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Introduction

Missed dental appointments have a negative impact on clinical efficiency and patients’ oral health. A failure to receive timely treatment prolongs dental management, further exacerbates disease, and denies opportunities for other patients to receive care. It has been found that the non-attended appointments in health care facilities create a disruption in the planned schedule and wastes resources, resulting in inefficiencies and a loss of clinical productivity.1 This problem is not only a concern in private practices but more so at educational institutions as students rely on patient attendance to fulfil curriculum requirements and academic competency. Patients miss their appointments for various reasons and will either cancel their appointment ahead of time, or by not attending their appointment on the day. Both of the cancelled or failed to attend (FTA) appointments cause pressure on administrative staff who have to reschedule appointments and fill the vacant times with other patients. In facilities that function as education institutions, non-attendance has a negative impact on teaching activities and an overall negative influence on the quantity and quality of clinical learning within the undergraduate and postgraduate clinics.2 Non-attendance could lead to reduced clinical teaching times, increased waiting times for patients to secure an appointment, further challenging students to meet requirements and in the future, compromising competency required for professional registration.3,4

The majority of studies on non-attendance have primarily focused on general medical practices, with fewer studies conducted at dental facilities.5 A study in the United Kingdom estimated the general medical practice non-attendance rate to be 6.5% to 7-7%.6 Similar studies conducted in the United States showed primary health care non-attendance rates ranging from 5% to 55%.5 Two Australian studies conducted at different dental schools reported similar rates of nonattendance of 33% and 35%.4,7 Research conducted at King Saud University Dental College in Saudi Arabia showed that 24% to 34% of patients missed their appointments, which negatively impacted on student’s learning and academic progress3.

The most common reasons of non-attendance have been found to be a lack of time, forgetfulness, limited access to transportation, the cost of treatment, weather conditions, and travel distance.3,4 Dental anxiety has also been a major factor affecting non-attendance, particularly involving paediatric patients.8 In addition, demographic characteristics such as age, gender, location and socioeconomic status (SES) had a role in non-attendance rates.4,7 A study conducted at The School of Dentistry and Oral Health at Griffith University reported that females had a greater chance of failing appointments due to family commitments as well as young adults due to forgetfulness.7 However, an additional study revealed that males had a higher proportion of missed appointments compared with females.3 Multiple studies have shown that interventions such as text messages, voice messages, written reminders, or appointment cards, have been effective in reducing the non-attendance rates.4,9 A better understanding of the reasons for non-attendance can assist in improving clinical efficiency and dental education.

The aim of the present study was to therefore investigate the non-attendance of appointments at the University of Otago’s Orthodontic clinic, and to explore the possible reasons for the attendance failure.

Materials and methods

Appointment data were collected from the Faculty of Dentistry, University of Otago, Dunedin, New Zealand, between August and October in 2013 (paper-appointment system using physical logbooks and posted letters) and 2019 (digital-appointment system using automatically generated short message service (SMS texts in the Titanium Management system) before the Covid-19 pandemic). August to October was a quarter of a year of routinely normal clinical time without disruption due to public holidays at the Faculty of Dentistry, University of Otago which is New Zealand’s National Centre for Dentistry.

The data of demographics and time attached to each appointment were collected. No patient names nor identifiable information collected for this study were disclosed in the manuscript. The percentage of FTA appointments was analysed according to gender, age, ethnicity, residential location, time of appointment, day of the week, type of treatment provided, and month. The residential location of the patient was converted into an index using the Social Deprivation Index (https://profile.idnz.co.nz/dunedin/deprivation-index), in which data is presented as a scale, and ranks the suburbs of Dunedin from the least deprived to the most deprived. The mean is 1000 index points of which the higher the number, the greater the deprivation. Data from 2013 and 2019 were also compared to analyse the effect of a SMS reminder system in improving attendance rate.

Statistical analysis

The frequency distribution of FTA appointments by patient demographics, treatment type, and time characteristics were analysed. The relationship between demographic characteristics of patients and non-attendance was evaluated using a multivariate multinomial regression analysis. An odds ratio (OR) and 95% confidence interval (CI) were presented for FTA rates. A p-value less than 0.05 was considered statistically significant.

Results

The total number of appointments was 5810, including 2761 by 1901 patients in 2013 and 3049 by 2009 patients in 2019. The overall FTA rates were 16.1% in 2013 and 12.9% in 2019. Female patients (56.4% in 2013 and 55.3% in 2019) missed attending slightly more than male patients (43.6% in 2013 and 44.7% in 2019). There was an increase in the variety of ethnicities from 2013 to 2019: Maori and Pasifika people had an increased missed attendance rate from 7.2% to 8.3%, Asian ethnicity increased from 3.7% to 4.4%, and the ‘other’ category increased from 6.3% to 19.0%. Over half of the patients who attended the orthodontic clinic were between the ages of 13 and 18 years (62.8% in 2013 and 50.4% in 2019) (Tables I and II).

Demographic characteristics of the patients (%, N) in 2013 and 2019

  2013 2019
Male Female Total Male Female Total
New ZealandEuropean 35.8% (681) 47.0% (894) 82.8% (1575) 31.0% (622) 37.4% (752) 68.4% (1374)
Māori/Pasifika 3.5% (66) 3.7% (70) 7.2% (136) 3.3% (67) 4.9% (99) 8.3% (166)
Asian 1.7% (33) 2.0% (38) 3.7% (71) 2.2% (44) 2.2% (44) 4.4% (88)
Others (Latino, Middle Eastern, or unstated) 2.6% (49) 3.7% (70) 6.3% (119) 8.2% (165) 10.8% (216) 19.0% (381)
Total 43.6% (829) 56.4% (1072) 100% (1901) 44.7% (898) 55.3% (1111) 100% (2009)

Age categories of the patients (%, N) in 2013 and 2019

2013 2019
Age(Years) Male Female Total Male Female Total
< 12 8.3% (157) 13.2% (250) 21.4% (407) 13.8% (277) 16.2% (325) 30.0% (602)
13-18 29.7% (565) 33.1% (629) 62.8% (1194) 23.2% (466) 27.2% (547) 50.4% (1013)
19-25 4.1% (78) 6.8% (129) 10.9% (207) 5.4% (108) 7.3% (147) 12.7% (255)
26-49 0.9% (18) 2.5% (48) 3.5% (66) 1.8% (37) 3.6% (73) 5.5% (110)
50-64 0.4% (7) 0.7% (14) 1.1% (21) 0.3% (6) 0.5% (11) 0.8% (17)
65+ 0.2% (4) 0.1% (2) 0.3% (6) 0.2% (4) 0.4% (8) 0.6% (12)
Total 43.6% (829) 56.4% (1072) 100% (1901) 44.7% (898) 55.3% (1111) 100% (2009)

The overall non-attendance rate in 2013 was 16.1% (N = 306) (Table III). People living in the 901 to 950 (higher SES) suburb index were 1.5 times less likely to fail compared with people living in the ‘others’ category (p < 0.05). The ‘others’ category included those who lived outside of central Dunedin or in suburbs without an index. August had the highest rate of failed appointments of 19.7% (N = 96) compared with the other months of September and October (p < 0.05).

Distribution of demographic and time characteristics, treatment and odds ratios (OR) for appointment status (N = 1,901) in 2013

Variable Attended %(N) FTA %(N) FTA OR (95% CI) P-value
Overall 83.9% (1594) 16.1% (306)
Ethnicity
  NZ European 83.4% (1314) 16.5% (260) 0.90 (0.54-1.51) 0.70
  ori/Pasifika 86.0% (117) 14.0% (19) 1.10 (0.55-2.20) 0.79
  Asian 87.3% (62) 12.7% (9) 1.23 (0.52-2.90) 0.64
  Others 84.9% (101) 15.1% (18) 1
Gender
  Male 82.5% (684) 17.5% (145) 0.83 (0.65-1.07) 0.15
  Female 85.0% (911) 15.0% (161) 1
Age group
  <12 86.0% (350) 14.0% (57) 1.23 (0.14-10.70) 0.85
  13-18 83.2% (993) 16.8% (201) 0.99 (0.12-8.50) 0.99
  19-25 81.6% (169) 18.4% (38) 0.89 (0.10-7.84) 0.92
  26-49 89.4% (59) 10.6% (7) 1.69 (0.17-16.57) 0.65
  50-64 85.7% (18) 14.3% (3) 0.89 (0.10-14.20) 0.20
  65+ 83.3.% (5) 16.7% (1) 1
Suburb index
  <900 72.2% (13) 27.8% (5) 0.62 (0.21-1.83) 0.39
  901-950 86.2% (676) 13.8% (108) 1.50 (1.05-2.15) 0.03
  951-1000 82.2% (341) 17.8% (74) 1.11 (0.75-1.63) 0.61
  1001+ 84.0% (336) 16.0% (64) 1.26 (0.85-1.88) 0.25
  Others 80.6% (229) 19.4% (55) 1
Time of day
  Morning 84.0% (561) 16.0% (107) 0.99 (0.77-1.28) 0.45
  Afternoon 87.9% (1034) 12.1% (199) 1
Day
  Monday 80.1% (278) 19.9% (69) 0.68 (0.45-1.03) 0.07
  Tuesday 85.0% (271) 15.0% (48) 0.95 (0.61-1.48) 0.83
  Wednesday 85.7% (444) 14.3% (74) 1.01 (0.68-1.51) 0.96
  Thursday 82.7% (335) 17.3% (70) 0.81 (0.54-1.21) 0.30
  Friday 85.6% (267) 14.4% (45) 1
Treatment
  Consultation 82.6% (161) 17.4% (34) 0.73 (0.29-1.86) 0.51
  Records 83.9% (26) 16.1% (5) 0.80 (0.22-2.90) 0.73
  Bonding 75.0% (6) 25.0% (2) 0.46 (0.08-2.84) 0.40
  Review/adjustment 81.9% (929) 18.1% (205) 0.70 (0.29-1.67) 0.42
  Debonding 92.1% (58) 7.9% (5) 1.79 (0.51-6.26) 0.37
  Retainer/retention 88.4% (374) 11.6% (49) 1.17 (0.47-2.92) 0.73
  Others 86.7% (39) 13.3% (6) 1
Month
  August 80.3% (392) 19.7% (96) 0.70 (0.52-0.95) 0.02
  September 84.9% (585) 15.1% (104) 0.97 (0.72-1.29) 0.81
  October 85.4% (618) 14.6% (106) 1

The overall appointment non-attendance rate in 2019 was 12.9% (392) (Table IV). Of the suburb index group, those over 1001+ had the lowest attendance rate of 88.3% (p < 0.05) and were 0.42 times less likely to fail in comparison to the ‘others’ category.

Distribution of demographic and time characteristics, treatment and odds ratios (OR) for appointment status (N = 2,009) in 2019

Variable Attended % (N) FTA % (N) FTA OR (95% CI) P-value
Overall (appointments) 87.1% (2657) 12.9% (392)
Ethnicity
  NZ European 92.8% (1275) 7.2% (99) 1.22 (0.81-1.84) 0.34
  Māori/Pasifika 87.3% (145) 12.7% (21) 0.66 (0.37-1.17) 0.15
  Asian 90.9% (80) 9.1% (8) 0.95 (0.42-2.13) 0.90
  Others 91.3% (348) 8.7% (33) 1
Gender
  Male 92.0% (826) 8.0% (72) 1.00 (0.72-1.38) 1.00
  Female 92.0% (1022) 8.0% (89) 1
Age group
  <12 90.7% (546) 9.3% (56) 0.89 (0.11-6.99) 0.91
  13-18 93.3% (945) 6.7% (68) 1.26 (0.16-9.93) 0.82
  19-25 89.8% (229) 10.2% (26) 0.80 (0.01-6.45) 0.84
  26-49 92.7% (102) 7.3% (8) 1.16 (0.13-10.15) 0.89
  50-64 88.2% (15) 11.8% (2) 0.68 (0.06-8.50) 0.76
  65+ 91.7% (11) 8.3% (1) 1
Suburb index
  <900 92.9% (13) 7.1% (1) 0.72 (0.09-5.85) 0.76
  901-950 93.6% (654) 6.4% (45) 0.81 (0.47-1.40) 0.46
  951-1000 91.2% (385) 8.8% (37) 0.58 (0.33-1.02) 0.06
  1001 + 88.3% (439) 11.7% (58) 0.42 (0.25-0.72) 0.00
  Others 94.7% (357) 5.3% (20) 1
Notification
  Yes 87.3% (2477) 12.7 (358) 1.26 (0.86-1.86) 0.23
  No 84.5% (180) 15.5% (33) 1
  SMS 88.1% (2001) 11.9% (271) 0.74 (0.50-1.09) 0.03
  Letter 82.8% (82) 17.2% (17) 1.13 (0.60-2.14) 0.71
  None 84.5% (180) 15.5% (33) 1
Time of day
  Morning 85.8% (386) 14.2% (64) 0.60 (0.40-0.91) 0.03
  After noon 88.9% (442) 11.1% (55) 1
Day
  Monday 83.2% (663) 16.8% (97) 0.98 (0.71- 1.34) 0.49
  Tuesday 87.7% (455) 12.3% (64) 0.94 (0.662- 1.33) 0.73
  Wednesday 87.6% (572) 12.4% (96) 1.12 (0.815- 1.54) 0.48
  Thursday 88.7% (425) 11.3% (54) 0.85 (0.59- 1.23) 0.38
  Friday 87.0% (541) 13.0% (81) 1
Treatment
  Consultation 81.8% (139) 18.2% 31 0.96 (0.39-2.38) 0.92
  Records 86.7% (78) 13.3% (12) 0.66 (0.24-1.83) 0.43
  Bonding 93.8% (196) 6.2% (13) 0.28 (0.11-0.77) 0.01
  Review/adjustment 87.4% (1995) 12.6% (288) 0.62 (0.27-1.42) 0.26
  Debonding 85.7% (6) 14.3% (1) 0.71 (0.07-6.92) 0.77
  Retainer/retention 84.2% (213) 15.8% (40) 0.81 (0.33-1.96) 0.63
  Others 81.1% (30) 18.9% (7) 1

Morning appointments (10.00am–1.00pm) had more FTAs than the afternoon appointments (2.00–5.00pm) (p < 0.05) (Tables II and III). Bonding appointments had a significantly lower failure rate compared with other treatment procedures with an attendance rate of 93.8% (p < 0.01). Monday was likely to have a higher FTA rate (p < 0.05) (Tables II and III).

FTA rates decreased from 2013 to 2019 after the automatic SMS text reminder system was implemented (p < 0.05 for all) (Tables IV and V).

Comparison of non-attendance between 2013 and 2019

Variable B Std. Error Exp (B) 95% CI P-value
Ethnicity
  NZ European 0.40 0.10 1.49 1.24-1.80 0.00
  Māori -0.15 0.27 0.86 0.51-1.48 0.59
  Asian -0.54 0.41 0.59 0.26-1.30 0.19
  Others 0.33 0.37 1.39 0.67-2.78 0.37
Gender
  Male 0.22 0.12 1.24 0.98-1.57 0.07
  Female 0.32 0.11 1.37 1.10-1.72 0.01
Age group
  <12 0.11 0.24 1.12 0.70-1.79 0.64
  13-18 0.49 0.10 1.63 1.33-2.00 0.00
  19-25 -0.07 0.21 0.94 0.62-1.41 0.76
  26-49 -0.29 0.46 0.75 0.30-1.85 0.53
  50-64 0.19 0.82 1.21 0.24-6.04 0.82
  65+ -18.74 0.00
Suburb index
  <900 1.64 0.66 5.17 1.43-18.69 0.01
  901-950 0.21 0.15 1.23 0.91-1.66 0.17
  951-1000 0.30 0.17 1.35 0.97-1.90 0.08
  1001+ 0.15 0.16 1.16 0.84-1.59 0.37
  Others 0.57 0.21 1.78 1.18-2.67 0.01
Time of day
  Morning 0.40 0.11 1.50 1.21-1.84 0.00
  Afternoon 0.09 0.13 1.09 0.84-1.42 0.50
Day
  Monday 0.52 0.17 1.68 1.20-2.35 0.00
  Tuesday 0.23 0.21 1.26 0.84-1.89 0.26
  Wednesday -0.01 0.17 0.99 0.72-1.38 0.97
  Thursday 0.50 0.20 1.65 1.12-2.42 0.01
  Friday 0.16 0.20 1.17 0.79-1.73 0.43
Treatment
  Consultation -0.67 0.27 0.94 0.55-1.60 0.81
  Records 0.22 0.58 1.25 0.40-3.88 0.70
  Bonding 1.62 0.87 5.03 0.92-27.40 0.06
  Review/adjustment 0.43 0.10 1.54 1.27-1.87 0.00
  Debonding -0.66 1.18 0.52 0.05-5.19 0.58
  Retainer/retention -0.36 0.23 0.70 0.45-1.09 0.12
  Others -0.42 0.61 0.66 0.20-2.17 0.49
Month
  August 0.62 0.16 1.85 1.36-2.51 0.00
  September 0.26 0.15 1.29 0.97-1.73 0.08
  October 0.05 0.13 1.05 0.81-1.36 0.71
Discussion

The present study analysed the non-attendance of appointments at the University of Otago Dental School’s Orthodontic Clinic. The overall nonattendance rate in 2013 was significantly higher than that in 2019. The introduction of SMS text reminders was a likely factor for this improvement in attendance rate which was consistent with other studies reporting similar results.10,11 The findings suggested that patients of lower SES may be more likely to miss their appointments compared with higher SES patients. Bonding appointments had a significantly higher rate of attendance compared with other types of appointments.

A limitation of the present study was that only three months of data were analysed. This was considered due to the nature of the orthodontic course as postgraduate orthodontic students have clinical breaks from November to January, June to July and an Easter break in April; the months of August to October had relatively less interruption due to public holidays. For a more robust study, an analysis of attendance throughout a 12-month period may be more accurate. An additional limitation was that reasons why patients missed their appointments were not collected and further research into identifying reasons would be useful in improving attendance rates.

With the introduction of the digital Titanium management system, patients were able to receive text reminders of their appointments, and were therefore more likely to remember compared with those without text reminders. Although the literature shows varied results related to appointment reminders and attendance rates, it has been noted that patients who received either postal or telephone reminders were more likely to attend their appointments.12 There have also been multiple studies that have indicated the effectiveness of SMS text reminders in improving attendance in health care settings.10,11 A similar study was undertaken in a dental setting and results revealed that SMS appointment reminders significantly reduced the number of failed appointments.13

The present results have shown that patients with morning appointments were more likely to fail to attend than those with the afternoon appointments. In addition, it was noted that certain days of the week appeared to have a higher rate of non-attendance, in particular Monday appointments. This is in agreement with the previous studies in which it was found that patients with morning appointments were less likely to cancel or FTA compared with afternoon appointments.4,14 A study by Storrs et al., also revealed that Monday appointments had a higher rate of failure and suggested amendments in the number of non-attended appointments such as rescheduling Monday appointments to an alternative session when the proportion of non-attendance is lower.4 Failure to attend appointments places pressure on the management of the clinic and decreases the efficiency for both clinicians and patients. Patients who fail to receive treatment at an optimal time, may extend treatment duration which may be more harmful than not starting treatment.15

It has been suggested that FTA appointments may be reconsidered for double bookings, or by booking extra patients to overcome the problem.16 This may also be a reason why bonding appointments had a significantly lower rate of non-attendance compared with other treatment appointments. Public system patients have often waited a long time to receive orthodontic treatment and have anticipated the start and may be less likely to fail to attend their initial bonding appointment.

In New Zealand, it is reported that Maori and Pasifika people are largely represented in the relatively lower SES groups.17 Statistics show that Maori and Pasifika people had poorer oral health outcomes and were less likely access dental services.18 This is also reflected in the current data as Maori and Pasifika people had the highest level of nonattendance amongst the different ethnicities in 2019 and the second highest in 2013. A failure to attend appointments meant that they missed out on required treatment, which could lead to poorer oral health outcomes. Patients from lower income families were more likely to miss appointments and this may be due to factors related to the difficulty in taking time off of work, a lack of transportation or access to transport, or orthodontic appointments not being a priority. This is supported by earlier studies and national data that have reported that patients from lower socio-economic areas were more likely to miss their appointments.9,18 The National Health Service (NHS) has stated that, although dental care is free for children and certain groups of adults, patients from lower socio-economic areas are least likely to nonattendance attend their annual dental visits.19 More research is required to improve attendance rates in patients from lower socio-economic areas.

Improving FTA rates will help increase clinic productivity and further reduce the loss of clinical teaching hours, resources, and cost. This is particularly important at education institutions as students rely heavily on patient attendance to fulfil their treatment and academic requirements. More information would also be useful to determine the relationship between oral health status and attendance as studies show that participants with optimal oral hygiene practices were almost six times more likely to attend appointments.20 Although the SMS text reminders have shown attendance rate improvements, other efforts such as telephone reminders and smart phone ‘apps’, as well educating patients of the importance of attendance should be implemented to increase compliance.

Conclusion

The failure to attend orthodontic appointments was approximately 15% in the Otago University’s Orthodontic Clinic, New Zealand. Patients of lower socioeconomic status, Maori and Pasifika peoples and morning appointments showed higher FTA rates. Bonding appointments had the lowest FTA rate. FTA significantly decreased after the introduction of a SMS text reminder system. The results of the present study may be useful in predicting potential missed appointments and further, to implement strategies that target particular groups to improve attendance rates for the enhancement of clinical efficiency (Table VI).

Comparison of attendance between 2013 and 2019

Variable B Std. Error Exp (B) 95% CI P-value
Ethnicity
  NZ European -0.40 0.10 0.67 0.557-0.807 0.00
  Mā ori -0.15 0.27 1.60 0.68-1.98 0.59
  Asian 0.54 0.41 1.71 0.77-3.79 0.19
  Others -0.33 0.37 0.72 0.35-1.48 0.37
Gender
  Male -0.22 0.12 0.81 0.64-1.02 0.07
  Female -0.32 0.11 0.73 0.59-0.91 0.01
Age group
  <12 -0.11 0.24 0.89 0.56-1.43 0.64
  13-18 -0.49 0.10 0.62 0.50-0.75 0.00
  19-25 0.07 0.21 1.01 0.71-1.61 0.76
  26-49 0.29 0.46 1.33 0.54-3.29 0.53
  50-64 -0.19 0.82 0.83 0.17-4.13 0.82
  65+ -0.34 1.53 0.71 0.04-14.35 0.83
Suburb index
  <900 -1.64 0.66 0.19 0.05-0.70 0.01
  901-950 -0.21 0.15 0.81 0.60-1.10 0.17
  951-1000 -0.30 0.17 0.74 0.53-1.04 0.08
  1001+ -0.15 0.16 0.87 0.63-1.19 0.37
  Others -0.57 0.21 1.78 1.18-2.67 0.01
Time of day
  Morning -0.40 0.11 0.67 0.54-0.83 0.00
  Afternoon -0.09 0.13 0.92 0.71-1.19 0.50
Day
  Monday -0.52 0.17 0.60 0.43-0.84 0.00
  Tuesday -0.23 0.21 0.79 0.53-1.19 0.26
  Wednesday 0.01 0.17 1.01 0.73-1.40 0.97
  Thursday -0.50 0.20 0.61 0.41-0.89 0.01
  Friday -0.16 0.20 0.85 0.58-1.26 0.43
Treatment
  Consultation 0.67 0.27 1.01 0.63-1.83 0.81
  Records -0.22 0.58 0.80 0.26-2.49 0.70
  Bonding -1.62 0.87 0.20 0.04-1.09 0.06
  Review/adjustment -0.43 0.10 0.65 0.54-0.79 0.00
  Debonding 0.66 1.18 1.93 0.19-19.39 0.58
  Retainer/retention 0.36 0.23 1.43 0.91-2.25 0.12
  Others 0.42 0.61 1.52 0.46-4.89 0.49
Month
  August -0.62 0.16 0.54 0.40-0.73 0.00
  September -0.26 0.15 0.77 0.58-1.03 0.08
  October -0.05 0.13 0.95 0.74-1.23 0.71
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Medicine, Basic Medical Science, other