N
N Hague
Researcher at St George's, University of London
Publications - 23
Citations - 1150
N Hague is an academic researcher from St George's, University of London. The author has contributed to research in topics: Population & Data quality. The author has an hindex of 15, co-authored 23 publications receiving 1103 citations. Previous affiliations of N Hague include St. George's University & St George's Hospital.
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Journal ArticleDOI
Chronic kidney disease management in the United Kingdom: NEOERICA project results.
Paul E. Stevens,Donal O'Donoghue,S de Lusignan,J van Vlymen,Bernhard Klebe,Rachel J. Middleton,N Hague,John P. New,Christopher K.T. Farmer +8 more
TL;DR: It is suggested that stage 3-5 CKD is easily detected in existing computerized records and the associated comorbidity and management is readily available enabling intervention and targeting of specialist resources.
Journal ArticleDOI
Identifying patients with chronic kidney disease from general practice computer records
Simon de Lusignan,Tom Chan,Paul E. Stevens,Donal O'Donoghue,N Hague,Billy Dzregah,Jeremy van Vlymen,Mel Walker,Sean Hilton +8 more
TL;DR: The New Opportunities for Early Renal Intervention by Computerised Assessment (NEOERICA) project as mentioned in this paper aimed to assess whether people with undiagnosed chronic kidney disease who might benefit from early intervention could be identified from GP computer records.
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A method of identifying and correcting miscoding, misclassification and misdiagnosis in diabetes: a pilot and validation study of routinely collected data.
S de Lusignan,Kamlesh Khunti,Jonathan Belsey,Andrew T. Hattersley,J van Vlymen,Hugh Gallagher,Christopher Millett,N Hague,Charles R.V. Tomson,Kevin Harris,Azeem Majeed +10 more
TL;DR: Incorrect classification, diagnosis and coding of the type of diabetes may have implications for patient management and limit our ability to measure quality as mentioned in this paper, and the aim of the study was to measure the accuracy of diabetes diagnostic data and explore the scope for identifying errors.
Journal ArticleDOI
Managers see the problems associated with coding clinical data as a technical issue whilst clinicians also see cultural barriers.
TL;DR: The barriers to recording structured information in computerised medical records were examined to explore whether managers and clinicians had different perspectives in how these barriers should be overcome.
Journal ArticleDOI
Problems with primary care data quality: osteoporosis as an exemplar.
TL;DR: Clinicians with an understanding of what data are clinically relevant need to have a stronger voice in the production of codes, and in the creation of recommended lists, because there is variability in inter-practice data quality.