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

algorithm co-morbidity complex needs general population health policy long term conditions segmentation

Journal

Frontiers in medicine
ISSN: 2296-858X
Titre abrégé: Front Med (Lausanne)
Pays: Switzerland
ID NLM: 101648047

Informations de publication

Date de publication:
2019
Historique:
received: 31 10 2018
accepted: 28 05 2019
entrez: 6 7 2019
pubmed: 6 7 2019
medline: 6 7 2019
Statut: epublish

Résumé

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.

Identifiants

pubmed: 31275939
doi: 10.3389/fmed.2019.00130
pmc: PMC6593300
doi:

Types de publication

Journal Article

Langues

eng

Pagination

130

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Auteurs

Michela Franchini (M)

Institute of Clinical Physiology, National Research Council, Pisa, Italy.

Stefania Pieroni (S)

Institute of Clinical Physiology, National Research Council, Pisa, Italy.

Arianna Cutilli (A)

Institute of Clinical Physiology, National Research Council, Pisa, Italy.

Michelangelo Caiolfa (M)

Federsanità-Anci Toscana, Firenze, Italy.

Simone Naldoni (S)

Federsanità-Anci Toscana, Firenze, Italy.

Sabrina Molinaro (S)

Institute of Clinical Physiology, National Research Council, Pisa, Italy.

Classifications MeSH