Digital Individualized and Collaborative Treatment of T2D in General Practice Based on Decision Aid

Overview

The purpose of this project is to improve life of patients with type 2 diabetes through an IT-supported lifestyle and treatment intervention. The intervention is based on combining and adapting existing and effective elements into the IT system of the general practitioner. In this way we will integrate specialist supervised treatment in general practice, individual patient coaching, and improved information exchange and data mining. The DICTA intervention consists of two integrated components: a patient-directed eHealth lifestyle coaching program delivered via the LIVA application, and a clinician-directed CDS tool embedded into the EPJ system. 1. eHealth lifestyle coaching: Individuals with T2D in the intervention group will receive individualized digital coaching from a health coach through the LIVA application. PROs are shared with GPs and health staff via the EPJ, enabling tailored, data-driven lifestyle support. 2. CDS: GPs receive real-time, individualized, algorithm-based pharmacological treatment recommendations for managing T2D, hypertension, and hypercholesterolemia, as appropriate. This is expected to facilitate use, assure individually tailored solutions, optimize treatment effects, and strengthen patient engagement. The study is a randomized controlled trial (RCT). It will include 400 patients with newly diagnosed type 2 diabetes. The patients will receive either treatment based on the intervention or usual care. After one year, we will assess quality of life and cardiovascular risk factors in both groups and evaluate if one group has improved management of their type 2 diabetes compared to the other. If the intervention proves effective, implementation on a national scale is highly feasible, and the intervention could probably be adapted to other lifestyle-related chronic diseases in Denmark and in other countries.

Background A study from the UK showed that an intensive intervention comprising a total diet replacement, stepped food reintroduction and structured support for long-term weight loss maintenance resulted in long-term T2D remission for almost half of the patients (Lean et al., 2018). In Denmark T2D is primarily managed in general practice, but despite intensive focus on T2D, many patients are not treated optimally, nor do they follow the recommendations for healthy lifestyle (Bo A et al, 2018). The Danish Center for Strategic Research in T2D (DD2) was initiated in 2010 with the overall aim of improving the quality of care for newly diagnosed T2D patients. The DD2 data comprises biological samples, as well clinical, lifestyle and quality of life data (Christensen et al, 2018). As of May 2019, DD2 holds samples from over 8,500 incident T2D patients. Based on the DD2 data, a model-intervention on individually tailored treatment of T2D was developed in 2013 and showed to be feasible in general practice (Stidsen et al, 2017). Further researchers from the DICTA study group have found in a pilot study, a collaborative eHealth tool in a GP setting to induce weight loss among obese patients resulted in a 7 kg weight reduction, which was maintained over a 20-month period (Brandt et al., 2011) and a 5,4 kg weight loss for T2D men after 12 months (Haste et al, 2017). This collaborative eHealth tool(LIVA) has been updated and refined on the basis of input from extensive interviews with patients, healthcare professionals, and GPs (Brandt 2018a, Brandt 2018b and Brandt 2018c) and is in use in several Danish municipalities with promising results (Komkova 2019). The DICTA project received support from Steno Collaboratory Grants 2018 and 2019 developing a web-based platform for patient registered outcome measurements and lifestyle coaching in collaboration with Liva Healthcare a/s, Cambio Healthcare Systems A/S and CGM A/S. This platform is now integrated in the electronic healthcare record systems used by the majority of Danish GPs (XMO, CGM). The intervention will provide novel, data-driven, individualized support to GPs, and individualized digital data-driven lifestyle support to their T2D patients supported by AI (machine learning) and timely accessible to the GPs when relevant. Aim The study aims to determine whether this integrated digital approach can enhance patient engagement, support sustained behavior change, and improve health outcomes compared to usual care in general practice targeting management of T2D patients in a RCT. Design and methods Design: The DICTA project is using a multi-method research approach including questionnaires, interviews, analysis of clinical outcome and health costs and all included in DICTA. This trial will recruit T2D patients in a GPs in the Region of Southern Denmark and Region of Zealand, and specialists from Odense University Hospital and Holbaek Hospital will electronically supervise the pharmacological treatment and specialized health coaches will offer online support for lifestyle changes. To ensure access to longitudinal data the investigators are aiming to enroll patients from GPs that also enroll their T2D patients in DD2. This will establish a comprehensive and strong inter-institutional and cross-sectional collaboration with the aim to improve care provided by the GPs and the quality of life for patients, based both on pharmacological and non-pharmacological treatments. The intervention: Based on the investigators previous research and subsequently developed IT programs and platforms, the investigators have implemented a complex intervention in collaboration with Liva Healthcare A/S, CGM and Cambio Healthcare Systems A/S. The two core elements of the intervention are: 1. Individualized supervised treatment Patients from DD2 who agree to participate have already been offered advanced phenotyping. Based on the phenotyping and algorithms developed by the hospital specialists at Odense University Hospital and Holbæk Hospital in collaboration with GPs. The GPs will receive specific clinical decision support recommendations on what drugs to prescribe to each patient based on the phenotyping in accordance with a clinical decision support tool (Cambio). 2. Individual digital coaching of T2D patients As part of DICTA, the patients are offered a personal health coach (dietician, nurse, occupational therapist, or physiotherapist) through the collaborative eHealth tool (Liva), and receive personalized empathic, relation driven coaching on healthy lifestyle on the individual patient's own terms (e.g. increased physical activity, healthier diet, weight loss, smoking cessation, personal goal setting, tailored information, peer to peer support), including optimal pharmacological treatment (Komkova, 2019). The collaborative eHealth tool will give health coaches access to patient registered outcome measurements (PROM) and support individual intervention goals. This forms the basis of the individual coaching and is partly supported by artificial intelligence (AI) to improve the coaching by the health coaches. As an example, health coaches are notified when patterns of usage is related to reduced success rates in weight loss. Presentation of patient registered outcomes to GPs Patient registered outcome measurements (PROM) on physical activity, steps, diet goal fulfillment, smoking status etc., are being provided for GPs in a web-based solution integrated into the GPs' health record system XMO, CGM (covering 52% of all Danish GPs). Method In this RCT the investigators will test the effect of a combined individualized lifestyle and pharmacological treatment intervention package among newly diagnosed T2D patients in a GP setting. The investigators will recruit GPs from DD2 practices and invite new GPs to DD2 in Denmark. At each GP appointment, all patients newly diagnosed with T2D will be informed about the study in writing and orally, and those who agree to participate will after committing to informed consent via an online questionnaire be randomized 2:3 to either intervention or control group, after relevant time to consider if they want to participate, typically within one to two weeks. Inclusion will start May 3, 2021 and the investigators expect to have included all 400 patients by June 1, 2024. The intervention group receives one year of individualized treatment (the intervention) in addition to usual care, while the control group receives usual care in the first year and then both individualized treatment and usual care in the second year. This design enables analysis of the effect of the intervention after the first year August 31 2025. Both groups (intervention and control) will be seen by their GP at 3, 6, 9 and 12 months. No extra biological material will be collected in this study apart from what is collected as part of usual care and DD2. Effect evaluation is displayed under outcome measures. Sample size Based on our experience from the ongoing IDA trial the investigators expect that approximately 50% of the patients in the control group will meet the composite endpoint. With a minimal clinically relevant difference of 25%, at least 62.5% should meet the composite endpoint in the intervention group. With a power of 80% and a significance level of 5%, the investigators will need 200 patients in each group. Statistical analysis The analyses will be performed by a statistician blinded to allocations. The primary analysis population will be the modified intention-to-treat population comprising those subjects with available data on the primary endpoint, i.e. those with completed 12-month follow-up. Per-protocol analyses will be predefined in the protocol and/or statistical analysis plan before any analyses are initiated. To enable the identification of the per-protocol population, major protocol deviations will be predefined in the protocol. To support future hypotheses, several ad-hoc exploratory analyses will also be performed. In general, categorical variables will be summarized as n (%), continuous variables as min-max, mean(sd), and median, Q1, Q3. All summaries will be by randomization group. Kaplan-Meier curves will be used to estimate survival functions related to time-to-event endpoints e.g. admissions stratified by group. Regression analyses, linear, logistic, and Cox proportional hazards will be used as appropriate. The type of analysis will depend on the endpoint in question. Before release of the data for analyses, a detailed statistical analysis plan will be written, reviewed, and approved. Data Management Through a collaboration with OPEN data will be collected using the online services provided in RedCap. In RedCap a project-specific and secure database can be developed for use in DICTA. This allows online and safe data sampling from all participating GP sites, and ensures a data handling process in concordance with current data protection legislation. Furthermore, RedCap supports automated integration between the eHealth solution and the GP-collected data, thus enabling merging of all data into one database. GP data will be laboratory results in accordance with the outcome descriptions as well as laboratory results, diagnose codes and medicine prescriptions of relevance for the clinical decision support tool developed in collaboration with Cambio. All statistics will be conducted via the service "OPEN analyze," placed on the same secure server as the project-specific OPEN database, or on the similarly protected research server at Statistics Denmark. A data management plan, including a protocol for access to and download of aggregated summaries and analysis results, will be available. Dissemination of results For the scientific dissemination, the investigators aim to publish in high-ranking scientific journals and present the data at scientific meetings, while at the same time pursuing the Science Europe principles on Open Access, ensuring the widest possible accessibility to the project outcomes. Ethics The overall assessment is that there are no risks of harm in project participation. Ethical permission will be obtained from the Danish Committee System on Health Research. Compliant to GDPR, written informed consent will be obtained from participants following an oral explanation of the project. Patient withdrawal from the study as well as the database can be done at any given time. All patient related data will be owned by SDCO. If ethical dilemmas should arise, experts at the involved institutions and ethical committees will be consulted. In case of disagreements, the PI decides about interpretation of data and on publication strategy.