To create the territorial typologies we used data held by the General Health Insurance Company of the Czech Republic (GHIC). This insurance company has the largest share of the Czech market, ensuring care is provided to almost 60% of insurance holders and holding contracts with almost 100% of providers, especially primary care ones, which are paid for through public health insurance (16). The data used in this research are therefore highly reliable and relevant. Two typological variants were created in an attempt to divide the territory into regions by distinguishing between GP practices along a basic urban–rural dimension.
Before going on to describe the various typologies in detail, we need to explain the basis of the administrative divisions in Czechia. In the NUTS classification Czechia is divided into eight NUTS 2 regions (administrative regions), and 14 NUTS 3 regions (regions). Below that level there are 77 LAU 1 units (districts, formerly NUTS 4) and 6,258 LAU 2 units (municipalities, formerly NUTS 5) (17). In addition to this classification Czechia is divided into local government administrative units, known as administrative units of municipalities with extended powers, and there are 206 of these. The “centres” of these are known as municipalities with extended powers (MEP). These municipalities function as local centres, partly for local government purposes (18). The MEPs are probably the most unsatisfactory level of regionalisation in Czechia, which function as basic catchment areas for local inhabitants, providing access to basic services (healthcare, social services, education etc.). In many areas the LAU 1 units are of more importance, as up until the end of the twentieth century the district towns were the main centres where all the state services were located and many specialist outpatient and inpatient healthcare services were concentrated here.
But let us return to the creation of the territorial typologies. The initial analysis, performed on the basis of the distribution of GP practices (FID – facility ID number) for 2014–2015, was undertaken from a purely geographical perspective. The basic idea was to divide the country based on size of population in the municipalities (LAU 2). Urban type centres had previously been identified along with their environs, which corresponded to the catchment area of potential insurance holders using the healthcare services in that town.
The resulting typology (Variant 1) contains three types (see additional Figure 1):
- Type I = town/city with a large population and its environs, where:
- town/city with a large population = all municipalities of 30,000 inhabitants and over, and the remaining district towns (LAU 1 centres)
- environs = municipal area (LAU 2), where the centre is within 5 km of the boundary of a town/city with a large population
- Type II = town with a smaller population and its environs, where:
- town with a smaller population = municipality with extended powers (MEP), which does not belong to type I
- environs = municipal area (LAU 2), where the centre is within 10 km of the boundary of a town with a smaller population (MEP)
- Type III = remaining areas, largely municipalities with smaller populations.
The results of this initial typology provoked discussion among experts and scholars, and within the research team. This led us to create a new typology that maintained some similarities to the original. We attempted to take into account not just the geographical and population aspects but also the wider context of the system of healthcare providers. In the subsequent analysis a wider spectrum of data was used, so we had to work at the provider (PID) level rather than the practice (FID) level. In Czechia a single provider (PID) may consist of one or more practices (FID), although the contractual agreement with the health insurance company for reimbursement of declared costs is at the PID level (and therefore also the available data). In cases where a PID had a FID that appeared in more than one of the types in the typology, it was decided the main FID would be used to determine which type the PID belonged to. The main FID is the location where the PID has the greatest capacity or the longest hours of work.
When the initial typologies were being modified, we decided not to take the environs into account (see Type I and Type II above). Whether the patient receiving care lives in the municipality or in the immediate environs is not important from the provider perspective. But what is important is whether there is a range of accessible outpatient and inpatient services where GPs can send their patients, as this affects GP activities. We therefore divided Type II of the resulting typology into two subtypes reflecting the existence or non-existence of a larger hospital. In addition to the three basic types, we also distinguished a further two subtypes. These contain a very specific type of GP practice and on that basis were excluded from the analysis along the urban–rural dimension. The result was the following typology (Variant 2) (see additional Figure 2)::
- Type I = town/city with a large population, all municipalities of 30,000 inhabitants and over, and the remaining district towns (LAU 1 centres)
- Type IIa = municipality with extended powers (MEP) not included in Type I, where there is an acute care inpatient hospital for at least one of the basic specialisms (internal medicine, paediatrics, surgery, and gynaecology), and selected municipalities with 15,000 inhabitants and over that are not MEPs but that are located within the immediate proximity of a Type I municipality (municipalities in which a Type I town/city has an identifiable impact and so are a de facto type of agglomeration; five of these were identified)
- Type IIb = municipality with extended powers (MEP) that does not belong in either Type I or IIa, i.e., it has no inpatient acute care
- Type III = remaining areas, mainly consisting of municipalities with smaller populations
- Type IV = providers that are part of “chains” of providers (the nature of the work performed by these practices differs; these are bigger companies generally containing a number of practices where the doctors work closely with various specialists, they have a large laboratory, operating either locally or nationwide, and have highly developed commercial skills)
- Type V = special GP practices – military and prisons.
We excluded types IV and V when identifying the differences in population and territorial distribution as these two types do not have strong links to the area they are located in but are defined by their activities.
The two variants capture the basic differences according to the two main polarities, urban versus rural. However, they also incorporate an intermediate category, the areas that are somewhere between the two basic dimensions. We used information from the OECD regional typology from 2011 (22, 23), which divides the territories into three basic types as follows:
- Predominantly Urban (PU) = proportion of inhabitants in the region living in rural settlements is less than 15.0%
- Intermediate (IN) = proportion of inhabitants in the region living in rural settlements is 15.0–49.9%
- Predominantly Rural (PR) = proportion of inhabitants in the region living in rural settlements is 50% or more
The OECD definition of a rural settlement is one in which the population density of the units (municipality = LAU 2) is under 150 inhabitants per 1 km2. The results are then applied to NUTS 3 regions. However, the NUTS 3 regions are too large to be used to define rural versus urban areas in Czechia and to create a typology of GP practices. We therefore took the idea of defining regions as PU, IN, and PR and applied it to the LAU 1, or MEP, level, which better reflects the natural catchment areas. We also adopted a different approach to defining size of rural settlement. Instead of population density our main criterion was size of population, where rural settlements were considered to be those with fewer than 5,000 inhabitants, as most MEPs have larger populations (192 out of 206 MEPs).
If we compare the results obtained using the OECD method for defining regions and our modified version, based on OECD methodology, it is clear that there is a high level of correspondence between the two types of regional distribution at both LAU 1 and MEP level (Table 1).
Table 1: Comparison of results for population structure using OECD typology and as applied to LAU 1 and MEP levels
|
Share of inhabitants in region using OECD typology (%)
|
Predominantly Urban (PU)
|
Intermediate (IN)
|
Predominantly Rural (PR)
|
OECD typology* for Czechia
|
24.2
|
42.9
|
32.9
|
Modified OECD** typology calculated for level:
|
LAU 1
|
22.8
|
42.4
|
34.8
|
MEP
|
23.9
|
38.1
|
38.0
|
* OECD typology from 2011, based on population data from 2014
** OECD typology applied to LAU 1 and MEP regions, based on population data from 1. 1. 2017.
Data source: 22, 23, 24; authors’ calculations