Author:
Soo Martin,Robertson Lynn M,Ali Tariq,Clark Laura E,Fluck Nicholas,Johnston Marjorie,Marks Angharad,Prescott Gordon J,Smith William Cairns S,Black Corri
Abstract
Abstract
Background
In clinical practice, research, and increasingly health surveillance, planning and costing, there is a need for high quality information to determine comorbidity information about patients. Electronic, routinely collected healthcare data is capturing increasing amounts of clinical information as part of routine care. The aim of this study was to assess the validity of routine hospital administrative data to determine comorbidity, as compared with clinician-based case note review, in a large cohort of patients with chronic kidney disease.
Methods
A validation study using record linkage. Routine hospital administrative data were compared with clinician-based case note review comorbidity data in a cohort of 3219 patients with chronic kidney disease. To assess agreement, we calculated prevalence, kappa statistic, sensitivity, specificity, positive predictive value and negative predictive value. Subgroup analyses were also performed.
Results
Median age at index date was 76.3 years, 44% were male, 67% had stage 3 chronic kidney disease and 31% had at least three comorbidities. For most comorbidities, we found a higher prevalence recorded from case notes compared with administrative data. The best agreement was found for cerebrovascular disease (κ = 0.80) ischaemic heart disease (κ = 0.63) and diabetes (κ = 0.65). Hypertension, peripheral vascular disease and dementia showed only fair agreement (κ = 0.28, 0.39, 0.38 respectively) and smoking status was found to be poorly recorded in administrative data. The patterns of prevalence across subgroups were as expected and for most comorbidities, agreement between case note and administrative data was similar. Agreement was less, however, in older ages and for those with three or more comorbidities for some conditions.
Conclusions
This study demonstrates that hospital administrative comorbidity data compared moderately well with case note review data for cerebrovascular disease, ischaemic heart disease and diabetes, however there was significant under-recording of some other comorbid conditions, and particularly common risk factors.
Publisher
Springer Science and Business Media LLC
Subject
General Biochemistry, Genetics and Molecular Biology,General Medicine
Reference26 articles.
1. Medical Research Council: UK e-Health Records Research Capacity and Capability. [http://www.mrc.ac.uk/Utilities/Documentrecord/index.htm?d=MRC007896]
2. Medical Research Council: Strategic Framework for Health Informatics in Support of Research. [http://www.mrc.ac.uk/Utilities/Documentrecord/index.htm?d=MRC006669]
3. Medical Research Council: Funding Opportunities, E-Health Informatics Research Centres (E-HIRCs) Call. [http://www.mrc.ac.uk/Fundingopportunities/Calls/E-healthCentresCall/index.htm]
4. World Health Organisation: International Classification of Diseases (ICD). [http://www.who.int/classifications/icd/en/]
5. Information Services Division Scotland: Assessment of SMR01 Data 2010–2011. [http://www.isdscotland.org/Health-Topics/Hospital-Care/Publications/2012-05-08/Assessment-of-SMR01Data-2010-2011-ScotlandReport.pdf]