Schizophrenia (Aug 2024)

Prevalence and incidence measures for schizophrenia among commercial health insurance and medicaid enrollees

  • Molly T. Finnerty,
  • Atif Khan,
  • Kai You,
  • Rui Wang,
  • Gyojeong Gu,
  • Deborah Layman,
  • Qingxian Chen,
  • Noémie Elhadad,
  • Shalmali Joshi,
  • Paul S. Appelbaum,
  • Todd Lencz,
  • Sander Markx,
  • Steven A. Kushner,
  • Andrey Rzhetsky

DOI
https://doi.org/10.1038/s41537-024-00490-0
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 9

Abstract

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Abstract Given the chronic nature of schizophrenia, it is important to examine age-specific prevalence and incidence to understand the scope of the burden of schizophrenia across the lifespan. Estimates of lifetime prevalence of schizophrenia have varied widely and have often relied upon community-based data estimates from over two decades ago, while more recent studies have shown considerable promise by leveraging pooled datasets. However, the validity of measures of schizophrenia, particularly new onset schizophrenia, has not been well studied in these large health databases. The current study examines prevalence and validity of incidence measures of new diagnoses of schizophrenia in 2019 using two U.S. administrative health databases: MarketScan, a national database of individuals receiving employer-sponsored commercial insurance (N = 16,365,997), and NYS Medicaid, a large state public insurance program (N = 4,414,153). Our results indicate that the prevalence of schizophrenia is over 10-fold higher, and the incidence two-fold higher, in the NYS Medicaid population compared to the MarketScan database. In addition, prevalence increased over the lifespan in the Medicaid population, but decreased in the employment based MarketScan database beginning in early adulthood. Incident measures of new diagnoses of schizophrenia had excellent validity, with positive predictive values and specificity exceeding 95%, but required a longer lookback period for Medicaid compared to MarketScan. Further work is needed to leverage these findings to develop robust clinical outcome predictors for new onset of schizophrenia within large administrative health data systems.