Defining and improving data quality in medical registries: a literature review, case study, and generic framework. - Wikidata - awgldk - TriplyDB

Defining and improving data quality in medical registries: a literature review, case study, and generic framework.

Defining and improving data quality in medical registries: a literature review, case study, and generic framework.

http://www.wikidata.org/entity/Q30739868

about

In the critically ill patient, diabetes predicts mortality independent of statin therapy but is not associated with acute lung injury: a cohort study Training in data definitions improves quality of intensive care data Burden of gastrointestinal cancers and problem of the incomplete information; how to make up the data?Zoonotic disease surveillance--inventory of systems integrating human and animal disease information [RD] PRISM Library: Patient Registry Item Specifications and Metadata for Rare Diseases Quantifying data quality for clinical trials using electronic data capture Glocal clinical registries: pacemaker registry design and implementation for global and local integration--methodology and case study Adverse drug event reporting systems: a systematic review Transparent reporting of data quality in distributed data networks.Timeliness and data element completeness of immunization data in Washington State in 2010: a comparison of data exchange methods A practical framework for data management processes and their evaluation in population-based medical registries.Renal replacement therapy registries--time for a structured data quality evaluation programme.Influences of hospital information systems, indicator data collection and computation on reported Dutch hospital performance indicator scores.Error rates in a clinical data repository: lessons from the transition to electronic data transfer--a descriptive study.Do intensive care data on respiratory infections reflect influenza epidemics?Real-time database drawn from an electronic health record for a thoracic surgery unit: high-quality clinical data saving time and human resources.Results of data verification of the Japan congenital cardiovascular database, 2008 to 2009.Strategies for improving the data quality in national hospital discharge data system: a delphi study Influence of data quality on computed Dutch hospital quality indicators: a case study in colorectal cancer surgery Data quality and completeness in a web stroke registry as the basis for data and process mining.Clinical research informatics and electronic health record data Small rural emergency services can electronically collect accurate episode-level data: A cross-sectional study.The Cardiology Audit and Registration Data Standards (CARDS), European data standards for clinical cardiology practice.Quality of Big Data in health care.Perceived Reasons for High and Low Quality Observational HIV Research Data.Survival of TNF antagonists in spondylarthritis is better than in rheumatoid arthritis. Data from the Spanish registry BIOBADASER.Data reporting constraints for the lymphatic filariasis mass drug administration activities in two districts in Ghana: A qualitative study Application of An Ontology for Characterizing Data Quality For a Secondary Use of EHR Data Analyzing the effect of data quality on the accuracy of clinical decision support systems: a computer simulation approach.Using primary care electronic health record data for comparative effectiveness research: experience of data quality assessment and preprocessing in The Netherlands.A New Paradigm to Analyze Data Completeness of Patient Data Applying a Participatory Design Approach to Define Objectives and Properties of a "Data Profiling" Tool for Electronic Health Data Inter-rater reliability of data elements from a prototype of the Paul Coverdell National Acute Stroke Registry.Italian Registry of Haemophilia and Allied Disorders. Objectives, methodology and data analysis.Analysis of data errors in clinical research databases.Designing and implementing an Australian and New Zealand intensive care data audit study.Bayesian adjustment of gastric cancer mortality rate in the presence of misclassification "Summary Page": a novel tool that reduces omitted data in research databases.Electronic audit and feedback intervention with action implementation toolbox to improve pain management in intensive care: protocol for a laboratory experiment and cluster randomised trial Detecting contaminated birthdates using generalized additive models.

P2860

Q24601189-A79A51C1-53E5-4CFF-A530-07548624F18B Q24794456-A5F3F3AE-CD2B-4442-B02A-679F2EB6652A Q26770163-D7638E64-47EA-4EE3-9A24-FDC4F822C4A4 Q27008190-C7E265BD-0349-4A86-80AD-C2EF25BE84C9 Q28384262-0E42F7A0-9568-438E-9BC0-0705B62BF14B Q28473481-12B02006-E420-494B-8BF3-14957BE427B2 Q28673371-E857DD51-93D9-4491-ABD9-E666BF1802B3 Q30251709-D352B52B-46C5-4150-9C93-5C63035269F9 Q30487978-52E3C202-3CF3-43AE-B833-30068B1E9539 Q30585417-1E2BD8DB-62B6-4D49-B175-4A2E29864F1C Q30586219-D1618DD7-A631-43DA-93D0-699BBF25A041 Q30587152-849FD9A8-01AA-4DA5-9E06-F64B0D60AF36 Q30646654-1FC1BC9F-B87F-4AB0-8094-F87B8165CDE0 Q30651147-48FC11E3-C4D5-44AB-A4BF-9745C3A9C583 Q30726454-DF602538-5C7B-4485-8DE7-3DD1C17727DD Q30726863-2E626BF5-DAA4-4443-8972-862C2E3189BB Q30729284-9B3BD615-AE1E-493A-A0D8-5AF7C3F6E98C Q30760906-5BBA55FB-D7F1-4EBA-9A6C-85E629D828B2 Q30798214-64780950-D610-4E98-8845-C8A88C55E918 Q30830372-51405907-BDF0-4833-BB2E-B0A154CBDDBE Q30842819-598BEDDE-58EC-4A7B-B77D-CEF2EDE2C1AE Q30918599-E431711B-79DB-4EED-A44D-9D409AB9C835 Q30979240-BBBFA203-E342-4504-8260-48ED3E744C20 Q30979338-0C045A9A-2E90-4CD9-A19D-DDCBAE3C7E17 Q30986522-6F1669CF-B812-4C99-B12B-05E3135005CE Q31036925-8405D917-0D42-4F5E-99C3-BF3C2D40F66E Q31037050-F4A30FAA-FA4B-4E06-9860-68CFEBD42AE7 Q31077807-BCDC785C-B2B1-41F1-A43A-897102B07121 Q31094889-5C69B06B-758F-4C96-936B-3FA048AFDF58 Q31110771-DD6B07D9-00E4-4B0E-855E-42E3B35BF304 Q31119177-CFA62030-E32F-4FAC-9899-ECBA02685AA5 Q31124803-6212AB7A-CD7C-478E-AB6B-66A082413F40 Q31158911-A8AFBA73-9F59-4CC5-90FC-AF7D06D47581 Q33324733-1B8E9CE5-17F5-4F43-B6A3-E47DF4EB9E71 Q33383474-7E8F2822-AB1E-42E7-89FF-7A0F2F42A7B8 Q33517148-56180E7D-2B61-4BE1-8055-04215935581B Q33560101-4199C0A0-9A36-4CD2-B758-0295303E4787 Q33713323-6880B9EB-F735-4D21-8B27-D90034956BC6 Q33730359-1D981BBC-9728-4FDF-A11E-E35E93181335 Q33785528-7F6A0FD4-80C0-4FE3-8430-A9678B01772C

P2860

Defining and improving data quality in medical registries: a literature review, case study, and generic framework.

http://www.wikidata.org/entity/Q30739868

description

2002 nî lūn-bûn

@nan

2002 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած

@hyw

2002 թվականի նոյեմբերին հրատարակված գիտական հոդված

@hy

2002年の論文

@ja

2002年論文

@yue

2002年論文

@zh-hant

2002年論文

@zh-hk

2002年論文

@zh-mo

2002年論文

@zh-tw

2002年论文

@wuu

name

Defining and improving data qu ...... study, and generic framework.

@ast

Defining and improving data qu ...... study, and generic framework.

@en

type

label

Defining and improving data qu ...... study, and generic framework.

@ast

Defining and improving data qu ...... study, and generic framework.

@en

prefLabel

Defining and improving data qu ...... study, and generic framework.

@ast

Defining and improving data qu ...... study, and generic framework.

@en

P1433

Q30739868-2627FFDF-9825-4603-920A-3FD10109DF4C

P1476

Q30739868-87D42387-89D0-4E56-B9B3-B1302B0FCAEE

P2093

Q30739868-2156EF74-123B-4987-98AB-8B05FED151C7

Q30739868-B36EE9CC-4AA6-4436-A2B8-7B4B3CC927AB

Q30739868-FF8D8E03-F7BC-4428-ADC1-A5B655DF0ED4

P2860

Q30739868-03DEA4EF-49D8-4671-A67E-5121D8C8EDE2

Q30739868-067F45A2-483D-4BBF-9870-D6A1426DEFB3

Q30739868-06B1AFB6-68B5-4779-891B-C92DA7065B15

Q30739868-071BD4EF-D55C-4802-AC7D-2D30454E1755

Q30739868-0780593E-7ED8-41D3-AF7C-64ED288806BF

Q30739868-0D9E61F0-E336-4E4A-A0D1-B3E8D708AC7C

Q30739868-0FF23810-5AD3-4FB5-9CB8-C3B40148FE93

Q30739868-1EDF2330-7E1C-43D8-904D-94A4AA4A775C

Q30739868-2C459E42-EB4C-4C88-9E57-EC635F9C72A5

Q30739868-31DF65C7-025B-4FBB-9656-2E7A4FC50A7F

P304

Q30739868-74C80BE0-0516-4E37-ACD6-7B06EE6A2280

P31

Q30739868-C0C2A291-427F-422E-8336-AA07FC3CD38D

P356

Q30739868-6AAD0B15-F8AB-4702-B243-CA9EEAAE30B3

P433

Q30739868-F63AF9C3-49C5-4244-844B-492ECC75D137

P478

Q30739868-5578F0F6-246A-402A-A5CA-91DAF19CE067

P577

Q30739868-5D38893E-B9AF-43DA-819E-79816FECE0A0

P698

Q30739868-3572B8F5-9C56-4CE0-B14E-8DAF892105C7

P921

Q30739868-C1E4D917-7904-4E2A-A4C8-48EEC0A44EF8

P932

Q30739868-6032CBF2-C108-4287-807E-B8EA70A372E4

P356

P1433

Journal of the American Medical Informatics Association

P1476

Defining and improving data qu ...... study, and generic framework.

@en

P2093

Danielle G T Arts

http://www.w3.org/2001/XMLSchema#string

Gert-Jan Scheffer

http://www.w3.org/2001/XMLSchema#string

Nicolette F De Keizer

http://www.w3.org/2001/XMLSchema#string

P2860

APACHE II: a severity of disease classification system

A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study

What lessons can be learned for cancer registration quality assurance from data users? Skin cancer as an example.

Quality control of dietary data collection in the CARDIA study.

Quality of data in the Manchester orthopaedic database

Quality control of validity of data collected in clinical trials. EORTC Study Group on Data Management (SGDM).

Exploring the degree of concordance of coded and textual data in answering clinical queries from a clinical data repository.

Assessing the quality of clinical data in a computer-based record for calculating the pneumonia severity index

APACHE II, data accuracy and outcome prediction.

Updates to the Data Quality Review Program: the Society of Thoracic Surgeons Adult Cardiac National Database.

P304

600-611

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1197/JAMIA.M1087

http://www.w3.org/2001/XMLSchema#string

P433

6

http://www.w3.org/2001/XMLSchema#string

P478

9

http://www.w3.org/2001/XMLSchema#string

P577

2002-11-01T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P698

12386111

http://www.w3.org/2001/XMLSchema#string

P921

P932

349377

http://www.w3.org/2001/XMLSchema#string