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Unpacking moonshot projects
Moonshot projects with a systems thinking approach to standards development in the healthcare industry
We believe that moonshot projects coupled with systems thinking and a systems capital approach to standards-driven innovation ecosystems is the way forward to reap the many benefits of the digital transformation of healthcare.
Systems thinking means complexity can be unpacked in healthcare innovation, to target desired endpoints effectively and efficiently, based on their data interoperability requirements. With systems thinking, ‘wicked’, seemingly insurmountable problems can be unpacked and repacked into a radical solution to that problem using disruptive technology. This means new care models and new collaboration models which circumvent the problem completely.
Systems thinking and practice means [1]:
1. Looking at situations from a holistic perspective (seeing the whole system).
2. Understanding the key relationships shaping how a system behaves.
3. Accepting the uncertainty and complexity of systems, and working in adaptive, flexible and learning-oriented ways.
4. Recognising that different people and different groups have legitimately different perspectives and see ‘the system’ differently.
5. Seeing that the resilience and adaptability of systems is related to strong communication networks, diversity, decentralised decision-making and redundancy.
6. Working in interdisciplinary and cross-sectoral ways.
Combined with moonshot thinking, systems thinking and an enabling connected innovation digital ecosystem, innovation partners can scale their business models while health systems scale the desired interventions in the following ways:
1. Connected innovation partners are empowered to look for solutions beyond their assumed boundaries, with a better understanding of perspectives and interrelationships between those and system actors – to overcome the innovator’s predicament and to significantly improve the odds of success through collaboration and partially open innovation.
2. Partners can greatly improve the pace of acquired knowledge translation, learning and improvement.
3. Partners are encouraged and empowered to explore new opportunities and pivot while focusing on their core competence.
[1] UKAID Systems Thinking and Practice. A guide to concepts, principles and tools for FCDO and Partners.
What to expect:
1. Leverage the Start-up community as critical enablers of health care innovation and important drivers of economic growth— Startups are nimble risktakers and essential stakeholders, catalysts for patient engagement and improved patient outcomes.
2. Enable the development of Translational AI by delivering sound data ecosystems for a) longitude in RWE and outcome data, b) precision of data sets - for diagnostic, preventative and treatment purposes, and c) provenance, shared care and accountability.
3. Accelerate the acquisition of Data Shadows— clinically coherent, robust and trusted, structured datasets. This can support the workforce of the future with telehealth, digital phenotyping applications, and virtual care workflow innovations.
4. Connect innovations together and cascade them in a collaborative innovation ecosystem to accelerate translational AI. Collaborative innovation includes seamless access to shared resources.
5. Leverage multi-omics for an AI adoption and resilience strategy— Combine omics with biomarkers and AI, into an extremely powerful translational precision medicine tool which can be used in feeding three different knowledge and data validation processes:
a. Framing Systems Medicine Knowledge (SMK), essential for disease trajectory phenotyping;
b. Discovering SMK, as in nuancing endotypes, populating and specializing the phenotypes-omics with biomarkers and other clinical data; and
c. Deploying the developed SMK capacity and structure to conduct digital phenotyping with Telehealth and to capture high quality data for different uses and reuses, incrementally raising the captured value of data to support health systems learning and intelligent transformation cycles (maintaining data recycling).
6. Enable data origin validation using smart mobile devices and applications designed to engage patients in capturing Patient Reported Outcome Measures (PROMs).
7. Exploit opportunities and provide a new pathway to radically different structures of delivery models, to reduce physician and nurse workload, improve outreach, engagement, and prevention at scale, all while collecting structured data in an open, continuous learning cycle.
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