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Canadian Public Health Association 2008 Annual Conference Halifax, Nova Scotia, CANADA. Characteristics of users with a high morbidity in Montreal. Reducing Health Inequalities through Evidence and Action On the Move: Neighbourhoods and Networks. - PowerPoint PPT Presentation
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Characteristics of users with a high morbidity in Montreal
Mamadou Bamba HANNE, Ph.D. Candidate – Public Health. Groupe de Recherche Interdisciplinaire en Santé (GRIS)
Faculté de médecine, Université de Montréal,CANADA
Tuesday 3 June 2008 Suite 304,WTCC
Canadian Public Health Association 2008 Annual ConferenceHalifax, Nova Scotia, CANADA
Reducing Health Inequalities through Evidence and Action
On the Move: Neighbourhoods and Networks
by
2008 Conference for CPHA. Mamadou Bamba Hanne
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PresentationContext and research questions
Framework
Method
Data
Prevalence of the morbidity in Montreal
Morbidity and use of the health services
Clustering of the users aged 65 years and +
Limits
Conclusions
2008 Conference for CPHA. Mamadou Bamba Hanne
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Context
Epidemiological definition: morbidity as the number of persons with a given condition (disease) within a given period – one year.
Three types of morbidity :
Objective morbidity
Perceived morbidity
Established morbidity
Classification of morbidity levels: best predictors of the use of health services
Focus of the existence of specific conditions : not a global vision of resources to build on (Adams et al., 2002).
2008 Conference for CPHA. Mamadou Bamba Hanne
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Questions
Main goal : description of the high morbidity in Montreal by using the ACG system
What are the characteristics of users with a high morbidity ?
How do they use the health services ?
Can me make a clustering of elder users ?
Issue:- To approach central problems in the management and the organization of the resources intended to dam up morbidity.
- best knowledge of the profile of challenging users and their localization: anticipation of the request for care and the expenditure
2008 Conference for CPHA. Mamadou Bamba Hanne
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Framework
Weiner (2003).
2008 Conference for CPHA. Mamadou Bamba Hanne
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MethodLevels of the morbidity: use of the ACG system software
Use of the International Classification of Disease (ICD-9)
Cataloging the patients into 93 different categorries of AGG (Adjusted Clinical Groups) according to the type of morbidity characterized by:
1. Likely persistence of the condition2. severity of the condition3. Aetiology 4. Diagnostic certaintly5. Needs for speciality care
Gathering the 93 ACG codes into6 major categories [0-5]: integration of the morbidity indicator RUB (Resource Utilization Bands)
0: nonusers 3: moderate morbidity1: healthy users 4:high morbidity2: low morbidity 5: very high morbidity
2008 Conference for CPHA. Mamadou Bamba Hanne
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Typology of the patient’s profile of 65 years old and over :
Process of cluster analysis (clustering)
Usage of the Euclidian Distance in a multi-dimensional space created by the variables specified
K-means methods: K groups, or "clusters"
Minimal distance
Constitution of homogenious group and differentiate one another
Methodology
2008 Conference for CPHA. Mamadou Bamba Hanne
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Data
iCLSC
Med-Echo
RAMQ - Actes médicaux
RAMQ - Médicaments
Info-Admission
Décès
medical-administratives data base
‘‘Agence de la Santé de Montréal’’
‘‘Banque de données jumelées’’
Junction of data bases
linkHealth Insurance Number
encrypted
confidentiality
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Prevalence of the morbidity in Montreal
Très grande morbidité
Grande morbidité
Morbidité modérée
Morbidité faible
Sans morbidité
niveau de morbidité (RUB)
50
40
30
20
10
0
pré
va
len
ce (
%)
14,9
3,16,8
32,7
42,5
Prévalence de la morbidité chez les bénéficiaires des soins, 2005-2006
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Prevalence of high and very high morbidity within age group, by sex
1,9
0,2
8,1
1,0
12,2
9,0
1,60,3
3,7
1,5
11,3
13,6
0,0
2,0
4,0
6,0
8,0
10,0
12,0
14,0
Grandemorbidité
Très grandemorbidité
Grandemorbidité
Très grandemorbidité
Grandemorbidité
Très grandemorbidité
moins de 20 ans 20 à 64 ans 65 ans et plus
prévalence (%)
femmes hommes CMIS, 2007
Prevalence of the morbidity in Montreal
2008 Conference for CPHA. Mamadou Bamba Hanne
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Prevalence of the morbidity in MontrealPrevalence of the morbidity within quintile of deprivation
Pampalon’s Indicators quintiles High morbidity Very high morbidity
Social deprivation 1 (more favored) 5,9 2,4
2 6,5 2,8
3 6,8 3,1
4 7,0 3,2
5 7,0 3,3
Material deprivation 1 (more favored) 6,5 2,9
2 6,8 3,1
3 6,8 3,2
4 7,1 3,3
5 6,9 3,0
Relationship between the morbidity and Pampalon’s indicators
Relationship sex N γ p-value
Morbidity and deprivation
Social deprivationfemales 779272 -0,028 0,000
males 625947 -0,003 0,025
Material deprivationfemales 779272 -0,008 0,000
males 625947 +0,013 0,000
Significatives Associations between dimensions of deprivation and the levels of morbidity
Very low values of γ
Positive sign of γ for males: the more material-favored have the higher level of morbidity.
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Morbidity and use of the health services
Quelques informations sur l’utilisation des services*
Grande morbidité Très grande morbidité Tous niveaux confondus
N Moyenne N Moyenne N Moyenne
prescriptions 59 569 64,7 33 563 108,1 601 945 37,8
renouvellement d'ordonnance 59 569 49,3 33 563 82,8 601 945 28,4
actes médicaux chez l'omni 86 354 11,8 42 105 27,8 1 192 054 6,1
actes médicaux chez le spécialiste 94 052 20,3 43 040 49,7 1 081 738 9,5
interventions en CLSC 42 059 11,4 23 726 30,2 321 820 8,3
recours au transport ambulancier 15 093 1,6 21 063 2,3 70 588 1,6
durée de séjour(s) en courte durée 48 742 7,6 34 763 270 150 565 10,49
durée séjour(s) en longue durée 48 742 0,4 34 763 20 150 565 0,6
durée séjour(s) en CHLSD 997 228,6 3 509 201,4 4 896 213,6
Morbidity levels and some information about health services usage, 2005-2006
Positive assiociation between levels of morbidity and volume of health services usage
Exception for the length of inpatient stay in CHLSD (Centre d’Hébergement et de Soins de Longue Durée): difference of 14% in favour of the very high morbidty
Explanation: high mortality induced by the very high mortality
2008 Conference for CPHA. Mamadou Bamba Hanne
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Morbidity and use of the health servicesShare of (%) patient of each level of morbidity in the total of prescriptions, medical acts, interventions in CLSC and emergency ambulance transport
17
14
19
18
21
23
20
22
16
16
21
27
42
59
73
68
0 10 20 30 40 50 60 70
prescriptions
actes médicaux chez l'omni
actes médicaux chez lespécialiste
interventions en CLSC
recours au transportambulancier
durée totale des séjours encourte durée
durée totale des séjours enlongue durée
durée totale des séjours enCHLD
part des patients (%)Grande morbidité Très grande morbidité CMIS, 2007
10% of the population of Montreal
Third of the annual total number of prescriptions
Quarter of the whole of medical acts passed through the general practioner
40% of the whole of medical acts passed through the the specialist
Impact of the two higher levels of morbidity
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Clustering of the users aged 65 years and +
Characteristics of elder patients
Variables de classification Classes Total
1 2 3
durée de séjour en courte durée 59,0 23,7 6,6 11,3
actes médicaux chez l'omni 51,1 28,5 16,4 19,5
actes médicaux chez le spécialiste 124,3 38,7 23,7 32,3
interventions en CLSC 17,6 189,9 5,4 10,6
recours au transport ambulancier 1,8 1,6 0,5 0,6
Proportion (%) 8,23 2,27 89,50 100,00
Classification according to the means of use of the services
Class 1: profile of hospitalization
Class 2: profile of great customer of CLSC
Class 3: profile of average user
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Clustering of the users aged 65 years and +
Validation of the classification: distribution (%) of patients of each class according to their degree of real heaviness
Class and profiles ACG codes (degree of real heaviness) Total
4430 4920 4930 4940 5040 5050 5060 5070
1 : hospitalization 2,07 5,54 7,22 5,60 0,47 3,39 10,74 64,95 100
2 : great customer of CLSC 11,52 17,22 15,09 8,08 0,94 4,45 11,27 31,43 100
3 : average user 24,37 30,52 15,39 5,04 2,85 5,47 6,99 9,37 100
Total 22,24 28,16 14,71 5,16 2,61 5,27 7,39 14,45 100
Three last ACG codes: patients living with at least ten combinaisons of diagnostics including at least two majors
79% of the patients with the profile hospitalization (class 1)
47% of the patients with the profile great customer of CLSC (class 2)
22% of the patients with the profile average user (class 3)
2008 Conference for CPHA. Mamadou Bamba Hanne
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Clustering of the users aged 65 years and +
Residence (RLS) Class Total
profilehospitalization
profilegreat customer of CLSC
profile
average user
Ahuntsic/Montréal-Nord 7,23 1,70 91,07 100,00
Côte-des-Neiges/Métro/Parc-Extension 8,60 2,51 88,89 100,00
Côte-Saint-Luc/NDG/Montréal-Ouest 9,19 2,40 88,41 100,00
Faubourgs/Plateau Mont-Royal/Saint-Louis-du-Parc 8,53 3,72 87,74 100,00
Hochelaga/Mercier-Ouest/Rosemont 9,47 2,35 88,18 100,00
LaSalle/Vieux-Lachine 6,78 1,97 91,25 100,00
Nord-de-l'île/Saint-Laurent 7,44 2,21 90,35 100,00
Petite-Patrie/Villeray 7,66 2,41 89,93 100,00
Pierrefonds/Lac Saint-Louis 7,16 2,07 90,77 100,00
RDPR/Anjou/Montréal-Est 8,25 2,31 89,44 100,00
Saint-Léonard/Saint-Michel 9,22 1,85 88,92 100,00
Verdun/Côte Saint-Paul/Saint-Henri 9,52 2,34 88,14 100,00
Total 8,23 2,27 89,50 100,00
max 9,52 3,72 91,25
min 6,78 1,70 87,74
Distribution (%) of patients aged 65 years and + , according to their residence
2008 Conference for CPHA. Mamadou Bamba Hanne
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Limits
Connection of AGG system with
- the number of medical visits registered
- the administration registrars of diagnostics
- the errors in diagnostic’s identification
Weakness of pharmaceutical data comparability :
- differentiation of prescription volumes
- Beneficiates of previous prescription from the current fiscal year
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ConclusionsHigh and very high morbidity levels : 10% of the population in Montreal
Characteristics of patients with higher morbidity: elderly• More stroked by the two extreme morbidity levels• Heterogeneous group, with three profiles
Vulnerability defined by the Quebec Health Insurance office : only 52% of patients with a very high morbidity… what happened ?
Positive association between the level of health services usage and the degree of morbidity
ACG System: facilitation of data process related to diagnostics
Best anticipation of care seekers
Allocation of resources and services organisation according to the profiles of expected patients
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Thank you for your attention !