Protocol design

Digital Family Doctor Collaboration Laboratory

Problem

Family health information is often fragmented across memory, devices, and institutions, causing incomplete records, repeated communication, and unclear responsibility boundaries.

Research question

Can structured records, authorized sharing, and responsibility cues improve the completeness, traceability, and timeliness of family-clinician information?

Testable hypothesis

The following is a testable proposition, not an established result.

Compared with the current workflow baseline, minimum-necessary fields and authorized collaboration will improve record completeness and handoff accuracy without increasing privacy or safety incidents; a single non-improving assessment is not decisive, and prespecified thresholds plus repeated validation determine whether evidence supports progression, while increased risk triggers stopping or revision.

Measures

  • Required-field completeness, duplicate or conflicting record rate, and source traceability
  • Handoff time, user understanding, and human-review correction rate
  • Unauthorized access, privacy events, dangerous misunderstanding, and escalation failures

Method

Begin with workflow interviews, field design, permission modeling, and scenario exercises, then test prototypes with non-sensitive or synthetic data; privacy, security, and clinical-responsibility review are required before real collaboration.

Current evidence

The following states the current record and evidence types separately from the hypothesis.

The current record contains only an information-collaboration framework and protocol design, with no real patient data, clinical-use result, or proof of diagnostic or treatment capability.

  • Theory source
  • Testable hypothesis
  • Research protocol

Evidence gaps

  • User-need validation, a data dictionary, permission model, and threat model are still missing
  • Clinical-responsibility, privacy-impact, usability, and safety validation are still missing

Milestones

  1. Complete the minimum-necessary data dictionary, authorization flow, and responsibility boundaries
  2. Complete a synthetic-data prototype, threat model, and hazardous-scenario testing
  3. Decide whether to pilot after privacy, clinical, and safety review

Governance

Manage data access through least privilege, explicit authorization, and revocability; clinicians and qualified health systems retain clinical responsibility, and system changes must be logged.

Ethics

Support information recording and collaboration only, not diagnosis, prescribing, emergency response, or other clinical decisions; users may view, correct, withdraw, and request deletion of authorized data.

Partner needs

  • Family-medicine, nursing, health-informatics, and patient-safety institutions
  • Privacy-engineering, cybersecurity, accessibility, and user-research partners

Planned public outputs

  • Minimum-necessary health-record data dictionary and authorization model
  • Digital-collaboration prototype, hazardous-scenario tests, and safety-boundary report

Last reviewed