Changes in reimbursement models, as well as patient and physician attitudes brought by COVID-19, have had a major impact on the rate of adoption of telemedicine. Early in the pandemic we saw a huge uptake, with a McKinsey report concluding that consumers were turning to telemedicine to address both physical and mental health issues. By August, the picture had evolved, with Epic reporting a study of EHR records from hospitals and clinics across the US that showed an initial rise in telemedicine appointments from 0.1% of the total before the pandemic to 69% in April and dropping to 21% by July.
This drop back is inevitable – many consultations require physical examination, lab tests or other procedures that are not practical to carry out remotely. However, the pandemic has given impetus to studies looking to rethink these constraints, such as the PVC-RAM study investigating the use of virtual care with remote automated monitoring for urgent and emergency surgery patients during recovery at home rather than in hospital.
The digital-first health strategies adopted by several countries to control the spread of the virus have rerouted the way healthcare systems function. Remote monitoring and telemedicine platforms, AI-powered assessment apps and devices have all become the new norm. For telemedicine to be truly useful, the patient must be able to collect and transmit a wide variety of data the healthcare professional needs, in order to assess the patient’s health.
Many state regulators have historically been sceptical of telemedicine precisely because they fear that the doctor-patient relationship in that context is too thin, with doctors being forced to make judgements based on too little available information. To encourage sustained usage of telemedicine by physicians post COVID-19, vendors and suppliers of telemedicine ecosystems and the data gathering devices that reside within them, must think carefully about how to craft the best service. It must leverage all available data to improve patient outcomes, it should deepen clinical insight, facilitate clinical decision support and carve out a competitive advantage in a noisy and crowded market space. Therefore, to push telemedicine toward its more natural value proposition, we will need to ask the patient to collect more data.
A major reset
For device manufacturers, this is a major resetting of the landscape, and product and technology roadmaps will need to respond. They must design or upgrade devices to be far simpler to use, as there will be a requirement for untrained users to manage and operate devices that have been traditionally restricted for healthcare professional use. COVID-19 has also forced the FDA to become far more flexible on repurposing devices for home use and telemedicine, with a number of emergency enforcement policies issued around consumer adaptation of ophthalmic devices such as visual acuity charts, visual-field devices, general-use ophthalmic cameras and even Class II tonometers for measuring intraocular pressure.
The FDA has also loosened regulations for AI-driven digital health devices for treating psychiatric disorders, given the rise in mental health issues during lockdown. There are clear financial and societal value propositions for offerings that can remotely diagnose, treat and manage physical and mental conditions. As device manufacturers work out how to be a part of this ‘new normal’ for healthcare, many will upgrade and repurpose existing connected devices with forms of AI that facilitate data collection, help physicians’ sort through and analyse data or even to deliver the therapy that patients need.
Of course, before designing or repurposing a medical device for the telemedicine ecosystem, a clear understanding is needed about the overall value proposition and the purpose of the device (what data must be collected), as well as who benefits and who pays.
Let’s look at who benefits from the actionable insights and therefore what data should be collected in order to generate them. Information each stakeholder will find useful will differ. But all are equally valid and must be catered for by the device design, if the value proposition is to be fully realised, in turn influencing adoption and reimbursement. Physicians may need daily or weekly usage and environmental data to understand compliance or the context of exacerbations. Patients may need real-time feedback to ensure correct device usage or maintain regime adherence. Payers may need monthly CSV files of anonymised usage data correlated to hospital admissions data. All these use case scenarios must be thought through before adding in the sensors and connectivity.
Who will pay?
Next, who will pay for the resulting service that is generated by this data and how will this influence reimbursement codes? The business model must be well thought through and consider revenue streams from the worried well, patient’s willingness to pay out of pocket for convenience, outcomes-based data that can influence Pharmacy Benefit Manager (PBM) Policy re formularies and so on.
Once the value proposition is thought through, a coherent strategy must follow. It is essential that the medical devices collecting usage and biometric data have a robust data acquisition strategy at the core of the design, provide accurate, reliable, secure, interpretable and compliant data onto the telemedicine platform for further analysis and insight to be generated. In order to avoid the GIGO principle (garbage in, garbage out) the devices must complement the digital ecosystem they sit within. There is little point offering a telemedicine service that is wrapped around medical devices that have not been optimised for that context. Inevitably there will be issues around a device’s power budget that may hamper real time (bi-directional) data transfer between patients and physicians.
Existing communication modules may not have been designed for the demands of the ecosystem and data will be lost, interrupted or not sent at all – compromising clinical decision support and actionable insights for both patient and physician. A complex or unintuitive user interface on the device can hinder the patient’s efforts to use the device correctly, again providing another lost opportunity for data capture or comprehension of visual and audio (real-time) feedback cues. Device design must reflect the potential of the service it sits within as opposed to the service reflecting the limitations of the device.
Once the device is at the centre of data generation, with data, strategy and user experience optimised for clinical insight, then the value proposition will be clear and unambiguous for all the relevant stakeholders (patients, payers, providers and device manufacturers). Finally, device manufacturers must build in security both within and around the device, so that it can be a discriminator for the telemedicine offering in the same way that safety has become in the car industry.
In the next of our series of articles focusing on device design for telemedicine, we will discuss the importance of a patient centric design philosophy and explore the relationship between form factor, user interface and overall trust and confidence in the system. Meanwhile, please do email me if you’d like to discuss any aspect of the topic in more detail.
