Literature DB >> 28710713

A consensus for the development of a vector model to assess clinical complexity.

Gino Roberto Corazza1,2, Catherine Klersy3, Pietro Formagnana4, Marco Vincenzo Lenti4, Donatella Padula4.   

Abstract

The progressive rise in multimorbidity has made management of complex patients one of the most topical and challenging issues in medicine, both in clinical practice and for healthcare organizations. To make this easier, a score of clinical complexity (CC) would be useful. A vector model to evaluate biological and extra-biological (socio-economic, cultural, behavioural, environmental) domains of CC was proposed a few years ago. However, given that the variables that grade each domain had never been defined, this model has never been used in clinical practice. To overcome these limits, a consensus meeting was organised to grade each domain of CC, and to establish the hierarchy of the domains. A one-day consensus meeting consisting of a multi-professional panel of 25 people was held at our Hospital. In a preliminary phase, the proponents selected seven variables as qualifiers for each of the five above-mentioned domains. In the course of the meeting, the panel voted for five variables considered to be the most representative for each domain. Consensus was established with 2/3 agreement, and all variables were dichotomised. Finally, the various domains were parametrized and ranked within a feasible vector model. A Clinical Complexity Index was set up using the chosen variables. All the domains were graphically represented through a vector model: the biological domain was chosen as the most significant (highest slope), followed by the behavioural and socio-economic domains (intermediate slope), and lastly by the cultural and environmental ones (lowest slope). A feasible and comprehensive tool to evaluate CC in clinical practice is proposed herein.

Entities:  

Keywords:  Comorbidity; Internal medicine; Medical decision making; Patient complexity; Polytherapy; Quality of healthcare

Mesh:

Year:  2017        PMID: 28710713     DOI: 10.1007/s11739-017-1709-6

Source DB:  PubMed          Journal:  Intern Emerg Med        ISSN: 1828-0447            Impact factor:   3.397


  17 in total

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Authors:  Monika M Safford
Journal:  J Gen Intern Med       Date:  2015-12       Impact factor: 5.128

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Authors:  Mary E Tinetti; Sidney T Bogardus; Joseph V Agostini
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5.  Risk factors for hospital readmission of elderly patients.

Authors:  Carlotta Franchi; Alessandro Nobili; Daniela Mari; Mauro Tettamanti; Codjo D Djade; Luca Pasina; Francesco Salerno; Salvatore Corrao; Alessandra Marengoni; Alfonso Iorio; Maura Marcucci; Pier Mannuccio Mannucci
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Review 6.  Risk factors for hospital readmissions in elderly patients: a systematic review.

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Journal:  Med Care Res Rev       Date:  2006-06       Impact factor: 3.929

8.  Primary care for patient complexity, not only disease.

Authors:  C J Peek; Macaran A Baird; Eli Coleman
Journal:  Fam Syst Health       Date:  2009-12       Impact factor: 1.950

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Authors:  Karen Barnett; Stewart W Mercer; Michael Norbury; Graham Watt; Sally Wyke; Bruce Guthrie
Journal:  Lancet       Date:  2012-05-10       Impact factor: 79.321

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Authors:  Monika M Safford; Jeroan J Allison; Catarina I Kiefe
Journal:  J Gen Intern Med       Date:  2007-12       Impact factor: 5.128

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  8 in total

1.  A multidimensional vector model measuring clinical complexity may increase effectiveness in patient assessment.

Authors:  Alvisa Palese; Silvio Brusaferro
Journal:  Intern Emerg Med       Date:  2017-08-04       Impact factor: 3.397

2.  Reproducibility in the Assessment of the Components of a Clinical Complexity Index.

Authors:  Marco Vincenzo Lenti; Catherine Klersy; Alice Silvia Brera; Irene Benedetti; Mariella Ciola; Giampiera Bertolino; Gino Roberto Corazza
Journal:  J Gen Intern Med       Date:  2019-11       Impact factor: 5.128

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Journal:  J Pers Med       Date:  2022-04-24

4.  Clinical complexity and hospital admissions in the December holiday period.

Authors:  Marco Vincenzo Lenti; Catherine Klersy; Alice Silvia Brera; Valeria Musella; Irene Benedetti; Lucia Padovini; Mariella Ciola; Gabriele Croce; Alessia Ballesio; Maria Fortunata Gorgone; Giampiera Bertolino; Antonio Di Sabatino; Gino Roberto Corazza
Journal:  PLoS One       Date:  2020-06-11       Impact factor: 3.240

5.  The Manage Care Model - Developing an Evidence-Based and Expert-Driven Chronic Care Management Model for Patients with Diabetes.

Authors:  Patrick Timpel; Caroline Lang; Johan Wens; Juan Carlos Contel; Peter E H Schwarz
Journal:  Int J Integr Care       Date:  2020-04-22       Impact factor: 5.120

6.  Diagnostic Reasoning in Internal Medicine. Cynefin Framework Makes Sense of Clinical Complexity.

Authors:  Gino Roberto Corazza; Marco Vincenzo Lenti
Journal:  Front Med (Lausanne)       Date:  2021-04-22

7.  Aging underlies heterogeneity between comorbidity and multimorbidity frameworks.

Authors:  Marco Vincenzo Lenti; Catherine Klersy; Alice Silvia Brera; Alessia Ballesio; Gabriele Croce; Lucia Padovini; Rachele Ciccocioppo; Giampiera Bertolino; Antonio Di Sabatino; Gino Roberto Corazza
Journal:  Intern Emerg Med       Date:  2022-01-07       Impact factor: 5.472

8.  Resilience is associated with frailty and older age in hospitalised patients.

Authors:  Marco Vincenzo Lenti; Alice Silvia Brera; Alessia Ballesio; Gabriele Croce; Lucia Padovini; Giampiera Bertolino; Antonio Di Sabatino; Catherine Klersy; Gino Roberto Corazza
Journal:  BMC Geriatr       Date:  2022-07-10       Impact factor: 4.070

  8 in total

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