17th PCS/E Conference
EFMI-WG1 Special Topic Conference
Case mix : global views, local actions
10-13 October 2001 Bruges, Belgium
Images of minimal clinical data – geographical variation of
pathology in Belgian hospitals
Dr. Hilde Pincé
MD, Doctor in medical sciences, Master in scientific computer applications
Institute : University Hospital of Leuven, Staff member of general direction, Herestraat
49, 3000 Leuven, Belgium (= address for correspondence)
Tel. 32-16-34.49.99
Fax. 32-16-34.49.20
e-mail : hilde.pince@uz.kuleuven.ac.be
Summary
This paper presents a project with as main objective the exploration of the
Belgian Minimal Clinical Data in an epidemiological context. The paper describes
the methodology used to produce maps of the country, for selected medical
domains. These maps visualise the geographical variation of pathology treated in
the Belgian hospitals. In some cases the variation can be explained by differences
in prevalence of the specific pathology. In other cases probably other factors
influence the data. The paper presents and discusses a few examples of different
elaborated themes.
In conclusion, the Minimal Clinical Data can be used for epidemiological
purposes, if potential influencing factors are taken into account. They should be
used together with other data sources as the general medical record and specific
health surveys. In this way, they can help to complete the global view of the
health status of the Belgian population. In addition, analyses done for this project
can be taken as starting point for further investigations in the domains of
registration audit, quality of care and evaluation of medical practice.
Objectives
This paper presents a project ‘MKG in Beeld’ (in French ‘RCM en images’), which
could be translated as ‘Images of Minimal Clinical Data’.
The objectives of the project were the following. The first goal was an exploration of the
possibilities of using the Belgian Minimal Clinical Data (MCD) 1 for epidemiological
purposes. Further, the result of the project should be a publication containing maps,
presenting the Minimal Clinical Data to a broad public and not as an instrument to refine
the hospital financing system. Further validation of the data, by analysing different
specific medical domains, is a third objective.
Session «Session»
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Methods
From the beginning of the project it was obvious that, working with a hospital stay
registration system, has some inherent limitations when used in an epidemiological
context. Incidence or prevalence figures are not available. Indeed, the Belgian hospital
registration system1 is based on care supplied in general hospitals. Morbidity present in
the population, but not treated, or treated in another setting (consultations, psychiatric
hospitals, …) is obviously missed. In addition, the registration unit is the hospital stay,
and not the patient. Despite these limitations, the number of hospital stays for a specific
pathology, generated by the population of a certain geographical area, will tell something
about the prevalence of that pathology in that specific area. Without a doubt, other
factors can influence the data, as we will see in the example of appendectomy below.
The methodology used to produce the maps is the same throughout the publication. The
geographical level is the administrative “arrondissement”. This is similar to a ‘district’,
this term will be used in the rest of the text. The basis to colour an area on a map is the
city where the patient lives and not the place of treatment. Thus a patient living in
Antwerp but treated in Leuven is counted for Antwerp and not for Leuven.
After the selection of hospital stays with a specific pathology, the data are standardise d
by age and sex. The methodology used here is the indirect standardisation 2. The
reference is the number of hospital stays for the specific pathology in the Belgian
population. For each administrative district a SAR is calculated (SAR = standardised
admission ratio) as
Observed number of stays
Expected number of stays
* 100
The value of the SAR is the basis to colour a district on the map. There are 6 distinct
classes. Districts in class 1, with a SAR value lower than 80, will be coloured white on
the maps; districts in class 6, with a SAR greater than 120 will be coloured dark green.
Because a certain selection often results in a rather small amount of stays, a 95%
confidence interval is calculated, to indicate whether the value of the SAR is
significantly different from 100. If this is the case, the district gets a small yellow star on
the map.
Results
The first result of the project is a publication in book form treating the national Minimal
Clinical Data of the year 1996 3.
The publication is divided in several parts. Each part addresses another aggregation level
of the data and has several themes: they are listed below.
Part I: 1) Number of hospital stays; 2) Number of days in hospital; 3) Hospital-based
outpatient care; 4) Hospital mortality
Part II: 1) MDC 15 “New-borns and other neonates”; 2) MDC 24 “HIV-infections”; 3)
MDC 25 “Multiple significant trauma”
Part III: 1) APR-DRG 194 “Heart Failure”, 2) APR-DRG 225 “Appendectomy”
Part IV: 1) Tuberculosis; 2) Malignant neoplasm of trachea, bronchus ad lung; 3)
Diabetes mellitus; 4) Ischemic heart disease
Part V: 1) Transurethral prostatectomy; 2) Hysterectomy
Each theme contains more or less the same components: a map of Belgium, a table
presenting all the data used to produce the map, a sex and age distribution, and some
additional relevant data available in the database. This last item differs for each specific
theme.
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Today, 10 of the 15 themes of version 1996 are updated for the registration year 1998.
Probably the results for 1998 will be published on an Internet site, together with the
results for 1996.
Two examples were chosen to illustrate the method. Both appear in the 1996 version 3
and in the 1998 version.
Examples
Malignant neoplasm of trachea, bronchus and lung - MCD 1998
Definition classes + (number of districts)
120 < SAR
110 < SAR =< 120
100 < SAR =< 110
90 < SAR =< 100
80 < SAR =< 90
SAR =< 80
(7)
(6)
(7)
(7)
(9)
(7)
* indicates that the value of the SAR is significantly different from 100
This map visualises the hospital stays with a malignant neoplasm of trac hea, bronchus
and lung as principal diagnosis. It shows that in two areas, much more admissions are
registered with this type of pathology than expected. In these areas, a lot of people have
worked in coal mines for many years. This example shows that, despite the limitations of
the methodology, a link between the class of the district and the prevalence of the
pathology can be demonstrated.
Another example shows, however, that also other factors can influence the data.
The following map is created based on the selection of hospital stays assigned to the
APR-DRG 225 “Appendectomy”. The DRG-level guarantees the selection of a
homogenous group of hospital stays where the appendectomy will be, in most cases the
only, and in all cases the most important procedure performed 4.
For the registration year 1998, in Belgium, 14855 hospital stays were assigned to APR DRG 225.
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APR-DRG 225 "Appendectomy" - MCD 1998
Definition classes + (number of districts)
120 < SAR
(11)
110 < SAR =< 120 (4)
100 < SAR =< 110 (6)
90 < SAR =< 100 (13)
80 < SAR =< 90 (6)
SAR =< 80
(3)
* indicates that the value of the SAR is significantly different from 100
The map presenting the hospital stays assigned to APR-DRG 225 “Appendectomy”
illustrates the existing variation within a small country as Belgium. Compared to the
same map for 1996 3, a small levelling can be found. In 1996 there were even less
districts in the more “neutral classes” 3 and 4 (14/43 while 19/43 in 1998). The global
view however is the same.
The sex and age distribution shows that more than 80% of the appendectomies are
performed for patients between 6 and 40 years. The procedure is somewhat more often
performed on women (52%) than on men (48%). The top of the distribution for men is
seen around the age of 10 years. For women, appendectomies are more often performed
on young fertile women. Probably the differential diagnosis with
Sex and age distributon - MCD 1998
100
90
80
70
Age
60
50
40
30
20
10
0
500
400
300
200
100
0
100
200
Number of hospital stays APR-DRG 225 "Appendectomy"
300
400
Men
500
Women
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extra-uterine pregnancy or ovary problems is a greater incentive to explore the female
abdomen. An American study 5 suggests that, although the life time risk of appendicitis is
higher for men than for women, the life time risk of appendectomy is almost twice as
high for women than for men.
Selections on APR-DRG-level have the advantage that the distribution of the admissions
over the four subclasses of severity of illness 4 can produce additional interesting
information.
Severity of Illness
subclass
minor
moderate
major
extreme
number of stays
11201
3332
267
55
% of stays
75,4
22,4
1,8
0,4
mean number of
secondary
diagnoses
0,2
0,9
2,9
6,8
total
14855
100,0
0,4
APR-DRG 225 "Appendectomy", "severity of illness"-subclasses - MCD 1998
mean length of
stay
3,7
6,4
11,8
23
4,5
The table above shows that more than 75% of all hospital stays in APR -DRG 225 are in
the subclass ‘minor severity of illness’, and this is exactly as expected. We are talking
about a young patient population. The principal diagnosis is in most cases a simple acute
appendicitis. Only one of five admissions in this subclass has an additional secondary
diagnosis. The mean length of stay for these admissions is 3,7 days. The figures for the
other subclasses clearly illustrate the importance of secondary diagnoses for the
determination of the severity of illness.
For most Belgian districts, the distribution of the admissions in APR -DRG 225, over the
four subclasses of severity of illness, is more or less the same as for Belgium as a whole.
Some districts however have a somewhat different distribution. The combination of data
about
1) the distribution of the admissions over the four subclasses of severity of illness,
2) the mean length of stay per severity of illness subclass, and
3) the class of the district on the map,
allows in some cases to formulate hypotheses about under- or overregistration, and/or
more or less selective therapeutic attitude of clinicians.
A few examples of these hypotheses are described below.
In most districts of the province West-Vlaanderen, the percentage appendectomies with a
minor severity of illness is greater than the national reference. On the map, most districts
of the province West-Vlaanderen are darkly coloured, which means that more
appendectomies than expected are performed. The combination of this information could
lead to the hypothesis that, in this area, clinicians tend to be less selective and quickly go
over to an intervention. The result should be a rather short length of stay for the patients
with a minor severity of illness. For example, in the districts Brugge and Ieper the mean
length of stay for patients with a minor severity of illness is 3,4 and 2,9 days,
respectively.
In the district Eeklo, there are rather few admissions with a minor severity of illness
(63.6%) and a lot of admissions with a major severity of illness (12.1%). The conclusion
should be that there are a lot of very sick appendectomy patients in Eeklo. The mean
length of stay, however, of these patients with a major severity of illness is much shorter
than the national mean length of stay for this subclass (6.1 days in Eeklo, whereas the
national mean length of stay is 11.8 days). The mean length of stay for patients with a
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major severity of illness in Eeklo comes close to the national mean length of stay for
patients with a moderate severity of illness. The hypothesis of over -registration of
secondary diagnoses can be put forth. One should be aware of the fact, however, that
only about 100 admissions are taken into account here. On the other hand, the pattern
found here is exactly the same as that found for the data of 1996, with one difference
namely in 1998 a shift from more ‘moderate’ admissions to more ‘major’ admissions is
found.
The example of APR-DRG 225 “Appendectomy’ has shown that the basic assumption
that the number of hospital stays with an appendectomy reflects the incidence of acute
appendicitis probably is not valid. Other factors such as a more or less therapeutically
selective attitude of the clinicians can influence the data. The evaluation of the attitude
of the clinicians is possible here. The reason is that in almost 80% of the cases, the
patient is treated in the district he lives. Indeed, people would not prefer to go to a long
distance reference centre for a basic pathology as appendicitis, which is, in addition, a
typical emergency.
Conclusions
In conclusion, we will retake the objectives of the project and evaluate whether the
different goals were attained.
The project explored the use of the Belgian Minimal Clinical Data for epidemiological
purposes. The limitations were well described. They could only be, partly, overcome
when the Minimal Clinical Data could use a unique, anonymous national patient number,
which is not the case at the moment. For some medical domains it was possible to
illustrate a relationship between the prevalence of the pathology and the number of
admissions for that pathology (e.g. tuberculosis, HIV, respiratory neoplasm 3 ). For other
medical domains, it was shown that probably other factors influence the data
(appendectomy, prostatectomy, hysterectomy 3). One huge advantage in using the
Minimal Clinical Data for such projects is the fact that they are available anyway. No
extra data collection is needed. In Belgium, at this moment, the hospital data of almost
ten years are accessible in an immense, exhaustive database.
The project definitely succeeded in the demonstration of existing geographical variation
in the number of hospital stays with a specific pathology. Some differences could be an
incentive for further investigation, for example in the domains of registration audit,
quality of care and evaluation of medical practice. In conclusion, the Minimal Clinical
Data can be used for epidemiological purposes, if potential influencing factors are taken
into account. They should be used together with other data sources as the general
medical record and specific health surveys performed in our country 6. In this way, they
can help to complete the global view of the health status of the Belgian population.
For the year 1996, the project result is a publication in book form 3, which was
distributed, for free, in the Belgian health care sector. This publication includes an
extensive description of the history, contents and organisation of the registration of the
Minimal Clinical Data. In each theme, relevant data available in the MCD are presented
(mostly in graph, sometimes in tables) to further elaborate the topic. Examples of such
‘additional data’ are external causes of injury (E-codes – theme ‘Multiple trauma’),
patient nationality (tuberculosis), length of stay, severity of illness, risk of mortality and
effective deaths (selections on DRG-level), and of course principal and secondary
diagnoses.
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For the year 1998 the goal is a publication on a web site of the Ministry of Public Health,
together with the data for 1996. In this way an even broader distribution of the results
would be achieved.
The project included further validation of the data, internal as well as external. Internal
validation was done by the check between ICD-9-CM procedure codes and ‘RIZVcodes’, both available in the Belgian MCD, for the surgical themes concerned. ‘RIZIV codes’ are the codes for the national public health insurance on which reimbursement is
based. In addition, the data of 1996 and 1998 could be compared, which allowed to
describe trends as well. External validation was performed by checking data registered
by other institutions, as for example the national institute for public health insurance,
and specific scientific organisations 7-8. No significant inconsistencies could be
demonstrated, which resulted in an increased confidence in the validity of the Minimal
Clinical Data.
References
1. Richtlijnen voor de registratie van de Minimale Klinische Gegevens (M.K.G.). Nieuw concept.
Ministerie van Sociale Zaken, Volksgezondheid en Leefmilieu, Bestuur van de gezondheidszorg,
Bestuursdirectie gezondheidszorgbeleid. Juni 1999.
Directions d’enregistrement du Résumé Clinique Minimum (R.C.M.). Nouveau concept. Ministère
des Affaires Sociales, de la Santé publique et de l’environnement. Administration des Soins de
Santé. Direction de la politique des soins de santé. Juni 1999.
2. Rothman, Kenneth, J., Modern Epidemiology, Little Brown, Boston (Mass), 1986, 358p.
3. MKG 1996 IN BEELD. Geografische variatie van de pathologie in de Belgische ziekenhuizen.
Ministerie van Sociale Zaken, Volksgezondheid en Leefmilieu, Bestuur van de Gezondheidszorg,
Bestuursdirectie Gezondheidszorgbeleid.
RCM 1996 EN IMAGES. Variation geographique de la pathologie dans les hôpitaux belges.
Ministère des Affaires Sociales, de la Santé publique et de l’environnement. Administration des
Soins de Santé. Direction de la politique des soins de santé.
4. APR-DRGs. All Patient Refined Diagnosis Related Groups. Definitions Manual Version 15.0. 3M
Health Information Systems.
5. Addiss DG, Shaffer N, Fowler BS, Tauxe RV. – The epidemiology of appendicitis and
appendectomy in the United States. Am J Epidemiol 1990 Nov, 132(5): 910-925.
6. Wetenschappelijk Instituut Volksgezondheid-Louis Pasteur, Afdeling Epidemiologie.
Gezondheidsenquete door interview. http://www.iph.fgov.be/epidemio/epinl/crospnl/hisnl/
7. Wetenschappelijk Instituut Volksgezondheid-Louis Pasteur, Afdeling Epidemiologie. AIDS in
België : semesteriële rapporten. http://www.iph.fgov.be/epidemio/epinl/aidsnl
8. Vlaamse vereniging voor respiratoire gezondheidszorg en tuberculosebestrijding (VRGT) VZW.
Tuberculose-indidentieregister België 1998-1999.