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Healthcare productivity is how effectively a health service turns its workforce, time, skills, facilities, equipment and information into care. It can be improved by reducing avoidable work, organising teams and staffing around real workload, and using data and technology to address specific care needs—but higher patient volume alone is not a productivity gain if safety, quality, access or fairness suffers.
What does healthcare productivity mean?
Productivity describes the relationship between the resources used to provide care and the outputs produced. Outputs might be consultations or hospital discharges; the relevant resources include clinicians and other staff, their time and skills, facilities, equipment and supporting services. Because care is usually produced by teams using shared resources, counting one profession’s activity in isolation can give an incomplete picture.
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More activity is not automatically better productivity. A service that sees more patients by shortening visits may be missing care needs, creating repeat visits or compromising safety. A meaningful gain means producing more or better care from a given set of resources—or achieving comparable care with fewer resources—while checking the effects on outcomes and the people who need and deliver that care.
The right measure depends on the setting. A clinic, hospital and national system do not produce the same outputs or use resources in the same mix.
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| Setting | Possible output to measure | Inputs to consider |
|---|---|---|
| Primary-care clinic | Consultations or completed care episodes | Clinical and administrative staff time, rooms, equipment and information systems |
| Hospital | Discharges or completed episodes of care | Team labour, beds, operating rooms, diagnostic equipment and other capital |
| National health system | Services delivered or health outcomes for a defined population | Workforce, facilities, technologies, financing and system-wide organisation |
These are examples, not interchangeable measures: a comparison needs a defined population, period, case mix and resource denominator.
What drives healthcare productivity?
Workforce capability and distribution
Training, experience and the fit between skills and tasks affect what a workforce can accomplish. So does where staff work and which levels of care they support. The World Health Organization (WHO) identifies inadequate resources, uneven distribution across geography and care levels, uncoordinated workforce practices and weak workforce information as management challenges. A system can have a staffing problem even when its total headcount appears adequate if skills or staff are poorly matched to need.
Teamwork and work design
Care depends on how tasks, referrals and handoffs are organised across professions. Administrative burden, duplicated steps and poorly coordinated work can consume time without adding useful care. OECD’s 2013 analysis distinguishes working smarter through skills, organisation and technology from working longer. More hours can increase total output over a period, but that is not the same as improving output per hour or making better use of the whole care team.
Facilities, equipment and technology
Labour is only part of the production process. A clinician’s work may depend on beds, diagnostic capacity, medicines, equipment and functioning information systems. Digital tools such as risk stratification, clinical decision support, telemonitoring and provider communication networks can support access or effectiveness, but their presence does not itself demonstrate a productivity gain. Their value depends on implementation, useful data, workforce preparation and the capacity to integrate them into care.
Demand and case mix
Services face different patient needs and levels of complexity. Two teams reporting the same number of consultations may be doing different work if one serves people with more complex conditions or requires more coordination per patient. Productivity comparisons need to account for the population served and the work involved rather than treating every unit of activity as equivalent.
How should healthcare productivity be measured?
Define the question and denominator first
Before comparing services, specify the setting, population, case mix, time period, output and inputs. The measure should fit the question: consultations per clinical hour can describe a narrow workflow, while completed episodes per combined labour and capital input capture more of a service’s production process. Outcomes achieved per unit of resource ask a different question again. State what is included in the denominator; a measure that counts clinician time but ignores team labour or equipment may miss important inputs.
Pair resource and output measures with safeguards
Throughput and resource use should be assessed alongside care quality, safety, access, equity and patient-centredness. OECD’s 2023 performance framework highlights people-centredness, resilience, environmental and economic sustainability, and equity, and makes trade-offs among dimensions explicit. An apparent efficiency gain that worsens one of these outcomes needs to be reported as a trade-off, not presented as an unqualified improvement.
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WHO’s 2017 health-system monitoring framework groups indicators across service delivery, workforce, health information, medical products, vaccines and technologies, financing, and leadership and governance. Considering these domains helps distinguish a system-level productivity issue from a narrow staffing or technology measure.
Best Value
How can healthcare productivity be improved?
Remove avoidable work and duplication
Review processes for unnecessary steps, repeated documentation, duplicative tests or services, and practices that do not contribute to better care. OECD’s 2019 report estimates that around one fifth of health-care expenditure in OECD countries—about USD 1.3 trillion annually—is not used to generate better health and may sometimes cause harm. That is a cross-country aggregate estimate, not a forecast of savings a particular clinic or health system can recover. Local changes need to identify the specific low-value activity and check that removing it does not interrupt needed care.
Match staffing and roles to workload
Use activity and time standards, skill mix, geography and level of care to plan staffing rather than relying on headcount alone. WHO’s Workload Indicators of Staffing Need (WISN) method relates staffing requirements to the workload generated by health-service activities and the time standards for those activities. Workload-based planning can make mismatches visible, but it must reflect local service patterns and workforce constraints.
Design teams and pathways around the work
Examine which tasks require which skills, how teams share responsibilities, and where referrals or handoffs create delay or duplication. Review role design together with capital and support services: changing one worker’s responsibilities may simply shift work elsewhere if the rest of the team or required equipment is unavailable. Coordination is especially relevant where patients need continuing support across services.
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Start with a care or workflow need, then assess whether a tool such as risk stratification, decision support, telemonitoring or a provider communication network addresses it. Evaluate implementation costs, data governance, data quality, workforce readiness and patient access as part of the decision. OECD’s 2019 analysis presents digital approaches as potential enablers of access, effectiveness and productivity, not as guaranteed results for every service.
Check whether the change produced a real gain
Compare results against a clearly defined baseline using the same population, case mix, period and inputs. Track the intended output or outcome along with the relevant safeguards, and examine whether the change shifts workload, limits access or affects groups differently. Local regulation, labour markets, capital constraints, data quality and implementation capacity can all shape whether an approach works in practice.
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