Rethinking productivity in healthcare: from targets to an operating mandate

by Jeff B.

This article will explore in more depth healthcare’s complicated relationship with productivity approaches and offer some practical key focuses for changing the narrative and making tangible improvement when looking to squeeze more from healthcare services. Based on real-life experiences and programmes in the UK National Health Service (NHS), the learnings are transferable across geographies and will resonate with leaders in the GCC (Gulf Cooperation Council) and other parts of the world.

“Productivity” has quietly become one of the most loaded words in healthcare.

For some, it means squeezing more activity out of already-stretched teams. For others, it’s a technical construct – implied productivity growth curves, index numbers and benchmarking dashboards. For many clinicians and operational leaders, it’s simply another demand layered on top of waiting-time standards, quality metrics, and financial control totals.

All of these perspectives are understandable. But if we stop there, productivity remains a Finance or Performance conversation – something done to services, not with them.

If we take productivity seriously, it needs to be reframed as an enterprise operating mandate: the way an organisation consistently converts resources into outcomes across pathways, sites and care settings. That is much closer to how it actually shows up in the day-to-day work. 

The real productivity problem: it lives between domains

Most of the biggest productivity losses in healthcare don’t sit neatly inside one department; they live in the handoffs and gaps:

• Patients medically fit for discharge but delayed by community capacity, transport, or housing issues.
• Clinics cancelled because digital and administrative processes for booking, reminding and re-booking are inconsistent.
• Community or mental health teams spending hours reconciling data from multiple systems because definitions differ by service.

In a spreadsheet, these issues appear as poor bed utilisation, low theatre productivity, or high “did not attend” rates. In reality, they are cross-functional flow problems: ambiguous ownership, inconsistent processes, and weak feedback loops between teams. This is why a narrow, department-by-department view of productivity so often disappoints. We optimise small pieces of the system while leaving the underlying operating model untouched.

Practical takeaway:

If your productivity conversation starts and ends with “activity per WTE (Whole Time Equivalent)” at the service level, you’re probably treating symptoms, not causes.

The maturity gap: acute vs non-acute services

In many systems, acute providers have spent years refining operational data: theatre utilisation, length of stay by HRG (Healthcare Resource Group), diagnostic turnaround times, bed occupancy profiles by hour of day. It’s not perfect – but it’s usable.

By contrast, non-acute settings (community, mental health, specialist services) often have:

• Fragmented or legacy systems.
• Inconsistent definitions of “contact,” “episode”, or “intervention.”
• Limited costing information at the pathway or team level.
• Manual workarounds that never quite make it into the official data.

This creates a paradox. The NHS narrative increasingly (and rightly) emphasises shifting care “closer to home.” But the largest headroom for productivity improvement lies precisely in those parts of the system where data maturity is weakest. Until we invest in better definitions, tooling and governance for non-acute productivity, we will chronically underestimate both the problems and the opportunities.

Example:

A community mental health team (CMHT) appears to have “low productivity” on crude contacts-per-WTE metrics. A closer look shows they are spending significant time on multi-agency meetings, safeguarding work and complex crisis planning – none of which is recorded as activity. The problem isn’t laziness; it’s a measurement model that can’t see the work.

Practical takeaway:

Where data is immature, start by improving definitions and capture, not by setting blunt productivity targets.

Defining the productivity mandate

Before designing dashboards or chasing percentage gains, organisations should answer three basic questions:

1. What are we trying to improve?
   Is the primary problem access, timeliness, experience, cost, outcomes – or some combination? “Be more productive” is not a strategy.
2. Where is the value destroyed today?
   Look beyond high-level indices. Where are the queues, rework, duplicated activity, stranded capacity, or avoidable failure demand?
3. Who owns cross-functional performance?
   If no single role is accountable for flow across services, your productivity programme will default back to silos.

A mature productivity mandate usually includes:

• A clear set of enterprise outcomes (e.g. time to first meaningful contact, safe length of stay, avoidable readmissions, staff time in value-adding work).
• A measurement framework that combines volume, cost, quality and equity – not just “activity per £”.
• An operating model: standard huddles, escalation routes, and decision rights that allow productivity issues to be identified and acted on quickly.

What good looks like: a short illustrative example

Imagine a mental health provider collaborative noticing sustained pressure on crisis services and inpatient beds. Rather than launching a generic “be more productive” initiative, they:

1. Define the problem:
   Unplanned admissions and length of stay are rising; crisis teams are firefighting; staff feel they are doing more but achieving less.
2. Map the pathway, not just the ward:
   They trace the journey from early deterioration in the community through to crisis, admission, and discharge – across CMHTs, crisis services, wards and local authorities.
3. Identify productivity pain points:
   • Duplicated assessment across teams.
   • Variation in gatekeeping practices.
   • Delays in housing and social care input.
   • Documentation and handovers are done differently in each team.
4. Redesign the operating model:
   • A single, standardised triage and assessment model.
   • Shared caseload views across teams via a common digital tool.
   • Joint discharge planning with community teams from day 1 of admission.
   • A tiered performance cadence: ward and team huddles, weekly cross-service flow meetings, and monthly system review.
5. Measure what matters:
   • Time from first contact to crisis plan.
   • Proportion of patients with a documented step-down plan at discharge.
   • Staff time spent on direct clinical work vs administrative rework.

Within a year, they may see fewer avoidable admissions, shorter stays and improved staff satisfaction – with better data, not despite it. This is productivity as better system design, not heroics.

Authority and governance: the make-or-break factors

Productivity programmes fail when:

• Responsibility is given to a small central team, but line leaders retain all the decision rights.
• Targets are set centrally, but clinical and operational leaders have no levers to change pathways, roles or digital tools.
• Boards demand results, but governance forums are fragmented, with performance, quality, workforce and finance discussed in isolation.

A more robust approach is to treat productivity as a governance design question:

• Who has the mandate to redesign work across departments, not just within them?
• How do performance meetings escalate issues from ward or team level to the Board, with clear actions and follow-through?
• Which forums explicitly review benefits realisation from digital and transformation programmes – not just delivery milestones?

Practical takeaway:

If productivity is everyone’s job, it is also no one’s job. Write down where the authority sits – and align your meeting structure to it.

Time-bound productivity missions

One useful pattern is to frame productivity as a time-bound mission, not an endless squeeze:

• Year 1 – See and stabilise:
  Improve data quality, agree on definitions, establish a basic operating cadence and fix the most obvious waste.
• Year 2 – Redesign and embed:
  Tackle cross-functional flow issues, redesign high-impact pathways, and align digital tools and workforce models.
• Year 3 – Optimise and hand over:
  Build local capability, refine measures, and embed productivity thinking into business planning and quality improvement.

 This makes the work tangible, allows progress to be tracked, and avoids fatigue from “eternal productivity drives” that never seem to end.

Key takeaways for healthcare leaders

1. Productivity is an operating system issue, not a spreadsheet issue.
   The biggest gains come from redesigning how work flows across teams, not from tightening individual targets.
2. Non-acute services are the next frontier.
   Invest in data maturity, definitions and tooling where they are weakest – community, mental health, specialist and primary care interfaces. That’s where much of the hidden opportunity lies.
3. Define the mandate before you define the metrics.
   Be explicit about what you are trying to fix, how you’ll measure it, and who has the authority to act.
4. Governance is a strategy made real.
   If your performance meetings don’t surface, prioritise and resolve productivity issues, your strategy will stay theoretical.
5. Make it a time-bound mission, not endless pressure.
   Structure productivity programmes with clear phases, milestones and hand-offs into business-as-usual.

Done well, productivity work is not about doing more with less; it is about doing the right things, in the right order, with the least friction for patients, their families, carers and staff.

That is a mandate worth taking seriously.