Validation of a Case Definition to Define Hypertension Using Administrative Data

We validated the accuracy of case definitions for hypertension derived from administrative data across time periods (year 2001 versus 2004) and geographic regions using physician charts. Physician charts were randomly selected in rural and urban areas from Alberta and British Columbia, Canada, during years 2001 and 2004. Physician charts were linked with administrative data through unique personal health number. We reviewed charts of ≈50 randomly selected patients >35 years of age from each clinic within 48 urban and 16 rural family physician clinics to identify physician diagnoses of hypertension during the years 2001 and 2004. The validity indices were estimated for diagnosed hypertension using 3 years of administrative data for the 8 case-definition combinations. Of the 3362 patient charts reviewed, the prevalence of hypertension ranged from 18.8% to 33.3%, depending on the year and region studied. The administrative data hypertension definition of “2 claims within 2 years or 1 hospitalization” had the highest validity relative to the other definitions evaluated (sensitivity 75%, specificity 94%, positive predictive value 81%, negative predictive value 92%, and &kgr; 0.71). After adjustment for age, sex, and comorbid conditions, the sensitivities between regions, years, and provinces were not significantly different, but the positive predictive value varied slightly across geographic regions. These results provide evidence that administrative data can be used as a relatively valid source of data to define cases of hypertension for surveillance and research purposes.

[1]  S. Harris,et al.  Recommendations from the Canadian Diabetes Association. 2003 guidelines for prevention and management of diabetes and related cardiovascular risk factors. , 2004, Canadian family physician Medecin de famille canadien.

[2]  Karen Tu,et al.  Accuracy of administrative databases in identifying patients with hypertension , 2007, Open medicine : a peer-reviewed, independent, open-access journal.

[3]  E. Schiffrin,et al.  The 2009 Canadian Hypertension Education Program recommendations for the management of hypertension: Part 1--blood pressure measurement, diagnosis and assessment of risk. , 2009, The Canadian journal of cardiology.

[4]  R. Collins,et al.  Blood pressure, stroke, and coronary heart disease Part 2, short-term reductions in blood pressure: overview of randomised drug trials in their epidemiological context , 1990, The Lancet.

[5]  R. Collins,et al.  Blood pressure, stroke, and coronary heart disease Part 1, prolonged differences in blood pressure: prospective observational studies corrected for the regression dilution bias , 1990, The Lancet.

[6]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[7]  Lawrence A Leiter,et al.  The 2007 Canadian Hypertension Education Program recommendations for the management of hypertension: part 2 - therapy. , 2007, The Canadian journal of cardiology.

[8]  W. Kannel Blood pressure as a cardiovascular risk factor: prevention and treatment. , 1996, JAMA.

[9]  E. Schiffrin,et al.  The 2008 Canadian Hypertension Education Program recommendations for the management of hypertension: Part 1 - blood pressure measurement, diagnosis and assessment of risk. , 2006, The Canadian journal of cardiology.

[10]  M. Pepe The Statistical Evaluation of Medical Tests for Classification and Prediction , 2003 .

[11]  Simon L Bacon,et al.  The 2010 Canadian Hypertension Education Program recommendations for the management of hypertension: part 2 - therapy. , 2010, The Canadian journal of cardiology.

[12]  D. K. Williams,et al.  Assessing hospital-associated deaths from discharge data. The role of length of stay and comorbidities. , 1988, JAMA.

[13]  J. Cutler,et al.  Effect of Antihypertensive Drug Treatment on Cardiovascular Outcomes in Women and Men , 1997, Annals of Internal Medicine.

[14]  E. Fisher,et al.  Comorbidities, complications, and coding bias. Does the number of diagnosis codes matter in predicting in-hospital mortality? , 1992, JAMA.

[15]  Alexander G Logan,et al.  The 2009 Canadian Hypertension Education Program recommendations for the management of hypertension: Part 2 – therapy , 2009 .

[16]  K. Reynolds,et al.  Global burden of hypertension: analysis of worldwide data , 2005, The Lancet.

[17]  H. Quan,et al.  Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database. , 2008, Health services research.

[18]  D. Gelskey,et al.  Comparison of survey and physician claims data for detecting hypertension. , 1997, Journal of clinical epidemiology.

[19]  Majid Ezzati,et al.  For Personal Use. Only Reproduce with Permission from the Lancet Publishing Group , 2022 .

[20]  Vicki Freedman,et al.  Specificity and sensitivity of claims-based algorithms for identifying members of Medicare+Choice health plans that have chronic medical conditions. , 2004, Health services research.