Tag Archives: Health care reform

Smarter and more Intelligent Healthcare in 2035

The King’s Fund, a UK health charity ran a scenario essay writing competition, and here is the link and of course congratulations to the winner: (winner, runner up and other scenarios, but not mine).

My scenario builds on the notion of service unbundling and draws on strong and weak signals of changes likely to impact health and social care perhaps to about 2035. The scenario is written as a retrospective view from the year 2047. My objective was to avoid a doctrinaire scenario.

Unbundling 2035

Between 2016 and 2035, the way that people worked had substantially changed by widespread digitisation of information. Smart machines and robots had moved from doing physical work to being central to much cognitive work and which led to fundamental restructuring of the economy. By 2035, taxation was changing from taxing people to taxing the work done by devices, cognologies, and robots.

The fault lines between reality and expectations were starkly evident during the 2020s, as public investment in health and social care struggled to cope with the rapidly changing world. People were becoming accustomed to flexible access to personalised services that came to them and expected the same from care provision. Rising displeasure at service decline led to middle-class flight to alternatives with rising use of private medical insurance, progressively fracturing the social contract that legitimated publicly-funded care. Indeed, by 2028, 38% of the population used private care, with over 55% amongst Millennials.

Fearful health and social executives and worried Ministers of Health had reacted to these stresses by pulling the system even more tightly together, to protect jobs and avoid the failure of publicly-funded institutions.

This fed further public displeasure by the dominant middle-aged Millennials who challenged the traditional approaches to health and social care. In the United Kingdom, for instance, this unrest led to the 2028 Referendum on their tax-funded healthcare system, leading to the replacement of this system with social insurers and personal Social and Health Care Savings Accounts.

The process of changes in health and social care around the world has become known as Unbundling. This brief historical retrospective outlines three of the key components of that unbundling.

The 1st Unbundling: of knowledge and clinical work

Professional knowledge was affected by digital technologies which had unbundled knowledge from the expert. This changed how expert knowledge was organised, used and accessed; research institutions and knowledge-based organisations were the first to feel the changes, with librarians being one of the first professions to face obsolescence. Rising under-employment, particularly in traditional male-dominated occupations was still being absorbed by the economy.

Routine cognitive work and access to information and services was increasingly provided by cognologies (intelligent technologies) or personal agents as they were called. Widely used across society, they were embedded in clinical workflow from diagnosis to autonomous minimally invasive surgery. By this time, jobs with “assistant” in the title had generally disappeared from the care system, despite having been seen as an innovative response to workforce shortages through the late 20-teens. These jobs had turned out to be uninteresting, and being highly fragmented, required time-consuming supervision.

The benefits of precision medicine were substantial by this time, enabling earlier diagnosis and simpler and less invasive treatments. Theranostics, the merging of diagnosis and therapy, unbundled the linear care pathway and the associated clinical and support work. This also led to the unbundling of specialist clinical services, laboratory testing and imaging from monopoly supply by hospitals. Indeed, the last hospital was planned in 2025, but by the time it opened in 2033, was deemed obsolete.

The 2nd Unbundling: of financing and payment

The unbearable and unsustainable rise in health and social care costs necessitated better ways to align individual behaviours and preferences with long term health and well-being. Behavioural science had shown that people did not always act in their own best interests; this meant the care system needed people to have ‘skin in the game’, best done by monetising highly salient personal risks.

Existing social insurance systems which used co-payments were more progressive in this direction, while countries with tax-funded systems were forced to reassess the use of co-payments, and financial incentives. The Millennials, having replaced the baby-boomers as the primary demographic group, were prepared to trade-off equity for more direct access to care. It also became politically difficult to advance equity as a goal against the evidence of poorer health outcomes as comparisons with peer countries drove performance improvements.

The use of medical/social savings accounts was one way that gave individuals control of their own money and building on consumerist behaviour, this directly led to improved service quality and incentivised provider performance as they could no longer hide behind the protecting veil of public funding. The social insurers were able to leverage significant reforms through novel payment systems, and influence individual health behaviours through value-based (or evidence-based) insurance not possible under a taxation system.

The 3rd Unbundling: of organisations

With people used to having their preferences met through personalised arrangements, care was organised around flexible patterns of provision able to respond easily to new models of care. This replaced the “tightly coupled” organisational approach known in the early part of the 21st century as “integration”, which we know led to constrained patient pathways, and limited patient choices unable to evolve with social, clinical and technological changes.

The big-data tipping point is reckoned to have occurred around 2025. Because the various technologies and cognologies had become ambient in care environments they were invisible to patients, informal carers, and care professionals alike; this enabled the genesis of smaller and more diverse working environments.

By 2032, medical consultants were no-longer hospital-based, having become clinical care social organisations, with their cheaper, smaller, portable, networked and intelligent clinical resources. Other care professionals had followed suit. These clinical groupings accessed additional clinical expertise on as-needed basis (known as the “Hollywood” work model); this way of organising clinical expertise helped downsize and reshape the provision of care and met patient expectations for a plurality of care experiences.

It takes time to shift from the reliance on monopoly supply of care from hospitals in those countries that continued to pursue a state monopoly role in care provision. However, most repurposed themselves quite quickly as focused factories, while the more research-oriented specialised in accelerating the translation of research into daily use, helped along by the new research discovery tools and the deepening impact of systems biology which was making clinical trials obsolete.

What Cognology Says

This Unbundling arose as a product of the evolution of social attitudes, informed by the emerging technological possibilities of the day. The period from 2016 to 2025 was a critical time for all countries, exacerbated by shortages in the workforce coupled with economic difficulties and political instability.

Today, in 2047, we are well removed from those stresses that caused such great anxiety. We must marvel, though, at the courage of those who were prepared to build what today is a leaner, simpler and more plural system, removed from politicised finance and management decisions.

It is hard to imagine our familiar home-based theranostic pods emerging had this trajectory of events not happened. As our Gen-Zeds enter middle age, they will, in their turn, reshape today’s system.

Plus ça change, plus c’est la même chose.

27 December 2047

Note on the Scenario

This scenario is informed by strong and weak signals, including:

Ayers A, Miller K, Park J, Schwartz L, Antcliff R. The Hollywood model: leveraging the capabilities of freelance talent to advance innovation and reduce risk. Research-Technology Management. 2016 Sep 2;59(5):27–37.

Babraham Institute. The zero person biotech company. Drug Baron. http://drugbaron.com/the-zero-person-biotech-company/

Cook D, Thompson JE, Habermann EB, Visscher SL, Dearani JA, Roger VL, et al. From ‘Solution Shop’ Model to ‘Focused Factory’ in hospital surgery: increasing care value and predictability. Health Affairs. 2014 May 1;33(5):746–55.

Cullis P. The personalized medicine revolution: how diagnosing and treating disease are about to change forever. Greystone Books, 2015.

Does machine learning spell the end of the data scientist? Innovation Enterprise. https://channels.theinnovationenterprise.com/articles/does-machine-learning-spell-the-end-of-the-data-scientist

Eberstadt, N. Men without work. Templeton, 2016.

Europe’s robots to become ‘electronic persons’ under draft plan. Reuters. www.reuters.com/article/us-europe-robotics-lawmaking-idUSKCN0Z72AY

First 3D-printed drug just unveiled: welcome to the future of medicine. https://futurism.com/first-3d-printed-drug-just-unveiled-welcome-future-medicine/

Ford M. The rise of the robots: technology and the threat of mass unemployment. Basic Books, 2015.

Frey BC, Osborne MA. The future of employment: how susceptible are jobs to computerisation? Oxford Martin School, Oxford University, 2013.

Generation uphill. The Economist. www.economist.com/news/special-report/21688591-millennials-are-brainiest-best-educated-generation-ever-yet-their-elders-often [accessed December 2016]

Lakdawalla DN, Bhattacharya J, Goldman DP. Are the young becoming more disabled? Health Affairs, 23(1-2004):168-176.

Susskind R, Susskind D. The future of the professions: how technology will transform the work of human experts. Oxford UP, 2015.

Topol E. The creative destruction of medicine: how the digital revolution will create better health care. Basic Books, 2012.

With Samsung’s ‘Bio-Processor,’ wearable health tech is about to get weird. Motherboard. http://motherboard.vice.com/read/with-samsungs-bio-processor-wearable-health-tech-is-about-to-get-weird

Small might be smarter, think hive mind for innovation

Healthcare systems are often seen as requiring an economy of scale. This in part is a function of how prevalent diseases are, such that in some small countries they would have one case in 2 years, rather than one case per million of population. Healthcare technologies can be incredibly pricey; for instance, a proton therapy facility will run between €100 and €200 million to set up. Healthcare buildings and research infrastructure are expensive to build and run. Health professionals can be expensive to train and employ and are generally globally mobile.

Associated with investment in healthcare within the EU, we find that almost every region or member state has life sciences, in some form, in their top 5 or so areas of national priority. Life sciences is challenging and demanding, and requires high degrees of global visibility and connectivity to other researchers. Commercialisation of life sciences in Europe is not great; the EU’s research budget does not strictly speaking focus on research translation and there is precious little to help good ideas bridge the ‘valley of death’ where unfunded good ideas go to die. Financing for life sciences developments consume vast quantities of risk capital, some of which will be unlikely to return any value for a decade or more. The problem is not for the EU, but for the risk appetite in member states: it is difficult to raise more than €30 million or so in venture funding in Europe. The brooding presence of state interference in entrepreneurial start-ups can be discouraging. And with the UK leaving the EU, a liberal enterprising culture will be lost within the EU. Statist solutions in Europe tend to dominate.

Many EU countries try to avoid downside risks of failure by punishing it, rather than creating opportunities to learn. Countries that encourage risk taking, and make it easy to start and close down companies, with associated flexible labour practices, will outstrip protectionist fearful countries. Many countries protect jobs not workers, so actually create unemployment and discourage job creation. Life sciences is one such area that requires particular flexibility owing to the nature of the work.

Small countries are particularly interesting. In one of the EU’s small states, there has been active progress developing a bioscience research and commercialisation centre (partly funded by the EU, thanks for that). Higher education is active across life sciences, though the research is of middling status globally, but that is typical of most of Europe’s universities. The country has a well-developed and well-financed healthcare system, recognised as one of the best globally based on outcomes.

Building life science (or any research-based commercial capacity for that matter) means that setting priorities is more important the smaller you are, as you can’t do everything. That means grappling with disappointment as not everything can be done, and if trying to do everything, mediocrity abounds. It means, too, that infrastructure projects are precious, as they are enablers of future potential — the longer term vision must be sustainable, as getting it wrong can be expensive — research buildings don’t make very good hotels and what do you do with failing science parks like we see across Europe.

What Cognology says.

  • build on what you already are doing well as that is evidence you have the expertise, networks and working practices in place
  • keep in mind that life sciences is much, much more than drugs; progress may be quicker in other areas, such as informatics, telecommunications, bio-engineering, materials science, agricultural biotech, etc.
  • you can’t sensibly do life sciences with a weak university, so this entails difficult and hard rethinking of priorities and a sensible review of research productivity
  • you can’t sensibly do life sciences without a teaching hospital; the academic health science centres in the US account for over 80% of productive life sciences research, so the infrastructure should enable closer collaborations and alignment between university and hospital and industry; this may, by the way, raise real issues for government if the teaching hospital(s) is state run and therefore subject to bureaucratic overhang
  • you can’t sensibly do life sciences without understanding the logic of ‘bench to bedside’; productive work lies in translational research and solving clinical problems; this can challenge academics whose careers are rewarded from the production of papers and volume of research funding rather than solving problems; in life sciences, solving problems is paramount; understand what the Grand Challenges in life sciences are and see which one(s) you can focus on and ignore the rest
  • you’ll need to consider the economic developments that come with building a life sciences sector to energise high net worth individuals in the country to develop a risk appetite for national investments along with a cadre of managerial expertise to take start-ups forward; I’d discourage doing this through the public sector hiring as it disincentivises university graduates from pursuing entrepreneurial careers (there is good global evidence that this can be a problem, so don’t make that mistake); best role for government is ensuring a flexible corporate start-up environment, a non-punitive bankruptcy regime, sensible taxation of start-ups, and seed funding; it might also be a good idea to give away all that publicly owned intellectual property
  • finally, the good news is that size doesn’t matter for innovation; there is no correlation between the size of a country and the ability of the country to innovate; many very large countries have clumsy policies that disincentivise and frustrate; the EU is full of them and in the main, the governments have assumed the wrong type of highly interventionist policies rather than creating an enabling culture that does not punish failures and really does reward success.