Clinic Visit No-Shows and Last-Minute Cancellations are Common Among Teens and Emerging Adults with Type 1 Diabetes

Abstract

Aims:

This study aimed to compare demographic and clinical information of teens and emerging adults with type 1 diabetes (T1D) by endocrinology visit completion status (no-showed, cancelled last-minute [within 8 days], attended).

Methods:

3 endocrinology clinic schedules (2 paediatric, 1 adult) were reviewed weekly over a 6-month period to identify people with T1D (≥1 year) ages 15–35. A1c, demographics, and use of emergency department (ED)/inpatient care over the last year were recorded. We compared these factors by visit completion status using ANOVA, chi-square, and Fisher’s exact tests.

Results:

Of 529 individuals, 9% no-showed and 21% cancelled their visit last-minute. Among those who cancelled, private insurance was more common than public (60% vs 38%, respectively) which differed from those who no-showed (40% vs 53%, p<0.001). A1c was higher in people who no-showed (79 mmol/mol, 9.4%) than cancelled (67 mmol/mol, 8.2%) or completed visits (62 mmol/mol, 7.8%, p<0.001). Those who no-showed were more likely to have 2+ ED visits/hospitalizations in the last year compared to those who cancelled or attended (21% vs 11% vs 6%, respectively; p=0.013).

Conclusions:

Among 15–35-year-olds with T1D no-shows and last-minute cancellations were common. Those who cancelled last-minute had higher A1cs and greater ED/hospital use than those who completed visits, though these were not as high as in those who no-showed. Mechanisms to identify and ensure appropriate follow-up among individuals with last-minute cancellations should be explored.

Introduction

Visit attendance and continuity of care (consistent contact with a particular provider or practice) are pressing issues in adolescents and emerging adults with type 1 diabetes (T1D). No-shows, while problematic, are visible to providers, while last-minute cancellations (which we define here as within 8 days of the appointment) may go unnoticed. Missed appointments are associated with reduced continuity of care and negative individual-level health outcomes. Visit no-shows in primary care clinics are associated with greater emergency department (ED) and hospital use,¹ and with higher A1c^1,2 among people with diabetes. In children with T1D, those with higher rates of diabetic ketoacidosis (DKA) had lower continuity of care and lower likelihood of completing preventative ophthalmology appointments.³ In a paediatric endocrinology clinic, Fortin et al. found that over a 43-month-period, individuals with T1D who no-showed 2 or more appointments were 3 times more likely to have experienced both DKA and an A1c greater than or equal to 69 mmol/mol (8.5%).⁴ No-shows are also associated with higher mortality in children with insulin-treated type 2 diabetes (T2D).⁵ Because they can lead to available appointment slots going unused, these missed visits may result in inefficiencies in the healthcare system contributing to higher wait times, suboptimal resource utilization, and reduced appointment availability.⁶

Younger adults with T1D or T2D have been found to be less likely to attend diabetes clinic visits than older populations, contributing to greater gaps in care.⁷ Teens and emerging adults with T1D are particularly vulnerable, as this period is associated with significant life changes, including the transfer from paediatric to adult care. One study reported 34% of emerging adults with T1D had a gap >6 months in establishing adult care.⁸ Emerging adults with T1D experience higher A1cs with only 14% meeting glycemic targets.⁹ Additionally, one-third of adolescents with T1D have evidence of at least one early diabetes-related complication.¹⁰ The challenges in diabetes management faced by adolescents and emerging adults emphasize the need for further investigation into appointment adherence in this population.

Although significant literature exists regarding no-shows or missed appointments, last-minute cancellations have not been extensively studied and are more likely to go unnoticed. We aim to characterize differences between adolescents and emerging adults with T1D who no-showed, cancelled last minute, and attended endocrinology visits.

Methods

In conducting in-person recruitment for a separate cross-sectional study, we received institutional review board approval to collect de-identified demographic and clinical information for all eligible individuals without requiring informed consent. Every Thursday over a 6-month period, we reviewed the schedules of the following week (Monday-Friday) of 3 endocrinology clinics (2 paediatric, 1 adult) to identify people who were diagnosed with T1D at least 1 year prior, ages 15–35 years, could read/speak English, and did not have significant cognitive or developmental disorders, pregnancy, conditions leading to inaccurate A1c reading, severe/untreated psychological illness, or major medical conditions such as malignancy or recent organ transplant. Our aim was to understand the differences between those that no-showed, cancelled last-minute, or attended their diabetes appointment. Our primary outcome was A1c. We hypothesized that those who cancelled last minute would have higher A1c than those who attended the index visit. Important secondary outcomes included use of emergency care or hospitalization for any reason and demographic characteristics.

We reviewed the electronic medical record of each eligible person with an upcoming appointment in the following week and manually recorded the demographic and clinical information from their medical record. This information included gender, age, insurance type (public, private, or self-pay), most recent A1c, number of days between the appointment and when the last A1c was collected, and details of healthcare usage in the 12 months prior to their appointment (including number of other completed endocrinology appointments, number of other no-shows or cancellations in the endocrinology clinic, and number of ED visits/hospitalizations).

The number of ED visits/hospitalizations in the last year were categorized as 0, 1, and 2+ in order to identify individuals who were routinely using a higher level of care. ED visits/hospitalizations of any cause were recorded, and they were limited to visits within our multi-center academic medical system, which includes 13 individual hospital campuses.

We recorded the most recent A1c from the electronic medical record. These were taken either from point-of-care (POC) or central laboratory analyses. Those with an A1c listed as “>14% (equivalent of 130 mmol/mol)” were recorded as 14.1% (131 mmol/mol).

On the day of the scheduled appointment, we recorded whether the person no-showed, cancelled last-minute (within 8 days of the appointment), or completed the appointment. Only the first visit for each individual that appeared on the schedule during the 6-month period was recorded for analysis. Individuals who had never had an A1c recorded within our system (n=4) were excluded from analysis, as we did not have a measure of the primary outcome.

A query was run in the electronic medical record within these 3 clinics over the same 6-month period to identify the total number of appointments. These were categorized based on whether the individual no-showed, cancelled last-minute (within 8 days of their appointment), or attended the appointment among the entire clinic population.

We compared the demographic and clinical factors by visit completion status (no-showed, cancelled last-minute, or attended) using ANOVA for continuous data, and chi-square or Fisher’s exact tests, as appropriate, for categorical data using SAS and JMP (Cary, NC) for statistical analysis. Statistical significance was defined as p < 0.05. Given concerns for differences between POC and central laboratory A1cs, stratified ANOVA of A1c by visit completion status was conducted as a sensitivity analysis, stratifying by type of A1c. Additionally, we calculated z-scores for the A1cs by type and combined these for ANOVA analysis as another sensitivity analysis.

Results

Over the 6-month period of data collection, 533 unique individuals met criteria for the study. Those with no A1c data available in the chart were excluded from analysis (n=4), so 529 individuals were included in the sample. The mean age of our sample was 23.7±6.3 years, and we found that those who cancelled were older than those who no-showed or completed their visit (p=0.028, Table 1). There were no significant differences in appointment attendance by gender (p=0.568). Of those who cancelled, 60% had private insurance, 38% had public insurance, and 2% were self-pay. This differed from those who no-showed, where 40% had private insurance, 53% had public insurance, and 6% were self-pay (p<0.001, Table 1).

Table 1 –

Background and demographics

	Total (N=529)	No-shows (n=47, 9%)	Last-Minute Cancellations (n=110, 21%)	Completed Appointments (n=372, 70%)	p-value*
Age (years) M±SD	23.7±6.3	23.8±6.4	25.1±6.1	23.3±6.3	0.028
Gender, n (%)					0.568
Male	238 (44%)	25 (53%)	52 (47%)	157 (42%)
Female	274 (52%)	21 (45%)	53 (48%)	200 (54%)
Trans/Non-Binary	21 (4%)	1 (2%)	5 (5%)	15 (4%)
Insurance, n (%)					<0.001
Private+	341 (64%)	19 (40%)	66 (60%)	256 (69%)
Public#	181 (34%)	25 (53%)	42 (38%)	114 (31%)
Self-Pay	7 (1%)	3 (6%)	2 (2%)	2 (1%)

^*p-values from ANOVA (age) or Fisher’s exact test (gender, insurance).

⁺Private includes those with private insurance and those with Tricare.

^#Public includes those with Medicaid and those receiving hospital-based financial assistance.

Those who no-showed their appointment had significantly higher A1c (79 mmol/mol, 9.4%) than those who cancelled (67 mmol/mol, 8.2%) or completed (62 mmol/mol, 7.8%, p<0.001, Table 2) their appointment. In the sensitivity analysis stratified by type of A1c, the same trends were seen among both lab and POC A1cs, and the relationship remained statistically significant (p=0.001 for POC A1c and p=0.004 for lab A1c, Supplementary Table 1). In the sensitivity analysis combining the z-scores of A1cs by type, the differences in A1cs by visit outcome remained statistically significant (p=0.001 for POC A1c, p=0.004 for lab A1c, p <0.001 for all A1c z-scores, Supplementary Table 2). There were no differences between days since last A1c or days since last completed appointment (Table 2). Those who attended the index appointment had completed more appointments (2.7±1.8) in the last 12 months than those who cancelled (2.3±1.6) and those who no-showed (2.1±1.6, p=0.028). Those who no-showed the index appointment had missed more appointments in the last 12 months (2.5±2.3), than those who cancelled (1.8±1.6), and those who attended (1.3±1.5, p<0.001). Those who no-showed the index appointment were most likely to have had 2 or more ED/hospital visits in the last 12 months followed by those who cancelled and then by those who completed the visit (21% vs 11% vs 6%, p=0.013, Table 2).

Table 2 –

Clinical Outcomes

	Total (N=529)	No-shows (n=47, 9%)	Last-Minute Cancellations (n=110, 21%)	Completed Appointments (n=372, 70%)	p-value*
A1c (mmol/mol) M±SD	65±22	79±27	67±23	62±21	<0.001
A1c (%) M±SD	8.1±2.0	9.4±2.4	8.2±2.1	7.8±1.9	<0.001
Days since A1c M±SD	168±127	135±85	174±139	170±127	0.170
Days since Last Appt M±SD	156±113	163±146	156±117	155±107	0.884
Completed Appts M±SD	2.5±1.7	2.1±1.6	2.3±1.6	2.7±1.8	0.028
Cancellations and No-Shows M±SD	1.5±1.7	2.5±2.4	1.8±1.6	1.3±1.5	<0.001
ED Visits or Hospitalizations					0.013
0	434 (82%)	33 (70%)	89 (81%)	312 (84%)
1	51 (10%)	4 (8%)	9 (8%)	38 (10%)
2 or more, n (%)	44 (8%)	10 (21%)	12 (11%)	22 (6%)

^*p-values from ANOVA (A1c, Days since last A1c, Days since last Appt, Completed Appts, Cancellations and No-Shows), or Fisher’s exact test (ED Visits or Hospitalizations)

Among those in this sample who had appointments at the adult endocrinology clinic, 9% of index appointments were no-showed and 25% were cancelled last-minute (within 8 days). In the general adult endocrinology clinic population, there were 5% no-shows and 21% last-minute cancellations. There was a numerically lower percentage of completed appointments in the adult clinic sample (67%) as compared to the adult clinic population (74%, Table 3). Among those in this sample who had appointments in the paediatric endocrinology clinics, there were 9% no-shows and 14% last-minute cancellations. The general paediatric endocrinology clinic population had 7% no-shows and 18% last-minute cancellations. In paediatrics, the percentage of completed appointments was numerically similar in the overall clinic population (75%) and in our sample (77%, Table 4).

Table 3 –

Comparison of adults in study sample with entire adult clinic

	Total (n=15717)	No-shows (n=759)	Last-minute Cancellations (n=3351)	Completed Appointments (n=11607)
Adult Clinic
Clinic Overall	15717 (100%)	759 (5%)	3351 (21%)	11607 (74%)
Study Sample	335 (2%)	29 (9%)	83 (25%)	223 (67%)

Table 4 –

Comparison of adolescents in study sample with entire paediatric clinic

	Total (n=6758)	No-shows (n=467)	Last-minute Cancellations (n=1243)	Completed Appointments (n=5048)
Paediatric Clinic
Clinic Overall	6758 (100%)	467 (7%)	1243 (18%)	5048 (75%)
Study Sample	194 (3%)	18 (9%)	27 (14%)	149 (77%)

Discussion

In this study of 529 adolescents and emerging adults with T1D, only 70% of scheduled visits were attended. The existing literature has shown that missed appointments are associated with adverse health outcomes among individuals with T1D. Last-minute cancellations have not been widely evaluated in the diabetes appointment non-adherence literature, as they are more difficult to identify and are often grouped in with no-shows. In this study, we have shown that last-minute cancellations are also associated with adverse outcomes including higher A1c and higher rates of ED/hospital usage than those who completed their appointment. While the missed appointments are likely not causative of the higher A1cs and use of emergency care, this is a high-risk group. If these individuals can be identified in clinical practice, they may benefit from targeted diabetes management support.

The emerging adults who cancelled visits were, on average, older than those who completed or no-showed their visits. As prior studies have shown that difficulty getting time off work is a common cause of missed appointments,¹¹ it is possible that older emerging adults have more work responsibilities than adolescents or younger emerging adults. The finding of a younger average age of those who no-showed is consistent with the existing literature, where adults younger than 24 years had higher no-show rates than all other age cohorts.¹² When transferring to adult care, visit non-adherence contributes to gaps in care. As of 2012, 34% of emerging adults with T1D had a >6-month gap in care when transferring to adult care.⁸ To optimally support adolescents and emerging adults in managing T1D, last-minute cancellations need to be evaluated alongside no-shows to identify those at high risk of adverse outcomes.

In this study, we found that those who no-showed were more likely to have public insurance but that those who cancelled last-minute were more likely to have private insurance. In an urban paediatric primary care clinic, common reasons for missed appointments included forgetting, transportation issues, and difficulties finding time off work.¹¹ These barriers may be more common in socioeconomically disadvantaged groups. Missed appointments are more common among lower income, single, uninsured or publicly insured people, people living in disadvantaged neighborhoods,¹³ and women who have children.¹⁴ In this study we did not directly collect socioeconomic data, but use of public insurance can serve as a proxy for socioeconomic status.¹⁵ Longer lead time (the time interval between scheduling the appointment and the appointment itself) is associated with lower likelihood of appointment adherence.¹⁶ In our subspecialty clinics, appointments are often scheduled 3–6 months in advance which could contribute to the rates of appointment non-adherence seen in this study. Characterizing the reasons for missed appointments in adolescents and emerging adults with T1D may be helpful to determine how to best support this population and will be an important area of future study.

Those who no-showed their appointment had more missed appointments in the last year than those who cancelled their appointment, who in turn had more than those who attended the appointment. While it is unknown if reducing missed appointments will impact health outcomes, several interventions have been evaluated in other populations to reduce missed appointments. In one study, reducing the appointment lead time from 12 weeks to 4 weeks was shown to reduce the relative weekly rate of no-shows and last-minute cancellations by 8.07–15.70%.¹⁷ Among people with T1D transferring from paediatric to adult care, use of a transition coordinator improved clinic attendance, reduced A1cs, and decreased hospital admissions.¹⁸ Calls from a patient navigator to people who were at high risk of no-showing appointments helped to reduce no-shows and last-minute cancellations.¹⁹ Monitoring trends in missed appointments may be helpful to identify people with T1D in need of additional support, and more research is needed to see if interventions that increase visit attendance can impact clinical outcomes.

The greatest limitation of this study is the cross-sectional study design. We cannot determine causality of the associations, and it is possible that people who had more ED visits/hospitalizations missed the appointments because of those ED visits or hospitalizations. Although this study design was necessary given how our data were collected, a prospective cohort study would allow for causal hypotheses to be evaluated and should be considered in the future. The study was conducted at a single academic medical system, so conclusions may not be applicable to all clinical settings. These numbers also underestimate the true frequency of ED/hospital care due to the collection of data from a single system, and do not take into consideration reasons for ED/hospital use. The A1cs collected from the medical record were both POC and central lab tests. POC A1c data may be less accurate,²⁰ though there is data to support combining POC and central laboratory A1cs for analysis²¹ and stratified analysis revealed that the significant relationship between A1c and visit status was maintained in both POC and central laboratory A1cs. We did not collect demographic data relating to race, ethnicity, income, or education, which may be important in understanding the makeup of the populations missing and making their appointments. This study’s strengths come from its large sample size, long duration of weekly data collection, and real-time determination of last-minute cancellations which has not been routinely included in other studies of appointment non-adherence.

Conclusion

In this study of 529 people with T1D who had an appointment at 1 of 3 academic center endocrinology clinics, 21% of people cancelled within 8 days of the visit and 9% no-showed. The known adverse associations with no-showed appointments, including higher A1cs and more frequent ED/hospital visits, were again demonstrated here. We additionally showed that those who cancelled visits last-minute had higher A1cs and required more frequent ED/hospital care than those who attended visits. More research is needed to determine how to best identify last-minute cancellations in routine clinical care, to understand the reasons behind last-minute cancellations, and eventually to design interventions that could reduce frequency of cancelled visits, particularly among adolescents and emerging adults with T1D.

Novelty Statement:

• What is known: Clinic no-shows are associated with higher A1cs and rates of diabetic ketoacidosis in people with type 1 diabetes. Emerging adults are more likely to no-show visits.

• Findings: Compared to completed visits, no-shows and last-minute cancellations were associated with higher A1cs and more frequent emergency department/hospital use. Compared to no-shows, those who cancelled were older, more likely to have private insurance, attended fewer appointments, and had more cancellations/no-shows over the last year.

• Implications: Last-minute cancellations should be monitored to identify at-risk individuals. More research is needed into last-minute cancellations including interventions to support diabetes management in this population.