Treatment inertia calls for an integrated personalized diabetes management: iPDM
Diabetes represents a huge and multidimensional challenge for European societes. It not only leads to premature ageing and frailty but also promotes chronic conditions like cardiovascular disease, blindness, dementia and even cancer. Despite the availability of numerous treatment options treatment inertia is still a common problem: many patents still fail to reach their treatment goals. According to the UK National Diabetes Audit data 2016- 2017, only 30% of people with type 1 diabetes and 67% of people with type 2 diabetes achieved a HbA1c target of not more than 58 mmol/l (7.5%).
The good news for innovators tackling treatment inertia in people with type 2 diabetes is that the disease leaves a huge space for innovation in personalised management strategies – due to the modifiability of risk factors, the potential reversibility of type 2 diabetes and the outstanding role of the patient’s self-management. On the other hand validated conceptual and procedural frameworks are required for realizing a personalization of diabetes care.
The recently proposed integrated personalized diabetes management (iPDM) provides such a framework for elaborating on the processes which could help to personalize diabetes care according to the individual patient's needs and requirements. Advancing diabetes treatment towards an iPDM regimen with a thorough consideration of the individual treatment-effect-modifiers can be considered a tremendous opportunity towards overcoming treatment inertia in diabetes care.
The conceptual roots
In 2012, Antonio Ceriello together with a panel of internationally recognized diabetologists published a concept paper entitled „Diabetes as a case study of chronic disease management with a personalized approach“ [1].
In this publication a structured and iterative six-step disease management process for the sustainable implementation of an iPDM regimen was proposed:
- Education and training to perform structured self-monitoring of blood glucose (SMBG) regimens
- Implementation of structured SMBG regimens
- Upload and documentation of SMBG data
- SMBG data analysis
- Personalised adaption of treatment
- Assessment of treatment efficacy based on another SMBG data analysis
Following the individual adjustment of diabetes therapy and SMBG regimen a new iPDM cycle can be entered. Repeatedly entering new cycles of iPDM was proposed to realize an iterative process securing a personalized diabetes management focusing on the individual patient's needs and requirements.
Whereas Ceriello and colleagues put a clear focus on the adjustment of SMBG and insulin administration regimens, more recently the framework of iPDM-like decision cycles has been put into wider context. The recent consensus report on the management of hyperglycemia in type 2 diabetes by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) proposed iterative cycles integrating diagnostics, joint decision making, treatment adjustment and monitoring for achieving a patient-centered glycemic management in people with type 2 diabetes [2].
Real-World effectiveness: the iPDM-ProValue study program
Inspired by the concept paper from Ceriello and colleagues the real-world iPDM-ProValue study program was initiated [3]. The iPDM-ProValue studies integrated low-threshold digital tools to prove the effectiveness of a 12-month iPDM regime in people with type 2 diabetes who are on insulin therapy. The iPDM-ProValue studies were designed as prospective, cluster-randomized, controlled intervention trials. iPDM was utilized in either general medical practices or diabetes specialized practices and compared to a control group where patients were continued to be treated according to their customary medical routine.
The primary endpoint variable reflected the quality of glycemic control in the iPDM group(s) vs. the control group as assessed by the between-group change in HbA1c from baseline to month 12. Secondary endpoints included the number of diabetes therapy adjustments, changes in SMBG testing frequency, and several patient-reported outcomes.
Overall iPDM-ProValue indicated that patients following the iPDM scheme achieved better glycemic outcomes. The better reduction of HbA1c after 12 months vs. usual care (0.5%, p < 0.0001 vs. 0.3%, p < 0.0001; Diff. 0.2%, p = 0.0324) was achieved without any impact on the incidence rate ratio of hypoglycemic episodes. At the same time a higher percentage of patients in the iPDM groups received recommendations to adjust their insulin therapy and experinced more behavioral and lifestyle recommendations. Also the satisfaction of both patients and healthcare providers as well as the adherence of patients to their pre-determined treatment regimens improved in the iPDM groups as compared to the controls [4]. A most recent analysis indicated that the usage of digital tools had a positive impact on iPDM effectiveness [5].
Particularly when considering that iPDM-ProValue study participants underwent only one iPDM cycle the impact of iPDM on the quality of glycemic control appears encouraging. The iPDM regimen can be considered an easily implementable low-cost approach which facilitates the evaluation of diagnostic data for informing subsequent therapeutic decision making. The iPDM-ProValue studies indicated a high potential of iPDM for bringing tangible benefits to people with type 2 diabetes and their healthcare providers.
iPDM-GO: from real-world validation studies towards European implementation
The encouraging outcome of the iPDM-ProValue studies stimulated initiatives aiming at a further enhancement and wider implementation of a personalized diabetes management. The recently started iPDM-GO (iPDM Goes Europe) initiative involves a consortium of diverse partners from industry, academia and healthcare administration in Europe [6]. The consortium integrates extensive expertise and skills in clinical practice, computer science, health psychology, health economics and bioinformatics and close-to-market clinical research and development. Within iPDM-GO Profil is coordinating a workpackage on „Research in iPDM enhancement, implementation and scalability“ and adds expertise in close-to-market clinical research and development.
The iPDM-GO consortium takes advantage from the dedicated innovation eco-system provided by the European EIT Health public-private partnership. iPDM-GO is a key part of the innovation project portfolio curated by EIT Health and alignes with the EIT Health focus areas „care pathways“ and „bringing care home“. This is going to facilitate the engagement with all the involved stakeholders for a successful launch of iPDM in different regions throughout Europe.
iPDM-GO is dedicated to implement iPDM, along with an outcomes-based payment model, first in innovative model regions to lay groundwork for expanding these concepts to additional European countries, and eventually throughout Europe. To support the transformation of healthcare from volume-based to value-based, iPDM-GO will develop a healthcare transformation toolkit that guides the implementation of outcomes-based care in European countries.
iPDM enhancement: for tangible impact on diabetes patients and diabetes care in Europe
There is a clear need for new approaches to diabetes management that place a strong focus on the assessment of patient-relevant outcomes and reducing the main cost drivers.
The iPDM-GO initiative realizes an open and collaborative approach answering the challenge that many people with diabetes still do not achieve their treatment goals - while the costs associated with chronic diseases continue to rise.
At the same time iPDM-GO provides an intriguing conceptual framework with multiple entry points for technological and procedural emhancement. Health economic analysis is going to be applied in order to prove cost-effectiveness of iPDM evolution – by either following the approach of identifying iPDM adjustments which could be particularly cost-effective or by calculating the cost implications of iPDM enhancements proposed from the side of stakeholders in iPDM.
Acknowledging the diversity of people with type 2 diabetes, their disease trajectories, treatment preferences and living conditions is important for the implementation of personalized diabetes management regimens people with diabetes are able and willing to adhere to. Therefore an accurate assessment of the patient‘s status is a key element in entering the iPDM process. Advanced assessment tools could integrate the usage of real-world data collected by sensors combined with telemedical tools for facilitating an in-depth understanding of the individual patient‘s needs and circumstances. Applying machine learning approaches to large epidemiological data sets will help to establish prediction models for estimating the individual risk of developing comorbid conditions under different treatment regimens. Integrating advanced artificial pancreas systems as developed by the CLOSE EIT Health innovation project [7] for a comprehensive monitoring of metabolic signatures and parameters reflecting patterns of everyday behaviour will produce a huge amount of real-world data which could inform iPDM by taking advantage of self-learning control algorithms.
The innovative goal of iPDM-GO is to establish a high adaptability of iPDM regimens along the lines of patient preferences, new drugs & technologies, treatment guidelines, geography and reimbursement policies, to name a few. Overall, data-driven iPDM feedback loops will trigger an adjustment of therapies, social interventions and behavioural patterns - leading to an amelioration of treatment inertia for making a tangible impact on the life of diabetes patients and the sustainability of diabetes care in Europe.
iPDM-GO and CLOSE are innovation project supported by EIT Health, a network of best-in-class health innovators that collaborates across borders and delivers solutions to enable European citizens to live longer, healthier lives. EIT Health is supported by the EIT, a body of the European Union.