File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1002/gps.5636
- Scopus: eid_2-s2.0-85116983154
- WOS: WOS:000707239900001
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Associations between depressive symptom clusters and care utilization and costs among community-dwelling older adults
Title | Associations between depressive symptom clusters and care utilization and costs among community-dwelling older adults |
---|---|
Authors | |
Issue Date | 2021 |
Publisher | John 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? |
Abstract | Objectives
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 Identifier | http://hdl.handle.net/10722/307724 |
ISSN | 2023 Impact Factor: 3.6 2023 SCImago Journal Rankings: 1.187 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lu, S | - |
dc.contributor.author | Zhang, YA | - |
dc.contributor.author | Liu, T | - |
dc.contributor.author | Leung, KYD | - |
dc.contributor.author | Kwok, WW | - |
dc.contributor.author | Luo, H | - |
dc.contributor.author | Tang, YMJ | - |
dc.contributor.author | Wong, GHY | - |
dc.contributor.author | Lum, TYS | - |
dc.date.accessioned | 2021-11-12T13:36:53Z | - |
dc.date.available | 2021-11-12T13:36:53Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | International Journal of Geriatric Psychiatry, 2021, v. 37 n. 1, p. 1-9 | - |
dc.identifier.issn | 0885-6230 | - |
dc.identifier.uri | http://hdl.handle.net/10722/307724 | - |
dc.description.abstract | Objectives 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.language | eng | - |
dc.publisher | John Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/4294 | - |
dc.relation.ispartof | International Journal of Geriatric Psychiatry | - |
dc.rights | Submitted (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.title | Associations between depressive symptom clusters and care utilization and costs among community-dwelling older adults | - |
dc.type | Article | - |
dc.identifier.email | Liu, T: tianyin@hku.hk | - |
dc.identifier.email | Leung, KYD: daralky@hku.hk | - |
dc.identifier.email | Kwok, WW: kwokww@hku.hk | - |
dc.identifier.email | Luo, H: haoluo@hku.hk | - |
dc.identifier.email | Wong, GHY: ghywong@hku.hk | - |
dc.identifier.email | Lum, TYS: tlum@hku.hk | - |
dc.identifier.authority | Lu, S=rp02609 | - |
dc.identifier.authority | Liu, T=rp02466 | - |
dc.identifier.authority | Luo, H=rp02317 | - |
dc.identifier.authority | Tang, YMJ=rp01997 | - |
dc.identifier.authority | Wong, GHY=rp01850 | - |
dc.identifier.authority | Lum, TYS=rp01513 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1002/gps.5636 | - |
dc.identifier.scopus | eid_2-s2.0-85116983154 | - |
dc.identifier.hkuros | 330264 | - |
dc.identifier.volume | 37 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 1 | - |
dc.identifier.epage | 9 | - |
dc.identifier.isi | WOS:000707239900001 | - |
dc.publisher.place | United Kingdom | - |