Breaking barriers: Adjunctive use of the Ontario Telemedicine Network (OTN) to reach adolescents with obesity living in remote locations

Abstract

Introduction

Implementation of telemedicine has been shown to improve health outcomes, such as body mass index (BMI). However, it is unclear whether telemedicine is useful alongside traditional weight-management programmes for adolescents with complex obesity. The objective was to evaluate implementation of the Ontario Telemedicine Network (OTN), a videoconferencing programme, as an adjunctive tool to face-to-face counselling within the setting of an established interdisciplinary obesity treatment programme.

Methods

Our observational cohort included two groups of adolescents enrolled in a clinical obesity-management programme over a two year period. Adolescents (n = 50) in group 1 attended both in-person and virtual visits (OTN group), and adolescents (n = 50) in group 2 received only in-person visits (comparison group). Within the OTN group, satisfaction survey responses were compared between patients and healthcare professionals. Change in BMI per month, paediatric quality of life scores, session attendance and demographic variables were compared between groups.

Results

OTN subjects averaged 4.9 telehealth visits per adolescent over the two year programme. Both OTN and comparison groups had similar changes in BMI (p = 0.757), with increases over time (p = 0.042). Paediatric quality of life scores in both groups improved over time compared to baseline (p < 0.001), with higher scores for children compared to parental-reported child scores (p = 0.008). Both adolescents and healthcare professionals using the OTN were similarly satisfied with their experience.

Conclusion

Adjunctive use of the OTN within the setting of a weight-management programme is feasible, well accepted by families and healthcare providers, and led to similar outcomes compared to usual care.

Keywords

Obesity telehealth BMI telemedicine adolescent

Introduction

Paediatric obesity is a complex condition associated with increased risk for cardiovascular disease, type 2 diabetes, lower quality of life, psychosocial difficulties and premature death.¹ Paediatric obesity disproportionately affects certain high-risk populations. Specifically, children and adolescents living in rural and remote communities are uniquely predisposed to obesity, with a higher proportion of overweight, compared to those living in urban environments.^2–4

Traditional treatment programmes for youth with obesity involve in-person visits with an interprofessional healthcare team over time.⁵ However, distance, travel costs and inconvenience are barriers that complicate the effective delivery of paediatric obesity care.⁶ Underserved populations have infrequent access to support from their healthcare professional (HCP) because of these barriers, leading to disparities in accessing care.^7,8 Importantly, a higher frequency of clinical encounters with allied HCPs is associated with superior weight outcomes.⁵ In order to provide the best care for all patients, there is a need to address these environmental and socio-economic factors, and augment intermittent in-person care with more accessible support.

For the past 50 years, telemedicine has provided access to healthcare for patients living at a distance through secure online portals. In one paediatric study, the use of a telemedicine-based programme increased clinic attendance and completion rates for an obesity intervention with high rates of parent satisfaction.⁷ Telemedicine can be used to reinforce treatment goals and behavioural interventions from in-person clinical appointments, while increasing patient–HCP interactions. When compared to traditional programmes, telemedicine weight-management consultations also appear to demonstrate equivalent treatment benefits,^9,10 including a reduction in patient body mass index (BMI).¹¹

Previous studies have largely focused on comparing weight-management programmes designed exclusively for telemedicine use; however, the efficacy of an integrated programme combining in-person and telemedicine visits for paediatric obesity treatment is less clear. Furthermore, most telehealth interventions have been conducted with parents of overweight children as the primary participants. Studies evaluating adjunctive use of telehealth to in-person treatments are limited in children and adolescents^12,13 and, to our knowledge, there have been no studies of an integrated programme delivering specialized obesity care using a combination of in-person and telehealth visits in Canadian adolescent patients with complex obesity. Therefore, the objective was to evaluate the implementation of the Ontario Telemedicine Network (OTN), a videoconferencing programme, as an adjunctive tool to face-to-face counselling within the setting of an established interdisciplinary obesity treatment programme for adolescents with complex obesity. We hypothesized that adolescents receiving treatment through the OTN had high levels of satisfaction with the technology and, compared to those receiving face-to-face counselling, had equivalent reductions in BMI and increased quality of life scores

Methods

Subjects

This study is an observational cohort study with patients recruited from the SickKids Team Obesity Management Program (STOMP) from 2014 to 2017. Briefly, STOMP is a two year intensive programme providing quality collaborative care to adolescents (12–18 years of age) living with severe and complex obesity, and their families, within Ontario, Canada. Severe and complex obesity were defined as having a BMI percentile greater than or equal to the 99th percentile for age and sex, or a BMI greater than or equal to the 95th percentile for age and sex with significant weight-related comorbidities.^14,15 Adolescents and families were offered education and support through individual and group sessions. All sessions were held face-to-face for the first 6 months of the programme, as the initial curriculum consists of interactive group sessions and are attended in person. Following this, individuals received ongoing regular support from HCPs (dietitians, exercise counsellors, social workers and psychologists) at frequencies varying from weekly to monthly over the two year period. The focus of the programme is on making small, sustainable, healthy lifestyle changes over time. Patients also attended in-person medical visits with the physician every 6 months for monitoring of their height and weight. The telemedicine visits were offered as an option 6 months following enrolment in the programme. The study was approved by the Research Ethics Board at The Hospital for Sick Children. Written consent was obtained directly from all adolescents in the study. Compensation was provided to participants in the form of volunteer hours.

OTN group

All patients were offered the option of telemedicine appointments to supplement their “in-person” medical visits to the programme. The OTN includes the use of Personal Video Conferencing (PCVC) and Guestlink. PCVC is a system that provides secure videoconferencing facilities in nearby clinics rather than requiring patients to travel long distances to attend face-to-face appointments at the hospital. Guestlink is a teleconferencing tool whereby patients receive an electronic invitation to their OTN appointment over email. Guestlink appointments can occur at any computer, or on a mobile phone or tablet, with internet access.

Data collection

Demographic information (parental income, BMI, age, geographical distance etc.) was measured at study entry (baseline) in both the comparison (no OTN) and OTN groups. A comparison group was selected based on the first 50 patients who enrolled in the programme in a similar time frame and who did not choose to use OTN. Participants’ height (m) and weight (kg) were measured at baseline, 6, 12 and 24 months using a stadiometer and a digital scale, respectively, while in light clothing and without shoes. In addition to BMI, age- and sex-specific BMI percentiles were calculated using World Health Organization growth charts.¹⁶ Psychological measurements were completed independently by both groups, as well as by parents at baseline, 6, 12 and 24 months. The Pediatric Quality of Life Questionnaire (PedsQL 4.0) (ages 13–18 years) is a validated 23-item measurement of health-related quality of life with six subscales.¹⁷ Scores range from 0 to 100, with 100 representing the best quality of life. It has established minimal clinically important difference scores that represent the smallest detectable change in quality of life.^18,19 Healthcare satisfaction (Appendix 1) was evaluated using two different validated tools for assessing patient satisfaction regarding a healthcare experience using telemedicine: the Telemedicine Satisfaction Questionnaire (TSQ) and the Telehealth Satisfaction Survey (TeSS). Containing 15 items, the TSQ analyses patient satisfaction based on four domains: interpersonal, communication, caring, care delivery and proficiency, and is scored on a five-point Likert Scale. The TeSS contains 10 items using a Likert scale assessing satisfaction.²⁰ Both measures have high levels of internal consistency, adequate levels of inter-rater reliability and high predictive validity. Patients and HCPs who used the telemedicine technology completed the healthcare satisfaction questionnaire following their first telemedicine appointment (Appendix 1A and Appendix 1B). Both the provider and the patient questionnaire covered six questions. Three overall scores were combined from the questionnaires: technological satisfaction, usability and overall satisfaction. The technological and usability scores were the summed responses on a five-point scale, while satisfaction was rated once on a five-point scale. Scores from the healthcare satisfaction questionnaire were collected by a trained research coordinator.

Statistical analysis

Statistical Analysis Software (SAS) version 9.4 (SAS Institute Inc., Carey, NC) was used for this study. Data are presented as means ± SEM, unless otherwise indicated. Significance was considered at p < 0.05.

Two-tailed unpaired tests were used to determine differences in baseline subject characteristics between the comparison and OTN groups, unless otherwise stated. Following the first telemedicine session, technological satisfaction, usability and overall satisfaction scores were compared between HCPs and adolescent patients using a Mann–Whitney U-test, and overall satisfaction was chosen as the primary outcome.

Since STOMP is ongoing, not all participants have completed the entire two year programme. Therefore, to account for variation in programme duration, change in BMI per month (0–6, 6–12 and 12–24 months) was chosen as the secondary outcome measure. In addition, to account for the uniform face-to-face treatment from entry to 6 months in both groups, we calculated the change in BMI from 6 months to the participant’s last session and used an unpaired Student’s t-test to determine differences between groups. Since all of the following data were non-normal, a PROC GLIMMIX (GLIMMIX Procedure) was used. A two-way analysis of variance (ANOVA) was used to analyse group (OTN, comparison) and time (0–6, 6–12 and 12–24 months, and 6 months to last session) and their interaction on change in BMI and weight. A three-way ANOVA was also used to analyse group (OTN, comparison), time (baseline and 6, 12 and 24 months), audience (parents, children) and their interactions on PedsQL scores. Post hoc analysis by the Tukey–Kramer test was performed when main and interaction effects were found to be statistically significant.

Results

Patient demographics and attendance data

Both OTN and non-OTN patients had similar ages, body weights, BMIs and income levels at baseline (Table 1). On average, OTN patients attended 4.86 visits in addition to their in-person sessions. Patients receiving OTN lived approximately 62 km further from the hospital compared to non-OTN patients (p = 0.002) (Table 2). Only 1.5% of the OTN appointments were conducted through PCVC (data not shown) and the remainder of the appointments utilized the Guestlink teleconferencing tool. For in-person visits, both comparison and OTN groups had similar attendance (∼72%), cancellations (∼15%) and no-show visits (13%). For the OTN group, attendance data demonstrated that 13.0% of OTN visits were cancelled and 23.4% of OTN visits were unattended by patients. Technical difficulties accounted for 3.0% of cancellations. The majority of the OTN appointments were scheduled with a registered dietician (48.4%), exercise therapist (20.4%), psychologist (21.5%) or nurse (2.5%).

Table 1.

Group demographics.

	Comparison group	OTN group	p-value
Males:females	30:20	16:34
Age (years)	14.3 ± 0.3	14.2 ± 0.3	0.773
Weight (kg) at entry	108.0 ± 3.8	108.6 ± 3.9	0.913
BMI (kg/m²) at entry	39.7 ± 1.4	40.8 ± 1.2	0.555
# of OTN visits attended	–	4.9 ± 1.0
# of in-person visits attended	47.0 ± 3.3	46.2 ± 4.0	0.883
# of total visits (in-person + OTN)	47.0 ± 3.3	51.1 ± 3.9	0.426
Distance from hospital: (km)	30.0 ± 4.4	92.5 ± 18.3	0.002
Income: (%)			p = 0.84^a
Less than $49,999:	38%	28%
$50,000–79,999:	22%	22%
$80,000–99,999:	6%	20%
$100,000 and above:	14%	16%
Not available:	20%	14%

Data shown as means ± SEM. n = 50 per group. An unpaired Student’s t-test was used to determine differences in characteristics.

BMI: body mass index; OTN: Ontario Telemedicine Network.

Chi square was used to determine differences in the percentage of patients with income less than $49,000.

Table 2.

Patient and healthcare practitioner Ontario Telemedicine Network attendance data 2014–2017.

		Comparison group	OTN group
Patients		In-person	Telemedicine	In-person
	Scheduled visits	3238	401	3276
	Visits attended (%)	2349 (72.5)	243 (60.6)	2311 (70.5)
	Visits cancelled (%)	377 (15.8)	52 (13.0)	464 (15.3)
	No-show visits (%)	512 (11.6)	94 (23.4)	501 (14.2)
	Visits cancelled due to technical difficulty (%)	–	12 (3.0)	–
HCPs	Attended OTN visits		279
	Registered dietitian (%)		135 (48.4)
	Exercise therapist (%)		57 (20.4)
	Psychologist (%)		60 (21.5)
	Social worker (%)		20 (7.2)
	Registered nurse/nurse practitioner (%)		7 (2.5)
	Physiotherapist (%)		0 (0.0)

Comparison group, n = 50; OTN group; n = 50.

HCP: Healthcare professional; OTN: Ontario Telemedicine Network.

Satisfaction survey responses

A patient questionnaire that evaluated technological satisfaction, usability and overall satisfaction demonstrated scores of 4.0 (3.7–4.9), 4.4 (4.2–4.8) and 5.0 (4.0–5.0), respectively (Table 3). Patient satisfaction scores were compared to HCP satisfaction scores, with no significant differences.

Table 3.

HCP and patient satisfaction survey responses.

	HCP	Patient	p-value
Device used during satisfaction survey	PC: 100%	PC: 50% MacBook: 20% iPhone/Android: 20% Tablet: 10%
Technological satisfaction^a	4.2 (3.6-4.6)	4.0 (3.7-4.9)	0.654
Usability	4.4 (3.6-4.4)	4.4 (4.2-4.8)	0.282
Overall satisfaction	4.0 (3.2-4.5)	5.0 (4.0-5.0)	0.282

Data shown as median and (interquartile range). Healthcare professional: n = 11 and patients: n = 10. A Mann–Whitney U-test was used for comparisons of differences in medians.

HCP: healthcare professional; PC: personal computer.

Maximum score = 5.

Changes in BMI and weight

BMI and weight trajectories over the course of the 24-month programme were assessed in the OTN and comparison groups (Table 4). In the OTN group, 20 adolescents completed the entire 24-month programme compared to 16 adolescents in the comparison group. Since participants joined on a rolling basis, the remaining participants were either active in the programme (n = 26 OTN, 26 comparison) or had dropped out (n = 4 OTN, 8 comparison). Time (p = 0.042), but not group (p = 0.757) affected change in BMI, with change in BMI from 0–6 months significantly lower in both groups compared to 6–12 months (p = 0.032). There was no significant interaction between group and time. Similarly, time (p = 0.045), a group by time interaction (p = 0.046), but not group (p = 0.670) affected change in weight. The interaction showed that change in weight from 6–12 months was significantly higher compared to 0–6 months in the comparison group only (p = 0.028). Change in BMI and weight from 6 months to the last visit was not different between groups (p > 0.05).

Table 4.

Change in body mass index (kg/m²/month) and weight between comparison and Ontario Telemedicine Network groups.

	Group		Time (months)
	Comparison	OTN	0–6	6–12	12–24
Change in BMI (kg/m²/month)¹	0.08 ± 0.02	0.08 ± 0.03	0.04 ± 0.03^a	0.13 ± 0.03^b	0.09 ± 0.03^ab
Change in BMI from 6 months to last visit²	0.13 ± 0.04	0.13 ± 0.05
Change in weight (kg/month)³	0.47 ± 0.07	0.48 ± 0.07	0.38 ± 0.07^a	0.61 ± 0.10^b	0.41 ± 0.10^ab
Change in weight from 6 months to last visit⁴	0.49 ± 0.09	0.53 ± 0.13

Data shown as means ± SEM (n = 50 per group). A two-factor analysis of variance was used for change in body mass index and weight, with group and time as main factors. An unpaired Student’s t-test was used to determine differences between groups for change in BMI and weight from 6 months to the last visit. Means in the same row for each main factor with different subscripts (i.e. a and b) are significantly different, p < 0.05.

BMI: body mass index; OTN: Ontario Telemedicine Network.

Change in BMI was affected by time (p = 0.042) but not group (p = 0.757), or a group-by-time interaction (p = 0.215).

Change in BMI from 6 months to the last visit was not different between groups (p = 0.950).

Change in weight was affected by time (p = 0.045) and a group-by-time interaction (p = 0.046), but not group (p = 0.670).

Change in weight from 6 months to the last visit was not different between groups (p = 0.758).

Changes in quality of life scores

In children, time (p < 0.001) and audience (p = 0.008), but not group (p = 0.167), affected PedsQL scores (Table 5), with higher scores (indicating greater quality of life) at 6, 12 and 24 months compared to baseline (p < 0.001), and lower parent-for-child compared to child scores (63 versus 70, p = 0.008). There were no significant interactions for PedsQL scores.

Table 5.

Pediatric Quality of Life Questionnaire scores between comparison and Ontario Telemedicine Network groups.

	Group		Audience		Time (months)
	Comparison	OTN	Parent	Child	Baseline	6	12	24
¹PedsQL scores	67.9 ± 1.2	65.5 ± 1.2	63.5 ± 1.2^a	70.2 ± 1.1^b	62.1 ± 1.4^a	68.2 ± 1.6^b	71.3 ± 1.7^b	70.9 ± 2.4^b

Data shown as means ± SEM (n = 50 per group). A three-factor analysis of variance was used for Pediatric Quality of Life Questionnaire scores with group, audience and time as main factors. Means in the same row for each main factor with different subscripts (i.e. a and b) are significantly different, p < 0.05.

OTN: Ontario Telemedicine Network; PedsQL: Pediatric Quality of Life Questionnaire.

PedsQL scores were affected by time (p < 0.001) and audience (p = 0.008), but not group (p = 0.167) or any interactions (p > 0.05).

Discussion

Telemedicine was utilized as an adjunctive tool in the context of a two year interdisciplinary weight-management programme for adolescents with complex obesity. In the current study, we compared an integrated obesity programme combining in-person and telemedicine visits for treatment of paediatric obesity with in-person visits alone on satisfaction, changes in BMI and weight, and quality of life scores. Both groups had similar in-person attendance rates and satisfaction levels were high amongst OTN users and HCPs. Furthermore, patients who chose to experience a portion of their in-patient clinic appointments as OTN telemedicine visits did not experience a difference in their weight outcomes compared to patients with in-person visits alone. Specifically, OTN and non-OTN patients experienced similar changes in BMI per month over a two year period. Quality of life scores increased over time compared to baseline in both groups. These findings indicate that adjunctive use of the OTN within the setting of a weight-management programme is an equally efficacious medium through which to deliver care to patients with complex obesity.

Telemedicine visits were utilized by a diverse group of HCPs. Compared to previous studies where one or two HCPs participated in telehealth visits,^21,22 our study patients had access to registered dieticians, exercise therapists, psychologists, social workers, registered nurses/nurse practitioners and physiotherapists. In contrast, unlike many other telehealth interventions in paediatric obesity care, the OTN visits in our programme were largely targeted to and attended by adolescent patients, who found this modality highly satisfactory. Certain HCPs were more likely to use OTN services; dietitians, exercise therapists and psychologists were the most frequent users of adjunctive OTN, whereas nursing professionals comprised a much smaller percentage of OTN providers. This suggests that certain aspects of paediatric weight-management care may be better suited to a telehealth model compared to approaches requiring face-to-face encounters. Further exploration of this observation may be helpful in better understanding areas within obesity care that would benefit most from the adoption of adjunctive telemedicine interventions.

Despite increases from 6–12 months compared to 0–6 months, changes in BMI and body weight over time were similar between the OTN and control groups. Consistent with our results, there was no difference in BMI^a,b percentile after 1 year in 10-year-old children who were randomized to attend four visits with either a physician or four telemedicine visits.²¹ Although our OTN group attended an average of four telehealth visits in addition to their face-to-face sessions, this raises the possibility that the number of OTN visits was not sufficient to lead to reductions in BMI. In line with this, a recent randomized control trial evaluated a telemedicine initiative that provided paediatric obesity subspecialty consultation to patients and their parents (10–17 years old) in combination with counselling by primary care providers, with 12 telehealth visits and 3 in-person visits over 6 months.²³ In general, weight reduction from lifestyle modifications is greatest within the first 6 months of treatment, with subsequent regain.²⁴ Therefore, it is unclear if the benefits observed in BMI were related to the frequency of visits or the relatively short duration of follow-up.

There were no differences in PedsQL scores between OTN and comparison groups. However, PedsQL scores significantly increased over time compared to baseline, indicating greater quality of life, irrespective of the type of visit. Interestingly, parents indicated lower quality of life scores for their children compared to the adolescent’s own perception of quality of life. This is similar to a study in Malaysian adolescents and their parents, which showed lower perceived health-related quality of life of adolescents from the parent's perspective compared to the perception of the adolescent themselves.²⁵ Lower parental scores may reflect poorer perceived physical, emotional, social and school functioning unrelated to the addition of telemedicine visits to face-to-face counselling.

This study adds to the limited literature on the use of telemedicine as an adjunctive therapy within a traditional weight-management programme. However, there are several limitations. First, the retrospective cohort design prevents us from being able to randomize participants, and patients self-selected use of OTN. While the participants in each group did have similar baseline characteristics, we cannot report on other unmeasured variables such as ethnicity. Despite having a relatively large number of paediatric participants, not all of the participants have completed the entire programme since the programme is ongoing, leading to potential selection bias. However, the sample size at the two year visits was similar in both groups, and baseline characteristics, with the exception of distance, were not different. Finally, as we were unable to track the total number of hours spent participating in additional face-to-face support visits versus OTN visits, it is difficult to draw conclusions about the relative impact of the extent of the contact versus the technology itself. The strengths of the study include the overall duration of the study, frequent anthropometric measurements and high retention rates amongst patients who require complex care, as well as the diversity in socio-economic status.

In summary, adolescents with complex obesity who participated in telemedicine in addition to their in-person HCP visits showed similar attendance rates, changes in BMI, body weight and quality of life scores over time compared to their peers who received only in-person weight-management sessions. Furthermore, both patients and HCPs were highly satisfied with their OTN experience. Taken together, these results demonstrate that telemedicine is highly feasible, and can be successfully integrated as an adjunctive tool within a paediatric weight-management program to complement or substitute in-person visits. This may potentially translate into less school absenteeism, reduced travel costs, and increased convenience for patients and families. Future work should determine the optimal frequency of in-person and telehealth visits, and determine strategies to improve retention.

Supplemental Material

Supplemental material for Breaking barriers: Adjunctive use of the Ontario Telemedicine Network (OTN) to reach adolescents with obesity living in remote locations

Supplemental Material for Breaking barriers: Adjunctive use of the Ontario Telemedicine Network (OTN) to reach adolescents with obesity living in remote locations by Nicole Coles, Barkha P Patel, Ping Li, Kristina Cordeiro, Alissa Steinberg, Ana Zdravkovic and Jill K Hamilton in Journal of Telemedicine and Telecare

Footnotes

Acknowledgements

We thank the families for their participation in this programme.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: J.H. is supported by the SickKids University of Toronto Mead Johnson Chair in Nutritional Science, which provides unrestricted funds for research.

Supplemental material

Supplemental material for this article is available online.

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