Data Visualisation for Pharmacy
2-hour pharmacist training

Data Visualisation in Pharmacy

Turning pharmacy data into clear visuals that support safer prescribing, better decisions, stronger audits and more confident UK pharmacy interviews.

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Definition

What is data visualisation?

Data visualisation means presenting data as charts, graphs, dashboards or visual summaries so people can understand the message quickly.

It is not about making data pretty. It is about making data easier to understand and act on.
Pharmacy context

Why pharmacists use it

Safety

Identify high-risk prescribing, incidents, allergies, interactions or overdue reviews.

Quality

Track antibiotic prescribing, medicines optimisation and clinical interventions.

Operations

Monitor stock, shortages, workload, dispensing volume and service activity.

Communication

Explain findings clearly to managers, GP practices, NHS teams or interview panels.

Before visualisation

A table gives information

Tables are useful, but the pattern is not always obvious immediately.

MonthAntibiotic prescriptions
January150
February160
March170
April310
The data is there, but the insight still needs to be found.
After visualisation

A chart gives insight

The April spike becomes immediately visible.

150
Jan
160
Feb
170
Mar
310
Apr
The visual leads naturally to a clinical question: why did antibiotic use increase?
Decision guide

Choosing the right chart

QuestionBest chartPharmacy example
Which category is highest?Bar chartMost dispensed medicine
Is something increasing or decreasing?Line chartAntibiotic use over months
What percentage of the whole?Pie chartShare of services delivered
Are two things related?Scatter plotAge and number of medicines
The best chart depends on the question, not on what looks most attractive.
Rule 1

Use bar charts to compare categories

CORRECT

Bar chart for comparing medicines

420
Amlodipine
310
Metformin
180
Salbutamol

Best when comparing different items or groups.

WRONG

Line chart for unrelated categories

FluBPNMSCPCS

Lines imply movement or sequence, which is misleading for unrelated categories.

Rule 2

Use line charts to show trends over time

CORRECT

Line chart for monthly trend

JanFebMarApr

Best when the order matters: days, weeks, months or years.

WRONG

Pie chart for time trend

A pie chart hides the direction of change over time.

Rule 3

Use pie charts carefully

CORRECT

Share of pharmacy services

Works when each slice is part of one total, such as service activity mix.

WRONG

Too many slices

Too many slices become hard to compare. A bar chart is usually clearer.

Rule 4

Use scatter plots to show relationships

CORRECT

Age vs number of medicines

Each dot can represent one patient. This helps reveal relationships or risk patterns.

WRONG

Bar chart for patient-level relationship

2
P1
5
P2
8
P3
11
P4

A bar chart hides the relationship between two numeric variables.

Dashboard thinking

A pharmacist dashboard

Antibiotic trend

Line chart showing monthly prescribing volume.

Overdue reviews

Bar chart ranking patients or practices by review backlog.

Service mix

Pie or bar chart showing types of pharmacy services delivered.

High-risk patients

Scatter plot or risk matrix showing patients needing attention.

Real-life scenario

Example: GP practice medicines dashboard

A pharmacist could use one dashboard to decide where to focus clinical time this week.

42
Medication reviews overdue
18
High-risk patients flagged
+36%
Antibiotic use vs last month
7
Stock items below minimum

The dashboard does not replace clinical judgement. It helps the pharmacist prioritise the right patients and services first.

Top overdue review areas
Diabetes
Hypertension
Asthma/COPD
Polypharmacy
Action 1: Review polypharmacy patientsHigh
Action 2: Investigate antibiotic spikeHigh
Action 3: Reorder low stock itemsMedium
Common mistakes

What makes a bad visual?

Too much detail

Every chart should answer one clear question.

Wrong chart type

A beautiful chart can still be misleading.

No clear title

The title should explain the message, not just name the data.

A good chart should make the important message obvious within seconds.
Interview answer

How have you used data to improve patient outcomes?

“I use data to identify patterns that may affect patient safety or treatment quality. For example, I would review prescribing or dispensing data to spot patients overdue for medication reviews, patients on high-risk medicines, or unusual increases in antibiotic or controlled drug use. By visualising this data in charts or dashboards, I can prioritise interventions, discuss findings with the clinical team, and support safer, more effective care. The aim is not just to report numbers, but to turn data into action that improves patient outcomes.”
Final takeaway

Data visualisation turns pharmacy data into better decisions.

Data becomes information. Information becomes insight. Insight improves patient care.