Test orders are received in inconsistent formats
CriticalReferrals, clinical context and priorities are communicated via documents or disparate integrations.
- Consequences
- Tests are registered inaccurately or require additional verification.
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
- high
- Digitalisation potential
- 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 situationTarget
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.