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Prevalence of chronic kidney disease in the Lazio region, Italy: a classification algorithm based on health information systems

BACKGROUND: Estimating CKD prevalence is difficult. Information on CKD prevalence is rather scanty in Italy and available figures come from surveys in selected geographical areas. Administrative data have been already demonstrated to be an effective tool in estimating the epidemiological burden of d...

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Autores principales: Marino, Claudia, Ferraro, Pietro Manuel, Bargagli, Matteo, Cascini, Silvia, Agabiti, Nera, Gambaro, Giovanni, Davoli, Marina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6986004/
https://www.ncbi.nlm.nih.gov/pubmed/31992222
http://dx.doi.org/10.1186/s12882-020-1689-z
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author Marino, Claudia
Ferraro, Pietro Manuel
Bargagli, Matteo
Cascini, Silvia
Agabiti, Nera
Gambaro, Giovanni
Davoli, Marina
author_facet Marino, Claudia
Ferraro, Pietro Manuel
Bargagli, Matteo
Cascini, Silvia
Agabiti, Nera
Gambaro, Giovanni
Davoli, Marina
author_sort Marino, Claudia
collection PubMed
description BACKGROUND: Estimating CKD prevalence is difficult. Information on CKD prevalence is rather scanty in Italy and available figures come from surveys in selected geographical areas. Administrative data have been already demonstrated to be an effective tool in estimating the epidemiological burden of diseases, however there is limited experience in literature as far as CKD is concerned. METHODS: The aim of this study is to develop an algorithm based on regional Health Administrative Databases to identify individuals with CKD and provide estimates of disease prevalence in Lazio Region (Italy); about 5.500.000 inhabitants in 2017. A population-level analysis based on a record-linkage strategy using data from Health Administrative Databases has been applied in Lazio Region. CKD cases were identified between January 1, 2012 and December 31, 2017 using Outpatient Specialist Service Information System, Hospital Discharge Registry, Ticket Exemption Registry and Drug Dispensing Registry. Age-specific and standardized prevalence rates were calculated by gender. CKD cases were classified as higher and lower severity. RESULTS: The algorithm identified 99,457 individuals with CKD (mean age 71 years, 55.8% males). The exclusive contributions of each regional source used were: 35,047 (35.2%) from Outpatient Specialist Service Information System, 27,778 (27.9%) from Hospital Discharge Registry, 4143 (4.2%) from Ticket Exemption Registry and 463 (0.5%) from Drug Dispensing Registry; 5.1% of cases were found in all databases. The standardized prevalence rate at December 31, 2017 was 1.76, 2.06% for males and 1.50% for females. The prevalence increased with age, rising from 0.33% (age 0–18) up to 14.18% (age 85+) among males and from 0.25% up to 8.18% among females. The proportion of CKD individuals with lower severity disease was 78.7% in both genders. CONCLUSIONS: The proposed algorithm represents a novel tool to monitor the burden of CKD disease, that can be used by the regional government to guide the development and implementation of evidence-based pathways of care for CKD patients. The high prevalence of people with CKD of lower severity should be carefully considered in order to promote diagnosis and optimal management at early stages.
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spelling pubmed-69860042020-01-30 Prevalence of chronic kidney disease in the Lazio region, Italy: a classification algorithm based on health information systems Marino, Claudia Ferraro, Pietro Manuel Bargagli, Matteo Cascini, Silvia Agabiti, Nera Gambaro, Giovanni Davoli, Marina BMC Nephrol Research Article BACKGROUND: Estimating CKD prevalence is difficult. Information on CKD prevalence is rather scanty in Italy and available figures come from surveys in selected geographical areas. Administrative data have been already demonstrated to be an effective tool in estimating the epidemiological burden of diseases, however there is limited experience in literature as far as CKD is concerned. METHODS: The aim of this study is to develop an algorithm based on regional Health Administrative Databases to identify individuals with CKD and provide estimates of disease prevalence in Lazio Region (Italy); about 5.500.000 inhabitants in 2017. A population-level analysis based on a record-linkage strategy using data from Health Administrative Databases has been applied in Lazio Region. CKD cases were identified between January 1, 2012 and December 31, 2017 using Outpatient Specialist Service Information System, Hospital Discharge Registry, Ticket Exemption Registry and Drug Dispensing Registry. Age-specific and standardized prevalence rates were calculated by gender. CKD cases were classified as higher and lower severity. RESULTS: The algorithm identified 99,457 individuals with CKD (mean age 71 years, 55.8% males). The exclusive contributions of each regional source used were: 35,047 (35.2%) from Outpatient Specialist Service Information System, 27,778 (27.9%) from Hospital Discharge Registry, 4143 (4.2%) from Ticket Exemption Registry and 463 (0.5%) from Drug Dispensing Registry; 5.1% of cases were found in all databases. The standardized prevalence rate at December 31, 2017 was 1.76, 2.06% for males and 1.50% for females. The prevalence increased with age, rising from 0.33% (age 0–18) up to 14.18% (age 85+) among males and from 0.25% up to 8.18% among females. The proportion of CKD individuals with lower severity disease was 78.7% in both genders. CONCLUSIONS: The proposed algorithm represents a novel tool to monitor the burden of CKD disease, that can be used by the regional government to guide the development and implementation of evidence-based pathways of care for CKD patients. The high prevalence of people with CKD of lower severity should be carefully considered in order to promote diagnosis and optimal management at early stages. BioMed Central 2020-01-28 /pmc/articles/PMC6986004/ /pubmed/31992222 http://dx.doi.org/10.1186/s12882-020-1689-z Text en © The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Marino, Claudia
Ferraro, Pietro Manuel
Bargagli, Matteo
Cascini, Silvia
Agabiti, Nera
Gambaro, Giovanni
Davoli, Marina
Prevalence of chronic kidney disease in the Lazio region, Italy: a classification algorithm based on health information systems
title Prevalence of chronic kidney disease in the Lazio region, Italy: a classification algorithm based on health information systems
title_full Prevalence of chronic kidney disease in the Lazio region, Italy: a classification algorithm based on health information systems
title_fullStr Prevalence of chronic kidney disease in the Lazio region, Italy: a classification algorithm based on health information systems
title_full_unstemmed Prevalence of chronic kidney disease in the Lazio region, Italy: a classification algorithm based on health information systems
title_short Prevalence of chronic kidney disease in the Lazio region, Italy: a classification algorithm based on health information systems
title_sort prevalence of chronic kidney disease in the lazio region, italy: a classification algorithm based on health information systems
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6986004/
https://www.ncbi.nlm.nih.gov/pubmed/31992222
http://dx.doi.org/10.1186/s12882-020-1689-z
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