Estimating Anesthesia Time Using the Medicare Claim: A Validation Study

INTRODUCTION: Procedure length is a fundamental variable associated with quality of care, though seldom studied on a large scale. The authors sought to estimate procedure length through information obtained in the anesthesia claim submitted to Medicare to validate this method for future studies. METHODS: The Obesity and Surgical Outcomes Study enlisted 47 hospitals located across New York, Texas, and Illinois to study patients undergoing hip, knee, colon, and thoracotomy procedures. A total of 15,914 charts were abstracted to determine body mass index and initial patient physiology. Included in this abstraction were induction, cut, close, and recovery room times. This chart information was merged to Medicare claims that included anesthesia Part B billing information. Correlations between chart times and claim times were analyzed, models developed, and median absolute differences in minutes calculated. RESULTS: Of the 15,914 eligible patients, there were 14,369 for whom both chart and claim times were available for analysis. For these 14,369, the Spearman correlation between chart and claim time was 0.94 (95% CI 0.94, 0.95), and the median absolute difference between chart and claim time was only 5 min (95% CI: 5.0, 5.5). The anesthesia claim can also be used to estimate surgical procedure length, with only a modest increase in error. CONCLUSION: The anesthesia bill found in Medicare claims provides an excellent source of information for studying surgery time on a vast scale throughout the United States. However, errors in both chart abstraction and anesthesia claims can occur. Care must be taken in the handling of outliers in these data

Obesity and Readmission in Elderly Surgical Patients

BACKGROUND: Reducing readmissions has become a focus in efforts by Medicare to improve health care quality and reduce costs. This study aimed to determine whether causes for readmission differed between obese and nonobese patients, possibly allowing for targeted interventions. METHODS: A matched case control study of Medicare patients admitted between 2002 and 2006 who were readmitted after hip or knee surgery, colectomy, or thoracotomy was performed. Patients were matched exactly for procedure, while also balancing on hospital, age, and sex. Conditional logistic regression was used to study the odds of readmission for very obese cases (body mass index \u3e35 kg/m2) versus normal weight patients (body mass index of 20-30 kg/m2) after also controlling for race, transfer-in and emergency status, and comorbidities. RESULTS: Among 15,914 patient admissions, we identified 1,380 readmitted patients and 2,760 controls. The risk of readmission was increased for obese compared to nonobese patients both before and after controlling for comorbidities (before: odds ratio, 1.35; P = .003; after: odds ratio, 1.25; P = .04). Reasons for readmission varied by procedure but were not different by body mass index category. CONCLUSION: Obese patients have an increased risk of readmission, yet the reasons for readmission in obese patients appear to be similar to those for nonobese patients, suggesting that improved postdischarge management for the obese cannot focus on a few specific causes of readmission but must instead provide a broad range of interventions

Medical and Financial Risks Associated with Surgery in the Elderly Obese

OBJECTIVE: To study the medical and financial outcomes associated with surgery in elderly obese patients and to ask if obesity itself influences outcomes above and beyond the effects from comorbidities that are known to be associated with obesity. BACKGROUND: Obesity is a surgical risk factor not present in Medicare\u27s risk adjustment or payment algorithms, as BMI is not collected in administrative claims. METHODS: A total of 2045 severely or morbidly obese patients (BMI ≥ 35 kg/m, aged between 65 and 80 years) selected from 15,914 elderly patients in 47 hospitals undergoing hip and knee surgery, colectomy, and thoracotomy were matched to 2 sets of 2045 nonobese patients (BMI = 20-30 kg/m). A limited match controlled for age, sex, race, procedure, and hospital. A complete match also controlled for 30 additional factors such as diabetes and admission clinical data from chart abstraction. RESULTS: Mean BMI in the obese patients was 40 kg/m compared with 26 kg/m in the nonobese. In the complete match, obese patients displayed increased odds of wound infection: OR (odds ratio) = 1.64 (95% CI: 1.21, 2.21); renal dysfunction: OR = 2.05 (1.39, 3.05); urinary tract infection: OR = 1.55 (1.24, 1.94); hypotension: OR = 1.38 (1.07, 1.80); respiratory events: OR = 1.44 (1.19, 1.75); 30-day readmission: OR = 1.38 (1.08, 1.77); and a 12% longer length of stay (8%, 17%). Provider costs were 10% (7%, 12%) greater in obese than in nonobese patients, whereas Medicare payments increased only 3% (2%, 5%). Findings were similar in the limited match. CONCLUSIONS: Obesity increases the risks and costs of surgery. Better approaches are needed to reduce these risks. Furthermore, to avoid incentives to underserve this population, Medicare should consider incorporating incremental costs of caring for obese patients into payment policy and include obesity in severity adjustment models

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014–2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder