MOISSCode vs MDCalc
MDCalc is the industry standard web tool for clinical calculators. MOISSCode takes a different approach: programmable, embeddable, and automatable clinical decision support.
MOISSCode is professional biomedical software. All clinical outputs require independent professional validation.
Feature Comparison
| Feature | MDCalc | MOISSCode |
|---|---|---|
| Interface | Web browser, manual input | Python library, CLI, REST API, DSL |
| Automation | No | Yes. Script entire workflows |
| Embedding | No (iframes only) | Yes. pip install into any app |
| Batch processing | One patient at a time | Process thousands programmatically |
| Custom protocols | No | Yes. Write .moiss protocol files |
| Pharmacokinetics | Limited | 100+ drug profiles with ADME |
| Lab interpretation | No | 80+ tests, 15 panels, critical flagging |
| FHIR export | No | FHIR R4 Patient, Bundle, MedicationRequest |
| Drug interactions | No | Built in interaction checking |
| Offline use | No (web only) | Yes. Runs locally |
| API access | Paid, limited | Included with Pro tier |
| Clinical scores | 600+ calculators | 13 validated scoring systems |
| Cost | Free (web), paid API | Free (research), Pro (production) |
Where MDCalc Excels
MDCalc offers 600+ clinical calculators with peer reviewed evidence summaries, creator commentary, and Next Steps guidance. It requires zero setup: open a browser, select a calculator, enter values. For individual clinicians at the bedside making one off calculations, MDCalc is excellent.
Where MOISSCode Excels
MOISSCode is built for automation, integration, and programmatic workflows:
Batch processing across patient cohorts:
from moisscode import ClinicalScores, Patient
scores = ClinicalScores()
patients = load_from_database() # Your data source
high_risk = [p for p in patients if scores.qsofa(p) >= 2]
print(f"{len(high_risk)} patients flagged for sepsis screening")
Embedding in clinical applications:
from moisscode import StandardLibrary
lib = StandardLibrary()
# Inside your EHR plugin or dashboard
def on_vitals_update(patient_data):
score = lib.scores.news2(patient_data)
if score >= 7:
trigger_rapid_response()
Combining scoring with pharmacokinetics and lab data:
from moisscode import StandardLibrary, Patient
lib = StandardLibrary()
p = Patient(bp=82, rr=26, gcs=13, lactate=4.2, creatinine=2.8, sex='M', age=68)
# Score
qsofa = lib.scores.qsofa(p)
# Check renal function for dosing
gfr = lib.lab.gfr(creatinine=2.8, age=68, sex='M')
# Adjust antibiotic dose
dose = lib.pk.calculate_dose("Vancomycin", weight_kg=75)
adjustment = lib.pk.renal_adjust("Vancomycin", gfr=gfr["eGFR"])
# Generate FHIR bundle
bundle = lib.fhir.to_fhir(p)
No web form can chain these calculations together automatically.
Summary
MDCalc is the right tool for individual clinicians performing manual lookups. MOISSCode is the right tool for developers, researchers, and informaticians who need to automate clinical logic, embed scoring in applications, or process patient data at scale.