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Record W4292093160 · doi:10.2196/preprints.40916

Mental health-related healthcare utilization and psychotropic drug dispensation trends in British Columbia during the COVID-19 pandemic: Observational Study (Preprint)

2022· preprint· en· W4292093160 on OpenAlexaboutno aff
Moe Zandy, Sylvia ElKurdi, Hasina Samji, Geoffrey McKee, Aman Dheri, Kate Smolina

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicHealthcare Systems and Public Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePandemicMental healthHealth careEmergency departmentPublic healthObservational studyPopulationFamily medicineMedical emergencyCoronavirus disease 2019 (COVID-19)PsychiatryEnvironmental healthDiseaseNursingInfectious disease (medical specialty)

Abstract

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BACKGROUND The impact of the coronavirus disease (COVID-19) pandemic on mental health of the population is important for informing public health policy and decision-making. However, there is limited information on trends in mental health-related healthcare service utilization during the pandemic. OBJECTIVE This study aimed to describe patterns of mental health-related healthcare service utilisation and psychotropic drug dispensations in British Columbia, Canada, during the COVID-19 pandemic compared to a pre-pandemic period. We explored trajectories of use across multiple data sources to determine whether the patterns were similar or different in acute and outpatient settings, and how these patterns differed by age, sex and type of condition. METHODS We conducted a population-based study using administrative health data to capture outpatient physician visits, emergency department visits, hospital admissions, and psychotropic drug dispensations. We examined time trends of mental health-related healthcare utilisation and psychotropic drug dispensations between January 2019 and December 2021. We calculated age-standardised rates and rate ratios to compare healthcare service utilisation before and during the COVID-19 pandemic and stratified by year, sex, age and condition. RESULTS Results: In April 2020, compared to the same period in 2019, we observed a 26% and 16% decrease in acute care visits for mental health-related emergency department visits and hospital admissions, respectively. By late 2020, with the exception of emergency department visits, healthcare service utilisation recovered to pre-pandemic (2019) levels. In 2021, overall mental health-related healthcare service utilisation increased to above pre-pandemic levels, with an increase in the monthly average rate of 22% for outpatient physician visits only and not in other datasets. However, notable and statistically significant increases in healthcare utilisation were observed across all data sources among 10-14 year olds (45% in outpatient physician visits, 31% in emergency department visits, 55% in hospital admissions, and 36% in psychotropic drug dispensations), and 15-19 year olds (51% in outpatient physician visits, 19% in emergency department visits, 13% in hospital admissions, and 39% in psychotropic drug dispensations). Increases were more prominent among females than males, but there was some variation for specific mental health-related conditions. CONCLUSIONS The increase in mental health-related healthcare utilisation and psychotropic drug dispensations in 2020 and 2021 likely reflects important societal consequences of both the pandemic itself and the associated measures. Recovery efforts in British Columbia should take these findings into consideration, especially among most affected sub-populations, such as adolescents. CLINICALTRIAL Not applicable.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.008
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.199
GPT teacher head0.424
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2022
Admission routes1
Has abstractyes

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