Investigating the spatiotemporal patterns and clustering of attendances for mental health services to inform policy and resource allocation in Thailand

Chawarat Rotejanaprasert; Papin Thanutchapat; Chiraphat Phoncharoenwirot; Ornrakorn Mekchaiporn; Peerut Chienwichai; Richard J Maude

doi:10.1186/s13033-024-00639-5

Investigating the spatiotemporal patterns and clustering of attendances for mental health services to inform policy and resource allocation in Thailand

Int J Ment Health Syst. 2024 May 9;18(1):19. doi: 10.1186/s13033-024-00639-5.

Authors

Chawarat Rotejanaprasert^{1

2}, Papin Thanutchapat^{3

4}, Chiraphat Phoncharoenwirot^{3

4}, Ornrakorn Mekchaiporn^{3

4}, Peerut Chienwichai³, Richard J Maude^{5

6

7}

Affiliations

¹ Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand. chawarat.rot@mahidol.ac.th.
² Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand. chawarat.rot@mahidol.ac.th.
³ Princess Srisavangavadhana College of Medicine, Chulabhorn Royal Academy, Bangkok, Thailand.
⁴ Department of Computer Engineering, Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangkok, Thailand.
⁵ Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
⁶ Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
⁷ The Open University, Milton Keynes, UK.

Abstract

Background: Mental illness poses a substantial global public health challenge, including in Thailand, where exploration of access to mental health services is limited. The spatial and temporal dimensions of mental illness in the country are not extensively studied, despite the recognized association between poor mental health and socioeconomic inequalities. Gaining insights into these dimensions is crucial for effective public health interventions and resource allocation.

Methods: This retrospective study analyzed mental health service utilization data in Thailand from 2015 to 2023. Temporal trends in annual numbers of individuals visiting mental health services by diagnosis were examined, while spatial pattern analysis employed Moran's I statistics to assess autocorrelation, identify small-area clustering, and hotspots. The implications of our findings for mental health resource allocation and policy were discussed.

Results: Between 2015 and 2023, mental health facilities documented a total of 13,793,884 visits. The study found anxiety, schizophrenia, and depression emerged as the top three illnesses for mental health visits, with an increase in patient attendance following the onset of the COVID-19 outbreak. Spatial analysis identified areas of significance for various disorders across different regions of Thailand. Positive correlations between certain disorder pairs were found in specific regions, suggesting shared risk factors or comorbidities.

Conclusions: This study highlights spatial and temporal variations in individuals visiting services for different mental disorders in Thailand, shedding light on service gaps and socioeconomic issues. Addressing these disparities requires increased attention to mental health, the development of appropriate interventions, and overcoming barriers to accessibility. The findings provide a baseline for policymakers and stakeholders to allocate resources and implement culturally responsive interventions to improve mental health outcomes.

Keywords: Equality; Health system; Mental health; Spatial; Temporal; Thailand.