3 practices Industrial IoT can learn from digital health and the Internet of Medical Things
Gone are the days when most healthcare providers kept patient information, inventory lists and other details in paper files. By using tablets and other rugged devices that are connected to each other, the healthcare sector has seemingly transferred their human-centric focus to digital health developers. Industrial developers can learn from these practices so that they can also improve their operational efficiencies.
I have been fortunate in my career as a technologist and product developer to have spent most of my years working across markets, e.g. aerospace, industrial automation, controls, medical/healthcare and consumer. One of the advantages of working horizontally is that I get the chance to learn how designers, developers and product managers leverage technology and design their businesses in different ways.
I was reminded of this again a couple of weeks ago when I spoke at the 2019 MedFuse conference. MedFuse is a medically focused follow-on to the industrial market focused IoTFuse conference so there were familiar participants from both the medical and industrial ecosystems. After talking with parties from both groups about how they were using the Internet of Things (IoT), and Internet of Medical Things (IoMT) in the case of the healthcare group, I thought I would share three ways where developers and product managers in the healthcare space might inspire their counterparts in the industrial space.
Pursue the Quadruple Aim, but patient first always
Today’s healthcare practitioners and digital health developers pursue what is known as the “Quadruple Aim.” The Quadruple Aim is a set of enterprise-level objectives that facilitate the often-difficult balance in healthcare between enterprise performance, including financial, with patient wellness and satisfaction. What I find inspiring about the Quadruple Aim and the healthcare product developers who pursue it is that they pursue the enterprise goals – lower costs, better outcomes and frictionless workflow – with a “patient first” mantra when designing and developing new offerings.
Reimbursement codes and fee-for-service payer models make the vast majority of medical device and digital health service sales enterprise, i.e. B2B, transactions. The consumerization of healthcare is coming, but the $3.5 trillion plus of spend in the US each year is still dominated by the system’s institutional payers. Yet as digital health grows it is the patients who are the users of healthcare solutions, particularly chronic illness products like hearing aids, insulin pumps and glucometers.
So digital health developers bring a patient-first attitude aligned with user-centric design methods when developing new offerings. Everything must be easy-to-use and provide recognized value for the patient/user so that they remain compliant with their care. Clinicians are also users, the “Better Clinician Experience” was added because the complexity and volume of digital information now generated in healthcare is creating clinician fatigue and dissatisfaction, but the primary focus of digital health developers is always the patient.
Contrast this with traditional Industrial IoT offerings that focus on optimization, efficiency and cost reduction for the operation or enterprise. The enterprise goals are the same – better outcomes at lower costs – but the method focuses more on the operation or enterprise itself than the users of the offering. Usability is often an afterthought because “the users will be trained” to be compliant. As the table below shows, there is a simple translation of the healthcare aims to industrial applications.
- Better outcome
- Lower cost
Industrial IoT aim
- Service tech/operator
- Lower cost
The industrial developer might say “I am healing the operation, not the user.” But that “healing” includes users and service techs, so outcome is still dependent on their satisfaction – the same as in healthcare. Industrial developers can learn the value of user-centric design in everything they do following the example of their digital health counterparts and in doing so will find greater adoption and enterprise success with their IoT implementations.
Value-based-care is a digital service
Digital service is personal and relevant information about how to maintain or optimize the availability, performance and security of a machine. —Dr. Timothy Chou
Replace “machine” with “patient” and you have value-based care (VBC). The point here is that healthcare participants have been working hard to change their commercial model from fee-for-service to value-based care for well over a decade. Fee-for-service models are classic re-occurring revenue models, i.e. customers make repeated decisions to purchase necessary materials or services. Consumables like pharmaceuticals, syringes, or test strips generate re-occuring revenue. But in healthcare the event that creates the repeat purchase or fee is a negative experience for the customer – the patient has to be unwell to generate revenue for the enterprise. Further, and this is a key learning for industrial counterparts, the re-occurring fee-for-service model is credited with continued waste and inefficiency driving increased costs in healthcare. Thus healthcare has been and is focused on transitioning to the digital services of value-based care.
Two key learnings for industrial adopters of the IoT from the value-based care initiative. First, consumables and truck-rolls are a step towards a service business model and subject to improvement with IoT technology but beware the economic hazards of break-fix. Fee-for-service can become an addiction, an addiction that disserves the customer. Healthcare innovators understand this problem and have turned their focus to value-based care models that change the focus from sickness to wellness, the desired outcome. In the case of chronic illnesses this deploys a recurring business model, i.e. subscription-based service.
Recurring models break the addition to fee-for-service and enable the provider to focus on reducing costs in any way possible as long as the outcome is achieved or maintained. Homecare and hospice-care models have had this opportunity for years because the payers pay the providers to maintain the patient for a period of time and that unit of time defines the unit economics, e.g. patient-day. Any improvement in how the patient-day is maintained is an improvement in operations. Likewise, industrial service organizations who move to value-based models can improve customer satisfaction while improving margins through diligent focus on delivering the desired outcome.
The second take away comes from the history of value-based care. While the transformation was economic in its origin, today VBC is driven by technology, specifically remote patient monitoring, telehealth and Patient Generated Health Data (PGHD) are accelerating how providers and patients participate in care. The transformation from fee-for-service to outcome-based services is not easy, but operators and innovators alike are fully engaged via digital health solutions created by the IoMT.
Industrial equipment service providers must focus on “system wellness” – uptime, avoiding truck rolls and optimizing the use of consumables so that customers see a “wellness service” – as opposed to continued break-fix transactions. As with healthcare, the maintenance service would now be recurring, paid by unit time. A “patient-day” becomes a “machine-day.”
The big advantage of this change, by the way, is perceived value. Customers will begin to value the service based on their experience with a day of “wellness,” i.e. the amount the produce in a day, vs the cost of the consumable or service. They also enjoy the certainty of knowing when and how much they pay versus the uncomfortable uncertainty of a break-fix model.
“Nudging” matters because behavior determines outcomes
“If patient engagement were a drug, it would be the blockbuster drug of the century.” —Leonard Kish, 2012
This statement has become a rallying point in healthcare because 90% of healthcare costs are for chronic care and as much as 70% of those costs are attributable to patient behavior, or more accurately patient misbehavior. As a result, digital health developers are highly motivated to take advantage of mobile technology and patient connectivity to extend therapy beyond the walls of the clinic into the everyday life of the patient.
Changing behavior, particularly habitual behavior, is hard. Enter the Nobel Laureate for behavior economics Richard Thaler and his book Nudge. Thaler and co-author Cass Sunstein provide a “how to” on helping people make better decisions about their own health and welfare. “Nudging” patients to therapy compliance and healthier behavior has become a foundation of digital health developers working to build Kish’s “drug of the century.”
The fact is behavior is equally important for IIoT developers. Individual behavior, specifically compliance with policy and procedures, is critical to achieving operational outcomes. Even more important is organizational behavior – the workflow. Workflow is not an outcome of policy and corporate design; it is the behavior an organization demonstrates in the execution of work and it can vary widely across organizational boundaries, e.g. stores, regions, or factories.
So, like their digital health counterparts IIoT developers must leverage the technologies of behavior modification – mobile, connectivity, sensing – to monitor both workers and organizations for compliance and best practices. IIoT applications should use choice architecture to “nudge” workers to more effective behavior.
The Industrial Internet of Things and Digital Health have common fundamental components. Both leverage the technology of connectivity, sensing and compute and both depend upon people to achieve enterprise outcomes. The human-centric focus of healthcare has given digital health developers a different perspective on how they deploy IoT technology. Industrial developers can learn from these practices – patient first, the Quadruple Aim and the Nudge – to accelerate the success of their operation-centric efforts.