Multimorbidity patterns in high-need, high-cost elderly patients

Autor: Mirko Claus, Giovanna Boccuzzo, Stefano Rigon, Alessandra Buja, Michele Rivera, Vincenzo Baldo, Maria Chiara Corti, Francesco Avossa, Roberto Toffanin, Elena Schievano, Lucia Perin
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Male
Pulmonology
Blood Pressure
030204 cardiovascular system & hematology
Alzheimer's Disease
Vascular Medicine
0302 clinical medicine
Endocrinology
Health care
Atrial Fibrillation
Medicine and Health Sciences
Coronary Heart Disease
030212 general & internal medicine
Medical diagnosis
Aged
80 and over
Multidisciplinary
Neurodegenerative Diseases
Latent class model
Neurology
Italy
Cohort
Hypertension
Medicine
Female
Arrhythmia
Research Article
medicine.medical_specialty
Endocrine Disorders
Chronic Obstructive Pulmonary Disease
Science
Cardiology
03 medical and health sciences
Intervention (counseling)
Mental Health and Psychiatry
medicine
Diabetes Mellitus
Multimorbidity
Humans
Intensive care medicine
Aged
Heart Failure
Health Services Needs and Demand
business.industry
Public health
medicine.disease
Geriatrics
Heart failure
Metabolic Disorders
Chronic Disease
Dementia
business
Zdroj: PLoS ONE, Vol 13, Iss 12, p e0208875 (2018)
PLoS ONE
ISSN: 1932-6203
Popis: 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.
Databáze: OpenAIRE
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