scholarly journals Pseudonmization Techniques for Privacy Study with Clinical Data

2012 ◽  
Vol 2 (6) ◽  
pp. 75-78 ◽  
Author(s):  
Yahaya Abd. Rahim ◽  
Shahrin Sahib ◽  
Mohd Khanapi Abd Ghani
Keyword(s):  
Clinical Data

Abstract # P-13: Characteristics of Korean T2DM Patients with Diabetic Retinopathy and Macular Edema: A Study Based on a Standardized Clinical Data

2016 ◽  
Vol 22 ◽  
pp. 19-20
Author(s):  
Sang Youl Rhee ◽  
Sejeong Park ◽  
Ki Young Kim ◽  
Suk Chon ◽  
Seung-Young Yu ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Macular Edema ◽  
Clinical Data

Lode for Clinical Data

1957 ◽  
Vol 2 (1) ◽  
pp. 14-15
Author(s):  
ALBERT BANDURA
Keyword(s):  
Clinical Data

Glare and age: Acquisition of a clinical data base for aircrew standards.

1990 ◽  
Author(s):  
Joseph M. Harrison ◽  
Peng Chen ◽  
Charles S. Ballentine ◽  
J. Terry Yates
Keyword(s):  
Data Base ◽  
Clinical Data

Keeping psychologists in the driver’s seat: Four perspectives on quality improvement and clinical data registries.

Psychotherapy ◽  
2020 ◽  
Vol 57 (4) ◽  
pp. 562-573 ◽  
Author(s):  
Tony Rousmaniere ◽  
Caroline Vaile Wright ◽  
James Boswell ◽  
Michael J. Constantino ◽  
Louis Castonguay ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Clinical Data

Neuravena® and the brain: first clinical data

2009 ◽  
Vol 30 (S 01) ◽  
Author(s):  
C Schellekens ◽  
T Perrinjaquet-Moccetti ◽  
M Verbruggen ◽  
W Dimpfel
Keyword(s):  
Clinical Data ◽  
The Brain

Haemophilia Registry of the Medical Committee of the Swiss Haemophilia Society

2009 ◽  
Vol 29 (S 01) ◽  
pp. S16-S18 ◽  
Author(s):  
B. Brand ◽  
N. von der Weid
Keyword(s):  
Quality Control ◽  
Infectious Diseases ◽  
Mutation Analysis ◽  
Clinical Data ◽  
Age Groups ◽  
Treatment Modalities ◽  
Global Survey ◽  
On Demand ◽  
Per Capita ◽  
Severity Of The Disease

SummaryThe Swiss Haemophilia Registry of the Medical Committee of the Swiss Haemophilia Society was established in 2000. Primarily it bears epidemiological and basic clinical data (incidence, type and severity of the disease, age groups, centres, mortality). Two thirds of the questions of the WFH Global Survey can be answered, especially those concerning use of concentrates (global, per capita) and treatment modalities (on-demand versus prophylactic regimens). Moreover, the registry is an important tool for quality control of the haemophilia treatment centres.There are no informations about infectious diseases like hepatitis or HIV, due to non-anonymisation of the data. We plan to incorporate the results of the mutation analysis in the future.

User Evaluation of an Integrated Medical Workstation for Clinical Data Analysis

1993 ◽  
Vol 32 (05) ◽  
pp. 365-372 ◽  
Author(s):  
T. Timmeis ◽  
J. H. van Bemmel ◽  
E. M. van Mulligen
Keyword(s):  
Data Analysis ◽  
Clinical Research ◽  
Clinical Data ◽  
University Hospital ◽  
User Evaluation ◽  
Scientific Staff ◽  
Medical Institutions ◽  
Clinical Data Analysis ◽  
Research Problems ◽  
The University

AbstractResults are presented of the user evaluation of an integrated medical workstation for support of clinical research. Twenty-seven users were recruited from medical and scientific staff of the University Hospital Dijkzigt, the Faculty of Medicine of the Erasmus University Rotterdam, and from other Dutch medical institutions; and all were given a written, self-contained tutorial. Subsequently, an experiment was done in which six clinical data analysis problems had to be solved and an evaluation form was filled out. The aim of this user evaluation was to obtain insight in the benefits of integration for support of clinical data analysis for clinicians and biomedical researchers. The problems were divided into two sets, with gradually more complex problems. In the first set users were guided in a stepwise fashion to solve the problems. In the second set each stepwise problem had an open counterpart. During the evaluation, the workstation continuously recorded the user’s actions. From these results significant differences became apparent between clinicians and non-clinicians for the correctness (means 54% and 81%, respectively, p = 0.04), completeness (means 64% and 88%, respectively, p = 0.01), and number of problems solved (means 67% and 90%, respectively, p = 0.02). These differences were absent for the stepwise problems. Physicians tend to skip more problems than biomedical researchers. No statistically significant differences were found between users with and without clinical data analysis experience, for correctness (means 74% and 72%, respectively, p = 0.95), and completeness (means 82% and 79%, respectively, p = 0.40). It appeared that various clinical research problems can be solved easily with support of the workstation; the results of this experiment can be used as guidance for the development of the successor of this prototype workstation and serve as a reference for the assessment of next versions.

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