BMC Health Services Research (Apr 2020)

No man is an island: spatial clustering and access to primary care as possible targets for the development of new community mental health approaches

  • M. Nascimento,
  • B. Lourenço,
  • I. Coelho,
  • J. Aguiar,
  • M. Lázaro,
  • M. Silva,
  • C. Pereira,
  • I. Neves-Caldas,
  • F. Gomes,
  • S. Garcia,
  • S. Nascimento,
  • G. Pereira,
  • V. Nogueira,
  • P. Costa,
  • A. Nobre

DOI
https://doi.org/10.1186/s12913-020-05190-w
Journal volume & issue
Vol. 20, no. 1
pp. 1 – 10

Abstract

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Abstract Background to understand if patients seen at Centro Hospitalar Psiquiátrico de Lisboa (CHPL) live in geographical clusters or randomly throughout the city, as well as determine their access to the psychiatric hospital and primary care facilities (PCF). Methods spatial autocorrelation statistics were performed (queen criterion of contiguity), regarding all patients observed at CHPL in 2017 (at the census subsection level), and considering not only their overall number but also main diagnosis, and admission to the psychiatric ward - voluntary or compulsory. Distance to the hospital and to the closest PCF was measured (for each patient and the variables cited above), and the mean values were compared. Finally, the total number of patients around each PCF was counted, considering specified radius sizes of 656 and 1000 m. Results All 5161 patients (509 psychiatric admissions) were geolocated, and statistical significance regarding patient clustering was found for the total number (p-0.0001) and specific group of disorders, namely Schizophrenia and related disorders (p-0.007) and depressive disorders (p-0.0002). Patients who were admitted in a psychiatric ward live farther away from the hospital (p-0.002), with the compulsory admissions (versus voluntary ones) living even farther (p-0.004). Furthermore, defining a radius of 1000 m for each PCF allowed the identification of two PCF with more than 1000 patients, and two others with more than 800. Conclusions as patients seem to live in geographical clusters (and considering PCFs with the highest number of them), possible locations for the development of programs regarding mental health treatment and prevention can now be identified.

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