Teams are rarely short of improvement ideas.
In most healthcare organisations, there are more opportunities for improvement than there is time, capacity, or resource to address them. Teams are often surrounded by problems that all feel important: delays, complaints, incidents, handover issues, documentation problems, variation in practice, and pressure from different stakeholders.
The challenge is not always knowing that improvement is needed.
The challenge is deciding where to start.
When everything feels important, teams can find themselves trying to solve too many problems at once. Effort becomes spread across multiple areas, progress slows, and it becomes harder to show measurable impact.
Prioritisation is therefore one of the most important decisions an improvement team makes.
Healthcare improvement work often begins with a broad goal.
A team might want to:
Each of these goals can quickly reveal a long list of possible causes and contributing factors.
For example, a team trying to reduce delayed discharges might identify issues with transport, medication, social care arrangements, documentation, communication, assessment processes, and ward routines.
Each issue may be real. Each may matter to someone. Each may have a reasonable case for attention. But trying to address all of them at once is rarely effective.
Improvement work depends on focus. Without focus, teams risk creating activity without progress.
Prioritisation is not difficult because teams lack commitment. It is difficult because improvement work involves competing signals.
A recent incident may feel urgent. A senior stakeholder may have a strong view. A particular problem may generate the most discussion in meetings. A vocal group of staff may highlight one issue repeatedly. A dataset may suggest something different again.
These signals do not always point in the same direction.
Teams can find themselves asking:
There is rarely a perfect answer. But there is a better way to make the decision.
Poor prioritisation has a real impact on improvement work.
When teams do not have a clear way to decide what matters most, they may:
This can be frustrating for teams who are working hard but not seeing the results they expected.
Often, the problem is not a lack of effort. It is that effort has not been focused where it will make the greatest difference.
Improvement teams often begin with assumptions about what is causing a problem.
That is natural. People closest to the work usually have valuable insight into what is happening and why. But assumptions can also mislead.
The most recent issue is not always the most common issue. The loudest complaint is not always the biggest driver of poor experience. The most visible problem is not always the highest-impact problem. The issue that feels easiest to fix is not always the one that matters most.
This is why teams need ways to combine local knowledge with evidence.
Good prioritisation does not ignore professional judgement. It strengthens it by grounding decisions in data.
When teams are faced with multiple possible priorities, a useful question is:
Which causes are contributing most to the problem we are trying to solve?
This question shifts the conversation.
Instead of asking which issue feels most important, teams begin asking which issue is having the greatest effect. That shift matters.
It helps teams move from opinion-led prioritisation to evidence-informed prioritisation. It also creates a stronger basis for shared decision-making. When the data is visible, teams can discuss priorities with a common understanding of the problem.
One simple way to answer this question is to use a Pareto chart.
A Pareto chart helps teams see which causes, categories, or types of issue contribute most to an overall problem. It does this by arranging categories from most frequent to least frequent and showing their cumulative contribution.
The value of a Pareto chart is not just that it displays data clearly. Its value is that it helps teams make a decision.
Instead of treating all causes equally, teams can identify the “vital few” areas where focused improvement effort is most likely to have the greatest impact.
For improvement teams, this can help:
A hospital team is working to reduce delayed discharges.
At first, the team has a long list of possible causes: transport delays, medication delays, social care arrangements, outstanding assessments, documentation issues, and communication problems.
Different team members have different views about what matters most.
Some feel social care availability is the biggest issue. Others believe the main problem is internal communication. Others point to pharmacy delays.
Rather than choosing based on opinion, the team collects data on the primary reason for each delayed discharge over several weeks.
The analysis shows that two causes account for a large proportion of the delays: transport coordination and medication delays.
This changes the nature of the discussion.
The team may still need to understand why those delays are happening, but they now have a clearer starting point. Instead of trying to improve every part of the discharge process at once, they can focus first on the areas most likely to reduce the overall number of delays.
A patient experience team wants to reduce complaints.
The complaints cover a wide range of themes, including waiting times, communication, staff attitude, appointment scheduling, access to services, and information quality.
The team initially assumes that waiting times are the dominant issue because they are mentioned frequently in meetings and are a visible source of frustration.
However, when complaints are categorised and analysed, communication issues emerge as the most common theme.
This insight changes the improvement opportunity.
The team may still need to work on waiting times, but the data suggests that communication should be a priority if the goal is to reduce the overall volume of complaints.
The improvement focus might then shift towards clearer appointment information, better updates during delays, improved discharge conversations, or more consistent communication standards across teams.
High-performing improvement teams do not simply work harder. They make better decisions about where to focus.
They are disciplined about separating the overall problem from its contributing causes. They use data to test assumptions. They make patterns visible. They create shared understanding before jumping into solutions.
This does not mean they wait for perfect evidence. In real improvement work, data is often incomplete, messy, or gathered from operational systems that were not designed for improvement. But even imperfect data can be useful when it is collected consistently and discussed carefully.
The goal is not to remove judgement from improvement work. The goal is to improve judgement by making the evidence easier to see.
Prioritisation should not happen in isolation.
A chart or dataset can show where problems appear to be concentrated, but frontline knowledge is still needed to interpret what the data means.
Teams should ask:
This is where Pareto analysis is most useful: not as a replacement for team judgement, but as a way to support better conversations.
Pareto charts are especially useful for showing which causes occur most often. But frequency should not be the only consideration when prioritising change.
Some issues may occur less often but carry greater risk, harm, cost, or regulatory significance. Others may be less frequent but highly distressing for patients, families, or staff.
Good prioritisation should consider:
Pareto charts are therefore best used as part of a wider improvement conversation.
They help teams see where the largest patterns are, but teams still need to decide how those patterns should influence action.
Once a team has identified where to focus, the next step is to understand the selected priority in more detail.
If medication delays are a major cause of delayed discharge, the team may need to understand:
The priority identified by the Pareto analysis becomes the starting point for deeper investigation and testing.
From there, teams can develop change ideas, test them on a small scale, and measure whether they are making a difference. (All of which they can easily do in Simana 😉).
The key is that the team is no longer trying to improve everything. It has chosen a focused starting point.
Improvement work requires energy, attention, and trust.
When teams repeatedly invest effort without seeing progress, confidence can fall. Staff may become sceptical about improvement initiatives, especially if they feel disconnected from the real issues affecting day-to-day work. Clear prioritisation helps prevent this.
When teams can see why a particular issue has been chosen, they are more likely to understand the rationale for action. When the chosen issue is visibly connected to the wider problem, progress is easier to explain. This helps improvement feel more focused, more credible, and more achievable.
Prioritisation is one of the most important challenges in improvement work.
Healthcare teams often face many possible problems, all competing for attention. Without a structured way to decide where to focus, effort can become fragmented and impact can be limited.
Pareto charts help teams make better prioritisation decisions by showing which causes contribute most to a problem.
They help teams move beyond assumptions, build shared understanding, and focus effort where it is most likely to make a meaningful difference.
For improvement teams working in complex healthcare environments, that clarity can be the difference between lots of activity and real progress.