Validation of a Population-Based Algorithm to Detect Chronic Psychotic Illness

Abstract

Using health administrative data to study population-based outcomes for people with chronic psychotic illness is feasible and valid. Researchers can select case identification methods based on whether a more sensitive or more specific definition of chronic psychotic illness is desired.

Trends in standardized mortality among individuals with schizophrenia, 1993–2012: a population-based, repeated cross-sectional study

“…We used a validated algorithm to detect all cases of schizophrenia and schizoaffective disorder in Ontario from linked, population-level health administrative data available at the Institute for Clinical Evaluative Sciences (ICES). 15 We ascertained cases on the basis of a single hospital admission within 12 months or 3 phys ician visits within 36 months (sensitivity 96.5%, specificity 57.1%). 15 Psychiatric hospital admissions before 2005 were captured in the Canadian Institute for Health Information (CIHI) Discharge Abstract Database, using the International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) codes F20 and F25; hospital admissions from 2005 onward were captured in the Ontario Mental Health Reporting System using diagnosis 295 from the Diagnostic and Statistical Manual of Mental Disorders, 4th edition.…”

“…15 We ascertained cases on the basis of a single hospital admission within 12 months or 3 phys ician visits within 36 months (sensitivity 96.5%, specificity 57.1%). 15 Psychiatric hospital admissions before 2005 were captured in the Canadian Institute for Health Information (CIHI) Discharge Abstract Database, using the International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) codes F20 and F25; hospital admissions from 2005 onward were captured in the Ontario Mental Health Reporting System using diagnosis 295 from the Diagnostic and Statistical Manual of Mental Disorders, 4th edition. We identified physician service claims from Ontario Health Insurance Plan data, which contain patient diagnostic codes for physician visits and consultation billings (specifically code 295).…”

“…Using hospital admission for case ascertainment misses individuals managed in ambulatory settings and biases the sample toward greater severity, underestimating the prevalence and overestimating the mortality burden of severe mental illness. [11][12][13]15 Mortality in more restricted populations of patients with schizophrenia is likely to be different from that in more hetero geneous populations with severe mental illness, because individuals with schizophrenia have a more chronic course of illness, 16 more cognitive and functional impairment 17 and likely a longer-term exposure to antipsychotics known to be associated with higher risk of diabetes mellitus. 18 Thus, investigating the mortality trends of individuals with schizophrenia is crucial for determining whether they have experienced the same health improvements as the general population or whether other approaches are required to address their unique needs.…”

Incidence of psychotic disorders among first-generation immigrants and refugees in Ontario

“…15 We calculated person-time of follow-up from the time of cohort inception, with censoring at the index episode of psychotic disorder, death or the end of the follow-up period. Available sociodemographic data included age, sex, and urban versus rural place of residence.…”

“…The moderate positive predictive value (67.4%) associated with the diagnostic algorithm that we used indicates that a proportion of cases in our sample may be false-positives, which may have also contributed to the high crude incidence rate we observed compared with other jurisdictions. 38 Additionally, the diagnostic algorithm that we used was validated for chronic psychotic illness, 15 and its performance may differ for firstonset or single acute episodes of psychotic disorders.…”