Definition and methods

‘Prevalence’ expresses the proportion of a defined population with a specific health problem in a defined period of time. FaMe-Net uses periods of one calendar year and reports a ‘contact prevalence proportion’. This figure represents the proportion of the population that had at least one interference with the GP (e.g., consultation, prescription) for a selected episode (i.e. final diagnosis). This is calculated by dividing the number of persons contacting their GP for a specific health problem during the selected calendar year(s), by the total number of patients in these years. More precisely, the denominator ‘patient years’ combines the number of listed patients in a practice with the length of their registration. This corrects for the dynamic population in a general practice in which patients are born, die, and move in or out of the practice. 

Thus, in the methods applied in FaMe-Net, some interference with the GP (practice) is needed in order to be included in the prevalence (‘contact prevalence proportion’) or incidence figures (see below). This method makes these data particularly good for an assessment of the epidemiological representation of illness and conditions under the treatment or surveillance of the GP. For diseases and conditions with a variable course, such as depression, gout, or allergic rhinitis, these methods reflect whether or not the disease is still severe enough to seek medical help. Consequently, medical problems not reported to the GP, e.g. minor problems for which no professional medical help is sought, are not included in these figures. Moreover, a severe disease that is exclusively handled by a specialist (e.g. HIV/AIDS) is also potentially underreported. This effect is probably limited as in most cases the GP receives (yearly) written reports on the situation, or is involved in prescribing medication or monitoring, for example by requesting lab tests.

For assessment of prevalence, the episode label that was recorded at the end of the calendar year is used. For episodes evolving over a longer period of time, and in episodes in which the final diagnosis is harder to make, it should be noted that this might result in some underestimation of the rate of these more severe diagnoses in the first year(s) that this condition is recorded. The Distributions tab page presents prevalence data of episodes.

Trends in prevalence

Prevalence figures fluctuate over years. The extent of this year-to-year fluctuation depends on the specific condition. To make optimal use of the complete data collection, FaMe-Net calculates and displays prevalence numbers over all calendar years in the dataset.  Prevalence numbers of single calendar years are summed up and divided by the number of calendar years to calculate the mean prevalence over the entire data period. 

All age and sex groups are included in these figures. 

The website user may adjust the calendar years if prevalence numbers are sought only for a selection of the entire period (‘Apply a selection of calendar years’). 

Data from before 2014 are available upon request by filling in an application form. 

Trend chart

In order to visualise the direction of changes in prevalence or incidence (see below) over time, charts are presented. Coincidental fluctuations are levelled by using a technique of ‘rolling three years average’, summing up the values for the actual year, its preceding year and its following year and then divide it by three. This emphasises the direction in which changes in prevalence or incidence stretch over years without underlining occasional outliers. 

The trend chart always shows data for the entire calendar period included in the dataset and remains unchanged, even when a shorter selection of calendar years is applied by the user (‘Apply a selection of calendar years’). The first and last year of the included dataset are not shown in the chart, because for these years the rolling average cannot be calculated as it requires data from the preceding and following year. 

The trend charts are presented on the Distributions tab page.

Definition and methods

‘Incidence’ expresses the rate of occurrence of new diagnoses of a specified health problem in a defined population during a defined time period. FaMe-Net uses periods of one calendar year and reports the ‘incidence proportion’. This counts all newly occurring (starting) episodes of a certain condition during a calendar year, and divides it by the total amount of patient years. Cases (new episodes) are counted and not persons with the diagnosis. It is up to the clinical judgment of the FaMe-Net GP whether the encounter is a continuation of an existing episode or the start of a new episode.  

All patient years are counted in the denominator of the ‘incidence proportion’, not ‘patient years at risk’ (which would be used in an ‘incidence rate’). 

For assessment of the incidence, the episode label that was recorded at the end of the calendar year is used. For episodes evolving over a longer period of time, and in episodes in which the final diagnosis is harder to make, it should be noted that this might result in some underestimation of the rate of more severe diagnoses.

The Distributions tab page presents incidence data of episodes.

Trends in incidence

FaMe-Net calculates and displays incidence numbers over all calendar years in the dataset.  Incidence numbers of single calendar years are summed up and divided by the number of calendar years to calculate the mean incidence over the entire data period. 

All age and sex groups are included in these figures.  

See also Trends in prevalence.

Trend chart

Trend charts visualise the direction of changes in incidence over multiple years, depicting ‘rolling three years averages’.

(See Prevalence)

This website provides statistical and epidemiologic data from the FaMe-Net registration. Three datasheets offer different types of data.

‘Distributions’ provides information about episodes, RFEs and interventions, and their distribution among different age and sex categories. It can for example be used to look up the incidence and prevalence of a specific diagnosis or the occurrence of a specific RFE.

‘Top lists’ shows the most common diagnoses, RFEs, referrals, prescriptions and (other) interventions.

‘Relations’ shows relations between episodes, RFEs and interventions. Prescriptions and referrals can be shown in more detail (i.e. the medication type prescribed or the specialism that is referred to).

The Textbook chapters guide the website visitor through the details of all the data sheets based on a specific disease or condition so that the reader gets familiarised with the possibilities of the website. Chapters contain clickable links to data on the website. Reading chapters helps the reader to interpret the data correctly and to identify some potential pitfalls.

Click on the links to read more information about the possibilities of the datasheets Distributions, Top lists and Relations.

All data are extracted as datasets of entire calendar years and are periodically updated. Users of this website may choose to display data only from a subset of the calendar years presented. The trend charts on the ‘Distributions’ datasheet are always shown for all calendar years included in the dataset. Click here for more information on the calculation of prevalence and incidence using the FaMe-Net data and on the construction of the graphs.