Diabetes log

App gallery / Health

Diabetes log: average a 1 c result by starts on, by month, new glucose reading form, glucose reading record

Shown in Friendly Notebook · 16 featured looks, 520+ more to choose from

Diabetes log

A personal health log for living with diabetes: blood glucose readings with their context, your medicines (picked from the RxNorm prescribable list) and each dose taken, meals with carbohydrates and calories, appointments with A1C results, and your diagnosed conditions from the ICD-10-CM list. Calendars show readings, meals and appointments by day. Your rows stay in your own database. Not medical advice.

Input-only tracker · 8 tables · design: Friendly Notebook

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A health app. Your entries stay in your own database: nothing is sent to CreativePower or to anyone else, and the app says on every page that it is not medical advice.

Tables

  • conditions_catalog3 columns · 74,879 rows in the full data
  • medicines_catalog4 columns · 20,175 rows in the full data
  • glucose_readings5 columns
  • medications9 columns
  • medication_doses5 columns
  • meals7 columns
  • appointments9 columns
  • conditions6 columns

Sources and licences

  • Own packs (ours) — Ours (Free to use)
  • ICD-10-CM — Public domain (Free to use)
  • RxNorm — Free; some included sources need a UMLS licence (Free with credit)

Shown in the app and its export: This product uses publicly available data from the U.S. National Library of Medicine (NLM), National Institutes of Health, Department of Health and Human Services; NLM is not responsible for the product and does not endorse or recommend this or any other product. Medicine names from the RxNorm current prescribable content; condition names from ICD-10-CM (public domain, CDC/CMS).

Data from www.nlm.nih.gov, imported 2026-10-20.

The full data, for your own database

95,054 rows, 1.1 MB to download. CreativePower keeps only the made-up sample rows in your project; load the full data into your own PostgreSQL database (Supabase works): download these files into one folder, unzip the .csv.gz files, then run psql "<your connection string>" -f load.sql.