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Accuracy of administrative databases in identifying patients with hypertension

. 2007 Apr 14;1(1):e18-26. Accuracy of administrative databases in identifying patients with hypertension

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Accuracy of administrative databases in identifying patients with hypertension

Karen Tu et al. Open Med. 2007.

. 2007 Apr 14;1(1):e18-26.

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Abstract

Background: Traditionally, the determination of the occurrence of hypertension in patients has relied on costly and time-consuming survey methods that do not allow patients to be followed over time.

Objectives: To determine the accuracy of using administrative claims data to identify rates of hypertension in a large population living in a single-payer health care system.

Methods: Various definitions for hypertension using administrative claims databases were compared with 2 other reference standards: (1) data obtained from a random sample of primary care physician offices throughout the province, and (2) self-reported survey data from a national census.

Results: A case-definition algorithm employing 2 outpatient physician billing claims for hypertension over a 3-year period had a sensitivity of 73% (95% confidence interval [CI] 69%-77%), a specificity of 95% (CI 93%-96%), a positive predictive value of 87% (CI 84%-90%), and a negative predictive value of 88% (CI 86%-90%) for detecting hypertensive adults compared with physician-assigned diagnoses. Compared with self-reported survey data, the algorithm had a sensitivity of 64% (CI 63%-66%), a specificity of 94%(CI 93%-94%), a positive predictive value of 77% (76%-78%), and negative predictive value of 89% (CI 88%-89%). When this algorithm was applied to the entire province of Ontario, the age- and sex-standardized prevalence of hypertension in adults older than 35 years increased from 20% in 1994 to 29% in 2002.

Conclusions: It is possible to use administrative data to accurately identify from a population sample those patients who have been diagnosed with hypertension. Given that administrative data are already routinely collected, their use is likely to be substantially less expensive compared with serial cross-sectional or cohort studies for surveillance of hypertension occurrence and outcomes over time in a large population.

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Conflict of interest statement

Competing interests: Dr. Campbell has been paid fees for speaking and for consulting by most pharmaceutical companies in Canada that produce prescription medications to lower blood pressure and has received research funds from Pfizer Canada, Sanofi-Aventis, Merck Frosst, Servier and Bristol-Myers-Squibb for research on the epidemiology of hypertension. Dr. Campbell also chairs the steering committee and executive committee of the Canadian Hypertension Education Program (CHEP) as a volunteer. CHEP has a mandate to improve the treatment and control of hypertension in Canada. Dr. McAlister has received operating grant funding from Pfizer Canada for an ongoing investigator-initiated trial co-funded by the Heart and Stroke Foundation of Canada and Pfizer Canada. The other authors have no potential conflicts of interest.

Figures

Figure 1

Forest plots for validation of…

Figure 1

Forest plots for validation of hypertension case-definition algorithms against primary care chart data…

Figure 1

Forest plots for validation of hypertension case-definition algorithms against primary care chart data for 1676 patients older than 35 years (32% with chart diagnosis of hypertension)

Figure 2

Forest plots for validation of…

Figure 2

Forest plots for validation of hypertension case-definition algorithms against self-report survey data for…

Figure 2

Forest plots for validation of hypertension case-definition algorithms against self-report survey data for 22,087 adult patients (23% with self-reported diagnosis of hypertension)

Figure 3

Annual population adjusted, age and…

Figure 3

Annual population adjusted, age and sex standardized prevalence and incidence of hypertension in…

Figure 3

Annual population adjusted, age and sex standardized prevalence and incidence of hypertension in adults age 35 and over in Ontario using 2 physician billing claims in 3 years from index claim.

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