PATIENT SAFETY IN FAMILY MEDICINE THROUGH THE EYES  
OF PEOPLE WITH CHRONIC CONDITIONS IN SLOVENIA
VARNOST BOLNIKOV V DRUŽINSKI MEDICINI – POGLED BOLNIKA
Staša GRABAR 1,2*  , Zalika KLEMENC-KETIŠ 1,3,4 
1University of Maribor, Faculty of Medicine, Department of Family Medicine, Taborska ulica 8, 2000 Maribor, Slovenia
2Community Health Centre Murska Sobota, Grajska ulica 24, 9000 Murska Sobota, Slovenia
3University of Ljubljana, Faculty of Medicine, Department of Family Medicine, Poljanski nasip 58, 1000 Ljubljana, Slovenia
4 Community Health Centre Ljubljana, Metelkova ulica 9, 1000 Ljubljana, Slovenia
Received: Oct 17, 2025
Accepted: Apr 14, 2026
Original scientific article
*Correspondence: stasa.vodicka@gmail.com
Published under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
© 2026 The Authors
10.2478/sjph-2026-0012
94
Grabar S, Klemenc-Ketiš Z. Patient safety in family medicine through the eyes of people with chronic conditions in Slovenia.  
Zdr Varst. 2026;65(2):94-103. doi: 10.2478/sjph-2026-0012.
Grabar S, Klemenc-Ketiš Z. Patient safety in family medicine through the eyes of people with chronic conditions in Slovenia.  
 Slovenian Journal of Public Health. 2026;65(2):94-103. doi: 10.2478/sjph-2026-0012.
ABSTRACT
Keywords: 
Patient safety
Family medicine
Primary care
Polypharmacy
Communication
PaRIS
Slovenia
IZVLEČEK
Ključne besede: 
varnost bolnikov
družinska medicina
primarno zdravstveno 
varstvo
polifarmacija
komunikacija
PaRIS
Slovenija
Introduction
Patient safety is a key dimension of healthcare quality, although most research has focused on hospital settings. 
This study analysed patient-reported experiences related to safety in Slovenian family medicine using data from 
the OECD PaRIS survey.
Methods
A cross-sectional study was conducted in 2023 among 70 family medicine practices in Slovenia. Data were 
collected using two validated questionnaires: the PaRIS Primary Care Patient Questionnaire (PaRIS-PQ) and the 
Primary Care Practice Questionnaire (PaRIS-PCPQ). Items Q69–Q75 of the PaRIS-PQ were analysed to assess 
experiences related to the use of medicines, medication review, repetition of information, adverse events, 
encouragement to express concerns, and barriers to care. Descriptive statistics, chi-square tests, correlation 
analysis, and binary logistic regression were used in data analysis.
Results
Respondents with chronic conditions totalled 2,133 (mean age 63.1 ± 10.9 years; 62.7% female). Polypharmacy (≥ 
3 medications) occurred in 27% of respondents; only 19.7% had received a medication review in the previous 12 
months. Seventeen percent reported experiencing at least one adverse event. Significant predictors of reported 
adverse events included repeated requests for personal medical information (p < 0.001), lack of encouragement 
to express concerns (p = 0.008), and transport barriers to accessing care (p = 0.024). The regression model 
explained a small proportion of the variance (Nagelkerke R² = 0.02).
Conclusions
Patient safety in Slovenian family medicine shows both strengths and areas requiring improvement. Communication 
processes, access barriers, and coordination of information appear to play an important role in perceived safety. 
Strengthening medication review practices and improving digital interoperability across healthcare settings may 
contribute to safer care in family medicine. Patient-reported measures such as PaRIS provide valuable insights 
for monitoring and improving patient safety in family medicine.
Uvod
Varnost bolnikov je ključna razsežnost kakovosti zdravstvene oskrbe, vendar se je večina dosedanjih raziskav 
osredotočala predvsem na bolnišnično okolje. Ta raziskava analizira izkušnje bolnikov, povezane z varnostjo v 
slovenski družinski medicini, na podlagi podatkov raziskave OECD PaRIS.
Metode
Leta 2023 je bila izvedena presečna raziskava v 70 ambulantah družinske medicine v Sloveniji. Podatki so bili 
zbrani z dvema validiranima vprašalnikoma: PaRIS vprašalnikom za bolnike v primarnem zdravstvu (PaRIS-PQ) 
in vprašalnikom za ambulante primarnega zdravstva (PaRIS-PCPQ). Za analizo so bila uporabljena vprašanja 
Q69–Q75 iz vprašalnika PaRIS-PQ, ki obravnavajo uporabo zdravil, pregled terapije, ponavljanje zdravstvenih 
informacij, neželene dogodke, spodbujanje bolnikov k izražanju skrbi ter ovire pri dostopu do zdravstvene 
oskrbe. Podatki so bili analizirani z deskriptivno statistiko, hi-kvadrat testom, korelacijsko analizo in binarno 
logistično regresijo.
Rezultati
V raziskavo je bilo vključenih 2133 pacientov s kroničnimi boleznimi (povprečna starost 63,1 ± 10,9 let; 62,7 
% žensk). Polifarmacija (≥ 3 zdravila) je bila prisotna pri 27 % anketirancev, medtem ko je le 19,7 % bolnikov 
poročalo o opravljenem pregledu terapije v zadnjih 12 mesecih. Sedemnajst odstotkov bolnikov je poročalo o vsaj 
enem neželenem dogodku. Pomembni napovedniki poročanih neželenih dogodkov so bili ponavljajoče zahteve po 
posredovanju osebnih zdravstvenih informacij (p < 0,001), pomanjkanje spodbujanja bolnikov k izražanju skrbi 
(p = 0,008) ter transportne ovire pri dostopu do zdravstvene oskrbe (p = 0,024). Regresijski model je pojasnil 
majhen delež variance (Nagelkerke R² = 0,02).
Zaključki
Varnost bolnikov v slovenski družinski medicini kaže tako prednosti kot tudi področja, ki zahtevajo izboljšave. 
Komunikacijski procesi, ovire pri dostopu do zdravstvene oskrbe ter usklajevanje informacij imajo pomembno 
vlogo pri zaznani varnosti. Krepitev sistematičnega pregleda terapije in izboljšanje digitalne interoperabilnosti 
med zdravstvenimi sistemi bi lahko prispevala k večji varnosti v primarnem zdravstvu. Bolnikom poročani 
kazalniki, kot je raziskava PaRIS, ponujajo pomemben vpogled v spremljanje in izboljševanje kakovosti in 
varnosti v družinski medicini.
1 INTRODUCTION
Patient safety is widely recognised as a core component of 
healthcare quality and an essential dimension of effective 
health systems. Although patient-safety research has 
historically focused on hospitals, evidence shows that 
primary care also faces important safety challenges, 
including delayed diagnoses, communication failures, 
incomplete medication reviews, and barriers to access. 
Despite its central role in health systems, patient safety in 
primary care remains less extensively studied than safety 
in hospital settings (1, 2).
According to the World Health Organization (WHO), about 
10% of patients globally experience healthcare errors 
(3). In primary care, risks arise from missed diagnoses, 
prescribing errors, communication failures, and limited 
access to services (3–6). The WHO’s Safer Primary Care 
manual highlights that safety in these settings requires a 
distinct approach from hospitals (3).
Diagnostic errors are leading hazards in family medicine (6, 
7). Prescribing errors also pose substantial risks; although 
digital tools reduce serious medication mistakes by over 
50%, prescribing remains a key source of harm (8, 9). 
Preventable drug-related adverse events occur in about 3% 
of patients, with one-quarter causing serious harm (10). 
Globally, medical errors lead to millions of preventable 
injuries each year (11–13). The landmark To Err Is Human 
report estimated 44,000–98,000 US deaths annually from 
medical errors (14), sparking the modern safety movement 
(15, 16). In primary care, safety is hindered by fragmented 
information systems and rising workloads (17–19). Physician 
burnout increases the risk of errors (20), while vulnerable 
populations—particularly older adults and people with 
chronic conditions—face higher exposure (21, 22).
In Slovenia, research shows a positive association between 
safety climate and outcomes, although regional and 
institutional variation persists (23, 24). Tools such as 
the Safety Attitudes Questionnaire (SAQ-SF) (25) and the 
Medical Office Survey on Patient Safety Culture (MOSPSC) 
have been used. A recent study reported an overall safety 
culture score of 59.6%, with strong domains in information 
exchange (93.5%) and organisational learning (90.2%), 
but weaknesses in work pressure (10.7%) and leadership 
support (27.1%) (26). 
In recent years, patient-reported outcome measures 
(PROMs) and patient-reported experience measures (PREMs) 
have gained importance as complementary indicators 
of healthcare quality and safety (27). The OECD Patient-
Reported Indicator Surveys (PaRIS) programme provides a 
unique opportunity to assess the experiences and outcomes 
of care from the perspective of people with chronic 
conditions across countries (23, 30–32). To our knowledge, 
patient-reported safety indicators from the PaRIS survey 
have not yet been analysed in Slovenia using this approach.
95
The aim of this study was therefore to examine patient-
reported safety indicators in Slovenian family medicine 
among people with chronic conditions, with particular 
attention to medication burden, medication review, 
communication and information continuity, and barriers 
to care. The study also explored predictors of reported 
adverse events in order to identify areas for improvement 
in the safety of family medicine practice.
2 METHODS
2.1 Study design and setting
This cross-sectional study was part of the international 
Patient-Reported Indicator Surveys (PaRIS) programme, 
coordinated by the Organization for Economic Co-operation 
and Development (OECD) (23). The Slovenian part of the 
study was conducted in 2023 at 70 randomly selected 
family medicine practices, representing various geographic 
and demographic areas (28–30). The OECD developed the 
overall PaRIS survey design and conceptual framework 
in consultation with several international collaborators, 
including the Netherlands Institute for Health Services 
Research (NIVEL), Ipsos MORI, the University of Exeter, the 
Avedis Donabedian Institute, and OptiMedis AG (23).
2.2 Participants
2.2.1 Providers
All active family medicine practices in Slovenia (N = 
978) were eligible for inclusion according to the national 
register kept by the Health Insurance Institute of Slovenia. 
Practices that provided care exclusively to children or to 
institutionalised patients only were excluded. Participation 
was voluntary and unincentivised.
2.2.2 Patients
Eligible participants were community-dwelling adults aged 
45 years or older with at least one chronic condition and 
at least one contact with their family physician in the 
previous 6 months, including face-to-face, telephone, or 
online contact. People with severe cognitive impairment, 
terminal illness, or other disabling conditions preventing 
participation were excluded. For each participating 
practice with electronic medical records, a random list of 
300 eligible patients was generated.
2.3 Instruments 
Two validated OECD PaRIS instruments were used.
At the practice level, the Primary Care Practice Questionnaire 
(PaRIS-PCPQ) was administered. The full instrument contains 
40 items covering organisational characteristics, workforce 
composition, care coordination, chronic care management, and 
the use of electronic health information systems (31). For the 
purposes of this analysis, the following PCPQ items were used:
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(1) practice location,
(2) practice type,
(3) electronic exchange of patient information with 
external providers,
(4) review of indicators of patient care, and
(5) routine development of patient care plans for groups 
of patients.
At the patient level, the Primary Care Patient Questionnaire 
(PaRIS-PQ) was used. The full instrument comprises 121 
items addressing sociodemographic characteristics, health 
behaviours, health status, patient-reported outcomes, and 
patient experiences of care (32). In the present study, 7 
patient-safety-related items from the PaRIS-PQ (Q69–Q75) 
were analysed, covering:
• number of medications taken regularly,
• medication review in the previous 12 months,
• repetition of medical information,
• reported adverse events,
• whether respondents were encouraged to express 
concerns,
• foregoing care due to transport difficulties, and
• foregoing care due to medical costs.
Both instruments were translated into Slovenian and 
culturally adapted using the TRAP-D process (Translation, 
Review, Adjudication, Pretesting, and Documentation) to 
ensure linguistic accuracy and conceptual equivalence (29).
2.4 Data collection and protection 
Data collection took place from April to June 2023. 
Participation was voluntary and anonymous. The study 
adhered to the General Data Protection Regulation (EU) 
2016/679. All responses were anonymised before analysis, 
and no personally identifiable data were collected or 
stored.
2.4.1 Providers
Participating providers received detailed instructions, 
consent forms, and unique identification codes to maintain 
confidentiality and to link provider- and patient-level data. 
Questionnaires were administered electronically or on 
paper, depending on participant preference.
2.4.2 Patients
Participants received clear information about the study’s 
purpose, a consent form, and a unique identification code to 
protect their privacy and to link their responses anonymously 
to their healthcare provider. Participants could complete the 
questionnaire either electronically or on paper, depending 
on their preference. Invitations used a multimodal approach: 
via email, SMS or postal mail. Non-respondents received a 
total of two reminders within a three-week period.
2.5 Variables 
The primary outcome variable was reported adverse 
events derived from PaRIS-PQ item Q72. This item asked 
respondents how often they had experienced harmful 
or adverse events related to their care. For regression 
analysis, this variable was dichotomised into the presence 
of adverse events versus no adverse events, as specified 
below.
Independent variables at the patient level included:
• number of regularly taken medications,
• medication review within the previous 12 months,
• repetition of medical information to healthcare 
providers,
• lack of encouragement for respondents to express their 
concerns,
• barriers to care due to transport difficulties, and
• barriers to care due to medical costs.
• At the provider level, independent variables included:
• practice location (urban/rural),
• practice type (public/private concession practice), and
• electronic exchange of patient information with 
external healthcare providers.
2.6 Statistical analysis 
Descriptive statistics were used to summarise provider- 
and patient-level characteristics, including frequencies, 
percentages, means, and standard deviations, as 
appropriate. Associations between categorical variables 
were examined using chi-square tests, and associations 
between ordinal patient-safety indicators were assessed 
using Spearman’s rank correlation coefficients.
The primary outcome for multivariable analysis was 
reported adverse events (Q72). For binary logistic 
regression, responses were dichotomised as follows: 
respondents reporting adverse events “always”, “often”, 
or “sometimes” were classified as having experienced 
an adverse event, whereas those responding “rarely” or 
“never” were classified as not having experienced an 
adverse event. Responses marked as “not suitable for me” 
or missing were excluded from the regression model.
Binary logistic regression was used to identify predictors of 
reported adverse events. Independent variables included 
the number of regularly taken medications, medication 
review within the previous 12 months, repetition 
of medical information, lack of encouragement for 
respondents to express concerns, barriers to care due to 
transport difficulties, and barriers to care due to medical 
costs. Results are presented as regression coefficients (B), 
standard errors (SE), Wald chi-square statistics, p-values, 
odds ratios (ORs), and 95% confidence intervals (CIs).
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Because respondents were clustered within practices, 
a multilevel mixed-effects logistic regression model 
with a random intercept for practice was applied in 
accordance with OECD PaRIS analytic procedures. Model 
fit was assessed using the model chi-square statistic and 
Nagelkerke R². Statistical significance was set at p < 0.05. 
Analyses were performed in SPSS version 31.
2.7 Ethical considerations 
The study was conducted in accordance with the principles 
of the Declaration of Helsinki and approved by the National 
Medical Ethics Committee of the Republic of Slovenia (No. 
0120-260/2021/3). All participants provided informed 
consent before inclusion in the study.
3 RESULTS
3.1 Demographic characteristics of the participants
3.1.1 Providers
Seventy family medicine practices with at least one registered 
person with a chronic condition took part in the study. Table 
1 presents the distribution of provider-level characteristics 
among participating family medicine practices.
3.1.2 Patients
Overall, 2,133 respondents with at least one chronic 
condition returned the questionnaire, representing 64.6% 
of all respondents in the Slovenian PaRIS sample. Table 
2 presents the distribution of patient-level demographic, 
socioeconomic, and lifestyle characteristics among 
respondents with chronic conditions who participated in 
the study.
Practice location 
Type of practice 
Electronic exchange  
of patient information
Review of indicators  
of patient care
Routine development of patient care 
plans for groups of patients
Sex 
Female 
Male
Age (years) categories 
45–54 
55–74 
75 +
Higher education 
Yes 
No
Employment 
Yes 
No
Income 
Low 
Medium 
High
Living place 
Urban 
Rural
Living with other people 
Yes 
No
Description N (number of practices)
N (number 
of practices)
%
%
Variables
Variables
Urban 
Rural
Public 
Private
Yes 
No
Yes 
No
Yes 
No
49 
21
60 
10
38 
32
44 
26
37 
33
 
1268 
754
 
505 
1355 
271
 
1247 
774
 
886 
1133
 
758 
597 
403
 
1094 
923
 
1402 
515
70.0 
30.0
85.7 
14.3
54.3 
45.7
62.9 
37.1
53.6 
46.4
 
62.7 
37.3
 
23.7 
63.6 
12.7
 
61.7 
38.3
 
43.9 
56.1
 
43.1 
34.0 
22.9
 
54.2 
45.8
 
73.1 
26.9
Characteristics of providers.
Characteristics of patients.
Table 1.
Table 2. 3.2 Patient safety indicators
Table 3 summarises the responses from respondents 
regarding patient safety indicators, including the pattern 
of medication use, medication review by healthcare 
professionals, communication safety, adverse events, 
encouragement of respondents to express concerns, and 
access barriers such as transport and cost.
Cross-tabulation analyses showed statistically significant 
associations between medication burden and several 
patient safety indicators. Respondents taking a higher 
number of medications were more likely to report having 
had a medication review, to report repeating their 
medical information, and to report adverse events. They 
were also more likely to report barriers to care related to 
transport and costs (all p < 0.001). These findings suggest 
that respondents with a greater medication burden may 
also face greater safety-related vulnerability.
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Number of medications regularly taken 
 
 
 
 
Medication review in the last 12 months
 
 
Repetition of medical information
 
 
 
 
Frequency of adverse events
 
 
 
 
 
Encouragement to express concerns
 
 
 
 
 
Foregoing care due to transport difficulties
 
 
 
 
 
Foregoing care due to medical costs 
Repetition
Adverse events
Encouragement 
Transport barriers 
Cost barriers 
No medication
1-2
3-4
5-9
≥ 10
Total
Category
Repetition Adverse events Encouragement Transport barriers Cost barriers
Medication review: 
Yes (N, %)
Medication review: 
No (N, %)
Not sure (N, %) Total (N)
N (number of practices) %Indicator
Variable
Number of 
medications
Does not take any medicine 
1-2 
3-4 
5-9 
10 or more
Yes 
No 
I’m not sure
Yes, definitely 
Yes, to some extent 
Neither 
Not at all 
I’m not sure
Always  
Often 
Sometimes 
Rarely 
Never 
Not applicable
Always  
Often 
Sometimes 
Rarely 
Never 
Not applicable
Always 
Often 
Sometimes 
Rarely 
Never 
Not applicable
Always  
Often 
Sometimes 
Rarely 
Never 
Not applicable
1.00
0.16
-0.05
0.09
0.11
0.16
1.00
-0.08
0.12
0.15
-0.05
-0.08
1.0
-0.04
-0.03
0.09
0.12
-0.04
1.00
0.22
0.11
0.15
-0.03
0.22
1.00
NA
277 (31.2%)
240 (39.9%)
119 (46.3%)
14 (43.8%)
650 (36.6%)
NA
554 (62.2%)
306 (50.8%)
120 (46.7%)
11 (34.4%)
991 (55.8%)
NA
56 (6.6%)
54 (9.0%)
18 (7.0%)
7 (21.9%)
135 (7.6%)
282
890
602
257
33
1776
282 
890 
602 
257 
33
650 
991 
135
155 
246 
849 
1439 
295
22 
157 
380 
721 
1596 
101
7 
95 
299 
457 
1967 
147
3 
33 
103 
230 
1695 
96
91 
123 
313 
400 
1700 
337
8.5 
27.0 
18.2 
7.8 
1.0
19.7 
30.0 
4.1
4.7 
7.4 
25.7 
43.6 
8.9
0.7 
4.8 
11.5 
21.8 
48.3 
3.1
0.2 
2.9 
9.1 
13.8 
59.6 
4.5
0.1 
1.0 
3.1 
7.0 
75.9 
2.9
2.8 
3.7 
9.5 
12.1 
51.5 
10.1
Distribution of responses to patient safety indicators. 
Spearman’s rank correlations between patient safety indicators.
Cross-tabulation of polypharmacy and medication review, NA – not applicable.
Table 3.
Table 5.
Table 4.
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Spearman’s correlation analyses showed that repetition 
of medical information was positively associated with 
reported adverse events (r_s = 0.16, p < 0.001). Transport 
barriers (r_s = 0.12, p < 0.001) and cost barriers (r_s = 0.15, 
p < 0.001) were also positively associated with adverse 
events. Encouragement to express concerns was negatively 
associated with adverse events (r_s = –0.08, p = 0.004). 
Although these associations were statistically significant, 
their magnitude was weak and should therefore be 
interpreted with caution (Table 5).
A multivariable logistic regression analysis was conducted 
to identify predictors of reported adverse events. The 
overall regression model was statistically significant (χ²(6) 
= 24.8, p < 0.001), although the proportion of explained 
variance was low (Nagelkerke R² = 0.02) (Table 6).
Among the examined predictors, repetition of medical 
information was significantly associated with a higher 
likelihood of reporting adverse events (B = 0.42, SE = 0.17, 
Wald χ² = 6.13, p < 0.001). Respondents who reported 
frequently having to repeat their medical information had 
approximately 1.53 times higher odds of reporting adverse 
events compared with those who did not (OR = 1.53, 95% 
CI 1.20–1.95). Similarly, lack of encouragement to express 
concerns was associated with increased odds of adverse 
events (B = 0.76, SE = 0.47, Wald χ² = 2.65, p = 0.008). 
Respondents who reported less encouragement to express 
concerns had 2.14 times higher odds of reporting adverse 
events (OR = 2.14, 95% CI 1.14–4.03). Transport barriers to 
care were also a significant predictor (B = 0.32, SE = 0.21, 
Wald χ² = 2.26, p = 0.024), indicating that respondents 
facing transportation difficulties had slightly higher odds 
of reporting adverse events (OR = 1.10, 95% CI 1.02–1.95). 
In contrast, the number of medications, medication review 
within the previous 12 months, and cost-related barriers 
to care were not statistically significant predictors in the 
adjusted model (all p > 0.05). For example, the number 
of medications taken regularly showed no significant 
association with adverse events (B = –0.28, SE = 0.34, p = 
0.492; OR = 0.75, 95% CI 0.34–1.62).
4 DISCUSSION
This study examined patient-reported safety indicators 
in Slovenian family medicine using OECD PaRIS data 
from people with chronic conditions. The findings point 
to several relevant safety challenges, particularly in 
medication-related care, information continuity, patient 
communication, and access to care. However, the strongest 
adjusted associations with reported adverse events were 
observed for repetition of medical information, lack of 
encouragement for respondents to express their concerns, 
and transport barriers, whereas medication burden itself 
was not a significant predictor after adjustment.
4.1 Medication safety and polypharmacy
Medication-related safety remains a key concern in primary 
care, especially among people with chronic conditions and 
multimorbidity. In our study, a substantial proportion of 
respondents reported regular medication use, yet only a 
minority reported having undergone a medication review 
within the previous 12 months. This finding suggests 
potential gaps in systematic medication monitoring in 
family medicine.
Polypharmacy is widely recognised as an important risk 
factor for adverse drug events, hospitalisations, and 
inappropriate prescribing, particularly in older populations. 
Numerous studies have shown that increasing medication 
burden is associated with a higher risk of medication-
related harm (1–2, 4, 10). However, in the present study 
polypharmacy was not significantly associated with reported 
adverse events in the adjusted regression model. This 
suggests that medication burden alone may not fully explain 
safety outcomes in this dataset. Instead, the relationship 
between polypharmacy and patient safety may be mediated 
by other factors, such as the quality of medication review, 
care coordination, and patient-provider communication.
These findings are consistent with previous research 
suggesting that medication-related safety risks often 
arise not only from the number of medications but also 
from system-level factors such as inadequate medication 
reconciliation and fragmented care processes (6, 18–19).
Number of medications / Polypharmacy
Medication review
Repetition of information
Encouragement to express concerns
Transport barriers
Cost barriers 
B (SE) Wald χ² p-value OR 95% CIPredictor
-0.28 (0.34)
-0.27 (0.30)
0.42 (0.17)
0.76 (0.47)
0.32 (0.21)
-0.07 (0.05)
0.69
0.83
6.13
2.65
2.26
1.66
0.492
0.406
< 0.001
0.008
0.024
0.097
0.75
0.76
1.53
2.14
1.1
0.93
0.34-1.62
0.42-1.36
1.20-1.95
1.14-4.03
1.02-1.95
0.86-1.99
Logistic regression analysis of predictors of adverse events.
Legend: SE– standard error; OR – odds ratio; C.I – confidence interval
Table 6.
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4.2 Communication and information continuity
One of the strongest predictors of reported adverse events 
in this study was the need for respondents to repeat 
medical information that should already be available in the 
medical record. This finding likely reflects fragmentation 
of health information systems and limited interoperability 
between providers. When patient information is not 
consistently accessible across care settings, the risk of 
communication errors, duplicated tests, and inappropriate 
treatment decisions may increase.
Similarly, respondents who reported less encouragement 
to express their concerns had higher odds of reporting 
adverse events. This finding highlights the importance 
of patient engagement and open communication in 
maintaining safe care processes. Previous studies have 
shown that when people feel comfortable voicing concerns 
and participating in decision-making, healthcare teams 
are more likely to detect potential safety issues early and 
prevent harm (27, 33-34).
Despite this, a large proportion of respondents reported 
that they were rarely or never encouraged to express 
concerns during consultations. This finding suggests that 
patient empowerment and shared decision-making may 
still represent an underdeveloped aspect of patient safety 
culture in primary care.
4.3 Access barriers and patient safety
Transport barriers were also associated with a higher 
likelihood of reporting adverse events. Although Slovenia 
has a largely publicly funded healthcare system, physical 
access to care may still represent an important determinant 
of patient safety, particularly for older adults and people 
with multimorbidity.
Barriers to transport may lead to delayed consultations, 
missed follow-up appointments, and reduced continuity 
of care, all of which may increase the risk of adverse 
outcomes. By contrast, cost-related barriers were 
not statistically significant predictors in the adjusted 
model, suggesting that in the Slovenian context physical 
accessibility may play a more important role than financial 
barriers in shaping patient safety experiences.
4.4 Interpretation of patient-reported adverse events
Approximately one in six respondents reported experiencing 
an adverse event at least occasionally. These results should 
be interpreted cautiously, as the survey item captures 
patient-reported experiences rather than clinically validated 
safety incidents. Patient-reported safety indicators provide 
valuable insight into perceived problems in care processes, 
but they may reflect a broader range of experiences than 
formally documented medical errors.
Nevertheless, respondent perspectives are increasingly 
recognised as an important component of safety 
monitoring, particularly in primary care where many 
safety events remain undocumented in clinical reporting 
systems (27, 33-34).
4.5 Model performance and interpretation
The regression model explained only a small proportion 
of the variance in reported adverse events (Nagelkerke 
R² = 0.02). Although this value appears low, such findings 
are common in studies examining complex social and 
behavioural phenomena such as patient safety in primary 
care. Safety outcomes are influenced by multiple interacting 
determinants at the patient, provider, organisational, and 
health-system levels, many of which were not captured in 
the present analysis.
Similarly, the correlations observed between safety 
indicators were generally weak. This pattern suggests that 
patient safety incidents in primary care are multifactorial 
and cannot be explained by individual indicators alone. 
Even so, identifying statistically significant predictors can 
still provide useful insights into areas where improvements 
in care processes may reduce safety risks.
4.6 Strengths and limitations
This study has several strengths. It uses data from the 
OECD PaRIS programme, applies internationally developed 
and culturally adapted instruments, and includes a large 
national sample of Slovenian people with chronic conditions 
in family medicine.
The study also has important limitations. First, the cross-
sectional design does not allow causal inference. Second, 
all patient-level data were self-reported, meaning that the 
adverse events captured in this study reflect respondent’ 
perceptions and experiences rather than clinically 
validated safety incidents. Third, the dichotomisation 
of the adverse-event item may have reduced nuance by 
combining different frequencies of reported events into a 
binary outcome. Fourth, the observed correlations were 
weak, and the regression model explained only a small 
proportion of the variance, indicating limited predictive 
power. Fifth, participation was voluntary, which raises 
the possibility of non-response bias, including possible 
overrepresentation of more engaged practices or 
respondents with higher health literacy. These factors may 
limit generalisability.
4.7 Implications for practice
Despite these limitations, the findings point to several 
actionable areas for improvement. First, medication 
review should be strengthened in routine family medicine 
care, especially for people with multimorbidity and higher 
medication burden. Second, digital interoperability and 
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10.2478/sjph-2026-0012
information continuity should be improved to reduce the 
need for respondents to repeat medical information across 
providers. Third, communication practices should more 
consistently support people in expressing concerns, as this 
may contribute to safer and more person-centred care. 
Finally, access barriers—particularly transport-related 
barriers—should be considered within national patient-
safety strategies, because safe care depends not only on 
clinical decisions but also on people’s ability to reach and 
navigate services.
Regular medication review, better digital information 
exchange, and incorporation of patient-reported experience 
and outcome measures into routine quality monitoring may 
represent feasible system-level steps toward improving 
patient safety in Slovenian family medicine.
5 CONCLUSION
Patient safety in Slovenian family medicine is shaped 
by multiple interacting factors. In this study, repetition 
of medical information, limited encouragement for 
respondents to express their concerns, and transport 
barriers were associated with higher odds of reported 
adverse events. Although medication burden was linked to 
several safety-related indicators in unadjusted analyses, it 
was not independently associated with adverse events after 
adjustment. These findings suggest that patient safety in 
primary care should be understood not only in terms of 
clinical complexity, but also in terms of communication 
quality, continuity of information, and access to care.
Strengthening routine medication review, improving digital 
interoperability, and supporting people’s voice within 
consultations may help improve safety in family medicine. 
OECD PaRIS data provide a valuable patient-centred 
perspective that can inform future quality improvement 
and national patient-safety policy in Slovenia.
ACKNOWLEDGEMENTS
The authors sincerely thank all participating family 
medicine practices and respondents for their valuable 
cooperation. The study was carried out as part of the 
international OECD PaRIS (Patient-Reported Indicator 
Surveys) programme.
CONFLICTS OF INTEREST
The authors declare that they have no conflicts of interest.
FUNDING
This project “Assessment of experiences and outcomes 
of healthcare for people with chronic non-communicable 
diseases in family medicine in Slovenia” was financially 
supported by the Slovenian Research Agency and the 
Ministry of Health of the Republic of Slovenia (Research 
project No. V3-2102).
ETHICAL APPROVAL
The study was approved by the National Medical Ethics 
Committee of the Republic of Slovenia (No. 0120-
260/2021/3) and conducted in accordance with the 
principles of the Declaration of Helsinki. All participants 
provided written informed consent prior to participation.
INFORMED CONSENT
Informed consent was obtained from all individual 
participants included in the study.
DATA AVAILABILITY STATEMENT
The data analysed in this study originate from the OECD 
Patient-Reported Indicator Surveys (PaRIS). Due to data 
protection regulations and the terms of the data use 
agreement with the OECD, the dataset is not publicly 
available. Access to the data may be granted upon 
reasonable request and with permission from the data 
owner.
AI USAGE STATEMENT
During the preparation of this article the author(s) used 
the GPT language model to:
• review and amend grammatical and spelling mistakes,
• ensure linguistic consistency and coherence,
• test and fine-tune the article’s wording,
• format the references.
After using this model, the author(s) reviewed and edited 
the content as needed and take full responsibility for the 
content of the publication.
PREPRINT STATEMENT
No preprint has been deposited. 
AUTHOR CONTRIBUTIONS
Staša Grabar contributed to the conceptualisation, 
statistical analysis, interpretation of results, and drafting 
of the manuscript. Zalika Klemenc Ketiš contributed to the 
study design, data collection, supervision, interpretation 
of results, and critical revision of the manuscript. Both 
authors read and approved the final version of the 
manuscript.
ORCID
Staša Grabar: 
https://orcid.org/0000-0001-6317-8971 
Zalika Klemenc-Ketiš:
https://orcid.org/0000-0002-0270-1754
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