Background

Health administrative data are frequently used for health services and population health research. Comparative research using these data has been facilitated by the use of a standard system for coding diagnoses, the International Classification of Diseases (ICD). Research using the data must deal with data quality and validity limitations which arise because the data are not created for research purposes. This paper presents a list of high-priority methodological areas for researchers using health administrative data.

Methods

A group of researchers and users of health administrative data from Canada, the United States, Switzerland, Australia, China and the United Kingdom came together in June 2005 in Banff, Canada to discuss and identify high-priority methodological research areas. The generation of ideas for research focussed not only on matters relating to the use of administrative data in health services and population health research, but also on the challenges created in transitioning from ICD-9 to ICD-10. After the brain-storming session, voting took place to rank-order the suggested projects. Participants were asked to rate the importance of each project from 1 (low priority) to 10 (high priority). Average ranks were computed to prioritise the projects.

Results

Thirteen potential areas of research were identified, some of which represented preparatory work rather than research per se. The three most highly ranked priorities were the documentation of data fields in each country's hospital administrative data (average score 8.4), the translation of patient safety indicators from ICD-9 to ICD-10 (average score 8.0), and the development and validation of algorithms to verify the logic and internal consistency of coding in hospital abstract data (average score 7.0).

Conclusion

The group discussions resulted in a list of expert views on critical international priorities for future methodological research relating to health administrative data. The consortium's members welcome contacts from investigators involved in research using health administrative data, especially in cross-jurisdictional collaborative studies or in studies that illustrate the application of ICD-10.

Purpose

To determine the clinical outcomes of women and men with nonobstructive coronary artery disease ( CAD coronary artery disease ) with coronary computed tomographic (CT) angiography data in patients who were similar in terms of CAD coronary artery disease risk factors, angina typicality, and CAD coronary artery disease extent and distribution.

Materials and methods

Institutional review board approval was obtained for all participating sites, with either informed consent or waiver of informed consent. In a prospective international multicenter cohort study of 27 125 patients undergoing coronary CT angiography at 12 centers, 18 158 patients with no CAD coronary artery disease or nonobstructive (<50% stenosis) CAD coronary artery disease were examined. Men and women were propensity matched for age, CAD coronary artery disease risk factors, angina typicality, and CAD coronary artery disease extent and distribution, which resulted in a final cohort of 11 462 subjects. Nonobstructive CAD coronary artery disease presence and extent were related to incident major adverse cardiovascular events ( MACE major adverse cardiovascular events ), which were inclusive of death and myocardial infarction and were estimated by using multivariable Cox proportional hazards models.

Results

At a mean follow-up ± standard deviation of 2.3 years ± 1.1, MACE major adverse cardiovascular events occurred in 164 patients (0.6% annual event rate). After matching, women and men experienced identical annualized rates of myocardial infarction (0.2% vs 0.2%, P = .72), death (0.5% vs 0.5%, P = .98), and MACE major adverse cardiovascular events (0.6% vs 0.6%, P = .94). In multivariable analysis, nonobstructive CAD coronary artery disease was associated with similarly increased MACE major adverse cardiovascular events for both women (hazard ratio: 1.96 [95% confidence interval { CI confidence interval }: 1.17, 3.28], P = .01) and men (hazard ratio: 1.77 [95% CI confidence interval : 1.07, 2.93], P = .03).

Conclusion

When matched for age, CAD coronary artery disease risk factors, angina typicality, and nonobstructive CAD coronary artery disease extent, women and men experience comparable rates of incident mortality and myocardial infarction.