academic radiologists correctly assigned subspecialties to 48.8% of private practice radiologists but incorrectly categorized 2.9%. Practice patterns of the remaining 48.3% were sufficiently varied such that no single subspecialty assignment was possible. CONCLUSIONS: Existing Medicare provider codes poorly mirror subspecialty radiologists' own practice website-designated subspecialties. Actual payer claims data permit far more granular and accurate subspecialty identification for many radiologists. As new payment models increasingly focus on subspecialty-specific performance measures, claims-based identification methodologies show promise for reproducibly and transparently matching radiologists to practice-relevant metrics.

Healthcare burden of pulmonary hypertension owing to lung disease and/or hypoxia.

BACKGROUND: Group 3 pulmonary hypertension (PH) encompasses PH owing to lung diseases and/or hypoxia. Treatment patterns, healthcare resource use, and economic burden to US payers of Group 3 PH patients were assessed. METHODS: This retrospective observational study extracted data from July 1, 2010 to June 30, 2013 from two Truven Health Analytics MarketScan databases. Adult Group 3 PH patients were identified based on claims for PH (ICD-9-CM 416.0/416.8), a related lung disease, and an echocardiogram or right heart catheterization (RHC). The index date was the date of the first PH claim; data were collected for 12 months pre- and post-index. A difference-in-difference approach using generalized estimating equations was done to account for baseline differences. RESULTS: Group 3 PH patients (n = 2,236) were matched 1:1 to controls on lung disease. PH patients had higher all-cause resource utilization and annual healthcare costs ($44,732 vs. $7,051) than controls. Costs were driven by inpatient admissions (35.4% of total costs), prescriptions (33.0%), and outpatient care (26.5%). Respiratory-related costs accounted for 11.4% of post-index annual costs for PH patients. PH diagnosis was not confirmed in the majority of PH patients (<7% RHC use) but nevertheless, 22% of PH patients post-index had claims for drugs approved for the treatment of pulmonary arterial hypertension (PAH). CONCLUSIONS: Group 3 PH poses a significant clinical and economic burden. Given the low use of RHC and the prevalence of PAH-indicated prescriptions that are not currently approved for Group 3 PH, this study suggests some Group 3 PH patients may not be receiving guideline-recommended treatment.

Academic Radiologist Subspecialty Identification Using a Novel Claims-Based Classification System.

OBJECTIVE: The objective of the present study is to assess the feasibility of a novel claims-based classification system for payer identification of academic radiologist subspecialties. MATERIALS AND METHODS: Using a categorization scheme based on the Neiman Imaging Types of Service (NITOS) system, we mapped the Medicare Part B services billed by all radiologists from 2012 to 2014, assigning them to the following subspecialty categories: abdominal imaging, breast imaging, cardiothoracic imaging, musculoskeletal imaging, nuclear medicine, interventional radiology, and neuroradiology. The percentage of subspecialty work relative value units (RVUs) to total billed work RVUs was calculated for each radiologist nationwide. For radiologists at the top 20 academic departments funded by the National Institutes of Health, those percentages were compared with subspecialties designated on faculty websites. NITOS-based subspecialty assignments were also compared with the only radiologist subspecialty classifications currently recognized by Medicare (i.e., nuclear medicine and interventional radiology). RESULTS: Of 1012 academic radiologists studied, the median percentage of Medicare-billed NITOS-based subspecialty work RVUs matching the subspecialty designated on radiologists' own websites ranged from 71.3% (for nuclear medicine) to 98.9% (for neuroradiology). A NITOS-based work RVU threshold of 50% correctly classified 89.8% of radiologists (5.9% were not mapped to any subspecialty; subspecialty error rate, 4.2%). In contrast, existing Medicare provider codes identified only 46.7% of nuclear medicine physicians and 39.4% of interventional radiologists. CONCLUSION: Using a framework based on a recently established imaging health services research tool that maps service codes based on imaging modality and body region, Medicare claims data can be used to consistently identify academic radiologists by subspecialty in a manner not possible with the use of existing Medicare physician specialty identifiers. This method may facilitate more appropriate performance metrics for subspecialty academic physicians under emerging value-based payment models.

Shannon entropy method of small-scale self-focusing assessment in high-power laser systems.

Through analysis of near-field beam profiles, we propose a method using Shannon entropy to assess the development of small-scale self-focusing during laser propagation and amplification in high-power laser systems. In this method, the entropy curve that corresponds to increasing B integral displays an evident turning point at which small-scale self-focusing starts to rapidly develop. In contrast to classical methods using contrast, modulation, or power spectral density, the proposed method provides the B integral criterion more clearly and objectively. This approach is an optimization method that can be utilized in the design and operation of high-power laser systems.

Next-Generation Molecular Testing of Newborn Dried Blood Spots for Cystic Fibrosis.

Newborn screening for cystic fibrosis enables early detection and management of this debilitating genetic disease. Implementing comprehensive CFTR analysis using Sanger sequencing as a component of confirmatory testing of all screen-positive newborns has remained impractical due to relatively lengthy turnaround times and high cost. Here, we describe CFseq, a highly sensitive, specific, rapid (<3 days), and cost-effective assay for comprehensive CFTR gene analysis from dried blood spots, the common newborn screening specimen. The unique design of CFseq integrates optimized dried blood spot sample processing, a novel multiplex amplification method from as little as 1 ng of genomic DNA, and multiplex next-generation sequencing of 96 samples in a single run to detect all relevant CFTR mutation types. Sequence data analysis utilizes publicly available software supplemented by an expert-curated compendium of >2000 CFTR variants. Validation studies across 190 dried blood spots demonstrated 100% sensitivity and a positive predictive value of 100% for single-nucleotide variants and insertions and deletions and complete concordance across the polymorphic poly-TG and consecutive poly-T tracts. Additionally, we accurately detected both a known exon 2,3 deletion and a previously undetected exon 22,23 deletion. CFseq is thus able to replace all existing CFTR molecular assays with a single robust, definitive assay at significant cost and time savings and could be adapted to high-throughput screening of other inherited conditions.