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The Individual Profile of Pathology as a New Model for Filling Knowledge Gaps in Health Policies for Chronicity

Chronicity is the real challenge for public healthcare systems especially in relation to multi-morbidity. The growing demand for multidisciplinary care could be addressed by implementing integrated programs in the primary care field and facilitating other specific care only as necessary. Some models...

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Autores principales: Franchini, Michela, Pieroni, Stefania, Cutilli, Arianna, Caiolfa, Michelangelo, Naldoni, Simone, Molinaro, Sabrina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6593300/
https://www.ncbi.nlm.nih.gov/pubmed/31275939
http://dx.doi.org/10.3389/fmed.2019.00130
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author Franchini, Michela
Pieroni, Stefania
Cutilli, Arianna
Caiolfa, Michelangelo
Naldoni, Simone
Molinaro, Sabrina
author_facet Franchini, Michela
Pieroni, Stefania
Cutilli, Arianna
Caiolfa, Michelangelo
Naldoni, Simone
Molinaro, Sabrina
author_sort Franchini, Michela
collection PubMed
description Chronicity is the real challenge for public healthcare systems especially in relation to multi-morbidity. The growing demand for multidisciplinary care could be addressed by implementing integrated programs in the primary care field and facilitating other specific care only as necessary. Some models of long-term management have been suggested since the 2000s. The objective here is to propose the Individual Profile of Pathology (IPP) model as the preliminary step for identifying groups of population which shares health and social needs and for optimizing the management of chronicity, referring to the Kaiser Permanente Pyramid paradigm. The IPP model is able to inform a data feedback system for improving performances at the patient's individual level and for addressing and evaluating health policies. The stratification of needs comes out of the IPP algorithm. It works on patient information databases based on the logic of disease as a process that evolves over time and interacts with many factors unique to that patient. Individual patients' data used in this work refers to 138,859 subjects from a large area in Italy and concerns hospitalization, outpatient drug prescriptions, access to the emergency room and outpatient prescriptions for visits, laboratory/imaging tests, and medications. The IPP model allows to identify for each subject a complexity level, taking into account the weight of groups of pathologies, both in terms of absorption of resources and the level of severity. Costs and healthcare performances have been analyzed taking into account the complexity levels. The IPP model can be an efficient methodology for (a) improving performances at the patient's individual level (b) allowing standardized comparison among different geographical areas (c) supporting large population-focused surveillance programs and (d) providing knowledge to identify and fill the gaps in public health policies. Currently, the IPP algorithm is limited by data availability, restricted to the administrative databases processing, but the theoretical model is able to include more data dimensions providing the potential to identify homogeneous groups of subjects with a higher level of precision.
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spelling pubmed-65933002019-07-03 The Individual Profile of Pathology as a New Model for Filling Knowledge Gaps in Health Policies for Chronicity Franchini, Michela Pieroni, Stefania Cutilli, Arianna Caiolfa, Michelangelo Naldoni, Simone Molinaro, Sabrina Front Med (Lausanne) Medicine Chronicity is the real challenge for public healthcare systems especially in relation to multi-morbidity. The growing demand for multidisciplinary care could be addressed by implementing integrated programs in the primary care field and facilitating other specific care only as necessary. Some models of long-term management have been suggested since the 2000s. The objective here is to propose the Individual Profile of Pathology (IPP) model as the preliminary step for identifying groups of population which shares health and social needs and for optimizing the management of chronicity, referring to the Kaiser Permanente Pyramid paradigm. The IPP model is able to inform a data feedback system for improving performances at the patient's individual level and for addressing and evaluating health policies. The stratification of needs comes out of the IPP algorithm. It works on patient information databases based on the logic of disease as a process that evolves over time and interacts with many factors unique to that patient. Individual patients' data used in this work refers to 138,859 subjects from a large area in Italy and concerns hospitalization, outpatient drug prescriptions, access to the emergency room and outpatient prescriptions for visits, laboratory/imaging tests, and medications. The IPP model allows to identify for each subject a complexity level, taking into account the weight of groups of pathologies, both in terms of absorption of resources and the level of severity. Costs and healthcare performances have been analyzed taking into account the complexity levels. The IPP model can be an efficient methodology for (a) improving performances at the patient's individual level (b) allowing standardized comparison among different geographical areas (c) supporting large population-focused surveillance programs and (d) providing knowledge to identify and fill the gaps in public health policies. Currently, the IPP algorithm is limited by data availability, restricted to the administrative databases processing, but the theoretical model is able to include more data dimensions providing the potential to identify homogeneous groups of subjects with a higher level of precision. Frontiers Media S.A. 2019-06-13 /pmc/articles/PMC6593300/ /pubmed/31275939 http://dx.doi.org/10.3389/fmed.2019.00130 Text en Copyright © 2019 Franchini, Pieroni, Cutilli, Caiolfa, Naldoni and Molinaro. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Franchini, Michela
Pieroni, Stefania
Cutilli, Arianna
Caiolfa, Michelangelo
Naldoni, Simone
Molinaro, Sabrina
The Individual Profile of Pathology as a New Model for Filling Knowledge Gaps in Health Policies for Chronicity
title The Individual Profile of Pathology as a New Model for Filling Knowledge Gaps in Health Policies for Chronicity
title_full The Individual Profile of Pathology as a New Model for Filling Knowledge Gaps in Health Policies for Chronicity
title_fullStr The Individual Profile of Pathology as a New Model for Filling Knowledge Gaps in Health Policies for Chronicity
title_full_unstemmed The Individual Profile of Pathology as a New Model for Filling Knowledge Gaps in Health Policies for Chronicity
title_short The Individual Profile of Pathology as a New Model for Filling Knowledge Gaps in Health Policies for Chronicity
title_sort individual profile of pathology as a new model for filling knowledge gaps in health policies for chronicity
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6593300/
https://www.ncbi.nlm.nih.gov/pubmed/31275939
http://dx.doi.org/10.3389/fmed.2019.00130
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