Rolf Benziger, lecturer in software engineering at the University of Westminster, examines what Florence Nightingale could teach us about NHS waiting lists.
Florence Nightingale is still remembered, above all, as “the lady with the lamp”, the nurse walking among the beds of the military hospital in Scutari during the Crimean War. However, Nightingale was not only a nurse. She was also a campaigner and one of the great pioneers of data communication. She didn’t just collect evidence – she made data visible, persuasive and politically difficult to ignore.
That distinction matters today. The NHS is not short of data. It has waiting time statistics, operational dashboards, performance targets, referral-to-treatment measures, theatre utilisation figures, discharge data and workforce metrics. Yet the waiting list for elective care in England remains stubbornly high: NHS England reported around 6.1 million people waiting for treatment at the end of February 2026. While the number is falling, it’s still far above constitutional ambitions.
So the problem is not simply the absence of information. It is whether information is being communicated in a way that leads to better decisions.
Nightingale Roses
Nightingale understood this. During the Crimean War, she showed that many soldiers were not dying primarily from battle wounds, but from preventable disease. Her famous “Nightingale Roses”, polar area diagrams showing the causes of death, made the scale of the deaths from preventable diseases visually unmistakable. The point was not decorative data visualisation. It was a moral argument through evidence. By clearly showing patterns, she helped persuade policymakers that sanitary reform was not optional but urgent.
That lesson is highly relevant to today’s NHS. Waiting lists are often discussed as a single large number. But a large number can obscure as much as it reveals. It tells us that patients are waiting, but not enough about where the delays arise, which parts of the system are under pressure, what types of patients are most affected, or which interventions would make the biggest difference.
If Nightingale were to look at NHS waiting lists now, I suspect she would not ask for more complex dashboards. She would ask better questions.
First, she would focus on causes. Many modern dashboards are descriptive: they show what has happened, how many people are waiting, and whether performance is moving up or down. Although useful, this is insufficient. A Nightingale-style approach would diagnose the issues and prescribe solutions. It would ask: which pathways are creating the longest delays? Are bottlenecks caused by diagnostics, outpatient capacity, theatre scheduling, staffing, discharge delays, cancellations, or follow-up processes? Which waits are clinically risky, and which are administratively avoidable?
Second, Nightingale would look at the whole end-to-end patient journey. Waiting lists are not produced at a single point. They emerge across pathways: referral, triage, diagnostics, outpatient review, decision to admit, pre-operative assessment, surgery, discharge and follow-up. Looking only at isolated statistics risks missing the flow of patients through the whole system. This is where process mining could help. Rather than treating waiting lists as static queues, we can examine the sequence of events that patients actually experience. We can identify where patients loop back, where handovers fail, where cases sit idle, where appointments are cancelled, and where different patient groups experience different patterns of delay. Recent reporting on elective surgery cancellations, for example, has highlighted how late identification of medical issues, missed tests, emergency pressures, and list overruns can disrupt planned care. These are not just numbers; they are signals about how the system behaves.
Third, Nightingale would communicate consequences, not just metrics. A waiting list is not merely an operational backlog. It represents pain, uncertainty, deterioration, anxiety, lost work, family stress and, in some cases, avoidable harm. Data communication should make those consequences visible without becoming sensationalist. It should connect system behaviour to human experience.
This is especially important in a world producing more data than ever. The research firm IDC estimates that more than 527 zettabytes of data will be generated globally in 2029. But more data does not automatically mean more understanding. In many organisations, including healthcare systems, the result is an abundance of dashboards that are technically impressive but strategically weak: crowded, fragmented, hard to interpret, and better at reporting performance than enabling action.
Better communication
Nightingale’s genius was not that she had data. It was that she transformed data into a case for reform. She understood that evidence must be arranged, framed and communicated so that decision-makers can see both the problem and the responsibility to act.
For the NHS, the lesson is simple but demanding. We should not ask dashboards merely to display waiting lists. We should ask them to explain waiting, expose preventable delay, connect operational failures to patient consequences, and guide action. The goal is not more measurement for its own sake, but better communication in the service of better care.
If Nightingale were here today, she would probably recognise the danger of mistaking visibility for insight. A number on a dashboard can tell us that the system is under strain. But unless it shows why the strain occurs, where it accumulates, and what could be changed, it risks becoming another lamp held over a problem we have already learned to tolerate.
Evidence matters. But Nightingale’s enduring lesson is that evidence only changes systems when it is made visible, intelligible and actionable.
