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Technology adoption in primary care

25th October 2023

What are the barriers to technology use in primary care and how can we overcome them? This question was addressed at the American Diabetes Association’s 83rd Scientific Sessions. Lisa Buckingham reports. 

Thomas Martens, a board-certified internist and Medical Director at the International Diabetes Center at the Park Nicollet Clinic, Minnesota, US, began by outlining the technologies we already have: insulin pens, fingerpick blood glucose monitors (BGM) and continuous glucose monitors (CGM). There is also emergent technology such as Smart pens, pumps and patch pumps such as V-Go, each of which have their barriers to use.

For the purposes of his presentation, though, he focused on CGM as the model for thinking about how to overcome barriers to use. Why have CGMs taken off in this setting? They’re easy to use; they decrease the burden of use relative to BGM; there is data to support efficacy, especially for those using insulin to manage their diabetes (they improve glycaemic outcomes or reduce hypoglycaemia when compared with optimised BGM use); guidelines such as the ADA’s have emerged to support their use; there is improved cost and availability, and this technology is very visible because of direct-to-consumer marketing. 

With regard to CGM uptake in the real world, it’s hard to get a concrete number for how many people with type 2 diabetes are using CGM, said Dr Martens. He drew attention to a 2023 paper that used administrative claims data and it showed that in 2016, 18.8% of patients with type 1 diabetes used CGM and 1.2% of those with type 2 diabetes; in 2020, those figures had risen to 58.2% and 14.9%, respectively. This may in part be due to a 2018 policy change by commercial insurers, which expanded coverage of CGM through the pharmacy benefit. Localised 2023 figures from the Health Partners/Park Nicollet Care System show that 49% of people with type 2 diabetes using insulin have a CGM on their medication list.  

When looking at their use in primary care, he distilled it down to three questions: Do people with diabetes have access to the technology? Do clinicians have access to the data from the technology? Do clinicians and people with diabetes know how to use data from technology to improve care? All three are necessary to optimise real-world patient care, he said.

First, with regard to access, what’s needed is the following:

  • Real-world research to identify individuals and populations that benefit 
  • A long-range view in evaluating cost-benefit and total cost of care
  • Adequate coverage for diabetes technology to allow access for populations that would benefit 

Dr Martens said that we’re currently achieving a grade B- for how we’re doing with the above objectives. 

With regard to data access, he listed the following barriers:

  • Access to smartphone and broadband
  • Institutional firewalls can cause difficulty managing software and importing/exporting data
  • The Health Insurance Portability and Accountability Act (HIPAA) confidentiality concerns 
  • Lack of ability to directly import data into EMR (a cloud big data platform)
  • Time constraints 

Without access to data, the impact of even the best technology is minimal. He highlighted a 2022 paper, which stated that, ‘As healthcare increasingly moves to a digital-first approach, digital inclusion is becoming intertwined with healthcare equity’. If you don’t have access to broadband, he said, you can be marooned on an island in the middle of the information superhighway.

Time barriers in primary care are also an issue. He showed a typical day for a primary care doctor, with nine patient hours and 20 minutes per patient. Out of that, time is taken interacting with electronic medical records – one paper showed that it eats up around 16 minutes per appointment. 

How do you address this? It comes down to creating a healthcare team and workflow redesign, said Dr Martens. A team should set up the CGM technology and ensure data acquisition can happen during appointments, and care team should be used to leverage ‘cycle times’. Clinicians should choose the correct goals for therapy, use data for shared decision making and teaching on the impact of lifestyle and medications, and should also consider cycle times with team hand-offs and reducing delay in advancing therapies. 

When all of this comes together, he said, it transforms a visit. What if we could leverage some of that 16 minutes we spend interacting with electronic medical records to review the data? His organisation has done work on this, attempting to connect CGM data with electronic health records and it’s harder than it seems. Six US institutions are working on the optimal path to giving rapid access to retrospective CGM data at visits, including Stanford University and the University of North Carolina. 

Combine this with factors such as the type 2 diabetes population being older and less technologically connected and the reduced bandwidth of primary care since the pandemic and he gave our current progress a grade C-. However, many groups doing research in this area are pushing us towards an A.

Lastly, he addressed the third area of clinician and patient training. Having the device and the data only helps when people know how to use the data. His organisation has created tools to enable patients to understand their data and clinicians to be able to use retrospective data. 

One thing they’ve worked hard on, he said, is enabling clinicians to look at an ambulatory glucose profile and very rapidly take action. They have created a three-step programme to help them judge when to act and adjust lifestyle and medications. They have also worked on a guide to medication choices and adjustments, and they’re currently working on guidelines to create straightforward, actionable CGM-based management, including guidance to advance therapy and reduce inertia. This is an opportunity, he said, to push towards precision medicine in managing type 2 diabetes. 

We’re progressing in this area, but it’s still a grade C. Again, many groups are working towards an A in optimally using data and we need to keep innovating. If we pushed all three of the above areas to an A, he said, we would have true quality improvement on both an individual and population level and optimised care. 

Lastly, he looked at how we push beyond CGM. He used the example of a colleague coming to him with an insulin pen prescription that needed the detail filling out and asking what they were supposed to do with it. Diabetes specialists do this kind of thing every day, but in primary care, it’s a foreign language, he said. The path forward is building the systems of support to allow technology to be optimally used in the larger world of primary care. There are resources beyond primary care, such as diabetes education, but there are also barriers to those such as cost and availability. Artificial intelligence is another emerging area of potential. 

To conclude, creating device availability, making data easily available, and improving ease of use, knowledge and systems of support to decrease the burden are the tricks to minimising barriers to technology use in primary care, he said, finishing with: ‘Make the best path the easiest path’. 

To learn more about technology use in type 1 diabetes, enrol on the EASD e-Learning course ‘Technology and type 1 diabetes’.

Any opinions expressed in this article are the responsibility of the EASD e-Learning Programme Director, Dr Eleanor D Kennedy