Evidence map›Paper›PMID 38728421›Full record

ArticleSchizophrenia bulletin2024

Validation of an ICD-Code-Based Case Definition for Psychotic Illness Across Three Health Systems.

Anthony J Deo, Victor M Castro, Ashley Baker, Devon Carroll, Joseph Gonzalez-Heydrich, David C Henderson, Daphne J Holt, Kimberly Hook, Rakesh Karmacharya, Joshua L Roffman and 13 more

Abstract readValidation Study
In one paragraph

Article in Schizophrenia bulletin, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Parkinson's Disease Progression and Exposure to Contaminated Water at Camp Lejeune.Movement disorders : official journal of the Movement Disorder Society · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

23 authors.

Anthony J DeoDepartment of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Victor M CastroResearch Information Science and Computing, Mass General Brigham, Somerville, MA, USA.
Ashley BakerAscend Integrative Medicine LLC, MA, USA.
Devon CarrollDepartment of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Joseph Gonzalez-HeydrichDepartment of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
David C HendersonBoston Medical Center, Boston, MA, USA.
Daphne J HoltDepartment of Psychiatry, Harvard Medical School, Boston, MA, USA.
Kimberly HookHarvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
Rakesh KarmacharyaDepartment of Psychiatry, Harvard Medical School, Boston, MA, USA.
Joshua L RoffmanDepartment of Psychiatry, Harvard Medical School, Boston, MA, USA.
Emily M MadsenPsychiatric & Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Eugene SongPsychiatric & Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
William G AdamsBoston Medical Center, Boston, MA, USA.
Luisa CamachoBoston Medical Center, Boston, MA, USA.
Sarah GasmanBoston Medical Center, Boston, MA, USA.
Jada S GibbsRutgers New Jersey Medical School, Newark, NJ, USA.
Rebecca G FortgangCenter for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
Chris J KennedyDepartment of Psychiatry, Harvard Medical School, Boston, MA, USA.
Galina LozinskiBoston Medical Center, Boston, MA, USA.
Daisy C PerezBoston Medical Center, Boston, MA, USA.
Marina WilsonPsychiatric & Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Ben Y ReisPredictive Medicine Group, Harvard Medical School, Boston, MA, USA.
Jordan W SmollerDepartment of Psychiatry, Harvard Medical School, Boston, MA, USA.

Funding

Development and validation of an electronic health record prediction tool for first-episode psychosisR01MH116042 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI REIS, BEN Y, SMOLLER, JORDAN W · 2019 to 2022
$3.3M
Institutional Career Development CoreKL2TR003018 · NCATS · RUTGERS BIOMEDICAL/HEALTH SCIENCES-RBHS · PI CHAN, JOHN R., HALM, ETHAN A · 2019 to 2023
$3.0M
Digital Monitoring of Impulsivity as a Proximal Risk Factor for Suicidal OutcomesK23MH132766 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI Rebecca Gwen Fortgang · 2023 to 2026
$783k
Implementing Evidence-Based Treatment for Common Mental Disorders in HIV Clinics in UkraineK23MH133520 · NIMH · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Kimberly Michelle Hook · 2023 to 2026
$750k
NCATS NIH HHS KL2 TR003018NIH HHS KL2TR003018NIMH NIH HHS K23 MH132766NIMH NIH HHS K23MH132766NIMH NIH HHS K23 MH133520NIMH NIH HHS R01 MH116042
6 · The paper itself

Abstract

background and hypothesisPsychosis-associated diagnostic codes are increasingly being utilized as case definitions for electronic health record (EHR)-based algorithms to predict and detect psychosis. However, data on the validity of psychosis-related diagnostic codes is limited. We evaluated the positive predictive value (PPV) of International Classification of Diseases (ICD) codes for psychosis. STUDY

designUsing EHRs at 3 health systems, ICD codes comprising primary psychotic disorders and mood disorders with psychosis were grouped into 5 higher-order groups. 1133 records were sampled for chart review using the full EHR. PPVs (the probability of chart-confirmed psychosis given ICD psychosis codes) were calculated across multiple treatment settings. STUDY

resultsPPVs across all diagnostic groups and hospital systems exceeded 70%: Mass General Brigham 0.72 [95% CI 0.68-0.77], Boston Children's Hospital 0.80 [0.75-0.84], and Boston Medical Center 0.83 [0.79-0.86]. Schizoaffective disorder PPVs were consistently the highest across sites (0.80-0.92) and major depressive disorder with psychosis were the most variable (0.57-0.79). To determine if the first documented code captured first-episode psychosis (FEP), we excluded cases with prior chart evidence of a diagnosis of or treatment for a psychotic illness, yielding substantially lower PPVs (0.08-0.62).

conclusionsWe found that the first documented psychosis diagnostic code accurately captured true episodes of psychosis but was a poor index of FEP. These data have important implications for the case definitions used in the development of risk prediction models designed to predict or detect undiagnosed psychosis.

Indexed as

Electronic Health RecordsInternational Classification of DiseasesPsychotic DisordersAdultAlgorithmsFemaleHumansMaleMiddle AgedReproducibility of ResultsYoung Adultbipolardetectionpredictionschizoaffectiveschizophrenia

Identifiers

PMID38728421
PMCPMC11548932

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.