Summary: Keeping people independent will need a systemic approach
One of the reasons why we’ve not mastered the ‘problem’ of ageing in place – or keeping people in their homes for as long as possible, is that nobody is in charge and financially incentivized to do this. Delivering on this goal, one of the key desires for many older people, comes down to a confusing patchwork with the older adult, their family, friends, broader community and the heath care system all owning different parts of the puzzle. This is fundamentally a systems challenge and as such we need a systems solution.
One suggestion for this system is a project I’m calling ‘Hive’. Hive is a proposal for a new system to enable ‘thriving in community’. In keeping with the ‘minimum viable ecosystem’ article from February 18, 2018 it’s a system with three layers:
- User experience: a seamless experience of individualized, relevant local services based on the needs of the older adult.
- Technical / data: a services matching platform takes account of the user needs and matches them with local services.
- Business model: a ‘pay for success’ business model rewards the members of the system when the independence goals are reached.
Background: Traditional players are not motivated to help older people age successfully in their homes
Few disagree that ‘thriving in community’ (a more socially connected version of ‘aging in place’) is a worthy goal, and as such it’s a key priority for many ‘age-friendly’ cities. However, the concept lacks a business model. Specifically, there has been no player (beyond the underfunded aging services network) whose primary job is to keep people successfully living at home. Such a player would need both an incentive and a holistic approach to address all the social determinants of health. Both are lacking. In most countries, the current fragmented approach leaves the older adult or their family with minimal support to stitch together relevant services and products (not to mention manage byzantine paperwork and siloed information) with little support.
About the Hive model: An integrated 3-part system
Hive takes an ecosystem approach – starting with the goal of keeping someone living successfully in a place of their choosing (this can be their home or an independent or assisted living facility) and on terms relevant for their choices and lifestyle. We don’t assume one size fits all; each person will have a personalized set of products and services that are right for them. Hive is a system with three layers:
User experience layer: An adaptable user interface. Hive will offer different interfaces based on the needs of the individuals: ranging from simple conversations with humans, through telephone and television to tablets, smartphones and voice interfaces. The goal is to introduce technology where appropriate – not for its own sake – to make the system better, more efficient and able to scale.
Technical / data layer: An intelligent platform that connects local services with unique needs. The platform ensures the right services are delivered at the right time so they can remain in their homes longer. Initially this will be done by humans – a case manager and over time it will be automated using AI / machine learning with case manager overseeing it (like a pilot monitors their autopilot). The platform has three roles: to assess initial needs (using passive analysis and a questionnaire), to match needs to local services (which will require access to real time availability) and to measure and learn about what works to refine and improve effectiveness.
Business model layer: A business model that aligns health payers with innovators and rewards success. A crucial part of Hive is a business model that rewards success – as measured by the ultimate ‘owner’ of the problem, such as the State, region, country, government department or insurance company. A logical target population for the United States are those on Medicare and Medicaid (referred to as ‘dual eligible’) who are the most frequent and expensive users of health care and social care, whereas in the EU and Asia the segmentation will likely be based on condition. Until the model and effectiveness of interventions has been proven, it is proposed that third party funding will enable the payor to avoid risk. The operational costs – which pay for creating and implementing Hive as well as paying for the day to day services of the chosen vendors – are covered by impact investors (traditional players or a new class of retail impact bond investors). When savings in the target group are realized, the payor shares some of the savings back to Hive which in turn pays back the investors. If no savings are realized, the investors don’t get their money back.
What success looks like
Given we’re talking about systems change at scale, there are lots of stakeholders, and indeed much is at stake. Successfully addressing the need for people to stay independent and thrive in communities would likely have major impacts for society and help to prepare our countries for the upcoming demographic shift.
In common with pay for performance projects, what counts as success is critical and will be agreed upon in advance. Logical targets are a reduction in health costs borne by the payor as well as as improved metrics of quality of life. Over time the program will develop a unique set of knowledge about what interventions are most appropriate for whom and why, and that will be a powerful asset that can then be deployed at scale.
An increasingly long list of open questions for how this would work
As there are some many moving parts above, there are still a lot of open questions, including:
- What metrics are the right ones to measure?
- How to minimize evaluation costs? Can blockchain – distributed, automated, immutable – help here?
- What group of customer / patients would be the initial target group?
- In which geography / state is most open to this approach?
- Which are the most promising existing holistic, person-centric, tech-enabled solutions to pilot?
- Who has best database of real time availability of local services providers?
- Who has best interface / API for booking local services providers?
- Are health insurance companies, cities or states the natural payor to target?
- Do payers have holistic, person-centric costs of older adults already?
- Who has best data about patients with conditions and expected lifetime costs?
- What are the personas and specific conditions that we should be starting with?
- What metrics would payers accept?
Needed now: a motivated payor and an innovative deal partner to structure a pilot
In keeping with the ‘minimum viable’ approach, the next step is to build a lightweight, kludgy implementation of this idea and see what the feedback is from customers (in this case would be both end users and the payers). There are six key partners:
- Payor: An innovative-minded health payor that could be a health plan or state government. Ideal partner: A state or large insurance company, a devolved city (e.g. Manchester).
- Transaction structuring partner: A foundation to support transaction structuring (business model, partnerships, legal). Ideal partners: Empire Health, Foundation, SCAN Foundation, RWJF, Wellcome Trust, impact investors.
- Political champion: Preferably a regional or State governor who can provide necessary political support and connections. Manchester’s Andy Burnham would be logical, since they have control of their own health budgets.
- Tech partner and platform: The hub for ‘thriving in community’ that is adaptable to the needs (voice, tablets) and integrates w/ services. Targets: Amazon, Google, Apple, Microsoft.
- Local services providers: A core group of local services providers (five initial categories: health, housing, meals, mobility and meaning / engagement). Companies such as Meals and Wheels and Lyft / Uber would be important players.
- Operating funds: Pays management and services to vendors and receives a return when the interventions are successful. An interesting 3rd party funding approach would be a Hive ICO where the token value directly relates to the value of the intervention. Tokens could also be given to care workers as additional payments. See here for more discussion about this idea.
Stephen:
All the best in this effort. As a provider of Medical Grade Wi-Fi for communities, we don’t fit the roles you have defined for a partner but I am personally vested in this idea of making a difference. The Hive concept seems to hold promise. If you are ever in the Philly area and would like to have a drink to bat around ideas, I would be happy to do so. If you need a conf room for brainstorming, you can use our facilities.
Cheers!
Ravi Bala, Healthsignals, LLC,
Thanks Ravi! Appreciate that and will take you up on the offer when I’m next in the ‘hood! Stephen
Hi Stephen,
Great stuff and happy to support these ideas with our platform!
Geert
Being intimately involved in caing for a 92-year old, a system like this would be a godsend! How could we go about setting up a pilot in France?
Hi Moira – thanks. Shoot me a mail with your details to stephen@fordcastle.com
Stephen
Devolve Silicon Valley
The piloting analogy might be modified to: pilot, co-pilot, autopilot; (care consumer, care manager, AI services mediation)
Accurately aligning investment incentives squarely on future quality and productivity gains would absolutely minimize investment risks. Both economic growth and our survival are now dependent on care productivity improvement. Given the enormous potential for automation technologies to deliver care productivity and quality improvement, something like Hive is crucial now to promote the development of a common forward vision and framework for concurrent development of the digital care systems technologies needed to support holistic care ecosystems.
In the U.S. we all need to think of ourselves as the constituent owners of the problem and hold ourselves and our representatives accountable. The San Francisco Bay Area is an appropriate and convenient place to start.
Thank you Stephen.
Thanks Mick, appreciate your considered insight. Yes would be great to see the Bay Area do something significant here.
Stephen