IMPLEMENTING QUALITY INDICATORS FOR DIABETES AND HYPERTENSION 
IN FAMILY MEDICINE IN SLOVENIA
Zalika KLEMENC-KETIŠ1*, Igor ŠVAB2, Antonija POPLAS SUSIČ3
1University of Maribor, Faculty of Medicine, Department of Family Medicine, Taborska 8, 2000 Maribor, Slovenia
2University of Ljubljana, Faculty of Medicine, Department of Family Medicine, 
Poljanski nasip 58, 1000 Ljubljana, Slovenia
3Community Health Centre Ljubljana, Metelkova 9, 1000 Ljubljana, Slovenia
Received: Nov 9, 2016
Accepted: Jul 6, 2017 
Original scientific article
*Corresponding author: Tel: + 386 41 516 067; E-mail: zalika.klemenc-ketis@uni-mb.si
10.1515/sjph-2017-0029 Zdr Varst 2017; 56(4): 211-219
211
UVAJANJE KAZALNIKOV KAKOVOSTI ZA SLADKORNO BOLEZEN 
IN ARTERIJSKO HIPERTENZIJO V DRUŽINSKI MEDICINI V SLOVENIJI
Klemenc-Ketiš Z, Švab I, Poplas Susič A. Implementing quality indicators for diabetes and hypertension in family medicine in Slovenia. Zdr Varst 2017; 56(4): 211-219.
Introduction. A new form of family practices was introduced in 2011 through a pilot project introducing nurse 
practitioners as members of team and determining a set of quality indicators. The aim of this article was to 
assess the quality of diabetes and hypertension management.
Methods. We included all family medicine practices that were participating in the project in December 2015 
(N=584). The following data were extracted from automatic electronic reports on quality indicators: gender 
and specialisation of the family physician, status (public servant/self-contracted), duration of participation in 
the project, region of Slovenia, the number of inhabitants covered by a family medicine practice, the name of 
IT provider, and levels of selected quality indicators.
Results. Out of 584 family medicine practices that were included in this project at the end of 2015, 568 (97.3%) 
had complete data and could be included in this analysis. The highest values were observed for structure 
quality indicator (list of diabetics) and the lowest for process and outcome quality indicators. The values of 
the selected quality indicators were independently associated with the duration of participation in the project, 
some regions of Slovenia where practices were located, and some IT providers of the practices.
Conclusion. First, the analysis of data on quality indicators for diabetes and hypertension in this primary care 
project pointed out the problems which are currently preventing higher quality of chronic patient management 
at the primary health care level.
Uvod. Pilotni projekt na področju družinske medicine v Sloveniji je leta 2011 uvedel novo metodo dela v 
družinski medicini, pri čemer je nov član tima postala diplomirana medicinska sestra, prav tako pa se je uvedel 
nadzor kakovosti s pomočjo kazalnikov kakovosti. Namen tega članka je bil oceniti kakovost vodenja bolnikov 
s sladkorno boleznijo in hipertenzijo.
Metode. V analizo smo vključili vse ambulante družinske medicine, ki so sodelovale v projektu konec 
decembra 2015. Iz avtomatične baze poročil smo izluščili in analizirali naslednje podatke: spol in specializacijo 
zdravnika, status zdravnika (javni uslužbenec, koncesionar), trajanje sodelovanja v projektu, regijo, v kateri 
je ambulanta, število prebivalcev na območju, ki ga pokriva ambulanta, računalniško hišo, ki nudi program, in 
raven izbranih kazalnikov kakovosti.
Rezultati. Od 584 ambulant družinske medicine jih je imelo 568 (97,3%) popolne podatke in so bile vključene 
v analizo. Najvišja vrednost kazalnikov kakovosti je bila opazovana pri kazalnikih kakovosti pogojev (register 
diabetikov), najnižja pa pri kazalnikih procesa in izida. Vrednosti izbranih kazalnikov kakovosti so bile neodvisno 
povezane s trajanjem sodelovanja v projektu, nekaterimi regijami Slovenije in nekaterimi računalniškimi 
hišami, ki nudijo elektronsko podporo.
Zaključek. Prva analiza podatkov kazalnikov kakovosti za diabetes in arterijsko hipertenzijo je pokazala 
na probleme, ki trenutno onemogočajo doseganje višje kakovosti obravnave bolnikov na primarni ravni 
zdravstvenega varstva.
ABSTRACT
Keywords: 
family practices, 
healthcare quality 
indicator, diabetes 
mellitus, hypertension, 
Slovenia
IZVLEČEK
Ključne besede: 
družinska medicina, 
kazalniki kakovosti, 
sladkorna bolezen, 
arterijska hipertenzija, 
Slovenija
© Nacionalni inštitut za javno zdravje, Slovenija. 
1 INTRODUCTION
Assessing quality of care with quality indicators is 
paramount (1) and has already become a standard for 
working in family practice in several countries (2-5). 
Various quality indicators are being used (6) and in some 
countries performance-related-pay based on quality 
indicators has been introduced (7-9). 
In Slovenia, quality assurance at the primary health care 
level is formally a priority, but the legislation that would 
ensure quality in this area is proceeding very slowly. 
External quality assessment and inspections commissioned 
by the Ministry of Health are rarely used. Supervision 
of quality in primary care is fragmented and poorly 
coordinated. Family physicians (FPs) are more involved in 
unofficial and ad hoc forms of quality improvement than 
in formalised procedures. There are formal instruments 
for assessing quality, such as attestation of physicians, 
voluntary certification and accreditation, and mandatory 
licensing of physicians or nurses, but quality of primary 
health care has not yet been systematically assessed 
by quality indicators (10), despite the fact that a set 
of quality indicators was developed for cardiovascular 
prevention (11, 12) and that there is ample scientific 
evidence in this field in the literature (1, 5-7, 13-17)
In 2011, an ongoing pilot project at the primary care level 
in Slovenia was launched with the support of the Ministry 
of Health. It introduced a new model of family medicine 
practice where the family physicians’ working team 
(consisting of one FP and one nurse with a baccalaureate 
degree – a practice nurse) was extended by a nurse 
practitioner working four hours a day or 0.5 full-time 
equivalents. The nurse practitioner is responsible for 
preventive activities (screening for and counselling on 
cardiovascular risk factors, diabetes, depression, chronic 
obstructive pulmonary disease (COPD), hypertension, and 
smoking and management of smoking and risky alcohol 
consumption) and routine management of patients with 
stable chronic diseases (COPD, asthma, hypertension, 
diabetes, benign enlargement of prostate, depression, 
osteoporosis and coronary heart disease) (18, 19). 
Preventive activities can also be carried out by physicians 
in terms of a comprehensive approach to the patients, but 
in this model of family medicine practice they are mainly 
performed by the nurse practitioners.
As part of this project, a list of quality indicators was 
introduced in order to monitor the work of family medicine 
practices participating in the project. The list included 35 
quality indicators, of which nine were structure quality 
indicators, 23 were process quality indicators, and three 
were outcome quality indicators (1, 20). 
The electronic database for collecting quality indicators 
was established at the beginning of 2015. Before that, 
data entry was manual and carried out by each practice 
itself into the Excel spreadsheets. There are five IT 
providers for family practices in Slovenia with their own 
data extraction systems, and data had to be gathered in 
one electronic database, which presented some problems 
at the start.
Hypertension and diabetes were among eight chronic 
diseases which were monitored by quality indicators, and 
are at the same time among the most common chronic 
diseases encountered in family medicine. 
The aim of this article was to assess the differences in 
the values of the selected quality indicators between 
new model family medicine practices with different 
characteristics. The objective of this article was to 
conduct a relationship analysis between values of two 
selected indicators and some important characteristics of 
practices.
2 METHODS
We included all family medicine practices that were 
participating in the project in December 2015 as the 
source of data. The data were gathered from automatic 
electronic reports on quality indicators provided monthly 
by each individual family medicine practice. The data 
are stored in a common electronic database which can 
be used by project managers. For the purpose of the 
analysis, the following data were extracted: gender and 
specialisation of the family physician, status (public 
servant/self-contracted), duration of participation in 
the project, region of Slovenia, number of inhabitants 
covered by the family physician, name of the information 
technology (IT) provider, and quality indicators. The 
units of observation were family medicine practices with 
their staff (a physician, a practice nurse and a nurse 
practitioner).
At the end of 2015, there were 35 different quality 
indicators that family medicine practices reported on 
(20). For the purpose of this study, we chose one quality 
indicator from each different type (structure, process and 
outcome quality indicator (1) (Table 1). 
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Table 1. Quality indicators for diabetes and hypertension.
1 Prevalence of diabetes in Slovenia which is 6% (21)
2 The expression “registered” describes the number of patients with diabetes/hypertension on the patient list of each family medicine     
  practice
Quality indicator Calculation formula Type of quality 
indicator
Quality standard Mean value (SD) Median
Statistical analysis was carried out using IBM SPSS Statistics 
version 22.0 (Armonk, NY: IBM Corp.). We performed 
multivariate analysis with general linear models. We set 
p<0.05 as the limit for statistical significance.
We used the observed outcome variables and explanatory 
factors in the analyses. The observed outcome variables 
were: 1) the value of the quality indicator “List of patients 
with diabetes”; 2) the value of the quality indicator 
“Percentage of patients with diabetes with measured 
HbA1C once a year” (continuous variable); and 3) the 
value of the quality indicator “Percentage of patients 
with hypertension with a systolic blood pressure 140/90 
mmHg or lower” (continuous variable). Higher levels of 
observed outcome variables indicated a higher quality of 
work.
The explanatory factors were: 1) gender (nominal 
variable: male/female); 2) specialisation of family 
physician (nominal variable: has specialisation in family/
general medicine/does not have specialisation in family/
general medicine; 3) status of family medicine practice 
(nominal variable: public servant/self-contracted); 4) 
duration of participation in the project (continuous 
variable); 5) region of Slovenia (nominal variable: Celje, 
Koper, Krsko, Kranj, Ljubljana, Maribor, Murska Sobota, 
Nova Gorica, Novo Mesto, Ravne na Koroskem); 6) area 
covered by the practice (nominal variable: urban/rural); 
and 7) name of IT provider (nominal variable: IT No. 1, IT 
No. 2, IT No. 3, IT No. 4, IT No. 5). The variable “Urban/
rural area” was determined according to the definition of 
rural areas in Slovenia provided by the Statistical Office 
of Slovenia, which defines rural areas as those with less 
than 5,000 inhabitants.
The dummy variables created for the multivariate 
analyses were gender (reference category: male gender), 
the region of Slovenia (reference category: Ravne na 
Koroskem), the IT provider (reference category: IT 
provider No. 5), specialisation (reference category: no 
specialisation), area (reference category: urban), and 
status (reference category: public servant)  and were 
created by a simple coding. 
3 RESULTS
3.1 Sample Description
Out of 584 family medicine practices that were included in 
this project at the end of 2015, 568 (97.3%) had complete 
data and could be included in this analysis (Table 2). 
The mean duration of participation in the project was 
28.7±18.7 months, with a median of 33.0 months. The 
mean age of the family physicians was 51.4±9.0 years, 
median 53.0.
List of patients with 
diabetes
Percentage of patients with 
diabetes with measured 
HbA1C once a year
Percentage of patients with 
hypertension with a systolic 
blood pressure 140/90 
mmHg or lower
Number of diabetic patients/
(Number of registered patients * 
0.061) * 100
Number of patients with diabetes 
with measured HbA1C at least 
once a year/number of registered 
diabetic patients2 * 100
Number of patients with 
hypertension with blood pressure 
140/90 mmHg or lower/number 
of registered3 patients with 
hypertension * 100
Structure
Process
Outcome
0
80
50
84.2 (53.6)
25.6 (22.3)
18.2 (16.3)
84.0
21.2
14.3
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Table 2.
Table 3.
Characteristics of family medicine practices included in 
the project.
Characteristics of family medicine practices included in the project.
Region
Celje
Koper
Krsko
Kranj
Ljubljana
Maribor
Murska Sobota
Nova Gorica
Novo Mesto
Ravne na Koroskem
Gender of the physician
Male
Female
Specialisation of the physician
General medicine
Family medicine
Other specialities
No specialisation
Status
Public servant
Self-contractor
IT provider
No. 1
No. 2
No. 3
No. 4
No. 5
Area
Urban
Rural 
Gender
Female
Male
Status
Self-contractor
Public servant
IT provider
No. 1
No. 2
No. 3
No. 4
No. 5
71 (12.5)
34 (6.0)
20 (3.5)
63 (11.1)
148 (26.1)
84 (14.8)
37 (6.5)
44 (7.7)
37 (6.5)
30 (5.3)
132 (23.2)
436 (76.8)
313 (55.1)
195 (34.3)
1 (0.2)
59 (10.4)
426 (75.0)
142 (25.0)
159 (28.0)
6 (1.1)
210 (37.0)
90 (15.8)
97 (17.1)
459 (80.8)
109 (19.2)
0.17
reference
6.47
reference
19.03
12.18
8.88
21.85
reference
4.66
5.22
8.13
19.57
6.53
7.79
-8.97, 9.30
-3.76, 16.70
3.10, 34.96
-26.18, 50.55
-3.92, 21.67
6.57, 37.12
0.972
0.215
0.019
0.534
0.174
0.005
Characteristic
Explanatory variables
Number (%)
Regression coefficient Standard Error Upper and lower 95% 
confidence Interval
p
3.2 Quality Indicator ‘List of Patients with Diabetes’
The mean value of this quality indicator was 84.2±53.6, 
with a median of 84.0 (Table 1).
The results of a multivariate analysis showed that the 
variables ‘IT provider No. 1 and 4’ and ‘Duration of 
participation in the project’ were significantly correlated 
with a higher value of this quality indicator, and ‘Working 
in the Maribor region’ was significantly correlated with a 
lower value of this quality indicator (Table 3).
For continuous variables regression coefficients indicate 
the change of the observed variable with each increasing 
unit of explanatory variable.
For categorical variables regression coefficients indicate 
the changes of the observed variable in comparison to a 
reference category.
3.4 Quality Indicator “Percentage of Patients with 
Diabetes with Measured HbA1C Once a Year”
The mean value of this quality indicator was 25.6±22.3, 
with a median of 21.2. 
The results of a multivariate analysis showed that the 
variable ‘Duration of participation in the project’ was 
significantly correlated with a higher value of this quality 
indicator, and ‘IT provider No. 3 and 4’ were significantly 
correlated with a lower value of this quality indicator 
(Table 4).
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Table 4. Multivariate analysis for higher value of the quality indicator ‘Measured HbA1C in patients with diabetes at least once a year’.
Gender
Female
Male
Status
Self-contractor
Public servant
IT provider
No. 1
No. 2
No. 3
No. 4
No. 5
Area
Rural
Urban
Specialisation
General Practice
Family Medicine
No specialisation
Area
Rural
Urban
Specialisation
General Practice
Family Medicine
No specialisation
Region
Celje
Koper
Krsko
Kranj
Ljubljana
Maribor
Murska Sobota
Nova Gorica
Novo Mesto
Ravne na Koroskem
Age (years)
Duration of participation 
in the project
1.60
Reference
1.03
reference
-6.27
-12.00
-6.05
-14.58
reference
-0.73
reference
5.13
3.34
-2.61
reference
-2.92
-0.46
reference
-8.32
-1.99
11.18
4.02
-4.58
-35.92
-17.34
-0.40
0.37
Reference
-0.17
1.47
2.11
2.37
3.68
8.87
2.96
3.53
2.34
3.17
3.17
5.17
6.99
7.00
11.03
11.92
14.45
10.70
9.42
10.97
11.32
11.00
11.45
0.22
0.11
-2.53, 5.74
-3.61, 5.66
-13.49, 0.95
-29.38, 5.38
-11.85, -0.25
-21.50, -7.66
-5.32, 3.86
-1,07, 11.34
-2.87, 9.55
-12.74, 7.52
-16.62, 10.78
-14.17, 13.26
-29.94, 13.31
-25.36, 21.38
-17.14, 39.49
-16.95, 24.99
-23.05, 13.88
-57.42, -14.42
-39.52, 4.85
-21.95, 21.15
-22.07, 22.80
-0.61, 0.26
1.24, 1.69
0.447
0.664
0.089
0.176
0.041
< 0.001
0.757
0.105
0.292
0.614
0.676
0.948
0.451
0.868
0.439
0.707
0.627
0.001
0.126
0.971
0.975
0.435
< 0.001
Explanatory variables
Explanatory variables
Regression coefficient
Regression coefficient
Standard Error 
Standard Error 
Upper and lower 95% 
confidence Interval
Upper and lower 95% 
confidence Interval
p
p
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Region
Celje
Koper
Krsko
Kranj
Ljubljana
Maribor
Murska Sobota
Nova Gorica
Novo Mesto
Ravne na Koroskem
Age (years)
Duration of participation 
in the project
-9.28
-6.55
-4.37
-6.37
0.85
3.88
7.20
-9.18
-0.40
reference
-0.11
0.30
5.00
5.40
6.54
4.85
4.27
4.97
5.13
4.98
5.18
0.10
0.05
-19.07, 0.52
-17.14, 4.04
-17.19, 8.46
-15.87, 3.13
-7.51, 9.22
-5.86, 13.62
-2.85, 17.25
-18.94, 0.58
-10.56, 9.76
-0.31, 0.08
0.20, 0.40
0.063
0.225
0.505
0.189
0.842
0.435
0.160
0.065
0.939
0.265
< 0.001
Explanatory variables Regression coefficient Standard Error Upper and lower 95% 
confidence Interval
p
For continuous variables regression coefficients indicate 
the change of the observed variable with each increasing 
unit of explanatory variable.
For categorical variables regression coefficients indicate 
the changes of the observed variable in comparison to a 
reference category.
3.3 Quality Indicator ‘Percentage of Patients with 
Hypertension with a Systolic Blood Pressure 140/90 
mmHg or Lower’
The mean value of this quality indicator was 18.2±14.3, 
with a median of 16.3 (Table 1). 
The results of a multivariate analysis showed that the 
variables ‘Duration of participation in the project,’ 
‘Female gender,’ ‘Self-contractor,’ ‘Working in the 
Maribor region’ and ‘Having IT No. 2’ were significantly 
correlated with a higher value of this quality indicator. 
Variables ‘IT provider No. 3’ and ‘IT provider No. 4’ were 
significantly correlated with lower values of this quality 
indicator (Table 5). 
Table 5. Multivariate analysis for higher value of the quality indicator ‘Percentage of patients with hypertension with a systolic blood 
pressure 140/90 mmHg or lower.’
Gender
Female
Male
Status
Self-contractor
Public servant
IT provider
No. 1
No. 2
No. 3
No. 4
No. 5
3.36
Reference
3.44
reference
-0.77
17.59
-6.64
-10.58
reference
1.48
1.65
2.57
6.20
2.07
2.47
0.47, 6.25
0.20, 6.68
-5.82, 4.27
5.45, 29.74
-10.69, -2.58
-15.42, -5.74
0.023
0.037
0.764
< 0.001
0.001
< 0.001
Explanatory variables Regression coefficient Standard Error Upper and lower 95% 
confidence Interval
p
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Area
Rural
Urban
Specialisation
General Practice
Family Medicine
No specialisation
Region
Celje
Koper
Krsko
Kranj
Ljubljana
Maribor
Murska Sobota
Nova Gorica
Novo Mesto
Ravne na Koroskem
Age (years)
Duration of participation 
in the project
-1.65
reference
2.05
-0.95
reference
-2.48
1.78
-1.15
-3.76
1.65
10.77
5.33
-1.65
-0.43
reference
-0.06
0.15
1.64
2.21
2.22
3.49
3.78
4.57
3.39
2.98
3.47
3.58
3.48
3.62
0.07
0.04
-4.86, 1.56
-2.29, 6.39
-5.29, 3.39
-9.32, 4.37
-5.62, 9.18
-10.11, 7.82
-10.40, 2.88
-4.19, 7.50
3.96, 17.57
-1.69, 12.36
-8,47, 5.18
-7.54, 6.67
-0.20, 0.07
0.08, 0.23
0.314
0.354
0.668
0.478
0.637
0.802
0.267
0.579
0.002
0.137
0.636
0.905
0.368
< 0.001
Explanatory variables Regression coefficient Standard Error Upper and lower 95% 
confidence Interval
p
For continuous variables regression coefficients indicate 
the change of the observed variable with each increasing 
unit of explanatory variable.
For categorical variables regression coefficients indicate 
the changes of the observed variable in comparison to a 
reference category.
4 DISCUSSION
This study showed that the structure quality indicator was 
achieved for diabetes (list of diabetic patients). However, 
it also showed that the values of the process and outcome 
indicators were low, which indicates that the quality of 
management of patients with diabetes and hypertension 
could be improved. The levels of the selected quality 
indicators were associated with several features, most 
commonly with the duration of participation in the 
project, the region of Slovenia where the practice was 
located, and the IT provider used by the practice.
4.1 The Assessment of Quality of the Management of 
Patients with Diabetes and Hypertension
High values of structure quality indicators are an important 
sign that the conditions for measuring quality have been 
established. On the other hand, lower levels of process 
quality indicators were found and could be attributed to 
several reasons. The lack of continuous quality control 
with feedback could be one of them; the project continued 
without continuous data analysis, feedback to practices 
on the quality of their work, or benchmarking (22), and no 
staff were employed to carry out these tasks.
It is also possible that adherence to the guidelines was low. 
A recent study from Slovenia showed that the introduction 
of this different model of chronic patient management in 
family medicine improved the process of quality of care, 
but the desired level of quality has not yet been achieved 
(23), which probably points to low adherence to the 
guidelines. Other studies have also shown that primary 
care physicians’ adherence to hypertension and diabetes 
guidelines is low (24-27). For example, adherence to 
hypertension guidelines was found to be between 10 and 
50% (24, 25). On the other hand, another study showed 
that HbA1C was measured in almost all the patients (26). 
It is also possible that the selection and development 
of the quality indicators themselves was not optimal. 
The development of quality indicators must be based 
on a systematic evidence-based approach, and expert 
consensus and guidelines should be considered. The 
indicators should be acceptable, feasible, reliable, 
sensitive to change, and valid (16). The quality indicators 
in our project have not yet been evaluated according to 
these features, and therefore it could be possible that the 
low levels of quality indicators are associated with their 
suboptimal nature. 
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4.2 Associations between Quality Indicators and 
Characteristics of Providers
The most important variable that was shown to be 
associated with higher levels of quality indicators was the 
duration of participation in the project. This indicates 
that the practical introduction of quality indicators in the 
everyday work of practices might be associated with some 
problems that could influence the quality. These problems 
are yet to be recognised. The region of practices was 
also recognised as important. Some previous data from 
Slovenia indicate that there are differences between 
regions in terms of quality (10). Which factors contribute 
to that is unknown and a subject for further studies. In 
addition, IT providers proved important in our research. 
Ensuring quality of data during electronic data capture 
is always a problem, and several ways of reducing errors 
must be applied (28, 29). There are no reports about the 
quality of data gathering in this project, and it therefore 
seems that there are some problems which still need to 
be recognised and addressed. 
The quality indicator ‘List of patients with diabetes’ 
indicates the prevalence of diabetes in registered patients 
of family medicine practices in Slovenia. It should be 
mentioned here that its value could also be affected by 
the actual prevalence of diabetes in the region of Slovenia 
(30), and does not only depend on the quality of work.
Other factors can also contribute to the quality 
management of chronic patients and were not included 
in this study. These might include systemic factors, 
reimbursement, service organisation and capacity, 
cultural factors, disease epidemiology, practice systems 
in terms of incentives, practice information capacity, 
access, the use of teams in quality policy, detection of 
quality and safety problems, staff and patient safety, 
inclusion of patients’ perspectives, and the length of 
consultations (31-34). These factors should be considered 
when studying this topic further.
4.3 Limitations of the Study
We chose only a few quality indicators because we 
focused on the management of chronic diseases and not 
on their prevention. This was done to ensure the clarity 
and focus of the study. It could, however, be possible that 
by excluding some quality indicators we overlooked some 
other differences.
The other problem is the quality of the data, as the 
electronic database was only established in 2015; our 
analysis was carried out at the end of 2015, and we can, 
therefore, anticipate that some technical problems had 
not yet been resolved. Therefore, the reliability of the 
data might not be as good as if we had done the research 
later.
Our study did not include other factors that could 
influence the quality of management of chronic diseases, 
especially the characteristics of other team members, 
particularly nurse practitioners. Since nurse practitioners 
are very involved in the management of chronic patients, 
the inclusion of their characteristics could have helped 
us to build a more comprehensive view of this matter, 
and produced more reliable statistical models. Other 
limitations are the exclusion of patient data, and the 
cross-sectional nature of this study, which prevents us 
from detecting causality. This would further increase the 
comprehensibility of the results.
In our study, we did not analyse the characteristics of 
those family medicine practices that did not participate 
in the project. Therefore, we do not know if they differ 
significantly from those included in the study. 
4.4 Theoretical and Practical Implications of the Study
The study showed that the quality assessment was a 
challenge, because the values of the quality indicators 
were set empirically while preparing the new model 
of family medicine practices in Slovenia. The quality 
indicators should be re-evaluated and changed if 
necessary according to the established methodology (16). 
It was also recognised that expert supervision at the 
location is necessary to assess the process of work of the 
family medicine team at different levels (e.g. following 
protocols, regularly measuring the parameters of chronic 
diseases, recording them in the electronic database, and 
their reporting and analysis), and to discuss the obstacles 
directly with care providers. Continuous quality control and 
benchmarking should be established in order to improve 
the quality of chronic patient management in Slovenian 
family medicine practices. The study also indicated the 
need for collaboration between different professionals (e. 
g. IT specialists and health care providers) to adopt the IT 
system to fully support patient management. The quality 
indicators should be a basis for financing the practices 
according to quality standards. It may also be important 
to inform each team about their quality results every 
month, and ask for their feedback.
4.5 Suggestions for Future Research in the Field
The regional differences in quality which emerged from 
our analysis should be further explored. Other possible 
factors that could contribute to quality should be studied. 
The quality indicators should be reviewed each year, 
which would allow a comparison of indicators between 
two points in time in the same practice, or between 
practices using the new approach and those using the 
classical approach, and to observe the trend of change 
according to the existing circumstances.
10.1515/sjph-2017-0029 Zdr Varst 2017; 56(4): 211-219
219
5 CONCLUSION
The first analysis of data on quality indicators for diabetes 
and hypertension in this primary care project pointed 
out the problems which are currently preventing higher 
quality of chronic patient management at the primary 
health care level. There are problems with the quality 
of data, especially with the IT support, which should be 
recognised and eliminated. 
ACKNOWLEDGEMENTS
We thank Barbara Šturm and Sara Peklaj from the project 
office for helping us in gathering the data.
CONFLICTS OF INTEREST
The authors declare that no conflicts of interest exist.
FUNDING
The authors acknowledge the financial support from the 
Slovenian Research Agency (research core funding No. P3 
0339). 
ETHICAL APPROVAL
Ethical approval was not sought as no patients were 
involved in the study. The values of quality indicators 
were extracted from the whole pool of data and other 
data were gathered from the project database. The data 
on providers were anonymous. 
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