Health in the 21st Century

Foreword
Acknowledgements
Acronyms and abbreviations
Executive summary
	Building people-centred, efficient and sustainable health systems
	Health can learn from how other sectors were transformed
	A digital transformation requires policy action and leadership
1 Bringing health into the 21st century
	1.1. Introduction
	1.2. The health sector is slow to embrace a digital transformation – this requires urgent attention
		1.2.1. Digital transformation entails much more than digitising existing processes
		1.2.2. Lessons from other sectors are relevant in health
			Lifting productivity and creating value through process innovation
			But risks and potential pitfalls must be actively managed
	1.3. Despite rising digitalisation, health systems remain ‘data rich but information poor’
		1.3.1. The right information to the right people at the right time
		1.3.2. Data can help identify health need and target care more accurately
		1.3.3. Most OECD countries are slow to harness data for safer and better treatments
		1.3.4. Big data are not used to their full potential in public health
		1.3.5. Harnessing data to improve efficiency and value across the health system is rare
		1.3.6. Information systems can enable better health funding models
		1.3.7.  Preparing the health workforce to make the most from a digital transformation is a challenge
	1.4. Tackling the barriers to a digital transformation needs an overhaul of policies and institutions
		1.4.1. Transforming skills and attitudes across the sector
		1.4.2. New ethical frameworks are needed
		1.4.3. Engaging patients while ensuring that no one is left behind
		1.4.4. Opening data availability and facilitating their integration
		1.4.5. The right incentives play a major part, and rely on policies and institutions
	1.5. A focus on strategy, governance and capacity will require sustained commitment but also deliver a healthy return on investment
		1.5.1. An overarching strategy is the foundation
			Strategy is the first step to address the key problem of fragmentation
			Cross-sectoral, whole-of government strategies appear to be most effective
		1.5.2. Good data governance can develop the key element of trust
			A key purpose of governance is to establish trust
			Governance across sectors and across borders
		1.5.3. Building capacity for a digital transformation requires investment
			Targeted and sustained investment is needed
		1.5.4. But the returns can be considerable
			Reducing wasteful and inefficient practices
			Improving health outcomes
	1.6. Conclusion
	References
	Notes
2 New ways of delivering care for better outcomes
	2.1. Introduction
	2.2. Using data to design better health services and target them more accurately
		2.2.1. Data present an opportunity to sustainably improve care for the growing number of patients with complex health needs
			Current ways of delivering care are ill-suited to emerging health needs
			ICT and data present an opportunity to make care more effective and efficient
		2.2.2. Personalising care with better information
			Ushering in ‘System Medicine’ with modern data analytics
			Making the necessary data available to unlock their knowledge potential
	2.3. Enhancing care delivery with digital technology
		2.3.1. Giving patients access to their own data and facilitating patient-provider communication
			Patients with complex needs benefit from empowerment through information
			Technologies that help engage patients in their care are underused
			Widening health disparities must be actively avoided
		2.3.2. Communication and coordination among providers is key to improving care and health outcomes
			Integrated health record systems are an important foundation
			Other ICT functionalities can also contribute
			Challenges to deploy ICT relate to engagement and workflow redesign
			Implementing ICT must be part of a broader change and improvement strategy
		2.3.3. Data-driven decision aids in clinical practice enhance diagnosis accuracy and appropriateness of treatment
			Decision support can be especially useful in complex patients
			Ensuring patient involvement in decision making
			Integration and interoperability are of vital importance
			More research is needed to establish the effectiveness of decision aids
		2.3.4. Tele-medicine can make care more appropriate and efficient
			Tele-monitoring can make care more responsive and appropriate, leading to increased effectiveness and efficiency
			Potential risks of tele-monitoring must be recognised and managed
			Evidence is encouraging but difficult to generalise
			Remote delivery of services can improve access and make care more efficient
			Tele-medicine often complements, rather than replaces, face-to-face care
			Ensuring equity is a challenge
	2.4. A strategic approach is needed to planning scalability and sustainability of new was of delivering care
		2.4.1. An overall ICT strategy can guide design of individual projects and facilitate their scale-up
		2.4.2. Financial, technological and cultural barriers commonly impede broader adoption of new ways of delivering care
			New models of care delivery also require new payment mechanisms
			Interoperability and shared infrastructure enable scale-up of new ways of delivering care
			Skills need to evolve and cultural change be managed
			Policy should tackle persistent disparities in digital and health literacy
		2.4.3. Pilot projects need to be evaluated rigorously to select successful ones for scale-up
			Routine health data should be deployed to evaluate care delivery
			A fit-for-purpose approval and regulation model may be needed
		2.4.4. Design of ICT tools should involve end users
	2.5. Conclusion
	References
	Notes
3 The informed patient
	3.1. Introduction
	3.2. Patients can access a growing number digital tools to engage in their own health
		3.2.1. Opt-out systems appear to be more effective in encouraging EHR adoption
		3.2.2. Uptake of electronic health records and patient portals is not even, and is low among high-need patients
			Not all users of the health system will benefit from more frequent engagement with digital health tools like patient portals
		3.2.3. The internet is a growing and influential source of information for health system users
			Peer-to peer networking can offer value to patients and the public
			Traditional inequalities persist despite these advances
		3.2.4. Mobile phones and apps increasingly serve as personal health monitors
			Most tools are developed without input from medical experts
			The data deluge introduces some new challenges
		3.2.5. Direct-to-consumer (DTC) medical testing presents challenges
	3.3. Using new digital tools effectively requires both health and digital literacy
		3.3.1. Overall health literacy remains low
			An emerging digital divide reflects existing inequalities
		3.3.2. The digital divide risks exacerbating instead of reducing inequalities
	3.4. Health systems need to prepare for the rise of the ‘informed patient’
		3.4.1. Patient empowerment can promote inefficient use of health system resources
		3.4.2. Public and individual interests need reconciling
	3.5. New approaches are needed to promote and govern digital tools for patient engagement
		3.5.1. Promoting the constructive use of digital technologies
		3.5.2. Governance and regulatory mechanisms need to be updated
	3.6. Conclusion
	References
	Notes
4 Engaging and transforming the health workforce
	4.1. Introduction
	4.2. Together, humans and machines can generate better health outcomes than either could alone
		4.2.1. Most health sector jobs will remain, but some specific tasks will become automated, freeing up time for more complex activities
	4.3. Engaging and transforming the health workforce is essential
		4.3.1. Adoption of digital data systems shifts the mix of skills required in health-sector jobs
		4.3.2. The necessary skills needed are often in short supply
			Need for tailored training curricula and leadership
			Skills supply and demand need to be considered simultaneously
		4.3.3. Technology must not ‘get in the way’ of work
			People-centeredness is important in the design and implementation of digital technology
		4.3.4. Legal and ethical questions must be addressed
			Health professionals must trust the digital tools at their disposal
	4.4. Addressing barriers to health workforce engagement and transformation in the digital era
		4.4.1. Investing in digital skills of front-line health workers
			Some countries have introduced guidelines on integrating digital technology in education and training
			Investment in digital health infrastructure needs commensurate investment in health workforce skills
		4.4.2. Investing in clinical IT leaders and a cadre of informaticians with clinical expertise
			Hybrid skills covering clinical leadership and informatics are needed
		4.4.3. Health education governance and health workforce planning require a new approach
		4.4.4. Reinforcing health workers’ trust and promoting engagement in the development of digital technologies
			Digital tools must be designed with the input of end-users
	4.5. Conclusion
	References
	Notes
5 Big data: A new dawn for public health?
	5.1. Introduction
	5.2. OECD countries are using new analytical tools to better link electronic health databases and draw policy insights for public health purposes
		5.2.1. New analytical techniques can enhance public health policy making
		5.2.2. Big data can improve the identification of population- and person-level risk factors
			Bigger is not necessarily better
	5.3. Harnessing novel data sources represents a new frontier for public health
		5.3.1. Novel data sources are uncommon as big data sources for public health
		5.3.2. Big data approaches can complement traditional disease surveillance methods
		5.3.3. Policy makers are starting to explore big data for precision public health
	5.4. Big data can be leveraged to implement more targeted public health interventions
		5.4.1. Big data approaches can help translate knowledge to practice
		5.4.2. Many promising uses of big data for public health have emerged from the municipal level
	5.5.  Clear and consistent policies designed to safeguard private data are needed
	5.6. Conclusion
	References
6 Data without borders: Boosting knowledge and innovation
	6.1. Introduction
	6.2. Cross-border collaboration using health data has a rich and fruitful history
		6.2.1. International sharing and use of data have promoted learning and improvement
		6.2.2. International reporting of cancer indicators began 50 years ago
		6.2.3. Multi-country collaborations have yielded dividends
		6.2.4. Global projects are establishing an international research infrastructure
		6.2.5. The European Union is developing a common health data infrastructure to promote data sharing across member states
			Ensuring data quality and accessibility to advance shared policy objectives
			Large pan-European datasets are developed to bolster biomedical research
	6.3. Key challenges concern data localisation, security, commoditisation and interoperability
		6.3.1. Data localisation laws and policies can limit cross-border sharing
		6.3.2. Emerging technologies pose data security threats that call for collaborating on innovative solutions
		6.3.3. The data ‘gold rush’ raises ethical concerns
		6.3.4. Lack of common standards and interoperability raises risks and limits potential for collaboration
	6.4. Strong governance, common data standards and a collaborative approach to data security is needed
		6.4.1. Appropriate regulations enable the secure and productive sharing of health data across borders
			Governments need to develop the right legal and regulatory frameworks that protect individuals and the public interest
		6.4.2. Common global health data standards are needed
		6.4.3. Data security in the digital era is greatly enhanced by global collaboration
	6.5. Conclusion
	References
	Notes
7 Harnessing data to manage biomedical technologies
	7.1. Introduction
	7.2. Scientific progress, changing disease burden and financial pressures are challenging the conventional approach to evidence generation
		7.2.1. Clinical trials are the gold standard, but come at a high cost
		7.2.2. Effectiveness and rare events are difficult to establish prospectively
		7.2.3. Changing health needs and disease profiles create further challenges
		7.2.4. Fulfilling the promise of precision medicine will be difficult under the existing model
		7.2.5. Raised expectations are a further challenge to the current approach
	7.3. Digitalisation makes a new paradigm possible
		7.3.1. Routine and real-world data open new possibilities for generating evidence and knowledge
		7.3.2. Other industries put their data to work to drive improvement and learning
		7.3.3. Learning from real-world and routine data is demonstrably possible in the health sector
			Regulators are already using routine data to monitor safety
			Evaluating effectiveness and comparative performance of medical products are also possible
		7.3.4. Statistical methods and techniques as well as veracity of routine data require continued development and refinement
		7.3.5. Real-world evidence to complement, not replace, traditional knowledge generation
	7.4. Patients and the public want and expect their data to be put to work
		7.4.1. Patients support secondary use of their data for scientific advancement
		7.4.2. The public is also in favour if the necessary protections are in place
	7.5. Most countries are not using data to their full potential
		7.5.1. Countries vary in their capacity to deploy clinical data for knowledge generation
		7.5.2. Countries report using routine data to inform policy in a limited way
		7.5.3. The key barriers concern capacity, infrastructure and governance
	7.6. Making better use of data requires concerted and coordinated policy action
		7.6.1. Countries must implement a governance framework the enables data use while maintaining privacy and security
		7.6.2. Building and investing in capacity and infrastructure is key
		7.6.3. Other stakeholders also play an important role
		7.6.4. All stakeholders stand to gain
	7.7. Conclusion
	References
	Notes
8 Intelligent system governance, stewardship and resource allocation
	8.1. Introduction
		8.1.1. Governance is a comprehensive process to achieve health system goals
	8.2. Smart use of data can help improve effectiveness, equity and efficiency of health systems
		8.2.1. Health is lagging behind other industries in analytical use of data
	8.3. Data and ICT can enhance governance but progress in countries is slow
		8.3.1. Needs assessment tools and needs-based resource allocation are under-used
			Needs-based resourcing can improve equity and efficiency but is the exception, not the norm
			Performance-based budgeting relies on good data
			Risk stratification can improve how resources are deployed
			Virtual registries: a very efficient way to generate valuable knowledge
		8.3.2. Harnessing data for more effective quality monitoring and improvement
			Routine data and their linkage enable more informed and responsive policy
			Assessing quality of care and health outcomes routinely
			It is possible to intervene at the community- and patient-levels
		8.3.3. Data can help identify low value care, but new services also require active monitoring and targeting to drive efficiency
			New services often increase aggregate expenditure even if unit costs are lower
			Opportunities for assessing costs and effectiveness of care
		8.3.4. Provider payment can incentivise improvement using data
			Broadening the scope of payment for services
			Provider payment models can pose barriers to ICT-enabled services
			Payers can incentivise better care with effective use of data, but some unbundled payments for specific activities may still be needed
	8.4. Overcoming historical barriers in health systems can enable progress but risks need to be managed
		8.4.1. A number of barriers to greater use of ICT and data need to be overcome
			Health system fragmentation and dispersed data challenge the use of ICT and data in governance
			While electronic health records still hold large potential, EHR systems often mirror health system fragmentation
		8.4.2. While data are becoming the key input to innovation and can be considered a public good, data often become privately owned commodities
		8.4.3. Making data more widely available could enable progress
			National data centres or distributed networks can store and facilitate the use of vast amounts of diverse data
			… increase availability of traditional data…
			…and integrate wider data sources
		8.4.4. More ICT and more data will not drive transformation without leadership and capacity
	8.5. Countries can progress on various fronts to harness data for better health system governance
		8.5.1. System-level strategies can guide the development and use of ICT and can serve governance objectives in and beyond the health system
		8.5.2. Instituting health data governance frameworks and infrastructure
			Sound data governance can enable secure use of data and build trust
			Continued focus on data standards and new analytical methods are needed
			Policy should also guide the ICT industry
		8.5.3. Building policy capacity
	8.6. Conclusion
	References
	Notes
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