Original ArticleHospital chart review provided more accurate comorbidity information than data from a general practitioner survey or an administrative database
Introduction
The linkage of medical records provides a potentially powerful tool for disease surveillance, evaluating health care outcomes and monitoring health service utilization [1], [2], [3], [4], [5]. Currently, there are at least six comprehensive population-based medical record linkage systems operating around the world that routinely link administrative health data [3], [6]. One of these is the Western Australian (WA) Data Linkage System, which includes links between seven core data sets: birth registrations, death registrations, hospital morbidity data, mental health records, midwives' notifications, cancer notifications, and electoral registrations variously dating back as early as 1966 to the present [3].
With the widespread use of record linkage systems, and other health-related administrative databases, there is a need to validate the quality of data they contain. Such validation assumes further importance when considering that research findings derived from these systems often form the basis of health care reforms [2], [7]. A number of validation studies have assessed the quality of data in administrative databases, including hospital morbidity data systems (HMDSs), with results suggesting that data on primary diagnoses and procedures are seldom missing and are accurately coded in more than 95% of instances [8], [9], [10], [11]. Within the WA Data Linkage System, a validation study of end-stage renal failure patients found that the administrative data pertaining to procedures such as renal dialysis and transplant were accurate in 97% of cases [6].
Although the quality of primary diagnosis data appears adequate, the accuracy of secondary diagnoses is less certain. This may pose problems for the numerous epidemiological investigations that use linked administrative data to adjust analyses for potential confounding produced by the presence of certain comorbid conditions [12], [13]. Since the development of the Charlson Comorbidity Index [14], it and similar indices of comorbidity have routinely been used for statistical adjustment by studies focusing on morbidity outcomes and hospital readmission [1], [15], [16], [17].
Clinical chart review, although more labor intensive and costly than the use of linked databases, has been shown to be a valid source for identifying primary and secondary conditions and has been suggested to be the best known available method for obtaining patient medical diagnosis data [18], [19], [20]. Moreover, data from patient interviews have been reported to correlate highly with measures of comorbidity based on medical records [19]. It is possible also that survey of patients' family physicians (known in Australia as general practitioners, or GPs) would also provide quality information on current and previous medical conditions.
In the present study we evaluated the accuracy of comorbidity data contained in the HMDS of the WA Data Linkage System by comparison with manual hospital chart review and survey of patients' GPs.
Section snippets
Selection of study comorbidities
One hundred comorbid conditions, categorized into 16 diagnostic chapters, were selected on the basis of their frequency of occurrence and potential to effect mortality or morbidity outcomes. The conditions were classified using the ninth revision of the International Classification of Diseases with Clinical Modifications (ICD-9-CM). Comorbidity diagnostic chapters and individual conditions comprising them are given in Table 1, Table 2, respectively. Corresponding ICD-9-CM codes for each of the
Comparison of administrative data and hospital charts
The occurrence (1986–1996) of comorbid conditions grouped under the 16 diagnostic chapters as recorded in the WA Data Linkage System and in the patients' hospital charts is given in Table 1. The number of comorbid conditions in HMDS records was underascertained in all diagnostic chapters, compared with hospital charts. In total, the frequency of recorded comorbidity in the administrative database accounted for only 45.5% of that found in hospital charts (range: 8.7–83.8% of hospital charts).
Discussion
The results indicate that, with few exceptions, large discrepancies existed in recorded comorbidity between hospital charts and the HMDS of the WA Data Linkage System for hospital admissions from 1986 to 1996. Examination of the individual comorbidities indicated that 83 of the selected 100 conditions were underascertained in administrative data compared with hospital charts. In addition, false-negative comorbidity diagnosis was high for all 16 comorbidity diagnostic chapters for those patients
Conclusions
Our conclusion is that comorbidity information in the WA Data Linkage System, preceding 1996, is poorly recorded compared with that contained in hospital charts, suggesting an inadequate transfer of comorbidity data from hospital to administrative database. To gain more accurate comorbidity data for research purposes, hospital chart review is required. Further, surveying GPs is an unsatisfactory alternative for obtaining quality retrospective information relating to patient comorbidity. Future
Acknowledgments
The initial construction of the Western Australian Data Linkage System was funded by the Western Australian Lotteries Commission. This study was supported by a project grant from the National Health and Medical Research Council. We thank the hospitals involved in the study for their assistance with hospital chart review.
References (34)
- et al.
Record linkage in Australian epidemiological research: health benefits, privacy safeguards and future potential
Aust J Public Health
(1995) - et al.
Population-based linkage of health records in Western Australia: development of a health services research linked database
Aust N Z J Public Health
(1999) - et al.
Validation of linked administrative data on end-stage renal failure: application of record linkage to a ‘clinical based population.’
Aust N Z J Public Health
(1999) - et al.
A research registry: uses, development and accuracy
J Clin Epidemiol
(1999) - et al.
A new method of classifying prognostic comorbidity in longitudinal studies: development and validation
J Chron Dis
(1987) - et al.
Searching for an improved clinical comorbidity index for use with ICD-9-CM administrative data
J Clin Epidemiol
(1996) - et al.
Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives
J Clin Epidemiol
(1993) - et al.
Accuracy of administrative data to assess comorbidity in patients with heart disease: an Australian perspective
J Clin Epidemiol
(2001) - et al.
Accuracy of administrative data for assessing outcomes after knee replacement surgery
J Clin Epidemiol
(1997) - et al.
Comorbidity measurement in elderly female breast cancer patients with administrative and medical records data
J Clin Epidemiol
(1997)
Practical considerations on the use of the Charlson Comorbidity Index with administrative databases
J Clin Epidemiol
Using administrative data to describe casemix: a comparison with the medical record
J Clin Epidemiol
Ischemic Heart Disease Patient Outcomes Research Team. A comparison of administrative versus clinical data: coronary artery bypass surgery as an example
J Clin Epidemiol
Utility of Charlson Comorbidity Index computed from routinely collected hospital discharge diagnosis codes
Method Inf Med
The Quality of Surgical Care Project: a model to evaluate surgical outcomes in Western Australia using population-based record linkage
Aust N Z J Surg
A population database for maternal and child health research in Western Australia using record linkage
Paediatr Perinat Epidemiol
Policy and program analysis using administrative databases
Ann Intern Med
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