Remote Monitoring Data Flow Graph Model
Description
This staged explorer separates a wearable-device path from a patient-portal path. Each stage makes the underlying data visible: four synthetic readings, an illustrative rule, the resulting alert, a telehealth visit, and a patient-reported outcome. Learners can advance one stage at a time or play the same bounded five-stage sequence.
Lesson Plan
Audience: undergraduate students and healthcare data practitioners. Allow 10–15 minutes. Prerequisites: nodes, directed relationships, timestamps, thresholds, and patient-generated data.
Learning objective: Explain how patient-generated data flows through a remote patient monitoring process into a telehealth visit, and classify each node by whether its data is patient-originated or system-generated.
- Predict: At Stage 1, predict which branch can produce an automated alert and which branch aggregates a patient report.
- Explain: Advance through Stages 2–4. Use the displayed readings and rule to explain exactly why the alert appears.
- Classify: Reveal Stage 5 and classify each visible node as patient-originated or system-generated. Defend one classification using the edge labels.
Assessment: a complete explanation names the sequence GENERATES → FEEDS → TRIGGERS → SCHEDULES, identifies the three consecutive readings used by the teaching rule, and correctly classifies the patient-reported outcome and portal.
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Quality Checks
Validated September 7, 2026. Completeness rubric: 100/100. Browser interaction tests passed at 400, 800, and 1200 pixels, including staged reveal and bounded playback; iframe visibility and visual layout checks passed; no JavaScript errors were observed.
Specification
The specification is recorded in the TODO entry and Chapter 11.
References
- Chapter 11: Specialty Care, Surgery, and Remote Monitoring — source learning objective and staged data-flow specification.
- vis-network documentation — rendering and interaction reference.