Organisational models supported by technology for the management of diabetic disease and its complications in a diabetic clinic setting: study protocol for a randomised controlled trial targeting type 2 diabetes individuals with non-ideal glycaemic values (Telemechron study)

Diabetes is a non-communicable disease characterised by an elevated level of blood glucose. About 422 million people have diabetes worldwide [3]; with 1.5 million deaths every year, diabetes is the fifth cause of death and represents one of the most serious public health challenges of the twenty-first century [3]. The most common type of diabetes, type 2 diabetes mellitus (T2DM), accounts for 90% of all diabetes cases. It is often described as a lifestyle disease because of its association with modifiable risk factors, such as overweight and physical inactivity. According to the World Health Organization (WHO), the incidence of T2DM is expected to rise in both developed and developing countries, leading to an increase in the economic loss for the people affected by the diseases, the society and the health systems [3]. Considering that diabetes is one of the main causes of severe long-term conditions, such as cardiovascular events, macro- and micro-vascular complications, it is urgent to tackle it by either preventing its onset or delaying its progression [4].

The management of diabetes is a sensitive issue, particularly when considering the (perceived) quality, acceptability and easiness of the service delivery, both from a patient and healthcare staff’s perspective [5]. WHO has advocated the use of mobile health (mHealth) as a potentially effective methodology to support patients in the management of their health [6]. MHealth is defined as a “medical and public health practice supported by mobile devices, such as mobile phones” for collecting, managing and sharing health-related data between patients—clinicians and researchers [6]. Therefore, mHealth constitutes a practice that can be effectively adopted for chronic diseases such as diabetes.

As part of the swift and disruptive development and use of technology in the context of public health and health care delivery that has characterised the last decades, there have been an increasing number of mHealth tools piloted in clinical contexts and targeting patients with diabetes [7]. A relevant number of studies tried to prove how communication technologies can increase self-management [8], as well as an effective improvement of clinical outcomes and better care costs [7, 9‐11]. Recent systematic reviews and meta-analysis corroborate the effectiveness of mHealth intervention in improving clinical outcomes when compared to usual care in people with diabetes. The vast majority of these studies considered the improvement of the glycosylated haemoglobin (HbA1c) levels as their main outcome. The systematic reviews and meta-analysis of Martos-Cabrera and colleagues [12], Wu and colleagues [13] and Bonoto and colleagues [14], including both type 1 and type 2 diabetes, showed that the use of mobile apps could yield to a significant reduction of HbA1c in comparison to usual care. Authors discussed the importance of further investigating the use of mHealth since current studies regarding mHealth are very heterogeneous by population and mHealth interventions and likely to focus on short-term effectiveness only (< 12 months). The need of conducting more studies on mHealth intervention is supported by other studies results not able to find significant improvements in clinical outcomes, as reported in the systematic review and meta-analysis of Hyun and colleagues [15]. In this systematic review and meta-analysis considering T2DM adult participants and including 14 randomised controlled trials (RCTs), the superiority of using a mobile application (App) or an App with e-coaching on HbA1c levels could only be observed on a limited number of subjects and for a short-term follow-up time [15].

In order to respond to the WHO emphasis on the importance of investing in strategies and public health programmes to prevent and manage diseases through the use of mHealth [16], the Italian Ministry of Health has made funds available to conduct studies focusing on the application of technology in the management of chronic diseases.

This study protocol focuses specifically on one of the Work Packages (WP), i.e. WP4, of a wider project called “Telemedicine for home-based management of patients with chronic diseases and comorbidities: analysis of current models and design of innovative strategies to improve quality of care and optimise resource utilisation: TELEMECHRON study”. WP4 has been approved to be implemented also in the Autonomous Province of Trento (PAT), where, with a slightly lower prevalence of diabetes than in the Italian and global population, currently there are 28.000 cases of people diagnosed with diabetes (5.0% of PAT total population) [17, 18]. The aim of this specific WP is to comprehensively assess an innovative healthcare management system targeting patients with T2DM in non-ideal glycaemic control status. The system is enabled by the use of a mHealth platform called “TreC Diabete”, including an App for participants/patients and a web-based dashboard for health care staff.

The Telemechron study was designed as a multi-centre, open-label, randomised, superiority study with two parallel groups and a 1:1 allocation ratio. This study design was chosen over others because RCTs are considered the best type of study design to evaluate the effectiveness of health interventions [19].

The participants are recruited in the diabetic outpatient clinics of the Hospitals of Rovereto and Trento, which are the most relevant diabetic clinics of PAT for diabetic individuals, with an average of 30 visits per day at Rovereto, and 40 visits per day at Trento. In the Province, the prevalence of T2DM is estimated to be 5.0%. This is slightly lower prevalence than the one estimated nationally (i.e. 6.2%) [17].

Participants must meet at randomisation all the inclusion criteria and none of the exclusion criteria listed in Table 1.

Potentially eligible participants are identified during diabetes clinic appointments, either face-to-face or via a remote appointment (phone call). Clinicians of the diabetes clinics will provide standardised and key information regarding the study. If patients are interested, they will receive the information sheet to read (either face-to-face or by email). The information sheet and the consent form for the participants are originally written in Italian. At this stage, patients will be contacted by a member of the research team (registered nurse) who will also ensure that the information sheet is fully read and understood. During another dedicated face-to-face appointment, the patient who volunteers to participate in the study will provide written informed consent, provided that all questions regarding his or her involvement in the study are answered. Clinicians are responsible to sign the informed consent form with the patient during this visit.

In addition to the informed consents for the study, the researchers collect the informed and specific consents for the personal data processing activities. In fact, the processing of personal data of this research should comply with the General Data Protection Regulation (Regulation 2016/679 or “GDPR”) and the Italian Data Protection Code (Decreto Legislativo—D.Lgs 101/2018) [21, 22]. The privacy policy has been elaborated under Articles 12 and 13 of the GDPR. The legal grounds of the processing are both the explicit consent of the data subjects (as regards data concerning health) and the performance of tasks carried out in the public interest by the data controller.

By signing the informed consent, participants will allow the appointed researchers to access their medical records’, including blood test results at follow-up. Blood tests are carried out by qualified nurses who are not part of the research team but are still part of the APSS organisation. Blood tests performed within the hospital organisation do not require additional written consent.

After being approached for face-to-face screening and enrolment, eligible individuals are randomised on a 1:1 allocation ratio to the intervention or the control group.

Those allocated to the intervention group are prescribed with the TreC Diabete App. This is one of several Apps created within the so-called TreC platform, which enables citizens from PAT to access, manage and share information about their health and wellbeing in the context of telemedicine [23‐26]. TreC is an acronym for Cartella Clinica del Cittadino (Citizens’ Clinical Records), in which the citizen/patient plays the role of the focal manager and owner of his/her own health data. The technological platform has been preliminarily used for other studies targeting patients with diabetes, specifically pregnant women [27].

Clinicians will then prescribe the App for a 12-month period through the online medical dashboard. The dashboard allows the visualisation of the information shared by the participant. Moreover, it enables healthcare staff to interact directly through video-chat and chat with the participant. A menu allows clinicians to set up a specific and personalised plan for each participant: they are asked to indicate which parameter (e.g. BP) should be registered in the App and to activate reminders at set intervals. During the 12-month follow-up, clinicians will regularly check the information entered by the participant (minimum frequency of 45 days). Clinicians can provide advice based on the information shared by the participant (e.g. inviting the participant to book an appointment with their general practitioner—GP). Participants will receive the training for the use of the App as soon as they are allocated to the intervention group. A member of the research team (registered nurse) will show the participant how the App works, highlighting its different features. The appointed person will specifically show how to enter the PIN when asked, insert different types of data in the App, write in the chat, and fill in the questionnaire. Also, the registered nurse could be contacted by phone in case of problems managing the app. The app’s chat was another way to contact researchers and IT personnel to solve management problems. Paper-based training material can be provided to the participant upon request.

Table 2 depicts the App features (for the prescriber and the participant perspectives) and provides an explanation of their use.

Participants in the control group are asked to record their health-related data such as body weight, BP, glycaemic levels, results of laboratory tests and diagnostic tests as usual (e.g. on a paper diary). Other information collected by the control group participants during the follow-up period can be shared, as routinely done, with their GP.

For the App functions described above and according to the Medical Device Regulation (MDR) (EU) 2017/745 requirements [2], the TreC Diabete App cannot be considered a medical device. The App does not perform operations on clinical data; it is used as data archive and for communication and simple research purposes. It does not provide direct recommendations to participants based on algorithms; it does not make changes or alterations to the collected data and it does not transfer data with implantable devices eventually belonging to the participants. Moreover, the App does not provide direct recommendation to the clinicians for diagnosis and treatment; it cannot be used to handle emergency situations.

Table 3 depicts the list of the therapeutic goals that people with T2DM should reach set by the current national and international guidelines [28‐31].

Participants can leave the study at any time and for any reason if they wish to do so.

Adherence to the study will be monitored by the research team and clinicians. Study participants allocated to the intervention group will receive set up reminders through the App regarding the tasks that need to be done (e.g. measure and record the blood sugar level). Adherence to the study will be monitored by the research team and clinicians, as usage and interaction by the participant with the App can be checked through the dashboard. Scheduled visits at the diabetes centres can also be an opportunity to discuss possible difficulties in using the App and to remind participants why it is important to regularly record their data.

Concomitant care is permitted in line with the local standard practice. In case of relevant care actions (e.g. emergency), data are recorded in line with the standard procedures as part of the patients’ record.

Post-trial care is delivered in line with the local standard practice.

Participants will be followed for 12 months (± 30 days)—T4—starting from the allocation time (T0). Post-allocation evaluations are set to be at 3, 6 and 9 months (± 30 days)—(T1, T2 and T3, respectively). Table 4 depicts the time schedules of enrolment, interventions and assessments at different time points [32].

The sample size was calculated on the basis of the primary hypothesis (Hb1Ac levels are likely to decrease more in the subjects of the intervention group than for the subjects of the control group at 12 months). A lower variability around the HbA1c mean level is also expected for the subjects in the intervention group when compared to the HbA1c mean level for the subjects in the control group. It was assumed that at 12 months, the mean Hb1Ac level will be 49 (SD ± 3) mmol/mol in the intervention group and 52 (SD ± 7) mmol/mol in the control group. In order to achieve a power of 80% and to keep the significance level at 5%, the sample size was calculated to be 102 (51 in each group) by using Open Epi (a freely accessible software, https://​www.​openepi.​com/​Menu/​OE_​Menu.​htm) as depicted in Fig. 1 below. Assuming 20% of drop-out, the required sample was calculated as 120.

Patients regularly attending diabetes clinics in PAT are invited to participate if meeting the eligibility criteria. In order to identify the eligible participants, clinicians will use the list of patients with a scheduled appointment at the clinics (either face-to-face or online) and then check their medical history through the HIS database. Recruitment will stop when the targeted sample size is reached. Enquires (by phone or by email) from the potential participants are answered by the staff of the clinics during business hours.

Stratification is applied by centre (Rovereto and Trento). Participants are randomised (block randomisation with block size of 10) to either the intervention or control group on a 1:1 basis.

Treatment assignment information is enclosed in opaque envelopes, which are unsealed once the participant provides the written informed consent and the baseline information is collected.

All patients who give consent for participation and who fulfil the inclusion criteria will be randomised.

The random allocation sequence was generated by one statistician from the Clinical and Evaluation Epidemiology Unit of the Local Health Trust (APSS of the PAT), not involved with the recruitment and enrolment of the participants. The statistician used a SAS macro applying blocks following stratification by centre of recruitment. In every centre, closed opaque envelopes with printed randomisation numbers on it are available. For every randomisation number, the corresponding code for the parallel groups of the randomisation list will be found inside the envelopes.

A dedicated member of the research team will open the envelope and will find the allocated group for the participant. Then, the same member of the research team will give the information about group allocation to the patient.

Given the nature of the intervention, which is the active use of the Smartphone App, it will not be possible to guarantee the blindness of participants, healthcare staff and the person responsible for data collection. Vital signs, body weight and height are recorded before randomisation by a trained nurse across sites, using standardised procedures and instruments. The blood tests’ analysis will be carried out within the Trusts according to standardised procedures. Laboratory personnel are not involved in the study, thus they are not aware of the participants’ allocation. Blindness is guaranteed during data analysis, as data analysis will be performed from assessors that are not directly involved in the study. Filled-in questionnaires will only report the unique randomisation number.

This is an open-label trial, in which only data analysts will not be aware of participant allocation. Therefore, unblinding of treatment allocation to the participants or the staff involved in the care of the participants will not be an applicable procedure for this specific trial.

The large majority of the data (e.g. demographic data, clinical information) are collected as part of the standard routine practice. Other data are collected through interviews and questionnaires that are provided during different times of the study. Those assigned to the intervention group will be asked to provide information through the App (e-diary and Virtual Coach), whilst those assigned to the control group will register the data as per routine (e.g. paper diary). Please refer to Table 4 under the “Outcomes {12}” section for the information regarding the involvement of personnel—participants and the source of information used for data collection.

Below, a short description of the questionnaires used during this study is provided:

Retention is critical to the success of our study, whose aim is to assess if the TreC Diabete platform will positively impact on clinical outcomes of T2DM subjects. Participants are invited to complete questionnaires and to undertake blood tests regardless of their level of engagement with the App. Moreover, participants will provide informed consent for the researcher team to access HIS database data, enabling them to collect information on clinical outcomes even if participants are not going to complete the study as planned. The regular visits planned at the Diabetic Clinics will allow nurses and clinicians to invite participants to use the App more frequently whenever the App is used in a suboptimal way. Lastly, we expect that frequent reminders will help the intervention group participants to engage with the App. No study within a trial (SWAT) was planned for our study.

Information collected through the study is stored securely in locked cabinets at the study sites. Locked cabinets are located in rooms which are accessible only by healthcare and research staff members. Any form containing personal identifiers are located separately from the study records forms containing the subjects’ unique code number through pseudonymisation techniques. Databases used for data collection are secured with personal passwords and can only be accessed by the authorised research staff.

Biological specimens will not be used for future search. Blood tests are carried by nurses of the Trust as outlined in the protocol. Once the results are reported on HIS, blood samples are destroyed.

The analyses of the primary and secondary endpoints will be performed based on the intention-to-treat and as per-protocol approaches. Continuous variables of the two groups will be presented as mean, SD and quartiles, whilst categorical variables will be presented as percentages.

Chi-squared test will be used for categorical outcomes. SAS 9.4 (SAS Institute Inc.) will be used to conduct analyses. For all tests, the significance level is set to 0.05 (2-sided). Professional statisticians (FV, MG) will conduct all analyses.

No interim analysis is planned. The study will stop in case the targeted sample size is not reached within the end of the funded initiative (Telemechron project is expected to end in late 2023) despite all efforts have been put in place to recruit participants. No harm is expected, and therefore, there are no other reasons why the study should be prematurely stopped.

No subgroup analyses were planned.

The analysis will be conducted by “intention to treat” and “per protocol”. Given our expectation that very few patients will crossover or be lost to follow-up, these analyses should agree very closely.

Missing data will be managed according to the SAS version 9.3 MI procedure, which consists of the multiple imputation methods chosen by pattern of data missingness and type of imputed variable (SAS Institute Inc.)

Data are not going to be available on an individual level, but only through aggregated form upon reasonable request.

The steering group is composed by healthcare professionals and experts from the different institutions involved in the local initiative, namely APSS, PAT, Bruno Kessler Foundation (FBK) (i.e. research and IT innovation institute) and TrentinoSalute4.0 (i.e. Competence Center for Digital Health of the Province of Trento).

The technical committee in charge of coordinating the implementation of the study is composed by experts from APSS (clinical and organisational component, statistical component, data management and analysis) and FBK (IT component), with the support of TrentinoSalute4.0 (Competence Center for Digital Health of the Province of Trento). Patient and public groups were not involved for this specific trial; however, the platform under investigation is similar to those developed for other studies, for which both patients and health care providers had been involved [27].

A data monitoring committee is not involved for this study.

Due to the nature of the intervention, no harm is expected. However, cyber security for both medical dashboard and the App needs to be guaranteed in order to protect personal data of the participants involved in the study. Healthcare staff members will receive appropriate training in the use of the technological platform. A username and a password will be provided to each healthcare staff member involved in the study, who will then be able to access the platform only by entering their username and personal password. A help desk is available to help and support the participant as well as the healthcare staff involved in the project. Efforts have been put in place and will be put in place to protect personal data in compliance with the EU GDPR 2016/679 and the subsequent national Italian laws, including the Data Protection Code (D.lgs. 196/2003) [21, 22]. The data controller and processor has implemented technical and organisational measures to safeguard data protection principles (Art. 5 GDPR) and guarantee the rights to the data subjects (Artt. 15–21 GDPR). Data collected will be pseudo-anonymised and pooled before being shared with third parties, as specified in the privacy policy that participants have to access and sign upon the start of the study. The data processor has been designated through a specific contract under Art. 28 of the GDPR and the data protection officer of both the data controller and processor will support the compliance with the legal requirements. Episodes of hospitalisation or complications due to T2DM itself (e.g. hypoglycaemic episode) will not be considered as an adverse event of the trial intervention or trial conduct.

No auditing was planned for this study. The Ethical Committee will be informed on the progress and emerging issues throughout the whole study period.

Any request for substantial amendments will be sent for evaluation to the Local Ethics Committee of the Healthcare Trust of PAT. The Ethics Committee will also be notified if there are any changes in the protocol that do not require substantial amendments. If amendments concern directly the participants, participants will be promptly informed about the changes.

The results of the study, either positive or negative, are planned to be published in a peer-reviewed journal. They will also be disclosed through conferences.

The study protocol was approved by the Local Ethics Committee for Clinical Trials of the Healthcare Trust (APSS) of PAT (Rep. Int. 9453–30/05/2022; project ID: A765 and Rep. Int. 17,489 -11/10/2022; project ID: ES463). The trial is currently ongoing and is planned to finish by September, 2024. Recruitment is planned to be completed by April 2023.