File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Associations between depressive symptom clusters and care utilization and costs among community-dwelling older adults

TitleAssociations between depressive symptom clusters and care utilization and costs among community-dwelling older adults
Authors
Issue Date2021
PublisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/4294
Citation
International Journal of Geriatric Psychiatry, 2021, v. 37 n. 1, p. 1-9 How to Cite?
AbstractObjectives Whether and how symptom clusters are associated with care utilization remains understudied. This study aims to investigate the economic impact of symptom clusters. Methods We conducted cross-sectional analyses of data collected from 3255 older adults aged 60 years and over in Hong Kong using the Patient Health Questionnaire-9 and the Client Service Receipt Inventory to measure depressive symptoms and service utilization to calculate 1-year care expenditure. Based on Research Domain Criteria framework, we categorized depressive symptoms into four clusters: Negative Valance Systems and Externalizing (NVSE; anhedonia and depression), Negative Valance Systems and Internalizing (guilt and self-harm), Arousal and Regulatory Systems (sleep, fatigue, and appetite), and Cognitive and Sensorimotor Systems (CSS; concentration and psychomotor). Two-part models were used with four symptom clusters to estimate economic impacts on care utilization. Results Core affective symptoms had the largest economic impact on non-psychiatric care expenditure; a one-point increase in NVSE was associated with USD$ 571 additional non-psychiatric care expenditure. The economic impacts of CSS on non-psychiatric care expenditure was attenuated when the severity level of NVSE was higher. Conclusions Our findings highlight the importance of understanding economic impacts on care utilization based on symptom profiles with a particular emphasis on symptom combinations. Policymakers should optimize care allocation based on older adults' depressive symptom profiles rather than simply considering their depression sum-score or the severity defined by cut-off points.
Persistent Identifierhttp://hdl.handle.net/10722/307724
ISSN
2023 Impact Factor: 3.6
2023 SCImago Journal Rankings: 1.187
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLu, S-
dc.contributor.authorZhang, YA-
dc.contributor.authorLiu, T-
dc.contributor.authorLeung, KYD-
dc.contributor.authorKwok, WW-
dc.contributor.authorLuo, H-
dc.contributor.authorTang, YMJ-
dc.contributor.authorWong, GHY-
dc.contributor.authorLum, TYS-
dc.date.accessioned2021-11-12T13:36:53Z-
dc.date.available2021-11-12T13:36:53Z-
dc.date.issued2021-
dc.identifier.citationInternational Journal of Geriatric Psychiatry, 2021, v. 37 n. 1, p. 1-9-
dc.identifier.issn0885-6230-
dc.identifier.urihttp://hdl.handle.net/10722/307724-
dc.description.abstractObjectives Whether and how symptom clusters are associated with care utilization remains understudied. This study aims to investigate the economic impact of symptom clusters. Methods We conducted cross-sectional analyses of data collected from 3255 older adults aged 60 years and over in Hong Kong using the Patient Health Questionnaire-9 and the Client Service Receipt Inventory to measure depressive symptoms and service utilization to calculate 1-year care expenditure. Based on Research Domain Criteria framework, we categorized depressive symptoms into four clusters: Negative Valance Systems and Externalizing (NVSE; anhedonia and depression), Negative Valance Systems and Internalizing (guilt and self-harm), Arousal and Regulatory Systems (sleep, fatigue, and appetite), and Cognitive and Sensorimotor Systems (CSS; concentration and psychomotor). Two-part models were used with four symptom clusters to estimate economic impacts on care utilization. Results Core affective symptoms had the largest economic impact on non-psychiatric care expenditure; a one-point increase in NVSE was associated with USD$ 571 additional non-psychiatric care expenditure. The economic impacts of CSS on non-psychiatric care expenditure was attenuated when the severity level of NVSE was higher. Conclusions Our findings highlight the importance of understanding economic impacts on care utilization based on symptom profiles with a particular emphasis on symptom combinations. Policymakers should optimize care allocation based on older adults' depressive symptom profiles rather than simply considering their depression sum-score or the severity defined by cut-off points.-
dc.languageeng-
dc.publisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/4294-
dc.relation.ispartofInternational Journal of Geriatric Psychiatry-
dc.rightsSubmitted (preprint) Version This is the pre-peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Accepted (peer-reviewed) Version This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.-
dc.titleAssociations between depressive symptom clusters and care utilization and costs among community-dwelling older adults-
dc.typeArticle-
dc.identifier.emailLiu, T: tianyin@hku.hk-
dc.identifier.emailLeung, KYD: daralky@hku.hk-
dc.identifier.emailKwok, WW: kwokww@hku.hk-
dc.identifier.emailLuo, H: haoluo@hku.hk-
dc.identifier.emailWong, GHY: ghywong@hku.hk-
dc.identifier.emailLum, TYS: tlum@hku.hk-
dc.identifier.authorityLu, S=rp02609-
dc.identifier.authorityLiu, T=rp02466-
dc.identifier.authorityLuo, H=rp02317-
dc.identifier.authorityTang, YMJ=rp01997-
dc.identifier.authorityWong, GHY=rp01850-
dc.identifier.authorityLum, TYS=rp01513-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/gps.5636-
dc.identifier.scopuseid_2-s2.0-85116983154-
dc.identifier.hkuros330264-
dc.identifier.volume37-
dc.identifier.issue1-
dc.identifier.spage1-
dc.identifier.epage9-
dc.identifier.isiWOS:000707239900001-
dc.publisher.placeUnited Kingdom-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats