Automate patient medical history collection into standardized intake forms.
npx skills add https://github.com/LKB-99/manus-auto-skills --skill patient-intake
Please help me install this Agent Skill. Skill: patient-intake Source: https://github.com/LKB-99/manus-auto-skills/tree/main/patient-intake Command: npx skills add https://github.com/LKB-99/manus-auto-skills --skill patient-intake
Automates the collection and processing of patient medical histories into standardized intake forms, reducing administrative workload and ensuring consistent data capture before consultations.
Generate a full patient intake form for a new patient using the full_intake template.
High-intent search queries and answers about installing and using this skill.
Automating patient intake form generation uses a templating engine with reusable templates to collect medical histories and output structured data for clinical workflows. It reduces administrative workload by standardizing data capture before consultations.
Multi-language patient medical history forms are supported directly, producing structured JSON and Markdown outputs. These structured formats ensure the collected clinical data is standardized and suitable for import into electronic health record systems.
Specialty-specific intakes for cardiology, mental health, and orthopedics are fully supported through template-based workflows. The system generates tailored pre-visit questionnaires that capture relevant clinical data for each specialty.
The best way to integrate patient intake data into an EHR system is by exporting structured JSON or Markdown outputs with built-in integration hooks. This enables seamless data transfer from the completed intake forms directly into clinical workflows.
A templating engine is required to standardize pre-visit questionnaires for clinical research. It enables reusable templates that ensure consistent data capture across multiple subjects, applying structured outputs suitable for research databases.
Follow-up visit intake is fully supported alongside full new patient registration. The system applies different template workflows to guide clinicians from tailored form creation through data review for both initial and subsequent visits.
VeradelaCruzDefine API requirements and generate OpenAPI or GraphQL schemas.
iterationlayerExtracts patient name, date of birth, diagnoses, and medications from medical records into structured JSON.
jaechang-hitsLoad EHR data from MIMIC-III/IV and OMOP-CDM for ML model training.
zjunlpAnalyze MIMIC-IV patient records and generate clinical QA pairs.
