Potential unmet need for gout diagnosis and treatment: capture-recapture analysis of a national administrative dataset

Abstract

Objective: To estimate the degree of undercount of people diagnosed with gout in administrative datasets using capture-recapture methods.

Methods: Hospitalization and drug dispensing claims (allopurinol or colchicine) data for all Aotearoa New Zealand were used to estimate the prevalence of gout in 2009 (n = 4 295 296). As a comparison, we calculated gout prevalence using a large primary care dataset using general practitioner diagnosis and prescribing records (n = 555 313). For each of these datasets, we estimated the undercount through capture-recapture analysis using a Poisson regression model. A two-list model was used, which included covariates such as age, gender, ethnic groups and New Zealand deprivation quintiles.

Results: The crude prevalence of diagnosed gout in the Aotearoa New Zealand population aged ≥ 20 years was 3.75%. The covariate-adjusted capture-recapture estimate of those not recorded but likely to have gout was 0.92%, giving an overall estimated prevalence of 4.67% (95% CI 4.49, 4.90%) for the population aged ≥ 20 years. This amounts to 80% of people with gout being identified by the algorithm for the Aotearoa New Zealand data-that is being recorded in either lists of dispensing of allopurinol or colchicine or hospital discharge. After capture-recapture, gout prevalence for all males aged ≥ 20 years was 7.3% and in older (≥ 65 years) Māori and Pacific men was >30%.

Conclusion: Capture-recapture analysis of administrative datasets provides a readily available method for estimating an aspect of unmet need in the population-in this instance potentially 20% of those with gout not being identified and treated specifically for this condition.