Accuracy of administrative databases in identifying patients with hypertension.
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
- Teacher spread
- 0.027 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- PubMed
- Topic
- Medical Coding and Health Information
- Field
- Health Professions
- Canadian institutions
- —
- Funders
- —
- Keywords
- MedicineConfidence intervalMedical diagnosisPredictive valuePopulationCensusHealth carePediatricsDatabaseDemographyInternal medicineEnvironmental health
- Has abstract in OpenAlex
- yes