The Vanderbilt PICC Service: Program, Procedural, and Patient Outcomes Successes

2005 ◽  
Vol 10 (4) ◽  
pp. 183-192 ◽  
Author(s):  
Doug Burns
Keyword(s):  
Patient Outcomes ◽  
Medical Center ◽  
Nursing Program ◽  
Data Driven ◽  
Complication Rates ◽  
Advanced Practice ◽  
The Past ◽  
Data Driven Approach ◽  
High Level ◽  
Vanderbilt University

Abstract Since its inception in early 2000, Vanderbilt University's Peripherally Inserted Central Catheter (PICC) Service has experienced a high level of success as measured by high proficiency rates and increasing patient procedures each year, low complication rates during and after PICC placements, and an increasing scope of influence within the Vanderbilt University Medical Center and Children's Hospital, the surrounding community, and in the Southeastern United States. Primary drivers of the PICC Service's continuing success include consistent applications of technique and technology, a data-driven approach to assessing the program's progress, and appropriately managing customers' expectations and needs. Over the past five years, data were collected on more than 12,500 PICC placements performed in this specialized nursing program. Retrospective analyses of the data demonstrate an increasing rate of successful placements (from 87.2% to 92.4%) since the program's inception in 2000 to late 2004. Furthermore, the choice of PICC technology has had a significant impact on the odds for occlusion or infection. The Vanderbilt PICC Service provides a model by which other programs can be established, maintained, and expanded into advanced practice.

Transfers for Hand Surgery Correlate with Increased Reoperations for Complications

2015 ◽  
Vol 81 (11) ◽  
pp. 1177-1181
Author(s):  
Hunter J. Rooks ◽  
Joshua R. Anthony ◽  
Kevin W. Sexton ◽  
Andre P. Marshall ◽  
Oscar D. Guillamondegul ◽  
...  
Keyword(s):  
Patient Outcomes ◽  
Revisional Surgery ◽  
Medical Center ◽  
Hand Surgery ◽  
Complication Rates ◽  
Patient Travel ◽  
Distance Difference ◽  
Outcomes Study ◽  
Vanderbilt University ◽  
Care Availability

Wrist, hand, and finger trauma are the most common nonlethal injuries presenting to emergency departments. In Tennessee, lack of available hand care, particularly the need for emergency hand surgery, could be detrimental to patient outcomes. This is a retrospective outcomes study of patients requiring revisional hand surgeries. Patients were identified and stratified by distance to Vanderbilt University Medical Center (VUMC) to determine if patient complications increase with distance from VUMC. As distance of patient county of residence from VUMC increased, per cent of patients without a complication decreased ( P < 0.0001). Counties without 24/7 comprehensive hand call also showed a distance difference in complication rates. Per capita income and mean household income showed no effect on complications. Distance from treating facility is correlated with patient outcomes and need for revisional surgery. Limitations in care availability in Tennessee are not specific to hand surgery. If the trend toward poorer outcomes as a result of limited local care availability extends to other specialties, this could have implications regarding health-care realignment. Specifically for patients with complex injuries or conditions that will be referred to centralized flagship hospitals, increases in patient travel may limit positive outcomes.

scholarly journals A data‐driven approach for predicting nepheline crystallization in high‐level waste glasses

2020 ◽  
Vol 103 (9) ◽  
pp. 4913-4924
Author(s):  
Irmak Sargin ◽  
Charmayne E. Lonergan ◽  
John D. Vienna ◽  
John S. McCloy ◽  
Scott P. Beckman
Keyword(s):  
Data Driven ◽  
High Level Waste ◽  
Data Driven Approach ◽  
High Level

scholarly journals A data‐driven approach to stimulus selection reveals an image‐based representation of objects in high‐level visual areas

2019 ◽  
Vol 40 (16) ◽  
pp. 4716-4731 ◽  
Author(s):  
David D. Coggan ◽  
Afrodite Giannakopoulou ◽  
Sanah Ali ◽  
Burcu Goz ◽  
David M. Watson ◽  
...  
Keyword(s):  
Data Driven ◽  
Stimulus Selection ◽  
Visual Areas ◽  
Data Driven Approach ◽  
High Level

scholarly journals A Data-Driven Approach to the Development and Understanding of Chiroptical Sensors for Alcohols with Remote γ-Stereocenters

2021 ◽  
Author(s):  
Jordan Dotson ◽  
Eric Anslyn ◽  
Matthew Sigman
Keyword(s):  
Density Functional ◽  
Level Density ◽  
Enantiomeric Excess ◽  
Data Driven ◽  
Functional Theory ◽  
Dynamic Covalent Chemistry ◽  
Sensor Optimization ◽  
Data Driven Approach ◽  
High Level ◽  
Sensor Molecules

Dynamic covalent chemistry-based sensors have recently emerged as powerful tools to rapidly determine the enantiomeric excess of organic small molecules. While a bevy of sensors have been developed, those for flexible molecules with stereocenters remote to the functional group that binds the chiroptical sensor remain scarce. In this study, we develop an iterative, data-driven workflow to design and analyze a chiroptical sensor capable of assessing challenging acyclic γ-stereogenic alcohols. Fol-lowing sensor optimization, the mechanism of sensing was probed with a combination of computational parameterization of the sensor molecules, statistical modeling, and high-level density functional theory (DFT) calculations. These were used to elucidate the mechanism of stereochemical recognition and revealed that competing attractive non-covalent interactions (NCIs) determine the overall performance of the sensor. It is anticipated that the data-driven workflows developed herein will be generally applicable to the development and understanding of dynamic covalent and supramolecular sensors.

Designing And Optimizing Production In A High Variety / Low Volume Environment Through Data-Driven Simulation

2021 ◽  
Author(s):  
Virginia Fani ◽  
Bianca Bindi ◽  
Romeo Bandinelli
Keyword(s):  
Simulation Model ◽  
Production Systems ◽  
Discrete Event ◽  
Simulation Models ◽  
Product Variety ◽  
Data Driven ◽  
Business Decisions ◽  
Footwear Industry ◽  
Data Driven Approach ◽  
High Level

HVLV environments are characterized by high product variety and small lot production, pushing companies to recursively design and optimize their production systems in a very short time to reach high-level performance. To increase their competitiveness, companies belonging to these industries, often SMEs working as third parties, ask for decision-making tools to support them in a quick and reactive reconfiguration of their production lines. Traditional discrete event simulation models, widely studied in the literature to solve production-related issues, do not allow real-time support to business decisions in dynamic contexts, due to the time-consuming activities needed to re-align parameters to changing environments. Data-driven approach overcomes these limitations, giving the possibility to easily update input and quickly rebuild the model itself without any changes in the modeling code. The proposed data-driven simulation model has also been interfaced with a commonly-used BI tool to support companies in the iterative comparison of different scenarios to define the optimal resource allocation for the requested production plan. The simulation model has been implemented into a SME operating in the footwear industry, showing how this approach can be used by companies to increase their performance even without a specific knowledge in building and validating simulation models.

Resection of Benign Duodenal Neoplasms

2007 ◽  
Vol 73 (11) ◽  
pp. 1086-1091 ◽  
Author(s):  
Clinton D. Kemp ◽  
Robert T. Russell ◽  
Kenneth W. Sharp
Keyword(s):  
Local Excision ◽  
Medical Center ◽  
Primary Anastomosis ◽  
Complication Rates ◽  
Duodenal Neoplasms ◽  
Frequent Use ◽  
Size Number ◽  
Small Bowel Neoplasms ◽  
Duodenal Resection ◽  
Vanderbilt University

Primary small bowel neoplasms (PSBN) are uncommon, accounting for less than 15 per cent of all gastrointestinal tumors. Benign duodenal neoplasms (BDN) are rare, comprising only 10 to 20 per cent of all PSBN. The treatment is generally surgical resection ranging from local excision to pancreaticoduodenectomy depending on size, location, and number of lesions. Patients undergoing surgical treatment for BDN at Vanderbilt University Medical Center from July 1984 to April 2006, were identified and reviewed retrospectively. Medical records were examined for demographics, operative details, results, and complications. Twenty-six patients were identified of which 56 per cent were male and the mean age was 56 ± 14 years. Lesions were found throughout the duodenum, but the majority (62%) were ampullary. Nearly 75 per cent were adenomas, including over half with dysplasia. Operative interventions and complication rates were: duodenal resection with primary anastomosis (n = 3, 0%), local excision (n = 6, 50%), ampullary resection (n = 10, 30%), and pancreaticoduodenectomy (n = 7, 86%). There were no reoperations or mortalities. Mean followup was 14 months. BDN are an increasingly common problem in an era of frequent use of upper endoscopy. The surgical management of these lesions must be tailored to their size, number, location, and malignant potential. A wide variety of surgical procedures can be performed with acceptable morbidity.

scholarly journals Identifying the best questions for rapid screening of secondhand smoke exposure among children

2020 ◽  
Author(s):  
Albert J Ksinan ◽  
Yaou Sheng ◽  
Elizabeth K Do ◽  
Julia C Schechter ◽  
Junfeng (Jim) Zhang ◽  
...  
Keyword(s):  
At Risk ◽  
Screening Tool ◽  
Smoke Exposure ◽  
Data Driven ◽  
The Past ◽  
Smoking Exposure ◽  
Data Driven Approach ◽  
Shs Exposure ◽  
Child Age ◽  
Cotinine Concentration

Abstract Introduction Many children suffer from secondhand smoke exposure (SHSe), which leads to a variety of negative health consequences. However, there is no consensus on how clinicians can best query parents for possible SHSe among children. We employed a data-driven approach to create an efficient screening tool for clinicians to quickly and correctly identify children at risk for SHSe. Methods Survey data from mothers and biospecimens from children were ascertained from the Neurodevelopment and Improving Children’s Health following Environmental Tobacco Smoke Exposure (NICHES) study. Included were mothers and their children whose saliva were assayed for cotinine (n = 351 pairs, mean child age = 5.6 years). Elastic net regression predicting SHSe, as indicated from cotinine concentration, was conducted on available smoking-related questions and cross-validated with 2015-2016 National Health and Nutrition Examination Survey (NHANES) data to select the most predictive items of SHSe among children (n = 1,670, mean child age = 8.4 years). Results Answering positively to at least one of the two final items (“During the past 30 days, did you smoke cigarettes at all?” and “Has anyone, including yourself, smoked tobacco in your home in the past 7 days?”) showed AUC = .82, and good specificity (.88) and sensitivity (.74). These results were validated with similar items in the nationally-representative NHANES sample, AUC = .82, specificity = .78, and sensitivity = .77. Conclusions Our data-driven approach identified and validated two items that may be useful as a screening tool for a speedy and accurate assessment of SHSe among children. Implications The current study used a rigorous data-driven approach to identify questions that could reliably predict secondhand smoking exposure (SHS) among children.Using saliva cotinine concentration levels as a gold standard for determining SHS exposure, our analysis employing elastic net regression identified two questions that served as good classifier for distinguishing children who might be at risk for SHS exposure. The two items that we validated in the current study can be readily used by clinicians, such as pediatricians, as part of screening procedures to quickly identify whether children might be at risk for secondhand smoking exposure.

scholarly journals A data driven approach to understanding the organization of high-level visual cortex

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
David M. Watson ◽  
Timothy J. Andrews ◽  
Tom Hartley
Keyword(s):  
Visual Cortex ◽  
Data Driven ◽  
Data Driven Approach ◽  
High Level

Failure Prognostics for In-Tank Fuel Pumps of the Returnless Fuel Systems

2016 ◽  
Author(s):  
Ehsan Taheri ◽  
Oleg Gusikhin ◽  
Ilya Kolmanovsky
Keyword(s):  
Electrical Signal ◽  
Data Driven ◽  
Connected Vehicle ◽  
Reliability Models ◽  
The Past ◽  
Degradation Modeling ◽  
Fuel Delivery ◽  
Data Driven Approach ◽  
Alternative Approaches ◽  
Type Fuel

With the motivation to develop Condition Based Maintenance (CBM) strategies for the automotive vehicles, this paper considers a data-driven approach to the prognostics of the automotive fuel pumps. Focusing on the returnless type fuel delivery systems, our approach is based on estimating the fuel pump workload based on the model learned from the past driving history. Statistical reliability models are then exploited to estimate failure probability. These models are formulated in terms of the workload and updated from data available from vehicles in the field. Numerical examples which illustrate the proposed methodology are reported. Compared to alternative approaches, which are based on detailed physics-based degradation modeling and/or electrical signal analysis, our approach is data-driven, exploits connected vehicle analytics and reliability-based modeling, and has a potential to lead to simpler implementations.

Sign in / Sign up

Export Citation Format

Share Document