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Research article
Miguel Nascimento
Centro Hospitalar Psiquiátrico de Lisboa
Corresponding Author
ORCiD: https://orcid.org/0000-0001-9134-3620
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Purpose: 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 regarding all patients observed at CHPL in 2017, at the census subsection level, considering a queen criterion of contiguity, regarding 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 1000m.
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 1000m 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.
Keywords
Join count statistics, Clusters, Primary care, Community psychiatry, Access to healthcare
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CURRENT STATUS: Published
View the published article at BMC Health Services Research.
No community comments so far
Editorial decision: Accept
On 04 Apr, 2020
Editor assigned
On 17 Mar, 2020
Submission checks complete
On 16 Mar, 2020
Editor invited
On 16 Mar, 2020
No comments provided
Editorial decision: Minor revision
On 09 Mar, 2020
Reviewer #1 agreed
On 02 Mar, 2020
Review #1 received
Received 02 Mar, 2020
Reviewers invited
Invitations sent on 01 Mar, 2020
Editor assigned
On 18 Feb, 2020
Submission checks complete
On 17 Feb, 2020
Editor invited
On 17 Feb, 2020
Version 1
Posted 30 Sep, 2019
No comments provided
Editorial decision: Minor revision
On 12 Dec, 2019
Review #2 received
Received 29 Nov, 2019
Reviewer #2 agreed
On 26 Nov, 2019
Review #1 received
Received 21 Oct, 2019
Reviewer #1 agreed
On 02 Oct, 2019
Reviewers invited
Invitations sent on 02 Oct, 2019
Submission checks complete
On 24 Sep, 2019
Editor assigned
On 16 Sep, 2019
Editor invited
On 15 Sep, 2019
First submitted
On 12 Sep, 2019
Metrics
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PDF Downloads: ...
HTML Views: ...
Subject Areas
Health Policy
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A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
See the published version of this preprint at BMC Health Services Research.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Miguel Nascimento
Centro Hospitalar Psiquiátrico de Lisboa
Corresponding Author
ORCiD: https://orcid.org/0000-0001-9134-3620
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Health Services Research.
No community comments so far
Editorial decision: Accept
On 04 Apr, 2020
Editor assigned
On 17 Mar, 2020
Submission checks complete
On 16 Mar, 2020
Editor invited
On 16 Mar, 2020
No comments provided
Editorial decision: Minor revision
On 09 Mar, 2020
Reviewer #1 agreed
On 02 Mar, 2020
Review #1 received
Received 02 Mar, 2020
Reviewers invited
Invitations sent on 01 Mar, 2020
Editor assigned
On 18 Feb, 2020
Submission checks complete
On 17 Feb, 2020
Editor invited
On 17 Feb, 2020
Version 1
Posted 30 Sep, 2019
No comments provided
Editorial decision: Minor revision
On 12 Dec, 2019
Review #2 received
Received 29 Nov, 2019
Reviewer #2 agreed
On 26 Nov, 2019
Review #1 received
Received 21 Oct, 2019
Reviewer #1 agreed
On 02 Oct, 2019
Reviewers invited
Invitations sent on 02 Oct, 2019
Submission checks complete
On 24 Sep, 2019
Editor assigned
On 16 Sep, 2019
Editor invited
On 15 Sep, 2019
First submitted
On 12 Sep, 2019
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Health Policy
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Health Services Research.
Purpose: 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 regarding all patients observed at CHPL in 2017, at the census subsection level, considering a queen criterion of contiguity, regarding 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 1000m.
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 1000m 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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