Structured findings
Lab values from LDT 3 and HL7 v2 enter one canonical model, per parameter, with reference ranges and status.
DocCom connects structured lab values with clear clinical interpretation, ensuring that communication about routine findings for patients with chronic conditions does not get lost between PDFs, phone calls, and appointment calendars.
1. Finding
Straight from the lab
2. Medical interpretation
Annotation by Dr. Schmidt
3. Delivery
Promptly and clearly available to the patient
Not another data portal. DocCom puts patient-centred communication first – clear, organised, and timely.
Lab values from LDT 3 and HL7 v2 enter one canonical model, per parameter, with reference ranges and status.
Text and voice notes remain directly on the finding or parameter. Context no longer disappears into another channel.
Appointments, medications, symptoms, and the individual disease course are brought together clearly, making changes and next steps understandable.
Clear enough for a daily check. Detailed enough for the next consultation.
All parameters – such as CRP and calprotectin – over time, with reference ranges and a clear summary.
Current CRP
0.4 mg/dl
View the plan and record intakes.
Keep routine examinations in view – with an automatically planned reminder for the next due examination.
Document symptoms and record observations for the next consultation.
View findings with the treating doctor's individual annotation promptly and in clear language.
No time delay. No extra workload.
Routine findings arrive directly from the lab in the practice application and, in parallel, in the patient app. The treating doctor only adds a patient-specific annotation – for individual parameters or the entire finding. No extra call slots, no missed callbacks, no repeated contact attempts. Routine findings are communicated promptly and clearly – with less workload and more time for actual medical work.
Open doctor demoMax Mustermann
Morbus Crohn · active
3
New findings
2
Due routines
Roles, assignments, and clinical context are part of the data model, not merely the interface.
Patient and doctor workspaces are technically separated.
Doctors can only see their own assigned patients.
Ingestion and presentation stay cleanly separated.
The doctor's interpretation stays directly on the finding and each parameter – without a separate messaging channel.