Article Text

Original research
Prevalence and factors associated with missed hospital appointments: a retrospective review of multiple clinics at Royal Hospital, Sultanate of Oman
  1. Ahmed Alawadhi1,
  2. Victoria Palin2,
  3. Tjeerd van Staa2
  1. 1Health Informatics, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, UK
  2. 2Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
  1. Correspondence to Ahmed Alawadhi; ahmed.alawadhi-2{at}postgrad.manchester.ac.uk

Abstract

Objectives Missed hospital appointments pose a major challenge for healthcare systems. There is a lack of information about drivers of missed hospital appointments in non-Western countries and extent of variability between different types of clinics. The aim was to evaluate the rate and predictors of missed hospital appointments and variability in drivers between multiple outpatient clinics.

Setting Outpatient clinics in the Royal hospital (tertiary referral hospital in Oman) between 2014 and 2018.

Participants All patients with a scheduled outpatient clinic appointment (N=7 69 118).

Study design Retrospective cross-sectional analysis.

Primary and secondary outcome measures A missed appointment was defined as a patient who did not show up for the scheduled hospital appointment without notifying or asking for the appointment to be cancelled or rescheduled. The outcomes were the rate and predictors of missed hospital appointments overall and variations by clinic. Conditional logistic regression compared patients who attended and those who missed their appointment.

Results The overall rate of missed hospital appointments was 22.3%, which varied between clinics (14.0% for Oncology and 30.3% for Urology). Important predictors were age, sex, service costs, patient’s residence distance from hospital, waiting time and appointment day and season. Substantive variability between clinics in ORs for a missed appointment was present for predictors such as service costs and waiting time. Patients aged 81–90 in the Diabetes and Endocrine clinic had an adjusted OR of 0.53 for missed appointments (95% CI 0.37 to 0.74) while those in Obstetrics and Gynaecology had OR of 1.70 (95% CI 1.11 to 2.59). Adjusted ORs for longer waiting times (>120 days) were 2.22 (95% CI 2.10 to 2.34) in Urology but 1.26 (95% CI 1.18 to 1.36) in Oncology.

Conclusion Predictors of a missed appointment varied between clinics in their effects. Interventions to reduce the rate of missed appointments should consider these factors and be tailored to clinic.

  • health informatics
  • information management
  • information technology
  • telemedicine
  • health services administration & management
  • organisation of health services

Data availability statement

Data may be obtained from a third party and are not publicly available.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Strengths and limitations of this study

  • Large data set including data from multiple clinic specialties.

  • Provides information about the frequency and drivers of missed hospital appointments in non-Western country (Oman) over 5-year period.

  • Substantial missing data for some of the risk factors (not missing at random); a missingness indicator variable was used in the logistic models.

  • The study examined one hospital from the tertiary care level and results may not be generalisable to other care levels.

Background

A missed appointment has been defined as a patient who does not show up for the scheduled hospital appointment without notifying the heath care facility or asking for the appointment to be cancelled or rescheduled.1 Missed hospital appointments are a challenge to healthcare systems around the world. In the USA, it is estimated that 5%–55% of hospital appointments are missed.2–4 In the UK, 1 in 10 outpatient appointments are missed annually in the National Health Service.5 A missed hospital appointment affects work flow, reduces patient and staff satisfaction and can lead to a loss in revenue as well as having a negative impact on patient’s health.6

Several studies have explored the reasons for a missed hospital appointment. Some patient-related reasons include forgetting, being confused about the appointment date and time, not receiving an appointment reminder, not having transportation to attend, work or family commitments, feeling unwell or being admitted to the hospital on the same day of the appointment.7–12 Factors associated with missed hospital appointments around the world include age, sex, appointment time, how long it took to get an appointment, distance to the hospital, marital status and socioeconomic level.13–17 Different strategies have been used to reduce the rate of a missed hospital appointment. The most common strategies used were short message service (SMS) text message reminders, phone call reminders, overbooking of the appointments, charging a fine to patients who miss their appointment and the use of an online scheduling system to ease the process of appointment cancellation and rebooking.18–23

There is a lack of information about the frequency and drivers of missed hospital appointments in non-Western countries such as Oman. The limited knowledge available tends to focus on overall rates of missed hospital appointments within one specialty. The aim of this study was to evaluate the rate and predictors of missed hospital appointments in the main tertiary referral hospital in Oman (Royal Hospital). In particular, this study focused on the unique tertiary hospital located in the capital city, Muscat, because patients who require specialised consultation and treatment can only receive treatment by referral to this tertiary hospital. The specific objectives were to identify the rate of missed appointments over time and identify the variation between different specialty clinics in the rate and predictors of missed appointments.

Methods

Study design

A retrospective cross-sectional analysis including patients with a scheduled appointment between 1 January 2014 and 31 December 2018 at the Royal Hospital in the capital city Muscat, Oman.

Setting

The sultanate of Oman is located in the southeast part of the Arabian Peninsula. The total population of 4 618 268 (2019) includes 2 655 453 Omani and 1 962 815 non-Omani habitants. The population is spread over 309 500 km2. There are 61 Walayats (cities) making up 11 governorates (see online supplemental figure 1) for a map of Oman depicting the governorates regions).

The government manages the healthcare system in Oman where there are three levels of healthcare facilities: primary, secondary and tertiary hospitals. Some additional hospitals are managed by other government sectors such as The Royal Police hospital, The Armed Force hospital and Sultan Qaboos University Hospital. In addition to hospitals, there are 207 local health centres throughout Oman. These centres provide primary health services, similar to general practice in the UK health system. Patients can seek basic health services at these centres before referral to specialist hospitals.

The Royal hospital located in the capital city of Muscat has 50 specialty and subspecialty clinics. It is considered a referral tertiary care hospital that receives patients from all regional primary and secondary hospitals in the Sultanate of Oman. The Royal hospital has 630 beds providing inpatient, outpatient and emergency medical service. The national cardiac centre, the national oncology centre and the national diabetic centre are all within the Royal Hospital. It is also the only government hospital that provides cancer care. Around 500 patients are referred to the outpatient’s clinics daily. Omani citizens, citizens of other GCC countries (The Cooperation Council for the Arab States of the Gulf) and expatriates working in the government sector receive free medical service with the requirement to pay an annual fee equating to two Great British Pound sterling for the maintenance of their patient record, alongside a visit fee equating to 50 Pence for each hospital visit.

Study sample

The final study sample included 769 118 scheduled appointments at the Royal Hospital. Figure 1 shows the exclusion process and the final analysis-ready data sets generated. A total of 893 observations were excluded in the first step due to outlying age for the clinic or appointments recorded on a Saturday and for duplication. Then, 53 710 appointments were excluded because of the missing data for age, medical specialties, service cost, governorates and appointment waiting days. The remaining 769 118 observations were divided three data sets: one data set including appointments from Paediatric clinic only (N=1 68 699), another data set including appointments from Obstetrics and Gynaecology clinic only (N=1 27 537), and an overall data set including appointments from all remaining medical specialties, except for Paediatrics and Obstetrics and Gynaecology (N=4 72 882). The reason for not including Paediatrics or Obstetrics and Gynaecology appointments into the overall data set was because the age and sex structure was different from other clinics and this would cause analytical problems in the regression model as some of the age and sex categories would be empty. The Paediatric clinic only included children who were 18 years or less, and the Obstetrics and Gynaecology clinic appointment included female patients only.

Figure 1

Inclusion and exclusion criteria for the study population.

Regression models were performed separately for the overall data set (N=4 72 882) adjusting for medical specialty; the Paediatric data set (N=1 68 699) and the Obstetrics and Gynaecology data set (N=1 27 537). Then, from the overall data set, five subsets of data were created, one for each of the top five clinics with (a) a large sample size (and, therefore, reasonable numbers of cases and controls) and (b) a higher rate of missed appointment. Separate model was then performed for these top five clinics including Diabetes and Endocrine clinic (N=84 769), Surgery clinic (N=74 762), Oncology clinic (N=62 041), Urology clinic (N=46 825) and Gastroenterology clinic (N=29 277).

Measures

The outcome of interest was a missed outpatient hospital appointment. This was defined, in line with previous research,24 as a patient who had a scheduled appointment but did not attend the appointment without contacting the hospital to cancel or rebook his/her appointment and is recorded in the system as failed to attend. The following predictors were evaluated: age, sex, the day, month and year of the appointment, marital status, region of patients’ residence (defined by the governorate), service cost, appointment waiting time, education level, patients’ nationality and specialty clinic. The appointment date was subtracted from the appointment schedule date to calculate the number of days that patients waited for their appointment. The Walayat parameter was used to group patients according to the 11 governorates in the Sultanate of Oman (online supplemental figure 1). Clinics within the same specialty were grouped together under one department making up 23 medical specialties. Education, nationality and financial level parameters were categorised into larger groups due to small numbers.

Data collection

The Royal Hospital uses electronic health records (EHRs) to record and store all clinical and non-clinical patient information. The EHRs (recorded to the ALSHIFA system; V.3+) were used to extract data for all patients who had a scheduled outpatient clinic appointment.

Statistical analysis

Descriptive statistics were used to describe the rate of missed hospital appointments. Conditional logistic regression was performed to determine the relationship between each factor and the likelihood of missing a hospital appointment with statistical adjustment for each variables (estimating the adjusted OR and 95% CIs). Independent predictors included age category, sex, appointment status (missed or attended), appointment day, appointment month, appointment year, marital status, governorate and the financial contribution service cost, appointment waiting days, education level and nationality. The R statistical programme (V.3.6.2) was used for the statistical analyses.25 26 An overall model was performed for all clinics (excluding Obstetrics and Gynaecology and Paediatric clinic) adjusting for clinic, and individual models were also performed for each of the clinics with the highest rate of missed hospital appointments. The logistic models stratified the analyses by the number of previous appointments (deciles). For example, scheduled appointments in stratum 1 included patients with no prior appointment, where those in stratum 9 had 9–15 prior appointments. For more details, see online supplemental table 1.

Patient and public involvement statement

The study did not require the involvement of patients and the public, but our future research will survey patients for the reasons of missed hospital appointments.

Results

There were 769 118 scheduled outpatient appointments between 2014 and 2018 included in the analysis. As shown in table 1, 464 081 (60.3%) of the appointments were for female patients and 166 942 (21.7%) were for patients aged between 30 and 40. A total of 171 951 appointments was missed (rate of 22.3%). The overall rate of missed hospital appointments was 22.4% in 2014 and 21.5% in 2018. When looking at monthly trends, the highest rate of missed appointments occurred in June (25.2%) and the lowest rate of missed appointments in March (20.3%). Additional baseline characteristics of the study population are found in online supplemental tables 2 and 3. Figure 2 shows the rate of missed appointments across the top seven clinics. Most appointments were missed for Urology (30.3%) followed by Gastroenterology (27.4%), then Diabetes and Endocrine (26.4%).

Table 1

Characteristics of the final study population overall and stratified by attended and missed appointments (online supplemental table 2 provides additional details)

Figure 2

Rate of missed appointment overall and by clinic, showing in the top seven clinics with the highest rate of missed appointments. *Excluding Obstetrics and Gynaecology clinics and the Paediatric clinic.

The adjusted OR of missed hospital appointment for patients with social affair coverage (exempted from all medical fees) was 0.64 (95% CI 0.60 to 0.68), indicating they were 36% less likely to miss their appointment compared with patients who had to pay the registration and visit fees (table 2). Patients living in a governorate that was further away from the hospital were more likely to attend their appointments (table 3). As example, patients living in the governorate of Musandam (540–620 km from Muscat) were 21% more likely to attend their appointment compared with patients who live in the capital city of South Batina (adjusted OR 0.79 (95% CI 0.76 to 0.82)).

Table 2

Fully adjusted ORs for the predictors of missed hospital appointment for all clinics combined (except Obstetrics and Gynaecology and Paediatric clinics)

Table 3

Distance between the Royal Hospital and each governorate and fully adjusted OR for missing appointment

Evaluating the predictors by individual clinic, a substantial heterogeneity in effects of predictors of missed hospital appointments was observed. Figure 3 shows the effects of age on missed appointments stratified by clinic. For example, a patient aged 71–80 years was a strong predictor for missing an appointment for all clinics except for Diabetes and Endocrine.

Figure 3

Age category as predictors of missed appointment stratified by clinic. *Reference group: age 31–40 years old.

Variations between clinics were also found for the number of days patients waited for their appointment. A waiting time of 60+ days was a strong predictor of missing an appointment for most clinics but had only a small effect for Oncology (figure 4). Details on the effects of other predictors by clinics are found in online supplemental tables 4–7 and figures 2–4.

Figure 4

Appointment waiting time (days) as predictors of missed appointment stratified by clinic. *Reference group: ≤30 waiting days.

Discussion

This is the first study that explored the prevalence and the factors associated with missed hospital appointments at outpatients’ clinics at tertiary referral hospital in the Sultanate of Oman. The rate of missed hospital appointments was found to vary by patient characteristics and clinics.

This study found that the overall missed hospital appointment was lower than some studies from neighbouring countries (Qatar, Iran), reporting rates of approximately 50%.3 4 Possible reasons for this could be the differences in the healthcare system structure, the healthcare coverage provided to patients by the government or variations between clinics. In addition, the rate of missed hospital appointments could have been lower in Oman because of the mobile phone SMS text reminder service implemented within the appointment system in 2010 (reminders sent 48 hours before the day of an appointment), while other studies included hospitals that did not use text reminder system. One study showed a reduction in missed hospital appointment rate from 49% to 18% when text reminder system was used.3

The current analysis showed that patients who had to wait longer for their appointment were more likely to miss their hospital appointment across all clinics. This finding was similar to the findings from the previous studies.13 15 27 This could be explained by the fact that patients who had to wait for long time will seek medical service somewhere else. In some cases, patient may have passed away while waiting for the appointment if he/she had a severe illness. Since all the healthcare services are free for all citizens, patients might find another appointment in other hospitals or seek care at private hospitals to avoid the wait.

Patients under social affair coverage were less likely to miss their appointment compared with other patients. On the other hand, patients who had to pay for all their medical service were more likely to miss their hospital appointment. This contradicts the findings from other studies, which reported that patients with low socioeconomic status are more likely to miss their hospital appointment.15 28 29 This may be because they either have no health coverage to pay for their treatment or they have limited coverage that does not cover every health service. However, in Oman, the healthcare service setting is different. All citizens receive free healthcare service with minimum charges only. Omanis with low income receive free services and are exempted from all charges and fees. As a result, not attending hospital appointment for patients who are under social affair coverage will be more costly for them because they will have to seek health service in private hospitals and pay for the service. On the other hand, patients who have to pay for all their medical services (expatriates only) were more likely to miss their appointment. This might be explained by the fact that since they pay for the health service, they might prefer to go to a private hospital without having to wait for their appointment since in both scenarios they will end up paying for their treatment.

The months of May, June, July and August were the highest for missed appointments. Previous studies support this finding showing that patients tend to miss more appointments in summer compared with the rest of the year because of high temperature.14 Giunta et al also stated that patients tend to miss more appointments during the holiday season. It is probable, with higher temperature of 40°C in May through to August in Oman, that patients are either on holiday or unable to travel in the extreme heat (June, July and August).13 30

Patients who are living in governorates located far away from the hospital are more likely to attend their appointment compared with patients in closer location overall and by clinic. This finding contradicts with the findings from other studies, that long travelling time is associated with high rates of missed appointments.28 This may be explained by the fact that some governorates only provide basic healthcare services, meaning patients have less access to more specialised care (public and private). As most of the referral hospitals providing specialised care are located in the capital city, patients will need to travel to the capital to receive treatment as it is not available locally. As more facilities are available in the capital and surrounding governorates, patients residing here have more available facilities and may choose to attend an appointment at an alternative facility, particularly if this reduces their waiting time.

The current analysis also showed that the younger and older patient populations were more likely to miss their appointment. This is consistent with other studies conducted in outpatient clinics that found that younger patients (17–40 years) and older patients (>65) missed more appointments.16 31 This could be explained by the fact that younger patients might have more responsibilities with school or work and are unavailable to attend their appointments, whereas older patients may be dependent on family to take them to their appointment and tend to miss their hospital appointments if families are unavailable to do so.

The analysis also showed that appointments scheduled in the beginning of the week (Sunday, Monday) were more likely to be missed compared with appointments scheduled in the end of the week (Thursday). This finding is consistent with findings from previous studies showing that patients missed more appointments scheduled on Monday and Tuesday compared with appointments towards the end of the week, Thursday and Friday.32 This can be explained by the fact that patients might have difficulties getting off work at the start of the week.

The current study has limitations as it included just one tertiary referral hospital in the capital city of Muscat. Although most specialist care is conducted at the Royal Hospital, future work may include other referral hospitals located in the capital city of Muscat to compare the rate of missed appointments within the capital city to see if this varies and if there is driving factors specific to different regions and individual hospitals. Another limitation was that this study just looked at the rate and factors associated with missed hospital appointments without looking at the reasons behind the problem either from the doctors’ or the patients’ perspectives. Work is currently ongoing to interview patients who missed their hospital appointment and clinical staff to identify the reasons from the patient’s and medical team perspectives, respectively. However, the diversity of the departments included in this study, the large sample size and the fact that it is the first attempt to investigate the rate and factors associated with missed hospital appointment in a tertiary Omani hospital are strengths of this study.

Conclusions

In conclusion, our study showed that age, service cost, waiting days for appointment, governorate (distance from hospital) and month of the appointment had substantive effects on the rate of missed hospital appointments. These predictors also varied between clinics in their effect on the rate of missed appointments. Interventions to reduce the rate of missed hospital appointments should consider these variations between clinics and be tailored to each clinic.

Data availability statement

Data may be obtained from a third party and are not publicly available.

Ethics statements

Ethics approval

The study was approved by the Study and Research Centre, Ministry of Health, Sultanate of Oman in 2 May 2019 (proposal ID: MoH/CSR/19/10045).

Acknowledgments

The researchers express their appreciation to the Centre for Research and Study in the Ministry of Health, Sultanate of Oman for the approval of this study and the Directorate General of Information Technology for providing the required data (Mr.Abdullah Al Raqadi).

References

Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

Footnotes

  • Contributors AA drafted the ethics application, analysed, interpreted the EHR data and drafted the manuscript. VP oversaw the statistical analyses and reviewed the manuscript. TvS reviewed the ethics application, supervised AA and reviewed the manuscript. All authors read and approved the final manuscript.

  • Funding This study was funded by the Ministry of Higher Education, Scientific Research and Innovation, Sultanate of Oman. Grant/Award Number: PGE24720.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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