Error component analysis for PACS: operational sources of data error in real world PACS for DICOM series, study, and patient level identifiers

2002 ◽  
Author(s):  
Richard L. Kennedy ◽  
James A. Seibert
Keyword(s):  
Real World ◽  
Component Analysis ◽  
Error Component ◽  
Patient Level ◽  
Data Error ◽  
Series Study

scholarly journals Seasonal Error Component Analysis of the GPM IMERG Version 05 Precipitation Estimations Over Sichuan Basin of China

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
S. Tang ◽  
R. Li ◽  
J. He ◽  
X. Fan ◽  
H. Wang ◽  
...  
Keyword(s):  
Sichuan Basin ◽  
Component Analysis ◽  
Error Component

scholarly journals Patient-reported outcomes 3 months after spine surgery: is it an accurate predictor of 12-month outcome in real-world registry platforms?

2015 ◽  
Vol 39 (6) ◽  
pp. E17 ◽  
Author(s):  
Scott L. Parker ◽  
Anthony L. Asher ◽  
Saniya S. Godil ◽  
Clinton J. Devin ◽  
Matthew J. McGirt
Keyword(s):  
Health Care ◽  
Spine Surgery ◽  
Real World ◽  
Patient Reported Outcomes ◽  
Lumbar Spine Surgery ◽  
Meaningful Improvement ◽  
Patient Level ◽  
Life Years ◽  
Patient Reported ◽  
Prospective Longitudinal

OBJECT The health care landscape is rapidly shifting to incentivize quality of care rather than quantity of care. Quality and outcomes registry platforms lie at the center of all emerging evidence-driven reform models and will be used to inform decision makers in health care delivery. Obtaining real-world registry outcomes data from patients 12 months after spine surgery remains a challenge. The authors set out to determine whether 3-month patient-reported outcomes accurately predict 12-month outcomes and, hence, whether 3-month measurement systems suffice to identify effective versus noneffective spine care. METHODS All patients undergoing lumbar spine surgery for degenerative disease at a single medical institution over a 2-year period were enrolled in a prospective longitudinal registry. Patient-reported outcome instruments (numeric rating scale [NRS], Oswestry Disability Index [ODI], 12-Item Short Form Health Survey [SF-12], EQ-5D, and the Zung Self-Rating Depression Scale) were recorded prospectively at baseline and at 3 months and 12 months after surgery. Linear regression was performed to determine the independent association of 3- and 12-month outcome. Receiver operating characteristic (ROC) curve analysis was performed to determine whether improvement in general health state (EQ-5D) and disability (ODI) at 3 months accurately predicted improvement and achievement of minimum clinical important difference (MCID) at 12 months. RESULTS A total of 593 patients undergoing elective lumbar surgery were included in the study. There was a significant correlation between 3-month and 12-month EQ-5D (r = 0.71; p < 0.0001) and ODI (r = 0.70; p < 0.0001); however, the authors observed a sizable discrepancy in achievement of a clinically significant improvement (MCID) threshold at 3 versus 12 months on an individual patient level. For postoperative disability (ODI), 11.5% of patients who achieved an MCID threshold at 3 months dropped below this threshold at 12 months; 10.5% of patients who did not meet the MCID threshold at 3 months continued to improve and ultimately surpassed the MCID threshold at 12 months. For ODI, achieving MCID at 3 months accurately predicted 12-month MCID with only 62.6% specificity and 86.8% sensitivity. For postoperative health utility (EQ-5D), 8.5% of patients lost an MCID threshold improvement from 3 months to 12 months, while 4.0% gained the MCID threshold between 3 and 12 months postoperatively. For EQ-5D (quality-adjusted life years), achieving MCID at 3 months accurately predicted 12-month MCID with only 87.7% specificity and 87.2% sensitivity. CONCLUSIONS In a prospective registry, patient-reported measures of treatment effectiveness obtained at 3 months correlated with 12-month measures overall in aggregate, but did not reliably predict 12-month outcome at the patient level. Many patients who do not benefit from surgery by 3 months do so by 12 months, and, conversely, many patients reporting meaningful improvement by 3 months report loss of benefit at 12 months. Prospective longitudinal spine outcomes registries need to span at least 12 months to identify effective versus noneffective patient care.

Domain Adaptation for Video Steganalysis against Motion Vector Based Steganography

2014 ◽  
Vol 998-999 ◽  
pp. 1138-1145
Author(s):  
Ke Ren Wang ◽  
Wen Xiang Li
Keyword(s):  
Real World ◽  
Domain Adaptation ◽  
Motion Vector ◽  
Component Analysis ◽  
Potential Effect ◽  
Opposite Case ◽  
Real World Applications ◽  
Performance Results ◽  
Video Steganalysis

Video steganalysis takes effect when videos corrupted by the target steganography method are available. Nevertheless, classical classifiers deteriorate in the opposite case. This paper presents a method to cope with the problem of steganography method mismatch for the detection of motion vector (MV) based steganography. Firstly, Adding-or-Subtracting-One (AoSO) feature against MV based steganography and Transfer Component Analysis (TCA) for domain adaptation are revisited. Distributions of AoSO feature against various MV based steganography methods are illustrated, followed by the potential effect of TCA based AoSO feature. Finally, experiments are carried out on various cases of steganography method mismatch. Performance results demonstrate that TCA+AoSO feature significantly outperforms AoSO feature, and is more favorable for real-world applications.

Impact of a checklist used by pharmacists on hospital antimicrobial use: a patient-level interrupted time series study

2019 ◽  
Vol 103 (3) ◽  
pp. 251-258
Author(s):  
M. Fortier ◽  
P. Pistre ◽  
V. Ferreira ◽  
M. Pinsonneault ◽  
J.M. Charbonneau ◽  
...  
Keyword(s):  
Time Series ◽  
Interrupted Time Series ◽  
Antimicrobial Use ◽  
Time Series Study ◽  
Patient Level ◽  
Series Study

OEN: Multi-center, international, real-world evidence studies performed using health records without data pooling—The use of a common data model and shared analytical methods.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13554-e13554
Author(s):  
Bethany Levick ◽  
Sue Cheeseman ◽  
Eun Ji Nam ◽  
Haewon Doh ◽  
Subin Lim ◽  
...  
Keyword(s):  
Real World ◽  
Data Model ◽  
Clinical Care ◽  
Common Data Model ◽  
Local Data ◽  
Large Hospital ◽  
Patient Level Data ◽  
Patient Level ◽  
Real World Evidence ◽  
Level Data

e13554 Background: The value of real-world evidence derived from the care of patients managed outside the context of clinical trials is well recognised. However, the ability to link data from multiple centres, especially those from different countries, is complicated by complex legal and information governance differences. The Oncology Evidence Network is a collaboration of large hospital centres, with strong clinical informatics capabilities in six countries in Europe and Asia working with the support of an industrial partner to provide high quality, real world data reflecting routine clinical care. We have developed an efficient workflow based on a study-specific common data model (CDM) clinically validated at each site and analysed with a single analysis script, which embeds a set of data quality rules. Local implementation allows each centre to generate analytical outputs aligned across the different sites without the need for any patient level data to leave the participating site. This approach has been designed and tested in Epithelial Ovarian Cancer (EOC) patients. Methods: A CDM was agreed using expert advisors from each centre. Clinical alignment was achieved through iterative assessment of clinical vignettes, to ensure common definitions of clinical assessment, prognosis, and treatment algorithms in EOC patients. A data guide detailing variable level derivations and validation rules, general data coding principles, and conversions/codes from international coding systems was developed. The analysis scripts were implemented as a bespoke package (OpenOvary) in R. The package includes functions to validate the data against the CDM, and generate a standard output including tables, numerical summaries and Kaplan-Meier analysis of progression and overall survival. Results: 2,925 patient records from 6 centres across 6 countries were included in the study with 27 key data items curated by each centre. Treatment data is available detailing relevant surgical procedures and their outcomes, and regimens of SACT throughout patients’ care from diagnosis to death. Data completeness was generally high for key data items, with missing data ranging from 0-16% for FIGO stage at diagnosis and 0-14% for tumour morphology. The CDM and R script will be made publicly available for other centres to adopt and facilitate analysis of their local data. Conclusions: This collaboration has brought together a substantial body of data describing the care and outcomes for EOC patients. A CDM and flexible shared analysis approach enabled unified analysis and reporting whilst avoiding the transfer of patient level data and its pooling into a common database. The process of clinical and data alignment has generated a replicable model for rapid extension to other study centres to join the EOC study, or application to other disease areas.

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