Abstract
Background
Missed appointments (patient no-shows) are a critical challenge undermining healthcare system efficiency globally. This study aims to characterize the patient no-show phenomenon in Poland, identify factors associated with missed appointments, and propose potential measures to reduce the no-show phenomenon in the Polish healthcare system.
Material/Methods
A nationwide cross-sectional survey was conducted using computer-assisted web interviews (CAWI) from August 1 to 4, 2025. The study used quota sampling stratified by sex, age, and residence to obtain a nationwide sample of 1162 Polish adults aged 18 to 96 years. A self-prepared questionnaire was used.
Results
Among all respondents, 88.5% used healthcare services within the previous 12 months. Among healthcare users (n=1014), 14% missed appointments without cancellation. Forgetting appointments (42.3%) and communication barriers (27.5%) were identified as the primary reasons for no-shows. Text message (SMS) reminder systems received 62.5% support, while 67.5% endorsed the implementation of a penalty fee for public system non-attendance. Multivariable analysis revealed significantly (P<0.05) increased odds of no-shows among adults aged under 60 years of age, parents with children <18 years (aOR, 2.09; 95% CI, 1.28–3.40), and individuals with moderate (aOR, 1.80; 95% CI, 1.19–2.72) or poor financial status (aOR, 2.60; 95% CI, 1.47–4.60).
Conclusions
This study showed a relatively high prevalence of missed appointments in Poland. Young age, parental responsibilities, and economic constraints were associated with higher odds of no-shows. Findings support expanding digital notification systems and multi-channel communication infrastructure to reduce no-shows, rather than using punitive approaches.
Keywords: Cross-Sectional Studies, Health Facilities, Health Services Research, Patient Compliance, Poland, Surveys and Questionnaires
Introduction
Missed appointments, also called no-shows, are defined as patient non-attendance to healthcare appointments without prior cancellation and are a growing and challenging issue for healthcare systems worldwide [1–3]. Patients and physicians can both miss scheduled appointments without prior cancellation; however, physician-related no-shows appear to be incidental or insufficiently researched, whereas patient-caused no-shows have been the subject of some studies [3] and have been identified as a significant problem for healthcare systems, both in public and private sectors [3]. The consequences of patient no-shows reach health, economic, and organizational levels, affecting patients themselves by generating longer wait times and further health issues resulting from delayed treatment [4,5]. They also lead to lost appointment bookings and increased administrative work [5]. In the private health sector, they also generate unnecessary financial losses, as a physician’s time is paid even in the absence of the patient [3].
No-shows are associated with economic and organizational burdens on healthcare systems. The financial implications of these missed appointments can be substantial. In 2019, the National Health Service (NHS) in the United Kingdom (UK) reported that a no-show rate of 5% resulted in costs of 216 million GBP [6]. Data from Canada indicate that the no-show rate can reach 10% to 25%, or even 30%, depending on the region [6]. In Poland, the National Health Fund (NFZ) reported that 1.4 million appointments were missed in 2024 [7]. This figure, however, concerns only 40 types of services monitored in the public system, suggesting that the actual number of missed appointments is considerably larger [7].
Poland’s healthcare system is financed through mandatory health insurance contributions paid to the NFZ [8]. All insured citizens are entitled to the wide scope of coverage, free of charge, without a co-payment requirement for visits. The NFZ finances planned and emergency care across inpatient and outpatient health services [8]. Access to most of the services requires a referral, with the exception of 5 specialties that are available directly: psychiatry, gynecology, oncology, venereology, and dentistry [8]. Selected hospitals provide emergency care units which, in case of urgent need, are also accessible without referrals [8].
Alongside the public system in Poland, there is a private sector, whose role is mainly supplemental, offering faster access to services [8,9]. The private sector provides services mostly through primary healthcare and specialist outpatient care, although private inpatient care is also available to some extent. Access to services is provided either through private health insurance or subscriptions and is limited to the selected medical facilities in the network [9]. The widest access to health services is available through out-of-pocket payments [8,9].
In recent years, the issue of no-shows and strategies to mitigate them has become the subject of a public debate in Poland [7,10]. To date, efforts in Poland to reduce and avoid no-shows are limited to educational campaigns and some reminder tools. Since 2020, the NFZ has been sending reminders in text messages, sent 4 days prior to the appointment, but only for first-time visits [10]. Evidence shows that reminders via text messages and phone calls can be effective at reducing missed appointments [11]. One study demonstrated that implementing reminders and follow-up calls after missed appointments reduced the no-show ratio by 50% and decreased wait time significantly [12]. However, the most effective reminders are those sent the same day or the day before the appointment [13]. This also applies to phone call reminders 24 hours before the appointment [14].
Internationally, some countries, such as Norway, have introduced monetary fines to address the no-show problem [13]. However, limited research reveals mixed results on the effectiveness of introducing fines for patients who miss appointments [13]. According to one study, the out-of-pocket mechanism did not have a significant effect on reducing no-shows or appointment cancellations [15]. Additionally, introducing fines and other financial means can be controversial and face public resistance [16]. Preferred methods focus on improving availability, also through telemedicine [11,17], and ease of canceling appointments [18]. It is even recommended to overbook appointments on days with a higher risk of missed appointments [19]. Moreover, the longer the wait time for the appointment after the booking date, the higher the risk of a no-show [20].
Sending reminders is clearly one of the most recommended solutions; however, further research on the most effective methods of delivering those reminders is needed. There is also a lack of evidence on other mechanisms [5].
It is necessary to understand the reasons and motivations of patients who miss and fail to cancel their appointments. Forgetfulness is reported as one of the most common reasons for failing to cancel the appointment [21]. Other reasons for no-shows include transportation issues, changes in health status (either improvement or deterioration), and family issues [21,22]. Other factors that can increase the risk of no-shows include longer distance from the medical facility, male sex, previous history of no-shows, younger age, and lower income [13,19,23]. Waiting time is also a significant factor contributing to missed appointments, with a longer interval between scheduling an appointment and the date of the visit increasing the likelihood that patients will either experience changes in their health status or forget about the visit.
Despite the importance of this issue and its broad implications for the whole healthcare system, the number of studies on this subject is limited. Currently, in Poland, there is a lack of research on the patients’ attitudes toward no-shows and strategies for preventing this issue. In a publicly funded health system like that in Poland, no-shows contribute to longer waiting times and economic losses due to underutilization of resources (free slots for visits). Data on no-shows, their reasons, and policy preferences may inform decision-makers on measures that should be implemented to reduce this phenomenon.
This study aimed to characterize the prevalence of no-shows in Poland, identify factors associated with these missed appointments, and identify potential organizational measures to reduce the no-show phenomenon in the Polish healthcare system.
Material and Methods
Ethical Statement
This study was conducted according to the principles expressed in the Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee at the Center of Postgraduate Medical Education (Warsaw, Poland; decision No. 70/2025, as of July 16, 2025). Informed consent was obtained from all individual participants included in the study. Data protection was provided, and the authors received an anonymous data set without any personal data of respondents.
Study Design and Population
This cross-sectional survey was conducted from August 1 to 4, 2025. Data were collected using computer-assisted web interviews (CAWI). To obtain a nationwide sample of adults in Poland, a dedicated public opinion survey company (Nationwide Research Panel Ariadna [24]) was contracted to collect data on behalf of the authors, who provided the study concept, methodology, and all necessary tools.
Respondents were selected from over 100 000 registered users (from all over Poland) of the research platform managed by the Nationwide Research Panel Ariadna, using quota sampling methods. The stratification model included sex, age, and place of residence and was based on the demographic data on the Polish population, published by Statistics Poland.
Each respondent selected to participate in this survey received a personal invitation with a URL link to the website where the study questionnaire was available. The invitation and study description were sent via text messages and email. Respondents who declared voluntary and informed consent to participate in this survey were asked to fill out the questionnaire. Respondents were required to answer all questions to prevent missing answers. If someone refused to participate, the next respondent was selected following the stratification criteria and requirements for obtaining a sample of adults in Poland that reflect the demographic structure of adult Poles by sex, age, and place of residence. A similar methodology was used in other nationwide cross-sectional studies in Poland [25–27].
Measures
We self-prepared the study questionnaire based on a literature review [1–6,11–15]. Respondents were asked about their use of public and private healthcare services in the last 12 months. The survey question was: “In the past 12 months, have you used any healthcare services (visited a doctor, clinic, or hospital, etc.), either public or private?” The 4 response options were as follows: (1) I used only private healthcare services; (2) I used only public healthcare services; (3) I used both public and private healthcare services; or (4) I did not use any healthcare services in the past 12 months. Use of emergency services was included.
Respondents were also asked about missed appointments (patient no-shows) in medical facilities with the following question: “In the past 12 months, have you ever scheduled a medical appointment but did not attend and failed to cancel it in advance – that is, you did not inform the facility that you would not be coming (no-show/missed appointment)?” The 2 response options were as follows: (1) Yes, this happened to me once; (2) Yes, this happened to me several times; (3) No, this never happened to me; and (4) I had no scheduled medical appointments in the past 12 months. This question identified no-shows among those who used scheduled medical services, and in statistical analysis, those respondents who did not use scheduled medical services in the last 12 months were not included in the analysis of factors associated with no-shows.
Respondents who reported having at least 1 missed appointment in medical facility were asked about most common reason for the no-show.
Respondents were also asked about their support for introducing a penalty fee for patients who miss a scheduled medical appointment under the public healthcare system (funded by the NFZ) without cancelling it in advance, with a 5-point Likert scale. Moreover, all respondents were asked about 6 potential solutions that would make it easier for them to cancel a medical appointment they were unable to attend.
Moreover, 9 questions on personal characteristics were addressed. A pilot study was conducted. A group of 7 adults, aged 18 to 67 years, completed the same questionnaire twice, 10 days apart. Responses were compared and analyzed. After this analysis, 1 question was modified and 3 answer variants were modified to reduce the potential risk of bias.
Statistical Analysis
Data were analyzed with SPSS version 29 (IBM Corp, Armonk, NY, USA). Frequencies and proportions are used to present categorical variables. The chi-squared test was used to compare differences between categorical variables. Logistic regression analyses were conducted. First, analysis was conducted to identify factors associated with no-shows among those who had scheduled appointments in the medical facility in the last 12 months. The second analysis included data on all respondents to identify factors associated with support for the idea of introducing a penalty fee for patients who miss a scheduled medical appointment under the public healthcare system, without canceling it in advance. In bivariable analyses, all variables were analyzed separately. Variables that demonstrated statistically significant associations in bivariable models were then included in the multivariable logistic regression analysis. The strength of the associations was presented as odds ratios (ORs) and 95% CIs. Statistical significance level was set at P<0.05.
Results
Completed questionnaires were collected from 1162 adults, aged 18 to 96 years. Among the respondents, 53.1% were women, 48.5% had higher education, and 36.7% lived in rural areas (Table 1).
Table 1.
Characteristics of the study population (n=1162).
| Variable | n | % |
|---|---|---|
| Sex | ||
| Female | 617 | 53.1 |
| Male | 545 | 46.9 |
| Age (years) | ||
| 18–29 | 158 | 13.6 |
| 30–39 | 228 | 19.6 |
| 40–49 | 227 | 19.5 |
| 50–59 | 204 | 17.6 |
| 60+ | 345 | 29.7 |
| Educational level | ||
| Higher | 564 | 48.5 |
| Less than higher | 598 | 51.5 |
| Marital status | ||
| Single | 318 | 27.4 |
| Married | 602 | 51.8 |
| Informal relationship | 185 | 15.9 |
| Other | 57 | 4.9 |
| Place of residence | ||
| Rural area | 426 | 36.7 |
| City below 20 000 residents | 146 | 12.6 |
| City from 20 000 to 99 999 residents | 237 | 20.4 |
| City from 100 000 to 499 999 residents | 197 | 17.0 |
| City ≥500000 residents | 156 | 13.4 |
| Having children under 18 years of age | ||
| Yes | 289 | 24.9 |
| No | 873 | 75.1 |
| Number of household members | ||
| 1 (living alone) | 192 | 16.5 |
| 2 | 435 | 37.4 |
| 3 or more | 535 | 46.0 |
| Occupational status | ||
| Active | 744 | 64.0 |
| Passive | 418 | 36.0 |
| Household financial status | ||
| Good | 571 | 49.1 |
| Moderate | 434 | 37.3 |
| Bad | 157 | 13.5 |
Among all respondents (n=1162), 88.5% used healthcare services in the last 12 months, wherein 10.2% used only private healthcare services, 31.6% only public healthcare services, and 46.7% used both public and private healthcare services (Table 2). Among those respondents who used healthcare services in the last 12 months (n=1014), 14% of respondents reported at least 1 no-show in a medical facility in the last 12 months. Receiving a text message reminder was the most common solution to reduce the no-show phenomenon, as indicated by 62.5% of respondents. Among all respondents, 67.5% supported (33.4% moderately supported and 34.1% strongly supported) the idea of introducing a penalty fee for patients who miss a scheduled medical appointment (no-show) under the public healthcare system (funded by the NFZ) without canceling it in advance (Table 2).
Table 2.
Public attitudes toward the missed appointments (no-shows) in medical facilities among adults in Poland (n=1162).
| Variable | n | % |
|---|---|---|
| In the past 12 months, have you used any healthcare services (visited a doctor, clinic, or hospital, etc.), either public or private? | ||
| I used only private healthcare services | 118 | 10.2 |
| I used only public healthcare services | 367 | 31.6 |
| I used both public and private healthcare services | 543 | 46.7 |
| I did not use any healthcare services in the past 12 months | 134 | 11.5 |
| In the past 12 months, have you ever scheduled a medical appointment but did not attend and failed to cancel it in advance – that is, you did not inform the facility that you would not be coming (no-show/missing appointment)? | ||
| Yes, this happened to me once | 100 | 8.6 |
| Yes, this happened to me several times | 42 | 3.6 |
| No, this never happened to me | 872 | 75.0 |
| I had no scheduled medical appointments in the past 12 months | 148 | 12.7 |
| Which of the following solutions would make it easier for you to cancel a medical appointment you are unable to attend? | ||
| Receiving a text message reminder that I can reply to | 726 | 62.5 |
| Receiving a call from a registration staff member | 392 | 33.7 |
| Receiving an automated phone call (eg, from a bot) | 146 | 12.6 |
| A verbal reminder from the doctor during the previous visit | 61 | 5.2 |
| The option to cancel online via the medical facility’s website or mobile app | 432 | 37.2 |
| The option to cancel online via the Internet Patient Account or through the official governmental mobile apps (mojeikp or mobywatel) | 402 | 34.6 |
| None of the above | 62 | 5.3 |
| Do you support the idea of introducing a penalty fee for patients who miss a scheduled medical appointment (no-show) under the public healthcare system (funded by the National Health Fund) without canceling it in advance? | ||
| Strongly oppose | 83 | 7.1 |
| Moderately oppose | 120 | 10.3 |
| Moderately support | 388 | 33.4 |
| Strongly support | 396 | 34.1 |
| I do not know/hard to say | 175 | 15.1 |
Factors Associated With No-Shows
Among respondents who had visited a healthcare facility in the last 12 months (n=1014), the frequency of no-shows in medical facilities decreased with the age of the respondents (Table 3). Those who had children reported more no-shows, as did those with a higher number of co-residents in the household (Table 3). Moreover, those with current employment status also reported more no-shows in a medical facility in the last 12 months.
Table 3.
Factors associated with at least one no-show in medical facilities in the last 12 months among those who used public or private healthcare services in Poland (n=1014).
| In the past 12 months, have you ever scheduled a medical appointment but did not attend and failed to cancel it in advance – that is, you did not inform the facility that you would not be coming (no-show/missing appointment)? – “yes, this happened to me once” or “yes, this happened to me several times” | ||||||
|---|---|---|---|---|---|---|
| Variable | % | P | Bivariable logistic regression | Multivariable logistic regression | ||
| OR (95% CI) | P | aOR (95% CI) | P | |||
| Sex | ||||||
| Female (n=554) | 12.8 | 0.2 | 0.81 (0.57–1.15) | 0.2 | ||
| Male (n=460) | 15.4 | Reference | ||||
| Age (years) | ||||||
| 18–29 (n=138) | 28.3 | <0.001 | 4.24 (15.61) | <0.001 | 7.69 (3.74–15.81) | <0.001 |
| 30–39 (n=195) | 19.0 | 4.83 (2.54–9.21) | <0.001 | 3.62 (1.71–7.64) | <0.001 | |
| 40–49 (n=190) | 15.8 | 3.87 (1.99–7.51) | <0.001 | 2.54 (1.18–5.49) | 0.02 | |
| 50–59 (n=188) | 11.7 | 2.74 (1.36–5.49) | 0.005 | 2.22 (1.05–4.70) | 0.04 | |
| 60+ (n=303) | 4.6 | Reference | Reference | |||
| Educational level | ||||||
| Higher (n=511) | 12.9 | 0.3 | 0.83 (0.58–1.19) | 0.3 | ||
| Less than higher (n=503) | 15.1 | Reference | ||||
| Marital status | ||||||
| Single (n=269) | 13.0 | 0.06 | Reference | |||
| Married (n=533) | 13.9 | 1.08 (0.70–1.66) | 0.7 | |||
| Informal relationship (n=164) | 18.9 | 1.56 (0.92–2.64) | 0.1 | |||
| Other (n=48) | 4.2 | 0.29 (0.07–1.25) | 0.1 | |||
| Place of residence | ||||||
| Rural area (n=360) | 15.8 | 0.3 | 1.26 (0.72–2.20) | 0.4 | ||
| City below 20 000 residents (n=125) | 9.6 | 0.71 (0.33–1.53) | 0.4 | |||
| City from 20 000 to 99 999 residents (n=212) | 16.0 | 1.28 (0.70–2.34) | 0.4 | |||
| City from 100 000 to 499 999 residents (n=171) | 11.7 | 0.89 (0.45–1.73) | 0.7 | |||
| City ≥500 000 residents (n=146) | 13.0 | Reference | ||||
| Having children under 18 years of age | ||||||
| Yes (n=249) | 24.1 | <0.001 | 2.64 (1.83–3.83) | <0.001 | 2.09 (1.28–3.40) | 0.003 |
| No (n=765) | 10.7 | Reference | Reference | |||
| Number of household members | ||||||
| 1 (living alone) (n=169) | 8.3 | 0.001 | Reference | Reference | ||
| 2 (n=379) | 11.3 | 1.42 (0.75–2.67) | 0.3 | 1.64 (0.84–3.20) | 0.1 | |
| 3 or more (n=466) | 18.2 | 2.47 (1.36–4.48) | 0.003 | 1.41 (0.71–2.81) | 0.3 | |
| Occupational status | ||||||
| Active (n=656) | 16.6 | 0.001 | 1.96 (1.30–2.97) | 0.001 | 1.16 (0.71–1.88) | 0.6 |
| Passive (n=358) | 9.2 | Reference | Reference | |||
| Household financial status | ||||||
| Good (n=515 | 11.8 | 0.08 | Reference | Reference | ||
| Moderate (n=371) | 15.4 | 1.35 (0.92–1.99) | 0.1 | 1.80 (1.19–2.72) | 0.005 | |
| Bad (n=128) | 18.8 | 1.72 (1.02–2.88) | 0.04 | 2.60 (1.47–4.60) | 0.001 | |
| Using scheduled healthcare services within the public healthcare system in the last 12 months | ||||||
| Yes (n=849) | 13.7 | 0.5 | 0.85 (0.53–1.34) | 0.5 | ||
| No (n=165) | 15.8 | Reference | ||||
| Using scheduled healthcare services within the private healthcare system in the last 12 months | ||||||
| Yes (n=616) | 15.2 | 0.2 | 1.29 (0.89–1.88) | 0.2 | ||
| No (n=395) | 12.2 | Reference | ||||
In the multivariable logistic regression model, among respondents who had visited a healthcare facility in the last 12 months, age below 60 years (P<0.05), having children (aOR, 2.09; 95% CI, 1.28–3.40; P=0.003), and moderate (aOR, 1.80; 95% CI, 1.19–2.72; P=0.005) or poor (aOR, 2.60; 95% CI, 1.47–4.60; P=0.001) household financial status were associated with higher odds for no-shows in a medical facility in the least 12 months (Table 3).
There was no significant effect of sex, educational level, marital status, place of residence, and type of healthcare services (public or private) used in the last 12 months on the odds for no-shows (Table 3).
Self-Declared Reasons For No-Shows in a Medical Facility
Respondents who declared at least 1 no-show in medical facilities in the last 12 months (n=142) were asked to indicate the major reason for the missed appointment (Table 4). The most common reason was forgetting about the appointment (42.3%). Moreover, 27.5% of respondents were unable to reach the facility by phone (27.5%), and 23.9% declared worsening of health conditions or being suddenly ill (23.9%). Sex and age differences were analyzed. Men, compared with women, more often (31% vs 16.9%; P=0.04) indicated worsening of health condition as a major reason for a no-show (Table 4). Respondents aged 60 years and over chose “other reasons for no-show” more often than the younger age groups (P<0.001). No other differences in major reasons for no-shows by sex or age were detected (Table 4).
Table 4.
Self-declared major reason for missed appointments (no-shows) in medical facility among adults in Poland who declared no-show in the last 12 months (n=142).
| Self-declared major reason for no-show in medical facility | Overall | Sex | Age group (years) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Female | Male | P | 18–29 | 30–39 | 40–49 | 50–59 | 60+ | P | ||
| I forgot about the appointment | 42.3% | 39.4% | 45.1% | 0.5 | 48.7% | 40.5% | 40.0% | 54.5% | 14.3% | 0.2 |
| I was unable to reach the facility by phone | 27.5% | 32.4% | 22.5% | 0.2 | 25.6% | 32.4% | 23.3% | 27.3% | 28.6% | 0.9 |
| I did not know how to cancel the appointment | 7.7% | 5.6% | 9.9% | 0.3 | 10.3% | 5.4% | 16.7% | 0.0% | 0.0% | 0.1 |
| I was not aware that appointments should be canceled | 8.5% | 5.6% | 11.3% | 0.2 | 15.4% | 2.7% | 13.3% | 4.5% | 0.0% | 0.2 |
| My health condition worsened/I became suddenly ill | 23.9% | 16.9% | 31.0% | 0.04 | 23.1% | 24.3% | 33.3% | 13.6% | 21.4% | 0.6 |
| Other reason | 7.0% | 8.5% | 5.6% | 0.5 | 2.6% | 5.4% | 3.3% | 3.5% | 35.7% | <0.001 |
Preferred Solutions to Reduce No-Shows in Medical Facilities
All respondents (n=1162) were asked about the preferred solutions to reduce no-shows in medical facilities (Tables 5, 6). Respondents with higher education, status of being married or in informal relationship, residence in big cities, current employment, good household financial status, and use of public and private healthcare services in the last 12 months more frequently supported the idea of introducing a penalty fee for patients who miss a scheduled medical appointment (no-show) under the public healthcare system without canceling it in advance (Table 5).
Table 5.
Factors associated with public support among adults in Poland (n=1162) for the idea of introducing a penalty fee for patients who miss a scheduled medical appointment (no-show) under the public healthcare system without canceling it in advance.
| Do you support the idea of introducing a penalty fee for patients who miss a scheduled medical appointment (no-show) under the public healthcare system (funded by the National Health Fund) without canceling it in advance? Responses included “moderately support” and “strongly support” | ||||||
|---|---|---|---|---|---|---|
| Variable | % | P | Bivariable logistic regression | Multivariable logistic regression | ||
| OR (95% CI) | P | aOR (95% CI) | P | |||
| Sex | ||||||
| Female (n=617) | 66.5 | 0.4 | 0.91 (0.71–1.16) | 0.4 | ||
| Male (n=545) | 68.6 | Reference | ||||
| Age (years) | ||||||
| 18–29 (n=158) | 61.4 | 0.2 | Reference | Reference | ||
| 30–39 (n=228) | 67.5 | 1.31 (0.86–2.00) | 0.2 | 1.19 (0.76–1.86) | 0.5 | |
| 40–49 (n=227) | 67.0 | 1.28 (0.84–1.95) | 0.3 | 1.26 (0.80–2.00) | 0.3 | |
| 50–59 (n=204) | 65.2 | 1.18 (0.77–1.81) | 0.5 | 1.29 (0.80–2.08) | 0.3 | |
| 60+ (n=345) | 71.9 | 1.61 (1.08–2.39) | 0.02 | 2.19 (1.36–3.53) | 0.001 | |
| Educational level | ||||||
| Higher (n=564) | 73.2 | <0.001 | 1.67 (1.31–2.15) | <0.001 | 1.40 (1.07–1.83) | 0.01 |
| Less than higher (n=598) | 62.0 | Reference | Reference | |||
| Marital status | ||||||
| Single (n=318) | 62.6 | 0.02 | Reference | Reference | ||
| Married (n=602) | 70.8 | 1.45 (1.09–1.93) | 0.01 | 1.12 (0.82–1.54) | 0.5 | |
| Informal relationship (n=185) | 68.6 | 1.31 (0.89–1.92) | 0.2 | 1.21 (0.81–1.81) | 0.4 | |
| Other (n=57) | 56.1 | 0.77 (0.43–1.35) | 0.4 | 0.71 (0.38–1.31) | 0.3 | |
| Place of residence | ||||||
| Rural area (n=426) | 62.9 | 0.01 | Reference | Reference | ||
| City below 20 000 residents (n=146) | 63.7 | 1.03 (0.70–1.53) | 0.9 | 1.00 (0.67–1.50) | 0.9 | |
| City from 20 000 to 99 999 residents (n=237) | 70.9 | 1.44 (1.02–2.02) | 0.04 | 1.33 (0.93–1.90) | 0.1 | |
| City from 100 000 to 499 999 residents (n=197) | 68.5 | 1.28 (0.90–1.84) | 0.2 | 1.11 (0.76–1.60) | 0.6 | |
| City ≥500 000 residents (n=156) | 76.9 | 1.97 (1.29–2.99) | 0.002 | 1.74 (1.13–2.71) | 0.01 | |
| Having children under 18 years of age | ||||||
| Yes (n=289) | 67.8 | 0.9 | 1.02 (0.77–1.36) | 0.9 | ||
| No (n=873) | 67.4 | Reference | ||||
| Number of household members | ||||||
| 1 (living alone) (n=192) | 67.2 | 0.4 | 0.94 (0.66–1.33) | 0.7 | ||
| 2 (n=435) | 69.7 | 1.12 (0.78–1.61) | 0.5 | |||
| 3 or more (n=535) | 65.8 | Reference | ||||
| Occupational status | ||||||
| Active (n=744) | 69.8 | 0.03 | 1.33 (1.03–1.72) | 0.03 | 1.47 (1.07–2.01) | 0.02 |
| Passive (n=418) | 63.4 | Reference | Reference | |||
| Household financial status | ||||||
| Good (n=571) | 75.1 | <0.001 | 2.13 (1.47–3.09) | <0.001 | 1.83 (1.23–2.71) | 0.003 |
| Moderate (n=434) | 60.6 | 1.09 (0.75–1.58) | 0.7 | 0.99 (0.67–1.45) | 0.9 | |
| Bad (n=157) | 58.6 | Reference | Reference | |||
| Using healthcare services in the last 12 months | ||||||
| Yes, within private healthcare system (n=118) | 65.3 | 0.008 | 1.39 (0.83–2.32) | 0.2 | 1.04 (0.61–1.79) | 0.9 |
| Yes, within public healthcare system (n=367) | 65.4 | 1.40 (0.93–2.10) | 0.1 | 1.23 (0.80–1.88) | 0.4 | |
| Yes, within both public and private healthcare system (n=543) | 71.8 | 1.89 (1.28–2.79) | 0.001 | 1.42 (0.94–2.15) | 0.09 | |
| No (n=134) | 57.5 | Reference | Reference | |||
Table 6.
Preferred solutions that would make it easier for patients to cancel a medical appointment they are unable to attend and limit the no-show phenomenon among adults in Poland (n=1162).
| Which of the following solutions would make it easier for you to cancel a medical appointment you are unable to attend? Positive responses: “yes” | ||||||
|---|---|---|---|---|---|---|
| Variable | Receiving a text message reminder that I can reply to | Receiving a call from a registration staff member | Receiving an automated phone call (eg, from a bot) | |||
| % | P | % | P | % | P | |
| Total (N=1162) | 62.5 | 33.7 | 12.6 | |||
| Sex | ||||||
| Female (n=617) | 67.1 | <0.001 | 35.3 | 0.2 | 12.0 | 0.5 |
| Male (n=545) | 57.2 | 31.9 | 13.2 | |||
| Age (years) | ||||||
| 18–29 (n=158) | 55.1 | 0.004 | 18.4 | <0.001 | 14.6 | 0.4 |
| 30–39 (n=228) | 56.1 | 27.6 | 11.8 | |||
| 40–49 (n=227) | 61.2 | 37.0 | 15.9 | |||
| 50–59 (n=204) | 65.2 | 40.2 | 10.3 | |||
| 60+ (n=345) | 69.3 | 38.8 | 11.3 | |||
| Educational level | ||||||
| Higher (n=564) | 64.4 | 0.2 | 31.6 | 0.1 | 11.3 | 0.2 |
| Less than higher (n=598) | 60.7 | 35.8 | 13.7 | |||
| Marital status | ||||||
| Single (n=318) | 58.2 | 0.07 | 30.2 | <0.001 | 14.5 | 0.4 |
| Married (n=602) | 63.8 | 39.9 | 12.6 | |||
| Informal relationship (n=185) | 68.1 | 22.7 | 9.2 | |||
| Other (n=57) | 54.4 | 24.6 | 12.3 | |||
| Place of residence | ||||||
| Rural area (n=426) | 60.6 | 0.3 | 35.4 | 0.2 | 11.7 | 0.6 |
| City below 20 000 residents (n=146) | 56.8 | 35.6 | 10.3 | |||
| City from 20 000 to 99 999 residents (n=237) | 65.0 | 36.7 | 12.2 | |||
| City from 100 000 to 499 999 residents (n=197) | 63.5 | 31.5 | 13.7 | |||
| City ≥500 000 residents (n=156) | 67.9 | 25.6 | 16.0 | |||
| Having children under 18 years of age | ||||||
| Yes (n=289) | 60.6 | 0.4 | 36.7 | 0.2 | 12.8 | 0.9 |
| No (n=873) | 63.1 | 32.8 | 12.5 | |||
| Number of household members | ||||||
| 1 (living alone) (n=192) | 63.5 | 0.8 | 30.2 | 0.5 | 14.1 | 0.7 |
| 2 (n=435) | 61.1 | 34.7 | 11.7 | |||
| 3 or more (n=535) | 63.2 | 34.2 | 12.7 | |||
| Occupational status | ||||||
| Active (n=744) | 61.6 | 0.4 | 32.3 | 0.2 | 13.8 | 0.08 |
| Passive (n=418) | 64.1 | 36.4 | 10.3 | |||
| Household financial status | ||||||
| Good (n=571) | 65.1 | 0.2 | 31.2 | 0.04 | 11.6 | 0.1 |
| Moderate (n=434) | 59.7 | 34.1 | 12.0 | |||
| Bad (n=157) | 60.5 | 42.0 | 17.8 | |||
| Using healthcare services in the last 12 months | ||||||
| Yes, within private healthcare system (n=118) | 59.3 | <0.001 | 23.7 | 0.003 | 12.7 | 0.9 |
| Yes, within public healthcare system (n=367) | 67.8 | 34.3 | 12.8 | |||
| Yes, within both public and private healthcare system (n=543) | 63.7 | 37.8 | 12.5 | |||
| No (n=134) | 45.5 | 24.6 | 11.9 | |||
| At least 1 no-show in medical facility in the last 12 months | ||||||
| Yes (n=142) | 49.3 | <0.001 | 26.8 | 0.06 | 20.4 | 0.003 |
| No (n=1020) | 64.3 | 34.7 | 11.5 | |||
| Which of the following solutions would make it easier for you to cancel a medical appointment you are unable to attend? Positive responses: “yes” | ||||||
| Variable | A verbal reminder from the doctor during the previous visit | The option to cancel online via the medical facility’s website or mobile app | The option to cancel online via the Internet Patient Account or through the official governmental mobile apps (mojeIKP or mObywatel) | |||
| % | P | % | P | % | P | |
| Total (N=1162) | 5.2 | 37.2 | 34.6 | |||
| Sex | ||||||
| Female (n=617) | 4.1 | 0.05 | 37.3 | 0.9 | 31.1 | 0.008 |
| Male (n=545) | 6.6 | 37.1 | 38.5 | |||
| Age (years) | ||||||
| 18–29 (n=158) | 6.3 | 0.2 | 48.1 | <0.001 | 46.2 | <0.001 |
| 30–39 (n=228) | 7.5 | 46.1 | 42.5 | |||
| 40–49 (n=227) | 4.4 | 38.8 | 34.4 | |||
| 50–59 (n=204) | 2.5 | 31.9 | 32.4 | |||
| 60+ (n=345) | 5.5 | 28.4 | 25.5 | |||
| Educational level | ||||||
| Higher (n=564) | 5.1 | 0.9 | 44.5 | <0.001 | 45.6 | <0.001 |
| Less than higher (n=598) | 5.4 | 30.3 | 24.2 | |||
| Marital status | ||||||
| Single (n=318) | 5.7 | 0.4 | 36.8 | <0.001 | 35.5 | 0.08 |
| Married (n=602) | 5.3 | 34.1 | 33.1 | |||
| Informal relationship (n=185) | 3.2 | 54.1 | 41.1 | |||
| Other (n=57) | 8.8 | 17.5 | 24.6 | |||
| Place of residence | ||||||
| Rural area (n=426) | 4.7 | 0.6 | 30.3 | <0.001 | 28.2 | <0.001 |
| City below 20 000 residents (n=146) | 4.8 | 30.1 | 39.5 | |||
| City from 20 000 to 99 999 residents (n=237) | 5.1 | 41.8 | 36.7 | |||
| City from 100 000 to 499 999 residents (n=197) | 7.6 | 42.6 | 42.1 | |||
| City ≥500 000 residents (n=156) | 4.5 | 48.7 | 44.2 | |||
| Having children under 18 years of age | ||||||
| Yes (n=289) | 6.2 | 0.4 | 39.1 | 0.4 | 37.0 | 0.3 |
| No (n=873) | 4.9 | 36.5 | 33.8 | |||
| Number of household members | ||||||
| 1 (living alone) (n=192) | 6.8 | 0.2 | 36.5 | 0.7 | 32.8 | 0.3 |
| 2 (n=435) | 3.7 | 35.9 | 37.5 | |||
| 3 or more (n=535) | 6.0 | 38.5 | 32.9 | |||
| Occupational status | ||||||
| Active (n=744) | 5.9 | 0.2 | 41.3 | <0.001 | 39.0 | <0.001 |
| Passive (n=418) | 4.1 | 29.9 | 26.8 | |||
| Household financial status | ||||||
| Good (n=571) | 3.5 | 0.001 | 43.8 | <0.001 | 42.9 | <0.001 |
| Moderate (n=434) | 5.5 | 32.0 | 26.5 | |||
| Bad (n=157) | 10.8 | 27.4 | 26.8 | |||
| Using healthcare services in the last 12 months | ||||||
| Yes, within private healthcare system (n=118) | 4.2 | 0.7 | 44.9 | <0.001 | 41.5 | <0.001 |
| Yes, within public healthcare system (n=367) | 6.3 | 28.9 | 26.4 | |||
| Yes, within both public and private healthcare system (n=543) | 5.0 | 42.7 | 39.4 | |||
| No (n=134) | 4.5 | 30.6 | 31.3 | |||
| At least 1 no-show in medical facility in the last 12 months | ||||||
| Yes (n=142) | 14.1 | <0.001 | 31.7 | 0.1 | 36.6 | 0.6 |
| No (n=1020) | 4.0 | 37.9 | 34.3 | |||
In multivariable logistic regression analysis, age 60 years and over (aOR, 2.19; 95% CI, 1.36–3.53; P=0.001), higher education (aOR, 1.40; 95% CI, 1.07–1.83; P=0.01), residence in cities with 500 000 or more residents (aOR, 1.74; 95% CI, 1.13–2.71; P=0.01), current employment (aOR, 1.47; 95% CI, 1.07–2.01; P=0.02), and good household financial status (aOR, 1.83; 95% CI, 1.23–2.71; P=0.003) were significantly associated with support for introducing a penalty fee for patients who miss a scheduled medical appointment (no-show) under the public healthcare system without canceling it in advance (Table 5).
Women, older respondents, and those who used healthcare services provided within the public system more often (P<0.05) indicated receiving a text message reminder as a preferred solution to reduce no-shows in medical facilities (Table 6). Older adults, those who were married, those with poor household financial status, and those who used health services provided by the public or public and private healthcare more often indicated (P<0.05) receiving a call from a registration staff member as a preferred solution to reduce no-shows. Respondents who reported at least 1 no-show in a medical facility in the last 12 months more often (P<0.05) indicated receiving an automated phone call (eg, from a bot) as a preferred solution to reduce no-shows in medical facilities (Table 6). Respondents with poor household financial status and those who reported at least 1 no-show in a medical facility in the last 12 months more often (P<0.05) indicated a verbal reminder from the doctor during the previous visit as a preferred solution to reduce no-shows in medical facilities (Table 6). Mobile solutions, such as the possibility to cancel scheduled appointments online via the medical facility’s website or mobile app, as well as the possibility to cancel online via the internet patient account or through the official governmental mobile apps (mojeIKP or mObywatel), were selected more often (P<0.05) by respondents with male sex, younger age, higher education, residence in larger cities, current employment, good household financial status, and use of health services provided within the private or public and private healthcare system (Table 6).
Discussion
This cross-sectional survey represents one of the most comprehensive studies in Poland dedicated to examining patient no-show behavior in medical facilities. Findings from this study revealed a relatively high prevalence of no-shows, estimated at 14% of patients who had scheduled appointments in the 12 months prior to the study. Forgetting about the appointment (42.3%) was the most common reason for no-shows. In multivariable logistic regression, younger age, having children under 18 years old, and moderate or poor financial status were the only factors significantly associated with a higher risk for no-shows. While the phenomenon of missed appointments has been extensively studied in various healthcare systems worldwide, the present study provides unique insights into the Polish healthcare context, establishing baseline data for this previously understudied area in Central and Eastern Europe.
The present study revealed that 14% of Polish inhabitants who used healthcare services in the past 12 months declared at least 1 no-show in medical facilities, with 8.6% experiencing 1 missed appointment, and 3.6% reporting multiple no-shows. These findings exceed international evidence from well-organized healthcare systems. Danish studies reported a 5% no-show rate in outpatient clinics for patients with chronic diseases [4], while French research documented 4.9% of missed appointments in urban primary care settings [28]. Italian healthcare districts recorded similar rates of 5.1% [26], and UK systematic reviews identified comparable patterns [30]. International systematic reviews report no-show rates ranging from 5% to 50%, with significant variation by healthcare setting and patient population [31]. The differences between the Polish data and that of other European countries suggest that different organizational structures and patient behavior regarding appointment adherence may affect the no-show patterns across developed healthcare systems.
Notably, our study found that younger patients were significantly more likely to miss appointments, with those aged 18 to 29 years showing the highest no-show rates (28.3%). This finding strongly corroborates international evidence from Denmark and the UK, where Danish research identified younger age as the strongest predictor of non-attendance (OR 4.17 for 18–29 year age group compared with 80+ years) [4], and UK systematic reviews consistently reported younger patients as high-risk groups [30]. The pattern suggests that younger patients may have less respect for healthcare system protocols and may not fully appreciate the resource implications of their missed appointments [2]. Additionally, patients with children under 18 years of age had over 2 times higher odds of no-shows, which aligns with international findings showing that family obligations, particularly child illness, frequently prevent attendance at scheduled medical visits [2,31]. This demographic characteristic reflects the competing priorities that parents face when children become suddenly ill, making it impossible to attend their own medical appointments.
The association between lower socioeconomic status and higher no-show rates observed in our Polish sample mirrors findings from French studies identifying socioeconomic instability, uncertain work hours, and social isolation as primary drivers [28], and Danish research showing increased non-attendance among recipients of long-term social benefits [2]. International systematic reviews consistently identify lower socioeconomic status as a predictor of missed appointments across diverse healthcare settings [2,31]. This suggests that economic barriers extend beyond direct costs to include work flexibility and social support systems that facilitate healthcare engagement.
The most frequently self-reported reason for no-shows in our Polish study was forgetting about the appointment (42.3%), which directly corresponds with international literature identifying forgetfulness as the primary cause of missed appointments across diverse healthcare settings [21]. French qualitative research emphasized similar themes, reporting socioeconomic instability, unpredictable work schedules, social isolation, and multiple life commitments as underlying factors [28]. Danish studies suggested that causes extend beyond simple forgetfulness to include acute health issues and life circumstances that make financial penalties ineffective [32].
The second most common reason in Poland was the inability to reach the facility by phone (27.5%), highlighting systemic communication barriers that differ from typical international findings, which more commonly cite transportation issues or changes in health status [21]. This suggests that Polish healthcare facilities may need to improve communication infrastructure and provide alternative cancellation methods beyond phone-based systems.
Male respondents in our study more frequently cited worsening health conditions (31% vs 16.9% among females) as a reason for non-attendance, which aligns with international evidence showing sex differences in healthcare-seeking behavior and appointment management strategies [33].
Our findings revealed that 67.5% of Polish adults supported introducing penalty fees for missed appointments under the public healthcare system, with support being strongest among older adults (aged 60 years and over), those with higher education, inhabitants of cities with 500 000 or more residents, and those with good financial status. This level of support contrasts sharply with effectiveness data from a randomized controlled trial in Denmark, in which a penalty fee of 250 Danish kroner (DKK; €34) did not reduce no-show rates from a baseline of approximately 5%. Critically, 79% of imposed fines went unpaid, and the administrative costs (7.72 DKK per appointment) made the system economically inefficient [34]. The disconnect between public support and practical effectiveness suggests that while Polish citizens may theoretically endorse penalties as a deterrent, real-world implementation may face similar challenges observed in Scandinavian healthcare systems [35]. The current public debate in Poland regarding financial penalties for no-shows should carefully consider these international experiences, particularly given the limited effectiveness demonstrated in countries with similar healthcare organization and socioeconomic profiles.
Polish respondents showed clear preferences for text message (SMS) reminders (62.5%), followed by online cancellation options through medical facility websites or mobile apps (37.2%) and government digital platforms (34.6%). This observation aligns remarkably with international evidence favoring digital communication methods. Over a decade ago, Gurol-Urganci et al in their Cochrane systematic review, demonstrated SMS effectiveness (11.1% vs 22.5% non-attendance rate compared with no reminders) [36], while Guy et al showed that mobile phone messaging reminders significantly improved appointment attendance [37]. Finkelstein et al found that patients preferred appointment reminders delivered less than 2 weeks before appointments [38].
The observed preference for impersonal, digital communication methods may reflect practical barriers, such as limited telephone accessibility at medical offices, as well as patients’ desire to avoid embarrassing phone conversations. This finding supports international evidence suggesting that patients prefer non-confrontational cancellation methods [39]. Younger, more educated, urban, and financially stable Polish respondents were significantly more likely to prefer mobile digital solutions, mirroring global trends in which technological adoption follows sociodemographic patterns. Saudi Arabian research confirmed that phone reminders were more effective than SMS among older patients (41–60 years), suggesting that age-tailored communication strategies may be necessary [40].
Importantly, our study found no significant association between place of residence and no-show frequency, indicating that transportation and communication barriers were less influential than personal life circumstances. This contrasts with some international studies that identified geographic distance as a predictor of non-attendance. However, our results align more closely with French research demonstrating that socioeconomic instability, work uncertainty, family responsibilities, and social isolation were more predictive of missed appointments than geographic accessibility [28]. Danish register-based cohort studies similarly found that socioeconomic factors, including recipients of long-term social benefits, lower education levels, and unmarried status, were stronger predictors of non-attendance than were geographic variables [41]. This suggests that in well-connected European healthcare systems, personal and socioeconomic factors rather than transportation logistics are primary determinants of appointment adherence.
Practical Implications
This nationwide survey highlights priorities for Polish healthcare policy and management for reducing the no-show rate. Policymakers should expand digital reminder systems, such as short text messages and voice bots. Moreover, national e-Health solutions, such as the internet patient account (mojeIKP), may serve as a digital infrastructure for other systems. These systems may address the gap in forgotten visits and enable patients to cancel appointments in advance, if needed. Interventions should target high-risk groups: adults aged 18 to 49 years, families with children, and financially disadvantaged patients, who face higher odds of non-attendance. Although 67.5% of respondents support penalty fees, evidence suggests that improving accessibility and communication, addressing forgetfulness (42.3%), and overcoming contact barriers are more effective approaches than punitive measures. Personalized communication, which also underlines the economic costs of no-shows, should be applied in Poland. Further studies should assess the prevalence of missed appointments across different types of care, particularly primary care and outpatient specialist care. Moreover, the effectiveness of different digital tools and demographic-specific strategies targeted at reducing missed appointments should be monitored in further studies.
Study Limitations
This is a cross-sectional survey; therefore, data on the no-shows in medical facilities were self-reported, and medical documentation was not verified. Recall bias can occur in this type of study. The most common reasons for no-shows in medical facilities were listed; however, the analysis was limited to the 5 most frequently mentioned situations in the public debate and scientific literature. A self-prepared questionnaire was used, without full validation, which is also a limitation of this study. Moreover, respondents were asked about preferred solutions that would reduce the risk of no-shows, but only 6 potential solutions were analyzed. Selection bias may also occur. The CAWI technique was used, so those without internet access were excluded. However, only 4% of households in Poland without internet access were unable to participate in this study.
Conclusions
This study provides the first comprehensive baseline data on missed medical appointments (no-shows) in Polish healthcare, a previously understudied topic in Central and Eastern Europe. This survey found a high rate of missed appointments in Poland. The main cause of no-shows was patient forgetfulness, followed by communication failures. Transport barriers were not a significant cause of no-shows. Younger age, having children under 18 years old, and moderate or bad financial status were associated with a higher risk for no-shows. The findings support investment in digital communication systems over punitive measures, highlighting the need to expand reminder services and improve accessibility through multi-channel platforms by organizations tasked with funding health services. The study offers evidence-based guidance for targeted interventions, with future research needed on SMS reminders, digital tools, and demographic-specific strategies.
Acknowledgements
The authors used the AI tool Grammarly for language editing.
Footnotes
Financial support: This study was conducted as a part of the statutory research project carried out by the School of Public Health, Center of Postgraduate Medical Education, Warsaw, Poland
Conflict of interest: None declared
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher
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