Real-Time Continuous Glucose Monitoring: Gadget or indisputable need?

Using insights from patients and providers to evaluate system readiness for innovation

 

(Exemplary research proposal)

Author: Lisa Ploeg
Affiliation: Maastricht University
Date: 11-03-2015

1. Introduction

 

Diabetes Mellitus is one of the current challenges to public health that has not gone unnoticed by many, presenting a burden and prevalence that continues to rise. According to the latest numbers by the International Diabetes Federation, 382 million people worldwide have diabetes (IDF, 2014). In the European Region, there are around 60 million cases which represent around 8,5 per cent of the adult population. One in every ten deaths in this region is a consequence of diabetes (IDF, 2014; WHO, 2014). According to the latest update by IDF, Europe has the highest prevalence of children with type 1 diabetes (IDF, 2014).

Distinguishing between the main types of the condition – type 1 and 2 diabetes mellitus – type 1 accounts for approximately 5 per cent of cases (CDC, 2011). Whereas type 2 diabetes can be largely prevented, as it is highly related to many lifestyle factors, type 1 cannot. The precise causes of its onset are still not understood today. Type 1 diabetes is an auto-immune disease in which no insulin is produced, making patients fully dependent on insulin administration (Diabetesfonds, n.d.; CDC, 2011). The main challenge for type 1 diabetes management is therefore to get as close as possible in mimicking the insulin and blood glucose regulation as it does in patients without the condition.

1.1 Management of type 1 diabetes

As there is no cure for type 1diabetes yet, patients rely on monitoring and regulating their diabetes to achieve better glycemic control. In order to do so, patients must measure their blood glucose levels, depend on insulin administration, and maintain a healthy diet and regular physical activity, to name the most important elements (DVN, 2014).  Blood glucose levels must be checked several times per day, and is done through fingerpricks upon which insulin dosages can be decided. Insulin administrations – either through injections or by insulin pumps – together with fingerprick glucose measurement are the most crucial and effective tools for self-management of diabetes. However, daily challenges are encountered by patients, in finding a balance with physical activity, insulin administration, diet, and uncontrollable impacts such as stress. It is in these daily life situations that tools fall short to mimic the endocrine functions of non-diabetics. This often results in the short term dangers of hypo- and hyperglycemia, and contributes to the long term complications of poorly controlled glucose that may develop, such as kidney failure, heart disease, blindness and amputations (Ramchandani, Saadon, Jornsay, 2010; IDF, 2014).
Fingerpricks are often found to be incommodious and uncomfortable by patients. Additionally, fingerprick measurements are only informative about glucose levels at single points in time, creating a boundary to view trends in rises and declines of blood glucose in patients over time (Langendam, 2012).
Apart from daily self-management techniques, it is of upmost importance to keep track of several indicators that are related to diabetes-related complications, including cholesterol levels, kidney functions and potential proteins in urine. The gold standard for assessing the risk of late complications however, remains the glycosylated haemoglobin A1c (HbA1c), a measure of glycemic control indicating an average blood glucose of several weeks (The Diabetes Control and Complications Trial Research Group, 1994).

1.2 The innovation: RT-CGM

Vast amounts of assisting technologies for diabetes care are available today, and continue to be defined and developed. Real-time continuous glucose monitoring (hereinafter: RT-CGM) is one of the latest breakthroughs and created a shift in the paradigms of diabetes management. The first systems were available since 2006. It allows a real-time format visualization of glucose levels for both patients and providers (Mamkin, Ten, Bhandari, Ramchandani, 2008). By being a major step forward in mimicking a non-diabetic endocrine functioning and therewith maintaining blood glucose levels closer to ‘normal’, the technique can be seen as one of the first generations of closed-loop blood glucose management systems (Ramchandani, Saadon, Jornsay, 2010).
Continuous glucose monitoring systems operate by measuring the interstitial fluid glucose levels, which are highly correlated to blood glucose levels, on a semi-continuous basis (Langendam et al, 2010). The system can be used to detect patterns in blood glucose and serve as a warning system for preventing severe hypo- and hyperglycemia.
The major advantage in comparison to conventional blood glucose measuring is that the continuous measurement can identify glucose fluctuations that would otherwise not be observed (Langendam et al 2010).
A Cochrane review that compared RT-CGM use to conventional self-monitoring of blood glucose (SMBG), confirmed that RT-CGM use helps lowering HbA1c levels more than SMBG. Additionally, no significant differences in health-related quality of life were reported in the included studies (Langendam, 2012). Indeed, multiple studies confirm significant improvements in glycemic control by the use of RT-CGM (Deiss et al, 2006; Maia, Araújo, 2007; The Diabetes Research in Children Network, 2008).

Besides convincing benefits, challenges remain surrounding RT-CGM use. The system is not fully automatic yet, and finger-stick glucose measurements are still required to calibrate the sensor. Additionally, as glucose is not measured directly from capillary blood, time lag of around four minutes occurs between the measurements of glucose from interstitial fluid as opposed to those from blood. This can be of significant concern in the case of hypoglycemia (Boyne, Silver, Kaplan, Saudek, 2003).

Although fairly easy to use, persistence and patient understanding are crucial in order for RT-CGM use to be taught appropriately (Mamkin, Ten, Bhandari, Ramchandani, 2008). For example, understanding the difference between absolute glucose values at given times – and changes in them – while considering time lag are essential assets (Danne, Lange, Kordonouri, 2008).  Poor understanding of the data and trends has been observed to be a common reason for patients to discontinue using RT-CGM (Ramchandani, Saadon, Jornsay, 2010). The need to invest in adequate training and profound education for using the technology is therefore unquestionable. Additionally, where many believe RT-CGM will become a standard for treatment within the next few years, the need for adequate studies and evaluations to identify the likelihood of patients to use RT-CGM continuously, is highly stressed (Danne, Lange, Kordonouri, 2008). It remains unclear which patients will gain most benefits by using RT-CGM and when, as well as how the technology should be optimally integrated to improve existing regimes (Ramchandani, Saadon, Jornsay, 2010). Therefore, “..studies inquiring about issues surrounding RT-CGM use, as well as differing perceptions of patients versus caregivers, need to be done to better describe these groups and so improvements to RT-CGM devices and technology can be made“ (Ramchandani, Arya, Ten, Bhandari, 2011).

1.3 Problem statement

RT-CGM has been a major breakthrough in management of type 1 diabetes and has proven to significantly improve glycemic control, and reduce the incidence and progression of diabetes-related complications. Although its benefits are convincingly reported, the issues surrounding adoption and use of the technology are yet to be further explored. Understanding different views and perceptions surrounding the technology are essential.

1.4 Aim

The aim of this study is to explore the main challenges surrounding the use of RT-CGM and to understand the issues that may hinder the decision to use the technology, by focusing on views of patients and providers. Additionally, the study seeks to explore whether providers and patients view RT-CGM as a fundamental need for diabetes management – or merely useful when there is a perceived benefit compared to other alternatives.

1.5 Research questions

  • How can the main challenges for adoption of RT-CGM be described?
    • How can the patient-provider relationship be described?
    • How does a provider assess/advocate for a patient to need this technology?
    • How does a patient come to view this technology desirable and beneficial to him/herself?
    • How do these experiences of actual users impact the views, opinions and decision-making?
    • How can the decision-making process on RT-CGM be described?
    • How is the urge of the technology, as fundamental need for diabetes management, viewed opposed to other treatment options?

 

2. Theory and conceptual model

In order to obtain sound answers to the research questions, this study will look at the system readiness for adoption of the technology, by considering characteristics and views of different adopters. It is important to denote here, that ‘the system’ and ‘the adopters’ in this study refer to the patient and the health care provider, as it is within this context that the decision regarding RT-CGM use is being made. The main theoretical foundation used for this study derives from Greenhalgh’s (2004) model of system readiness. Additionally, the model on the innovation decision process from the theory on the diffusion of innovations (DOI) by Rogers (2003) will be used. A conceptual model that combines aspects of both theories has been developed to match the purposes of this specific study and will be presented in this section (figure 1). This was done to create a better theoretical balance between the more organization-focused theory from Greenhalgh (2004) and the individual and collective choice focus from Rogers (2003).

Starting with Rogers’ (2003) model of the Decision-Innovation Process, the first three stages are of main interest for this study. Firstly, the knowledge phase describes how an individual is first exposed to the innovation, yet lacks information about it and has not yet been triggered to seek more information. Secondly, the persuasion phase describes the interested individual actively seeking information regarding the innovation. Thirdly, the decision phase involves the individual balancing the advantages and disadvantages of the innovation and making the decision on adoption or rejection of it. As Rogers (2003) notes, this phase is the most challenging one to acquire empirical evidence on, due to the individualistic nature of decision-making. The process from knowledge exchange to decision making of adopting RT-CGM is one that occurs not only in the individual (patient), but rather as a continuous two-way communication process between the patient and the healthcare provider, resulting in a mutual agreement decision for adoption or rejection of the innovation, or a collective innovation-decision (Rogers, 2003).

In order to enable a more careful consideration of what, then, drives the information seeking and decision-making processes, and to look further than merely characteristics of the patient, provider and their relationship, the concepts of system readiness for innovation – derived from Greenhalgh’s (2004) model – are used.  

According to Greenhalgh (2004), System Readiness for Innovation describes how formal consideration of an innovation leads to a specific state of system readiness to it. System readiness can be described along six components; tension for change, innovation-system fit, assessment of implications, support and advocacy, dedicated time and resources, and capacity to evaluate the innovation. Further operationalisation of these components for this study is elaborated on in annex 1. For now it is important to denote that two elements of system readiness are in a way isolated from the others in the conceptual model. First, assessment of implications, which describes the assessment and anticipation of the innovation’s implications and effects. Second, support and advocacy, where the increased likelihood for assimilation is determined by the numbers of supporters versus opponents of it. It is assumed that for RT-CGM use, these components are for a great part determined by the experiences of actual users of the innovation. Looking back at Roger’s model again, these novel users have gone through the implementation and confirmation phase, where they have been able to (1) determine the usefulness of the innovation and (2) finalized a decision to (dis)continue use. The decision to continue use is then again both intrapersonal, as well as interpersonal, confirming whether a group has made the right decision – in this case the patient-provider (Rogers, 2003). Therefore, the final two stages of Roger’s Decision Innovation Process were included in the model as a feedback loop. It is assumed that experiences by users of the technology so far are likely to be taken into account in the information seeking and decision-making process.


Figure 1 - Lisa

Figure 1. Conceptual model based on Greenhalgh’s (2004) elements of System Readiness and Rogers’ (2003) Decision Innovation Process (own contribution)

3. Methodology

3.1 Study design

The study will be of qualitative nature, using direct observations and in-depth, semi-structured interviews as data collection methods. In-depth interviews with potential users and caregivers/providers will form the main body of the study. In addition, observations of consultations between patients – potential users – and providers will be performed. The study will take place in the Netherlands, where academic hospitals will be selected. Qualitative interviews will build upon Greenhalgh’s (2004) model of system readiness, and focus on information seeking and exchange, perception of the technology, and the patient-provider relationship. The study will have an estimated time frame of one year for completion.

3.2 Data collection

Data will be collected by means of observations and in-depth interviews. Academic hospitals in the Netherlands were chosen as locations, where one researcher from each participating university can conduct data collection. There are currently eight academic hospitals in the Netherlands, distributed across the country: Amsterdam (2), Utrecht, Leiden, Rotterdam, Groningen, Nijmegen and Maastricht (RIVM, 2014). Diabetes care standards, protocols and organizational structures for type 1 diabetes treatment are coordinated on national level. Additionally, multi-professional diabetes teams are therefore rather similar across different hospitals (ZorgstandaardDiabetes.nl, 2013). This ensures appropriateness for working with different hospitals, as the basic roles and culture of the patient-provider relations can be seen as rather similar.

It is sought to sample around three providers and three patients in each participating hospital, to allow for sufficient representativeness whilst simultaneously ensuring depth rather than breadth of research. Working with different researchers across the country enables cross-checking and feedback throughout the research process. Additionally, comparing hospitals expands the study size and may promote dissemination and transferability, which is of importance considering the pressure on knowledge needs in this field.

Questionnaires for the interviews will be developed according to Greenhalgh’s elements of system readiness. Additionally, in-depth inquiry regarding the patient-provider relationship, the exchange and seeking of information, and the perceptions on RT-CGM will form substantial themes throughout the inquiry.  Separate questionnaires will be developed for providers and patients. The ‘novel users’, as described in the conceptual model will not be interviewed considering the fact that a vast amount of literature on the experiences of users is available already and allowed for a firm overview of the current advantages and disadvantages of RT-CGM use. However, the questionnaires for the providers will include inquiries regarding the feedback they receive from users, and how this information influences or shapes their view on RT-CGM use, and the subsequent recommendation to patients that are potential users. Annex 1 elaborates a bit further on ideas on the content of the interview schedule relating specifically to the elements of Greenhalgh (2004), to clarify how these elements will be reflected.

Participants will be selected via purposeful sampling. Health care providers are diabetes specialists, which are the primary caregivers to the patients (ZorgstandaardDiabetes.nl, 2013). Selection criteria for selecting the providers are experience with own patients that have adopted RT-CGM, and having multiple patients with type 1 diabetes that are not yet using RT-CGM.

Criteria for patients are having type 1 diabetes whilst not having personal experience with the use of RT-CGM yet. Regarding age, only patients above the age of eighteen will be included, regarding the fact that children and teenagers are managed by a different diabetes team composition (e.g. paediatrician instead of endocrinologist), and transition of these teams has usually taken place by this age. Additionally, involving patients under this age would be a very different scope of study, considering the prevailing role of parental decisions in young age. 

3.3 Data analysis

Direct observations will provide the basic elements of human behaviour in a specific context (Trochim, 2006), which will serve as a useful tool in connecting findings from interviews to observations of reality. Especially when working with multiple researchers, differing interpretations may become a threat to the study’s trustworthiness. Therefore, observations in this study are mainly used to allow for a ‘reality-check’ in the cooperation and peer-reviews between researchers.
To analyse the interviews, written transcripts will be made and analysed using content analysis. Not only content of interviews, but also context – voice intonations, non-verbal communication etc. – will be considered in analysis. This will allow interpretations of underlying meanings, or latent content (Graneheim, Lundman, 2004). Coding and the creation of categories, sub-categories and themes are crucial in content analysis, where final themes will enable to answer the ‘how’ questions of the research’ aims (Graneheim, Lundman, 2004).

3.4 Assuring quality

Where validity and reliability form main quality considerations in quantitative research, trustworthiness describes these concepts for qualitative studies. Credibility, transferability and dependability are therefore of interest in assuring quality (Graneheim, Lundman, 2004).

The use of direct observations will provide evidence that can be used to communicate or elaborate on conclusions that followed the analysis of in-depth interviews, to enhance credibility of the study. Additionally, the decisions considering the inclusion of participants and data collection approach are viewed to match the phenomena under study.
Moreover, researcher reflexivity will be enhanced by discussion and feedback within the research team. It is of particular importance here that the interview schedules are developed and peer-reviewed by including all researchers, to ensure proper interpretation of its purpose. Research findings will also be communicated with the study’s participants.

Regarding dependability, or the degree of stability of data over time, it is important to note that the time frame chosen for this study was carefully considered. The technology – RT-CGM – is very new and its use and development is predicted to change rapidly over time, indicating the dependability of this study would decrease with a longer time frame.

Finally, the study is transferable to other settings, and this will be highly promoted. However, careful considerations and adaptations may need to be made, for example when exporting the study to settings or countries with different health care systems and patient-provider relationship cultures. Clear and distinct descriptions of data collection and analysis in the research process shall therefore be sought in the study’s final report or article.

3.5 Ethical Considerations

Of crucial importance is to make ethical considerations on a continuous basis throughout the study and critically reflect on the choices made. Involving participants for in-depth interviews therefore requires considerations such as informed consent, anonymity assurance and confidentiality of data (Mauthner, Birch, Jessop, Miller, 2002). These measures shall all be taken. Additionally, the study’s findings will be communicated with participants.

Moreover, as this study will involve patients in the clinical setting, a medical ethics committee shall be approached in order to grant ethical approval for the study. This step is of specific importance considering that one of the purposes of the study is reaching larger populations, and thus publishing of the results is key for dissemination.

3.6 Limitations

The study is limited to the Netherlands, which could be seen as a limitation by only including the Dutch health system. However, it is important to bear in mind that this was carefully opted for regarding the time frame of the study. Additionally, the study is meant to promote similar studies across the EU Member States, to identify where additional challenges may lie considering potential inequalities in access to RT-CGM.

Additionally, length of study could be considered a limitation. However, as before mentioned, increasing length or expanding the study would endanger its dependability and therewith trustworthiness.

The qualitative nature of this study could be viewed as a limitation in terms of the number of patients and providers actually included. Quantitative inquiry could be a successful complementary study, where surveys to large groups of patients and providers could inquire their views and provide quick results and overview. This was not chosen as a complement of this study, as development and validation of survey tools would again be a timely matter.

A final point of limitation to this study would be the potential researcher bias occurring because of different interpretations by researchers. However, necessary measures to limit this will be taken as described before.

4. Dissemination

The results of this study could contribute to a state-of-the-art understanding of ‘roadblocks’ hindering adoption – or causing an unequal distribution of adoption in terms of need. Therefore, it is of upmost important to invest in dissemination efforts of the study’s results, for a multitude of reasons. As stated in the introductory section of this proposal, several authors have indicated the need for understanding issues and views on RT-CGM use from patient’s and provider’s perspectives. Promotion of this study may therefore stress this need and inspire other initiatives.

In order to stimulate dissemination, the study results will be sought to be published in a relevant journal. Additionally, national diabetes federations and associations will be contacted to promote the study and describe its results and/or relevance. An example for the Netherlands would be the Diabetesvereniging Nederland (DVN), who represent one of the major organisations providing information on their website, and publish a magazine with news for patients and providers (DVN, 2015). Moreover, presenting the study at conferences would be another way of communicating the findings effectively, especially considering how the study could inspire other countries within the EU to perform similar studies.

Finally, it is important to consider the research impact (ESRC, 2015), that shall be promoted as well. The study could add to increasing the effectiveness of services and policy with regard to diabetes management. Additionally, if similar studies were to be conducted in other Member States, not only differences in access to RT-CGM could be identified, but also valuable insights might be obtained on best practices regarding patient-provider relationships.

5. Self-evaluation

As mentioned, peer-review and feedback processes will be introduced to the study to ensure proper conduct. Additionally, evaluation moments will be planned around each main phase of research – e.g. after development of questionnaires, to ensure equal interpretation and agreement on constructs and before the start of data analysis.

Apart from these feedback moments, it is important for every researcher taking part to go through self-evaluation methods to become aware of one’s capacity and competences, but also to question and learn from one’s contribution and reflect on relevance, effectiveness and efficiency of the research project. Researchers will therefore also be asked to set specific targets at the start of the study, which will be reflected upon after completion of the study. Figure 2 displays a self-evaluation process, that indicates at which steps considerations for self-evaluation are made (IWT, 2009).

Figure 2 - Lisa
Figure 2. The self-evaluation process (IWT, 2009)

6. Timetable

Timetable - Lisa

References

  • Boyne, M., Silver, D.M., Kaplan, J., & Saudek, C.D. (2003).Timing of changes in interstitial and venous blood glucose measured with a continuous subcutaneous glucose sensor. Diabetes 52(110):2790-4.
  • CDC (2011). Diabetes. Retrieved February 15, 2015, from http://www.cdc.gov/chronicdisease/resources/publications/AAG/ddt.htm
  • Danne, J., Lange, K.,  & Kordonouri, O. (2008). Real-Time Glucose Sensors in Children and Adolescents with Type-1 Diabetes. Hormone Research, 70, 193-202.
  • Deiss, D., Bolinder, J., Riveline, J.P., Battelino, T., Bosi, E., Tubiana-Rufi, N., Kerr, D., & Phillip, M. (2006). Improved glycemic control in poorly controlled patients with type 1 diabetes using real-time continuous glucose monitoring. Diabetes Care 29(12):2730-2.
  • Diabetesfonds. (n.d.). Over diabetes: Verschil tussen diabetes type 1 en 2. Retrieved February 15, 2015, from https://www.diabetesfonds.nl/over-diabetes/soorten-diabetes/verschil-tussen-diabetes-type-1-en-2
  • DVN – Diabetesvereniging Nederland (2015). Organisatie. Retrieved March 8, 2015, from: http://www.dvn.nl/dvn/organisatie
  • DVN – Diabetesvereniging Nederland (2014). Diabetes type 1. Retrieved February 16, 2015, from: http://www.dvn.nl/diabetes/over-diabetes/diabetes-type-1
  • ESRC – Economic and Social Research Council. (2015). Impact – what, how and why. Retrieved March 7, 2015 from https://www.esrc.ac.uk/funding-and-guidance/impact-toolkit/what-how-and-why/index.aspx
  • Graneheim, U., & Lundman, B. (2004). Qualitative Content Analysis In Nursing Research: Concepts, Procedures And Measures To Achieve Trustworthiness. Nurse Education Today, (24), 105-112.
  • IDF International Diabetes Federation (2014). IDF Diabetes Atlas (6th ed.): 2014 revision. Brussels, Belgium: International Diabetes Federation 2014.
  • IWT (2009). Self-Evaluation of Competence Research Centres: A manual. Retrieved March 7, 2015 from: http://www.iwt.be/sites/default/files/publicaties/iwt_studie62.pdf
  • Jones, J., & Hunter, D. (1995). Qualitative Research: Consensus methods for medical and health services research. BMJ 311, 376-380.
  • Maia, F.F., & Araújo, L.R. (2007). Efficacy of continuous glucose monitoring system (CGMS) to detect postprandial hyperglycemia and unrecognized hypoglycemia in type 1 diabetic patients. Diabetes Res Clin Pract 75(1):30-4.
  • Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P., & Kyriakidou, O. (2004). Diffusion of innovations in service organizations: systematic review and recommendations. The Milbank Quarterly 82(4) 581-629. doi:10.1111/j.0887-378X.2004.00325.x.
  • Langendam, M., Luijf, Y.M., Hooft, L., DeVries, J.H., Mudde, A.H., & Scholten, R.J.P.M. (2012). Continuous glucose monitoring systems for type 1 diabetes mellitus. Cochrane Database of Systematic Reviews 1. DOI: 10.1002/14651858.CD008101.pub2.
  • Mamkin, I., Ten, S., Bhandari, S., & Ramchandani, N. (2008). Real-Time Continuous Glucose Monitoring in the Clinical Setting: The Good, the Bad, and the Practical. Journal of Diabetes Science and Technology 2(5), 882-889.
  • Mauthner, M., Birch, M., Jessop, J., & Miller, T. (2002). Ethics in qualitative research. London; Thousand Oaks, CA: Sage.
  • Ramchandani, N., Arya, S., Ten, S., & Bhandari, S. (2011). Real-Life Utilization of Real-Time Continuous Glucose Monitoring: The Complete Picture. Journal of Diabetes Science and Technology 5(4), 860-870.
  • Ramchandani, N., Saadon, Y., & Jornsay, D. (2010). Real-Time Continuous Glucose Monitoring. In: Diabetes Under Control, The American Journal of Nursing 110 (4): 60-64
  • RIVM. (2014). Zorgatlas: Locaties ziekenhuizen juli 2014. Retrieved March 7, 2015 from: http://www.zorgatlas.nl/zorg/ziekenhuiszorg/algemene-en-academische-ziekenhuizen/aanbod/locaties-algemene-en-academische-ziekenhuizen/
  • Rogers, E. M. (2003). Diffusion of Innovations. (5th Edition). New York: Free Press.
  • The Diabetes Control and Complications Trial Research Group (TDR) (1994). Effect of intensive diabetes treatment on the development and progression of long-term complications in adolescents with insulin dependent diabetes mellitus: Diabetes Control and Complications Trial. J Pediatr. 125(2):177-88.
  • The Diabetes Research in Children Network (DirecNet) Study Group (TDR). (2008). FreeStyle navigator continuous glucose monitoring system use in children with type 1 diabetes using glargine-based multiple daily dose regimens: results of a pilot trial. Diabetes Care 31(3):525-7.
  • Trochim, W.M.K. (2006). Qualitative Measures. Retrieved March 7, 2015, from: http://www.socialresearchmethods.net/kb/qualmeth.php
  • WHO. (2014). Diabetes – Data and statistics. Retrieved February 15, 2015, from http://www.euro.who.int/en/health-topics/noncommunicable-diseases/diabetes/data-and-statistics
  • ZorgstandaardDiabetes.nl – Nerderlandse Diabetes Federatie (2013). Type 1. Retrieved March 7, 2015 from: http://www.zorgstandaarddiabetes.nl/type-1/

 

Annex 1: Operationalisation of Greenhalgh’s elements of system readiness

Tension for changeRevolves around the perception of the current situation, and the tolerability or successfulness. (Greenhalgh, 2004) I.e: How well does the patient’s current therapy seem to work?

Provider: Clinical and professional opinion on patient’s status, e.g. when Hba1c levels are perceived tolerable or demanding adaptations in treatment.

Patient: When does a patient feel the need for different treatment or management tools? How well or poorly controlled is the diabetes?
Innovation-system fitGeneral: How well does RT-CGM use seem to fit in the way of management between the patient and provider? (e.g. one must consider that consultations and intensity of contact may need to increase).

Provider: How does the provider describe the visions, norms, values of optimal diabetes treatment and how would RT-CGM use fit in this?

Patient: How does the patient view RT-CGM use to fit in his/her current life and management of diabetes?
Dedicated time and resourcesWhat is the role of budget available for the innovation (e.g. hospital budget or insurance schemes) in determining the desirability? How much extra time is perceived to be needed for adequate adoption of RT-CGM? Adequate training etc.
Capacity to evaluateProvider: How does the provider perceive its skills to evaluate the impact or RT-CGM use in his/her patients?
Assessment of implications*According to Greenhalgh (2004), the decision on RT-CGM use is more likely to be made when its implications and effects are fully known and anticipated. Therefore;
Provider: How does the provider seek information on RT-CGM use and make judgments on this? What is the impact of knowing experiences so far by other users?

Patient: How does the patient balance out the implications of RT-CGM use? What role does the provider’s view play?
Support and Advocacy*Rather similar to previous; What is the impact of the experiences of other users in creating a judgment on the need of RT-CGM for a potential user?

*These elements will reflect in the interviews how they are impacted by experiences of users of RT-CGM