Burden of diabetes mellitus estimated with a longitudinal population-based study using administrative databases

Luciana Scalone; Giancarlo Cesana; Gianluca Furneri; Roberta Ciampichini; Paolo Beck-Peccoz; Virginio Chiodini; Silvia Mangioni; Emanuela Orsi; Carla Fornari; Lorenzo Giovanni Mantovani

doi:10.1371/journal.pone.0113745

Burden of diabetes mellitus estimated with a longitudinal population-based study using administrative databases

Luciana Scalone, Giancarlo Cesana, Gianluca Furneri, Roberta Ciampichini, Paolo Beck-Peccoz, Virginio Chiodini, Silvia Mangioni, Emanuela Orsi, Carla Fornari, Lorenzo Giovanni Mantovani

Fondazione IRCCS Ca' Granda- Ospedale Maggiore Policlinico

Research output: Contribution to journal › Article › peer-review

Abstract

Objective: To assess the epidemiologic and economic burden of diabetes mellitus (DM) from a longitudinal population-based study.

Research Design and Methods: Lombardy Region includes 9.9 million individuals. Its DM population was identified through a data warehouse (DENALI), which matches with a probabilistic linkage demographic, clinical and economic data of different Healthcare Administrative databases. All individuals, who, during the year 2000 had an hospital discharge with a IDC-9 CM code 250.XX, and/or two consecutive prescriptions of drugs for diabetes (ATC code A10XXXX) within one year, and/or an exemption from co-payment healthcare costs specific for DM, were selected and followed up to 9 years. We calculated prevalence, mortality and healthcare costs (hospitalizations, drugs and outpatient examinations/visits) from the National Health Service's perspective.

Results: We identified 312,223 eligible subjects. The study population (51% male) had a mean age of 66 (from 0.03 to 105.12) years at the index date. Prevalence ranged from 0.4% among subjects aged ≤45 years to 10.1% among those >85 years old. Overall 43.4 deaths per 1,000 patients per year were estimated, significantly (p

Conclusions: Merging different administrative databases can provide with many data from large populations observed for long time periods. DENALI shows to be an efficient instrument to obtain accurate estimates of burden of diseases such as diabetes mellitus.

Original language	English
Article number	e113741
Journal	PLoS One
Volume	9
Issue number	12
DOIs	https://doi.org/10.1371/journal.pone.0113745
Publication status	Published - Dec 3 2014

ASJC Scopus subject areas

Agricultural and Biological Sciences(all)
Biochemistry, Genetics and Molecular Biology(all)
Medicine(all)

Access to Document

10.1371/journal.pone.0113745

Cite this

Burden of diabetes mellitus estimated with a longitudinal population-based study using administrative databases. / Scalone, Luciana; Cesana, Giancarlo; Furneri, Gianluca; Ciampichini, Roberta; Beck-Peccoz, Paolo; Chiodini, Virginio; Mangioni, Silvia; Orsi, Emanuela; Fornari, Carla; Mantovani, Lorenzo Giovanni.

In: PLoS One, Vol. 9, No. 12, e113741, 03.12.2014.

Research output: Contribution to journal › Article › peer-review

@article{811421a0680e4895bf84f35810b57ef0,

title = "Burden of diabetes mellitus estimated with a longitudinal population-based study using administrative databases",

abstract = "Objective: To assess the epidemiologic and economic burden of diabetes mellitus (DM) from a longitudinal population-based study.Research Design and Methods: Lombardy Region includes 9.9 million individuals. Its DM population was identified through a data warehouse (DENALI), which matches with a probabilistic linkage demographic, clinical and economic data of different Healthcare Administrative databases. All individuals, who, during the year 2000 had an hospital discharge with a IDC-9 CM code 250.XX, and/or two consecutive prescriptions of drugs for diabetes (ATC code A10XXXX) within one year, and/or an exemption from co-payment healthcare costs specific for DM, were selected and followed up to 9 years. We calculated prevalence, mortality and healthcare costs (hospitalizations, drugs and outpatient examinations/visits) from the National Health Service's perspective.Results: We identified 312,223 eligible subjects. The study population (51% male) had a mean age of 66 (from 0.03 to 105.12) years at the index date. Prevalence ranged from 0.4% among subjects aged ≤45 years to 10.1% among those >85 years old. Overall 43.4 deaths per 1,000 patients per year were estimated, significantly (pConclusions: Merging different administrative databases can provide with many data from large populations observed for long time periods. DENALI shows to be an efficient instrument to obtain accurate estimates of burden of diseases such as diabetes mellitus.",

author = "Luciana Scalone and Giancarlo Cesana and Gianluca Furneri and Roberta Ciampichini and Paolo Beck-Peccoz and Virginio Chiodini and Silvia Mangioni and Emanuela Orsi and Carla Fornari and Mantovani, {Lorenzo Giovanni}",

year = "2014",

month = dec,

day = "3",

doi = "10.1371/journal.pone.0113745",

language = "English",

volume = "9",

journal = "PLoS One",

issn = "1932-6203",

publisher = "Public Library of Science",

number = "12",

}

TY - JOUR

T1 - Burden of diabetes mellitus estimated with a longitudinal population-based study using administrative databases

AU - Scalone, Luciana

AU - Cesana, Giancarlo

AU - Furneri, Gianluca

AU - Ciampichini, Roberta

AU - Beck-Peccoz, Paolo

AU - Chiodini, Virginio

AU - Mangioni, Silvia

AU - Orsi, Emanuela

AU - Fornari, Carla

AU - Mantovani, Lorenzo Giovanni

PY - 2014/12/3

Y1 - 2014/12/3

N2 - Objective: To assess the epidemiologic and economic burden of diabetes mellitus (DM) from a longitudinal population-based study.Research Design and Methods: Lombardy Region includes 9.9 million individuals. Its DM population was identified through a data warehouse (DENALI), which matches with a probabilistic linkage demographic, clinical and economic data of different Healthcare Administrative databases. All individuals, who, during the year 2000 had an hospital discharge with a IDC-9 CM code 250.XX, and/or two consecutive prescriptions of drugs for diabetes (ATC code A10XXXX) within one year, and/or an exemption from co-payment healthcare costs specific for DM, were selected and followed up to 9 years. We calculated prevalence, mortality and healthcare costs (hospitalizations, drugs and outpatient examinations/visits) from the National Health Service's perspective.Results: We identified 312,223 eligible subjects. The study population (51% male) had a mean age of 66 (from 0.03 to 105.12) years at the index date. Prevalence ranged from 0.4% among subjects aged ≤45 years to 10.1% among those >85 years old. Overall 43.4 deaths per 1,000 patients per year were estimated, significantly (pConclusions: Merging different administrative databases can provide with many data from large populations observed for long time periods. DENALI shows to be an efficient instrument to obtain accurate estimates of burden of diseases such as diabetes mellitus.

AB - Objective: To assess the epidemiologic and economic burden of diabetes mellitus (DM) from a longitudinal population-based study.Research Design and Methods: Lombardy Region includes 9.9 million individuals. Its DM population was identified through a data warehouse (DENALI), which matches with a probabilistic linkage demographic, clinical and economic data of different Healthcare Administrative databases. All individuals, who, during the year 2000 had an hospital discharge with a IDC-9 CM code 250.XX, and/or two consecutive prescriptions of drugs for diabetes (ATC code A10XXXX) within one year, and/or an exemption from co-payment healthcare costs specific for DM, were selected and followed up to 9 years. We calculated prevalence, mortality and healthcare costs (hospitalizations, drugs and outpatient examinations/visits) from the National Health Service's perspective.Results: We identified 312,223 eligible subjects. The study population (51% male) had a mean age of 66 (from 0.03 to 105.12) years at the index date. Prevalence ranged from 0.4% among subjects aged ≤45 years to 10.1% among those >85 years old. Overall 43.4 deaths per 1,000 patients per year were estimated, significantly (pConclusions: Merging different administrative databases can provide with many data from large populations observed for long time periods. DENALI shows to be an efficient instrument to obtain accurate estimates of burden of diseases such as diabetes mellitus.

UR - http://www.scopus.com/inward/record.url?scp=84956658151&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84956658151&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0113745

DO - 10.1371/journal.pone.0113745

M3 - Article

VL - 9

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 12

M1 - e113741

ER -

Burden of diabetes mellitus estimated with a longitudinal population-based study using administrative databases

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this