Literature DB >> 17510106

The value of administrative databases.

Mohammed A Mohammed, Andrew Stevens.   

Abstract

Mesh:

Year:  2007        PMID: 17510106      PMCID: PMC1871738          DOI: 10.1136/bmj.39211.453275.80

Source DB:  PubMed          Journal:  BMJ        ISSN: 0959-8138


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  12 in total

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Authors:  Shukri F Khuri; Jennifer Daley; William G Henderson
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2.  Hospital episode statistics: time for clinicians to get involved?

Authors:  J G Williams; R Y Mann
Journal:  Clin Med (Lond)       Date:  2002 Jan-Feb       Impact factor: 2.659

3.  Explaining differences in English hospital death rates using routinely collected data.

Authors:  B Jarman; S Gault; B Alves; A Hider; S Dolan; A Cook; B Hurwitz; L I Iezzoni
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4.  Towards a national clinical minimum data set for general surgery.

Authors:  D R Prytherch; J S Sirl; P C Weaver; P Schmidt; B Higgins; G L Sutton
Journal:  Br J Surg       Date:  2003-10       Impact factor: 6.939

5.  Surgery for congenital heart conditions in Oxford.

Authors:  Bruce Keogh
Journal:  BMJ       Date:  2005-02-12

6.  Was Rodney Ledward a statistical outlier? Retrospective analysis using routine hospital data to identify gynaecologists' performance.

Authors:  Mike Harley; Mohammed A Mohammed; Shakir Hussain; John Yates; Abdullah Almasri
Journal:  BMJ       Date:  2005-04-15

7.  Administrative databases: fact or fiction?

Authors:  W J Marshall
Journal:  CMAJ       Date:  1998-02-24       Impact factor: 8.262

8.  Mortality after noncardiac surgery: prediction from administrative versus clinical data.

Authors:  Howard S Gordon; Michael L Johnson; Nelda P Wray; Nancy J Petersen; William G Henderson; Shukri F Khuri; Jane M Geraci
Journal:  Med Care       Date:  2005-02       Impact factor: 2.983

Review 9.  Assessing quality using administrative data.

Authors:  L I Iezzoni
Journal:  Ann Intern Med       Date:  1997-10-15       Impact factor: 25.391

10.  Use of administrative data or clinical databases as predictors of risk of death in hospital: comparison of models.

Authors:  Paul Aylin; Alex Bottle; Azeem Majeed
Journal:  BMJ       Date:  2007-04-23
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  14 in total

1.  Why Everyone Should Care About "Computable Phenotypes".

Authors:  Robert C Tasker
Journal:  Pediatr Crit Care Med       Date:  2017-05       Impact factor: 3.624

2.  Validation of Administrative Coding and Clinical Notes for Hospital-Acquired Acute Kidney Injury in Adults.

Authors:  Jianqiu Zhang; Paul E Drawz; Ying Zhu; Gretchen Hultman; Gyorgy Simon; Genevieve B Melton
Journal:  AMIA Annu Symp Proc       Date:  2022-02-21

3.  Validation of an ICD code for accurately identifying emergency department patients who suffer an out-of-hospital cardiac arrest.

Authors:  Shelby K Shelton; Steve B Chukwulebe; David F Gaieski; Benjamin S Abella; Brendan G Carr; Sarah M Perman
Journal:  Resuscitation       Date:  2018-01-16       Impact factor: 5.262

4.  Do inter-hospital comparisons of in-hospital, acute myocardial infarction case-fatality rates serve the purpose of fostering quality improvement? An evaluative study.

Authors:  Willem Aelvoet; Nathalie Terryn; Geert Molenberghs; Guy De Backer; Christiaan Vrints; Marc van Sprundel
Journal:  BMC Health Serv Res       Date:  2010-12-08       Impact factor: 2.655

5.  How Reliable Are Current Data for Assessing the Actual Prevalence of Chronic Obstructive Pulmonary Disease?

Authors:  Anna Maria Romanelli; Mauro Raciti; Maria Angela Protti; Renato Prediletto; Edo Fornai; Annunziata Faustini
Journal:  PLoS One       Date:  2016-02-22       Impact factor: 3.240

6.  Validity of the International Classification of Diseases, Tenth Revision code for acute kidney injury in elderly patients at presentation to the emergency department and at hospital admission.

Authors:  Y Joseph Hwang; Salimah Z Shariff; Sonja Gandhi; Ron Wald; Edward Clark; Jamie L Fleet; Amit X Garg
Journal:  BMJ Open       Date:  2012-11-29       Impact factor: 2.692

7.  Index blood tests and national early warning scores within 24 hours of emergency admission can predict the risk of in-hospital mortality: a model development and validation study.

Authors:  Mohammed A Mohammed; Gavin Rudge; Duncan Watson; Gordon Wood; Gary B Smith; David R Prytherch; Alan Girling; Andrew Stevens
Journal:  PLoS One       Date:  2013-05-29       Impact factor: 3.240

8.  Which is more useful in predicting hospital mortality--dichotomised blood test results or actual test values? A retrospective study in two hospitals.

Authors:  Mohammed A Mohammed; Gavin Rudge; Gordon Wood; Gary Smith; Vishal Nangalia; David Prytherch; Roger Holder; Jim Briggs
Journal:  PLoS One       Date:  2012-10-15       Impact factor: 3.240

9.  From evidence based bioethics to evidence based social policies.

Authors:  Luc Bonneux
Journal:  Eur J Epidemiol       Date:  2007-07-27       Impact factor: 8.082

10.  Statistical profiling of hospital performance using acute coronary syndrome mortality.

Authors:  S O Manda; C P Gale; A S Hall; M S Gilthorpe
Journal:  Cardiovasc J Afr       Date:  2012-11       Impact factor: 1.167

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