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International variations

Comparing the rates of use with countries with a health system similar to Belgium makes it possible to raise hypotheses about the level of use in Belgium, whether in terms of access, choice of techniques or epidemiology, for example.


We followed this approach, for example, for bariatric surgery. The International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO), which has around fifty members from around the globe, regularly records the different rates of bariatric surgery. If we single out the European Union countries, we can see that, in 2014[1], Belgium had the highest rate of bariatric surgery (see figure below).

 

Variations Internationales

These results are clearly very surprising, particularly since they do not directly reflect the prevalence of obesity in our country, which is close to the European average. If we look at the European obesity figures, then among the 17 EU countries included in the IFSO study, Belgium is in eighth place for men and ninth for women[2].

For information purposes, we also publish on this site an interactive map to other European websites dealing with medical practices variations.

 


[1] Angrisani, L., Santonicola, A., Iovino, P., Vitiello, A., Zundel, N., Buchwald, H., & Scopinaro, N. (2017, Sept). Bariatric Surgery and Endoluminal Procedures: IFSO Worldwide Survey 2014. Obesity Surgery, 27(9), pp. 2279–2289.

[2] According to the national rates recorded by the WHO for 2014: http://apps.who.int/gho/data/node.main.A900A?lang=en

Variations in techniques used

A medical practice often consists of several different techniques whose cumulative rates of use constitute the overall rate of use. The proportion of use rates for these techniques is not always consistent across geographical areas, which may reflect differences in therapeutic choices, especially if overall rates of use are similar.

One example is bariatric surgery, which, as a whole, shows a fairly clear geographical split between the North and South of the country (see figure below).

Variations Techniques1

If we take the analysis further, and consider the use of the main bariatric surgery techniques (‘bypass’, ‘sleeve’ and ‘banding’), we gain new information, showing very different choices of technique in the various regions of Belgium (see figure below). We can then compare these relative rates of choice of technique with the procedures used in other countries[1] (the right-hand column - ‘Global data’): this shows that, despite the overall high rates, the South of the country chooses to use techniques more in line with international practice.

Variations Techniques2


[1] Angrisani, L., Santonicola, A., Iovino, P., Vitiello, A., Zundel, N., Buchwald, H., & Scopinaro, N. (2017,Sept). Bariatric Surgery and Endoluminal Procedures: IFSO Worldwide Survey 2014. Obesity Surgery, 27(9), pp. 2279–2289.

What is the cause of these variations?

The cause of these variations is rarely unique and more often composed, in varying proportions, of different factors from the triad formed by the patient, the health care provider and their environment. These causes can also be divided up into supply- or demand-related causal factors.

In general, although the causes identified sometimes may indicate a non-optimal use of resources, they cannot always be described as unjustified and the existence of variations is therefore not automatically to be accused of inefficiency in the health care system.

The causes of variations are in any case to be considered on a case-by-case basis depending on the theme analysed and its context. If we consider again the categorization of these factors according to supply and demand, here are in a very brief way the main categories of causes that can be found, as identified by the KCE[1] , with the exception of possible unknown factors in coding by health care providers:

  •  Demand-related causes  :
    • Epidemiology of the disease
    • Socio-economic variables
    • Patient's choice

  • Supply-related causes :
    • Medical density
    • Access to health care
    • Characteristics and practice style of the health care provider

[1] J. Jacques, D. Gillain, F. Fecher, S. Van De Sande, F. Vrijens, D. Ramaekers, N. Swartenbroekx and P. Gillet (2006). Étude des disparités de la chirurgie élective en Belgique Brussels : Belgian Health Care Knowledge Centre (KCE) KCE Reports vol.42B.

Variations in trends over time

As well as considering ‘snapshot’ rates of provision of a practice in a given year or over a given period, it is interesting to compare how these rates have evolved, in the country as a whole or in a particular area. Significant differences can be observed, which can be explained by the epidemiology of the underlying pathology, differences in access to care or heterogeneous therapeutic choices.

Furthermore, high rates with an upwards trend, for example, are interpreted differently from high rates which are levelling out or declining.

This latter scenario can be seen if we analyse trends in the rates of tonsillectomies and adenoidectomies carried out. The graph shows clearly (see figure below) that the arrondissement with the highest rate in 2017 has also experienced the steepest decline since 2012.

Variations Trends

Variations by care category

Variations may also be observed depending on the type of care offered to the insured for the same practice. This analysis compares traditional hospitalization rates with ambulatory care. Significant differences can be a reflection of variations in care related to the provision of care.

For procedures such as inguinal hernia surgery, for example (see figure below), where there are few geographical variations in the rate of provision (coefficient of variation = 12.2), there are nevertheless clear differences in the choice of care category, with a difference of approximately 7:1 between the most extreme values.

Variations Ambu

Variations by social status

The health care reimbursement system makes it possible to estimate the social status of insured persons (statistical proxy). After standardization, higher utilization rates are generally observed among beneficiaries of enhanced intervention than among insured persons who do not benefit from it. The opposite situation could then be a sign of some inequity of access.

We can see this, for example, in the case of lower limb varicose vein treatment (see figure below). In all provinces, rates are clearly higher for people not eligible for preferential reimbursement (a ratio of 1.46).

Variations BIM2

Geographical variations

The utilization rates recorded by geographical area are based exclusively on the insured's administrative domicile and not on the place of intervention. The geographical areas of breakdown are regions, provinces and boroughs. 

Since the data are standardized for gender, age and social status, geographical differences are then linked to a particular epidemiology of the pathology underlying the intervention, to a difference in access to care or to potential variations in practices.

Representations of geographical variations:


These variations can be illustrated in various ways. One way of assessing them is to plot the rates per arrondissement of a particular practice on a dot-plot graph. This is useful as it highlights clusters of data, gaps in the distribution, and outlier values. In the case of carotid ultrasounds, for example, (see figure below), the ratio of maximum: minimum values is approximately 4:1.

Variations DotPlot


Another, probably the most intuitive, way of showing unwarranted variations is to use mapping. A colour code is used to show how much the rate in each arrondissement differs from the national mean. This makes it quick to see where the variations are greatest and least pronounced, and indicates whether the arrondissements furthest from the mean are geographically close to each other.

  variations géo carte

In the case of thyroidectomies, for example (see figure above), we can see a clear North-South divide in how rates vary, in each arrondissement, from the mean thyroidectomy rate.


Another way of presenting the data on geographical variations is to use a funnel plot. The rates per arrondissement are positioned according to the size of the population. The confidence intervals typically take the shape of a funnel: for arrondissements with small populations, the expected variation is greater than for those with large populations. The arrondissements falling outside the upper and lower limits of the 99.7% confidence intervals can then be defined as ‘outliers’.

In the example of maxillofacial surgery (see figure below), we can see that one arrondissement, with a large population, very much stands out, with a significantly higher rate than in other arrondissements: it is well above the upper confidence level.

Variations FunnelPlot


One key indicator of the extent of geographical variations is the coefficient of variation between arrondissements.The coefficient of variation measures the position of data vis-a-vis the mean (standard deviation: mean). A high coefficient of variation indicates that practices vary between arrondissements. It is still difficult, however, to set a threshold value beyond which the coefficient of variation is considered too high.   

variations géo CV

If, to illustrate this, we plot the distribution of coefficients of variation for around a hundred varied and distinct medical practices in Belgium (see figure above), we can see that this distribution follows a Gaussian curve around a mean coefficient of variation of about 33. Even without a threshold value, we can deduce from this curve that, generally-speaking, there are high levels of geographical variation, and that there is, therefore, real evidence of unwarranted geographical variations in Belgium.

Variations by age group

Like variations by gender, variations by age group can also be explained by the nature of a condition or by a particular policy, such as a screening policy. Variations linked to age can therefore be categorised as unwarranted if they do not reflect these parameters. They can also be considered unwarranted if a high coefficient of variation is observed for one or several age groups, despite overall high rates for the same age groups.

Looking at the example of mammograms, current recommendations call for breast cancer screening for women aged 50 to 69. While the coefficient of variation is relatively stable in these age groups (see figure below), we can see that it is significantly higher in the 40-50 age groups. The increased coefficient of variation in these age groups probably indicates that prescribers are uncertain as to whether mammograms are advisable for women of this age category.

Variations Age

Variations by gender

While certain rate variations by gender are intrinsically linked to the nature of the procedure (hysterectomies, prostate ultrasounds, etc.), the same may not be true of other types of practice not so clearly linked to gender.

Differences in utilization rates between men and women are a priori a reflection of the epidemiology of the underlying pathology. A difference between the sex ratio of this pathology and that of the utilization rate must draw attention to the justification for this therapeutic approach different according to gender.

In 2017, for example, we can see that the rate of percutaneous coronary interventions is significantly higher for men than for women. This suggests that there may have been ‘underuse’ for women (see figure below).

Variations Genre

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