Paper Care Logs to Analysis-Ready Data: The ParkinSync Pipeline

ParkinSync is a serverless pipeline that takes paper-based home-care logs — the kind a family caregiver actually keeps — and turns them into a dataset you can review alongside weather and indoor-temperature context.

The most important design decision is what we didn’t build: we did not try to automate everything. In health-adjacent records, an OCR misread that looks plausible is the most dangerous kind of data. So human-verified records are the source of truth, and the cloud handles what machines are good at: ingestion, shaping, enrichment, and aggregation. (The full reasoning is in Why We Chose Human-in-the-Loop Over Full Automation.)

The architecture

• Amazon S3 — upload target for PDFs and record files
• AWS Lambda — ingestion plus scheduled jobs
• Amazon Textract — table/form structure checks on scanned logs
• AWS Secrets Manager — API keys and Google credentials
• Google Sheets API — the master ledger
• SwitchBot Open API — indoor temperature
• Visual Crossing Weather API — per-date weather context
• Python analysis scripts — schema checks and exploratory analysis over a 25-column dataset

There are two Lambdas. One ingests care logs: it fires on S3 uploads, fetches the weather for the record’s date, and appends to Google Sheets. The other logs indoor temperature: EventBridge runs it on a schedule, it reads the sensor API, and writes to the same ledger.

Why Google Sheets instead of a database

We had the usual options — DynamoDB, RDS, even SQLite on a schedule. We chose Google Sheets, and it was not a compromise.

Care logs don’t just need to be processed; they need to be trusted by non-engineers. A spreadsheet is something the caregiver themselves can open, read, correct, and export. Making the master ledger human-legible is part of the same human-in-the-loop stance as the OCR checkpoint: if the person who wrote the paper log can’t verify what the pipeline did with it, the pipeline is wrong.

What’s next

The honest to-do list: idempotent S3 processing, a review queue for OCR failures, notifications, and an anonymized sample dataset so others can try the pipeline.

ParkinSync doesn’t automate any medical decision. It is an information layer — it turns daily caregiving records into something you can verify later and bring to a care team.

The project is open source, and the product page tracks where it stands: ParkinSync · GitHub. If you are curious how this looks from the caregiver’s side, the Japanese essay 紙の介護記録は、そのままでいい is the same philosophy, minus the YAML.