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Business area digitalisation analysis

Diagnostic centres and laboratories: digitalisation analysis

How to connect test orders, samples, equipment, results, quality control and clinical responsibility

Digital maturity

Typical digital maturity

Shows the level of technological and process digitalisation at which companies in the sector or business area typically operate today.

A typical market situation is assessed, not the most advanced companies.

The assessment consists of five equally weighted dimensions:

Core system usage
Whether ERP, CRM, WMS, MES, customer portals or other operationally important systems are widespread in companies.
Process digitalisation
How many core processes run in systems and how many are still managed manually.
Systems integration
Whether core systems exchange data between themselves or whether employees transfer information manually.
Data quality and readiness
Whether core data is structured, up-to-date, consistent and suitable for automation and analytics.
Advanced data use
Whether real-time analytics, forecasting, automated alerts, optimisation models or AI are used.

The final score is the average of the five dimensions.

1–5 scale

  • 1 very low maturity
  • 2 low maturity
  • 3 medium maturity
  • 4 high maturity
  • 5 very high maturity

A low maturity score does not necessarily indicate low potential. On the contrary, low maturity and a high level of manual work may indicate significant untapped digitalisation value.

high
Skaitmenizacijos potencialas

Digitalisation potential

Shows how much significant business value a typical sector or business area company can create by systematically digitalising core processes.

The rating is calculated on a 100-point scale across five dimensions:

Process frequency and scale 20 %
An assessment of how frequently the digitalised processes recur and what proportion of operations they represent.
Manual work intensity 20 %
An assessment of the extent to which processes depend on email, telephone, Excel, paper documents and repeated data entry.
Impact on revenue and costs 25 %
An assessment of the potential effect on sales, margin, customer retention, administrative costs, errors, downtime or inventory.
Growth and scale potential 20 %
An assessment of whether digitalisation would enable operational capacity to be increased without expanding headcount and costs at the same rate.
Impact on decisions and risk 15 %
An assessment of the potential effect on data reliability, decision-making speed, customer experience, and the reduction of errors and operational risk.

The final score is calculated according to the assessments and weights of all dimensions.

100-point scale

  • 0–20 very low potential
  • 21–40 low potential
  • 41–60 moderate potential
  • 61–80 high potential
  • 81–100 very high potential

A high score does not mean the solution will be easy to implement. It indicates the size of the potential value, not the implementation complexity.

92/100
Biggest challenge
Test orders are received in inconsistent formats
Biggest opportunity
Closed-loop diagnostics

Very high potential and highly complex business area.

How diagnostic centres and laboratories operate

The business area encompasses laboratory medicine, radiology, pathology and other diagnostic centres, where value is created not only by performing the test, but also by reliable management of the entire information chain.

Each test has a traceable object

In the laboratory it is a specimen, in radiology – a study and image series, in pathology – material, a slide and a digital image.

Technical automation does not eliminate clinical responsibility

Equipment can perform a measurement or assist in prioritisation, but the appropriateness of the result and its clinical significance are confirmed by a specialist.

Critical handover points determine safety

The greatest risk arises between referral, identity, specimen or image, result, alert and responsible clinical action.

Quality control is an integral part of the process

Reagents, calibration, control specimens, equipment status and non-conformances must be linked to specific results.

Market and technology context

Diagnostics digitalisation is shaped by HL7 FHIR health data and DICOM medical imaging standards, digital pathology, automated sample traceability and validated AI support for medical image and quality signal analysis.

  • Test volumes are growing faster than specialist capacityThere is growing demand to automate routine checks, prioritise tasks and reduce unnecessary data re-entry.
  • Interoperability is becoming a fundamental condition for service qualityAn order and result must move between different clinical systems without losing identity, terminology and context.
  • Digital images expand remote working possibilitiesRadiology and pathology specialists can collaborate regardless of physical location, provided image quality and secure access are assured.
  • AI is moving from experiment to controlled workflowThe greatest value is created not by an individual model, but by its integration into specialist review, prioritisation, audit history and outcome monitoring.

Typical diagnostic chain

01

Test prescription and ordering

Test purpose, clinical context, priority and patient identity are captured.

02

Sample collection or image creation

A unique test object is created and its collection or performance conditions are recorded.

03

Transport, preparation and analysis

Sample or image is transferred to equipment or specialist, recording each state and exception.

04

Technical and clinical validation

Quality, reference ranges, previous results and conclusion validity are checked.

05

Publication and delivery of the result

The validated result is securely provided to the referring specialist and, where appropriate, to the patient.

06

Closure of critical result or exception

The alert is assigned to the responsible person, review is confirmed, and the follow-up action is recorded.

Digital maturity model

0

Manual orders and separate result files

Referrals, sample logs, images and result transmission depend on paper, email or local folders.

1

Separate diagnostic systems

LIS, RIS or PACS are in use, but senders, equipment, quality control and patient channels are only partially connected.

2

Digitalised core testing cycle

Orders, sample codes, equipment results and approval are managed in the system, but exceptions and critical transmissions still depend on manual actions.

3

Integrated closed-loop diagnostics

Test identity, status, quality data, approval, publication and accountable clinical action are linked in a single traceable chain.

4

Key diagnostic processes are governed by shared data Typical current situationSiektina

In the main test groups, order, diagnostic object, equipment, result, quality control and approval are linked, but partner integrations, exceptions and critical result closure are not yet consistent across the organisation.

5

Safely learning diagnostic system

AI and advanced analytics are continuously evaluated for clinical accuracy, false signals, performance, impact across different groups and data drift.

Key conclusion

Diagnostic value depends not only on performing the test, but on the entire traceable information chain.

The biggest problem is the handover points between different systems, equipment and clinical responsibility.

The first priority should be one complete test type from order to confirmed action.

Related topics

Laboratory information systemPACS integration
Next step

Let us close the entire diagnostic chain

The journey of a single test will be reviewed from order to confirmed clinical action, helping to define a safe, measurable first version.

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