Rethinking Healthcare Delivery
Rethinking Healthcare Delivery
The need to redesign care delivery, and how redesigning delivery processes, supported by current AI and other present-day technology, can address rising costs and the shortage of healthcare personnel.
Health systems face rising cost and a workforce that cannot keep pace. Technology, including AI, offers real capability but delivers gains only when the work around it is redesigned. Adding tools to unchanged workflows tends to raise cost and clerical load rather than reduce them.
The pressures are structural
Health systems across Europe and beyond face two pressures at once. Spending keeps climbing: across OECD countries, health expenditure averaged 9.3% of GDP in 2024, with official projections attributing continued growth to ageing populations, rising public expectations, and the cost of new technology. At the same time, the workforce available to deliver care is not keeping pace. A peer-reviewed reassessment of WHO workforce data projects a global shortfall of about 10 million health workers by 2030, most acute among nurses and in lower-income regions, but felt in recruitment and retention across high-income systems as well. Demand is rising faster than the supply of people able to meet it.
of GDP across OECD countries, and projected to keep climbing.
health workers short by 2030, most acute among nurses.
Demand is rising faster than the supply of people able to meet it.
What current technology, including AI, can and cannot do
Several technologies are now mature enough to change how care is delivered: electronic records, remote monitoring, clinical decision support, and a widening set of artificial-intelligence applications. The evidence calls for a careful reading. A systematic review and meta-analysis in The Lancet Digital Health found that deep-learning models matched health professionals at detecting disease from medical images, sensitivity of roughly 87% against 86%, yet fewer than 1% of the reviewed studies were of sufficient quality to support firm conclusions. A later scoping review in the same journal reported that only a small fraction of registered clinical AI trials have published results, and that strong diagnostic performance does not reliably translate into better patient outcomes. The capability is real; the benefit depends on how a tool is deployed, not on the tool itself. AI has to earn its place in the encounter.
of reviewed studies were strong enough to support firm conclusions.
of large-scale digital initiatives miss their intended objectives.
The capability is real. The benefit depends on how a tool is deployed, not on the tool itself.
Redesign is where the gains are realised
The clearest opportunity lies in how clinicians spend their time. A direct observational study of ambulatory practice found physicians spent only about 27% of the working day in direct contact with patients, and close to two hours on records and administrative work for every hour of patient care.
Adding technology to an unchanged workflow tends to raise cost and clerical load rather than reduce them. The gains come from redesigning the work around the technology: returning clinical time to patients, easing pressure on scarce staff, restraining cost growth. Which tasks are automated, which are reassigned, which are removed, and how the remaining steps connect.
of the working day is spent in direct contact with patients, nearly two hours on records for every hour of care.
Adding technology to an unchanged workflow tends to raise cost and clerical load. Redesign is where the gains are realised.
How we support this work
We help provider and payer organisations rethink delivery along these lines, with analysis grounded in peer-reviewed evidence rather than vendor claims. Typical engagements include:
- Measuring where clinical and administrative time is actually spent, and where technology can recover it.
- Appraising specific AI and digital tools against published evidence and the organisation's own data, separating proven capability from marketing.
- Redesigning care pathways and operating models so that automation and task reallocation reduce, rather than add to, the burden on staff.
- Building the measurement needed to test whether changes improve patient outcomes, workload and cost, before and after adoption.
The pressures on care delivery are structural and will intensify. Organisations that redesign how care is delivered, and adopt technology in service of that redesign, will be far better placed than those that buy tools and hope. Technology dropped onto unchanged workflows, and onto users who were not brought with it, usually produces expensive failure. Published healthcare literature consistently reports high failure rates for large-scale digital health rollouts, while industry studies commonly estimate that around 70% of initiatives fail to achieve their intended objectives. The standard is simple: redesign the work first, adopt the technology in service of that redesign, and measure whether the redesign delivers.
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Redesign the work first.
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Adopt the technology in service of that redesign.
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Measure whether the redesign delivers.
- 01Boniol M, et al. The global health workforce stock and distribution in 2020 and 2030: a threat to equity and 'universal' health coverage? BMJ Global Health. 2022;7(6):e009316. doi:10.1136/bmjgh-2022-009316.
- 02Dendere R, Janda M, Sullivan C. Are we doing it right? We need to evaluate the current approaches for implementation of digital health systems. Aust Health Rev. 2021 Dec;45(6):778–781. doi:10.1071/AH20289. PMID: 34488938.
- 03Liu X, Faes L, Kale AU, et al. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. The Lancet Digital Health. 2019;1(6):e271–e297. doi:10.1016/S2589-7500(19)30123-2.
- 04Han R, Acosta JN, Shakeri Z, Ioannidis JPA, Topol EJ, Rajpurkar P. Randomised controlled trials evaluating artificial intelligence in clinical practice: a scoping review. The Lancet Digital Health. 2024;6:e367–e373. doi:10.1016/S2589-7500(24)00047-5.
- 05Sinsky C, Colligan L, Li L, et al. Allocation of physician time in ambulatory practice: a time and motion study in 4 specialties. Annals of Internal Medicine. 2016;165(11):753–760. doi:10.7326/M16-0961.
- 06OECD. Health at a Glance 2025: OECD Indicators. Paris: OECD Publishing; 2025. doi:10.1787/8f9e3f98-en.
References 1 to 5 are peer-reviewed; reference 6 is an official OECD statistical compilation.
Acuvera Advisory · Healthcare strategy, market intelligence and organisational advisory · Prepared June 2026