Digitised Diseases Making sense of health data, research and public health

Digitised Diseases

Making sense of health data, research and public health

Latest Articles

The Ledger of Harm: Reading NHS Patient Safety Incidents as a Record of Reporting
Public Health Data

The Ledger of Harm: Reading NHS Patient Safety Incidents as a Record of Reporting

Patient safety incident figures are often read as a direct count of harm, but they are better understood as a record of what was noticed, reported and coded. This article explains how NHS incident data is made in 2026, why reporting variation matters, and how to read safety headlines without turning a learning ledger into a league table of blame.
Public Health Data

The Sorting Room: How NHS Referral Data Shapes the Waiting List We See

NHS waiting-list headlines begin after a referral has been received, triaged and accepted. This article explains what e-Referral Service and referral-to-treatment data record in that earlier sorting room, and how to read redirects, rejections and choice data without confusing a management metric with the patient experience.
Staffed, Not Empty: Reading Adult Social Care Data Beyond the Discharge Headline
Public Health Data

Staffed, Not Empty: Reading Adult Social Care Data Beyond the Discharge Headline

Adult social care figures are now a fixture of the winter discharge debate, yet occupancy, staffing hours and inspection ratings are three different instruments measuring three different things. This is a guide to the 2026 numbers — and to the denominators, case mix and reporting cycles that can turn a complicated picture into a tidy but misleading headline.
Behind the Counter: What Pharmacy First’s Consultation Data Can and Cannot Tell Us in 2026
Public Health Data

Behind the Counter: What Pharmacy First’s Consultation Data Can and Cannot Tell Us in 2026

Pharmacy First has created a new administrative record of consultations in community pharmacy, but the ledger measures paid activity rather than the whole of minor-illness demand. This article explains how consultations, condition pathways and referral outcomes are recorded, and why the figures should not be read as a direct substitute for GP appointments.
The Unwritten Category: Reading the Gaps in NHS Ethnicity Data
Public Health Data

The Unwritten Category: Reading the Gaps in NHS Ethnicity Data

Blank ethnicity fields are often treated as background noise in NHS datasets. This article explains how 'not stated', 'unknown' and genuinely absent data differ, why completeness varies across settings, and how missingness can reshape Britain's health inequality statistics in 2026.
Counting Resistance: How One Urine Sample Becomes a National AMR Statistic
Public Health Data

Counting Resistance: How One Urine Sample Becomes a National AMR Statistic

A single urine sample sent from a GP surgery can end up as part of a national antimicrobial resistance percentage. Tracing that journey shows why denominators, sampling and laboratory practice matter as much as the headline figure. In 2026, reading AMR surveillance well means asking what was tested, what was counted and what was left out.
The Scale Is Not the Suffering: Interpreting Pain Scores in NHS Data
Digital Health & Devices

The Scale Is Not the Suffering: Interpreting Pain Scores in NHS Data

Pain scores are now a routine digital entry in many NHS records, from emergency departments to community nursing. But a 0–10 rating is a request for communication, not a measurement of suffering. Reading pain data well means asking who was asked, how the question was put, and what happens next.
Between the Envelope and the Result: Reading Cancer Screening Uptake in 2026
Public Health Data

Between the Envelope and the Result: Reading Cancer Screening Uptake in 2026

Cancer screening statistics are often read as a verdict on public behaviour, but they are better understood as a record of an administrative process. This article explains how invitation coverage, uptake and data lag shape what the NHS figures can and cannot tell us in 2026.
The Probability in the Report: Reading NHS Genomic Test Data Without Overreading It
Pathology & AI

The Probability in the Report: Reading NHS Genomic Test Data Without Overreading It

NHS genomic testing figures are often reported as if every finding were a diagnosis. This guide separates laboratory detection from clinical explanation, explains why variants of uncertain significance belong in the data, and shows how to read Genomic Medicine Service counts in 2026 with the right denominators and categories.
The Unit and the Patient: Reading NHS Dental Access Data Beyond the Headlines
Public Health Data

The Unit and the Patient: Reading NHS Dental Access Data Beyond the Headlines

NHS dental access is frequently reported as a simple story of shortage, but the figures behind it are built from activity counts, contract currencies and rolling time windows. This guide explains what the data actually records, where regional variation comes from, and why a headline about disappearing dentists can obscure more than it reveals.
Between the Call and the Care: Reading NHS 111 as a Triage Ledger in 2026
Public Health Data

Between the Call and the Care: Reading NHS 111 as a Triage Ledger in 2026

NHS 111 produces a detailed record of how calls are routed, not a diagnosis of the nation’s health. In 2026, reading call volumes, dispositions and emergency-department referrals means distinguishing demand from capacity, and unmet need from the absence of a record.
The Notification Chain: Why Britain’s Measles Count Is a Process, Not a Number
Public Health Data

The Notification Chain: Why Britain’s Measles Count Is a Process, Not a Number

A measles alert looks like a simple count, but every figure on a UK dashboard has passed through clinical notification, laboratory confirmation, local investigation and outbreak definitions. In 2026, reading those layers carefully matters more than reacting to every cluster as if it were a crisis.
Certified Absence: Reading Britain's Fit-Note Data Without Overdiagnosing the Nation
Public Health Data

Certified Absence: Reading Britain's Fit-Note Data Without Overdiagnosing the Nation

Digitised fit-note records are now a substantial public data source, routinely cited in debates about work, welfare and illness. But a fit note is an administrative document, shaped by GP workload, employer practice and benefit rules, not a clean register of disease. This article sets out which claims the fit-note record can support in 2026, and which it quietly distorts.
The Bed That Isn't There: Reading the Data Behind NHS Virtual Wards
Digital Health & Devices

The Bed That Isn't There: Reading the Data Behind NHS Virtual Wards

Virtual wards move the observation of illness from a hospital bay into a living room, and with it the point at which data is created. This piece examines what remote-monitoring records capture, which patients quietly fall out of the feed, and why a stable dashboard is not the same thing as a stable patient.
Three Clocks, One Scan: Reading NHS Diagnostic Imaging Queues in 2026
Public Health Data

Three Clocks, One Scan: Reading NHS Diagnostic Imaging Queues in 2026

NHS imaging waiting-list figures compress a complex journey—referral, triage, appointment, report—into a single number. This guide explains how modality, referral route and community diagnostic centres shape the queue, and why the interval between referral and result deserves more attention than the headline count.
Counting Absence, Missing Cause: What NHS No-Show Records Actually Measure
Public Health Data

Counting Absence, Missing Cause: What NHS No-Show Records Actually Measure

Missed appointments are often framed as waste or patient failure. But NHS no-show figures are operational records shaped by definitions, digital systems and local circumstances. Read carefully, they can point towards access barriers rather than apathy.
The Unspecified Patient: What NHS R-Codes Reveal About Diagnostic Uncertainty
Public Health Data

The Unspecified Patient: What NHS R-Codes Reveal About Diagnostic Uncertainty

ICD-10 codes in the R00–R99 chapter are often read as a sign of medical mystery. In NHS hospital statistics and ONS mortality data, they more often record a familiar administrative and clinical reality: a patient needed a code before a firm diagnosis was available.
From Certificate to Statistic: A Reader’s Guide to UK Mortality Data
Public Health Data

From Certificate to Statistic: A Reader’s Guide to UK Mortality Data

Death certificates become public health statistics through a chain of clinical judgement, legal process and coding. This guide explains how cause-of-death data is produced in the UK, what underlying and contributing causes mean, and why mortality figures deserve careful reading rather than immediate conclusions.
Occupancy Is Not a Diagnosis: Reading NHS Winter Flow Data in 2026
Public Health Data

Occupancy Is Not a Diagnosis: Reading NHS Winter Flow Data in 2026

As winter 2026 approaches, NHS bed occupancy and discharge delays return to the headlines. But flow data are operational instruments, not a verdict on care. This analysis explains what the numbers record, where they mislead and how to read them with winter in mind.
The Report Is Not the Event: Reading Britain’s Yellow Card Signals Carefully
Public Health Data

The Report Is Not the Event: Reading Britain’s Yellow Card Signals Carefully

The MHRA Yellow Card scheme turns individual suspicions about medicines into a national safety signal. But a report is not a proven harm, and a rise in entries is not automatically a rise in disease. This guide explains how to read the data with the caution the system itself requires.