Traditional models of evaluating, licensing and reimbursing interventions for diabetes are inadequate for the digital technologies that could improve management of the condition.
Dr Farhad Fatehi, a research fellow in the University of Queensland’s Centre for Online Health, told the limbic traditional models of producing evidence that take years were clearly ineffective when mobile health applications could be updated in two weeks.
“There are a few challenges around producing evidence for new technologies. One of them is that typical clinical trials last around four to five years from conception to funding, conduct of study and publishing the results.”
“This duration of time is too long for digital technologies because during these 4 to 5 years, new technologies have arrived and older technologies have become obsolete.”
“There should be another way around it to make sure the app works and doctors can safely prescribe that app.”
Dr Fatehi, a medical doctor whose PhD was in telehealth, admitted newer, faster ways to evaluate mobile based or digital health interventions may not have the robustness of results that policy makers and clinicians currently expect.
He said other challenges also required work-arounds before digital health could really deliver on the opportunities to improve diabetes care.
“Some countries have regulated some of these issues like privacy and security of data and other countries have yet to develop those regulations and rules.”
“Also in terms of the reimbursement, in Australia we have a small number of MBS item numbers for telehealth interventions but nothing has been suggested or approved for mobile-based interventions.”
“Because even if you prove those technologies are safe and effective, if doctors aren’t able to get reimbursed for the time that they spend providing consultation to the patients, they will not be adopted widely and uptake will remain low.”
Co-author of a review of diabetes care in the digital era, Dr Fatehi said the future of insulin delivery would include closed loop systems, nanotherapeutics and cloud-connected injectable therapies.
Artificial intelligence (AI) techniques and machine learning algorithms were also on the way.
“There are some research groups working on them to make meaningful information out of big data which are being accumulated in hospitals. AI-enabled chatbots are still in the development phase though; we’re yet to see them in clinical practice.”