multimorbidity patterns in high-need, high-cost elderly patients.
Clicks: 229
ID: 130638
2018
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Popular Article
30.0
/100
229 views
49 readers
AI Quality Assessment
Not analyzed
Readership in this journal
PopularRanked #62 of 234 articles by views in ensaio pesquisa em educação em ciências
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 234 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
INTRODUCTION:Patients with complex health care needs (PCHCN) are individuals who require numerous, costly care services and have been shown to place a heavy burden on health care resources. It has been argued that an important issue in providing value-based primary care concerns how to identify groups of patients with similar needs (who pose similar challenges) so that care teams and care delivery processes can be tailored to each patient subgroup. Our study aims to describe the most common chronic conditions and their combinations in a cohort of elderly PCHCN. METHODS:We focused on a cohort of PCHCN residing in an area served by a local public health unit (the "Azienda ULSS4-Veneto") and belonging to Resource Utilization Bands 4 and 5 according to the ACG System. For each patient we extracted Expanded Diagnosis Clusters, and combined them with information available from Rx-MGs diagnoses. For the present work we focused on 15 diseases/disorders, analyzing their combinations as dyads and triads. Latent class analysis was used to elucidate the patterns of the morbidities considered in the PCHCN. RESULTS:Five disease clusters were identified: one concerned metabolic-ischemic heart diseases; one was labelled as neurological and mental disorders; one mainly comprised cardiac diseases such as congestive heart failure and atrial fibrillation; one was largely associated with respiratory conditions; and one involved neoplasms. CONCLUSIONS:Our study showed specific common associations between certain chronic diseases, shedding light on the patterns of multimorbidity often seen in PCHCN. Studying these patterns in more depth may help to better organize the intervention needed to deal with these patients.
| Reference Key |
buja2018plosmultimorbidity
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Alessandra Buja;Mirko Claus;Lucia Perin;Michele Rivera;Maria Chiara Corti;Francesco Avossa;Elena Schievano;Stefano Rigon;Roberto Toffanin;Vincenzo Baldo;Giovanna Boccuzzo |
| Journal | ensaio pesquisa em educação em ciências |
| Year | 2018 |
| DOI |
10.1371/journal.pone.0208875
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.