A Validation Study of Administrative Data Algorithms to Identify Patients with Parkinsonism with Prevalence and Incidence Trends

Abstract

Background: Epidemiological studies for identifying patients with Parkinson's disease (PD) or Parkinsonism (PKM) have been limited by their nonrandom sampling techniques and mainly veteran populations. This reduces their use for health services planning. The purpose of this study was to validate algorithms for the case ascertainment of PKM from administrative databases using primary care patients as the reference standard. Methods: We conducted a retrospective chart abstraction using a random sample of 73,003 adults aged ≥20 years from a primary care Electronic Medical Record Administrative data Linked Database (EMRALD) in Ontario, Canada. Physician diagnosis in the EMR was used as the reference standard and population-based administrative databases were used to identify patients with PKM from the derivation of algorithms. We calculated algorithm performance using sensitivity, specificity, and predictive values and then determined the population-level prevalence and incidence trends with the most accurate algorithms. Results: We selected, ‘2 physician billing codes in 1 year' as the optimal administrative data algorithm in adults and seniors (≥65 years) due to its sensitivity (70.6-72.3%), specificity (99.9-99.8%), positive predictive value (79.5-82.8%), negative predictive value (99.9-99.7%), and prevalence (0.28-1.20%), respectively. Conclusions: Algorithms using administrative databases can reliably identify patients with PKM with a high degree of accuracy.

Manual review of electronic medical records as a reference standard for case definition development: a validation study

“…They reported insufficient validity, with sensitivity ranging from 0.05% to 0.49%. The EMRALD database in Ontario, based on a single primary care EMR system, has been used as a reference standard for several studies validating case definitions; [7][8][9][10] however, these studies tend to validate case definitions using administrative data with EMR data as the reference standard.…”

Appendectomy in mid and later life and risk of Parkinson's disease: A population‐based study

“…PD was identified according to a previously published algorithm modified to exclude secondary and atypical parkinsonism codes. Under age 65, two PD OHIP International Classification of Diseases (ICD)‐8 or ICD‐9/ICD‐10 diagnostic codes (see Supporting table 1) within 1 year with at least 30 days between claims were required.…”

Association Between Gadolinium Contrast Exposure and the Risk of Parkinsonism

“…In addition, person-to-person transmission of SFTSV has been observed repeatedly. 4 To establish the very unlikely possibility that all 10 patients in the original article were co-infected with both A phagocytophilum and SFTSV, the authors should have the…”

“…The primary outcome, assessed from the initial MRI until death, emigration, or March 2015, was a new diagnosis of parkinsonism based on a validated definition (sensitivity, 81.7%; specificity, 99.7%; positive predictive value, 78.0%; negative predictive value, 99.8%; accuracy, 99.5%; and disease prevalence, 1.4%) using diagnosis codes from hospital admissions and physician visits or a dispensed Parkinson disease-specific medication. 4 We measured 105 covariates 5 and evaluated significant inequalities between patients who underwent only non-gadolinium-enhanced MRIs and those who underwent 1 or more gadoliniumenhanced MRI. A subset of 38 covariates particularly relevant to parkinsonism (based on potential associations from the literature) or significantly different at baseline (standardized difference >10%) were included in a multivariable timedependent extended Cox regression model using SAS (SAS Institute), version 9.4; the hazard ratio (HR) is interpreted as the hazard of parkinsonism per additional gadolinium exposure.…”