Calculator Input Form
Example Data Table
| Cohort | Total Patients | Persistent Patients | Covered Days | Follow-up Days | Allowed Gap | Max Gap | Result Note |
|---|---|---|---|---|---|---|---|
| Cohort A | 150 | 112 | 16800 | 21000 | 30 | 45 | Needs review because max gap is high. |
| Cohort B | 200 | 176 | 31000 | 36000 | 45 | 28 | Strong persistence with acceptable gaps. |
| Cohort C | 90 | 49 | 7200 | 12600 | 30 | 70 | High risk with low continuity. |
Formula Used
Persistence Rate = Persistent Patients / Total Patients × 100
PDC = Covered Days Total / Follow-up Days Total × 100. The shown PDC is capped at 100%.
Discontinuation Rate = Discontinuation Events / Total Patients × 100
Mean Gap Per Patient = Total Gap Days / Total Patients
Refill Intensity = Total Refills / Total Patients
Gap Status compares the observed maximum gap against the allowed gap rule.
Persistence Index = Persistence Rate × 0.45 + PDC × 0.45 + Remaining Rate × 0.10 − Gap Penalty
How to Use This Calculator
- Enter a cohort label for reporting.
- Add the total number of eligible subjects.
- Enter the number still persistent at the end date.
- Add total covered days and total follow-up days.
- Enter total gap days, allowed gap days, and maximum observed gap.
- Add discontinuation events and refill count.
- Choose the pass threshold used by your review plan.
- Press Calculate to view results above the form.
- Use CSV or PDF buttons to save the report.
Article
Understanding Persistence Macro Planning
Persistence analysis often measures whether people remain active in a treatment, program, subscription, workflow, or study path. A SAS macro can automate that work, but the logic still needs clear planning before data is processed. This calculator helps you test the major rates before writing or reviewing a production macro.
Why Persistence Matters
Persistence is not the same as simple activity. A record may show some covered days, yet still include long gaps. Those gaps can signal discontinuation, delayed follow up, or weak engagement. By comparing covered days, follow up days, allowed gaps, and active members, the calculator gives a practical summary of continuity.
Macro Ready Thinking
The output is designed to resemble values often passed into a macro report. You can review persistence rate, discontinuation rate, average coverage, refill intensity, and gap status. These values help analysts verify assumptions before running grouped logic on larger datasets. The macro text also gives a quick template for notes or documentation.
Use In Real Reviews
Teams can use this page during audits, model checks, cohort setup, or stakeholder reviews. Enter totals from a sample table. Then compare the result with your expected manual answer. If the result looks wrong, check dates, patient counts, gap definitions, and denominator choices. These issues are common in persistence projects.
Good Data Habits
Strong persistence work starts with clean index dates, valid end dates, and consistent supply records. Duplicate fills, missing dates, and negative follow up can distort every metric. Always define whether the analysis counts calendar days, supplied days, claim intervals, or observed program days. State the maximum gap rule before presenting final rates.
Better Decisions
A clear persistence summary supports better decisions. It shows how many subjects remain active. It also shows how much observation time is covered. The export buttons help preserve assumptions for review. The example table gives a fast benchmark for testing. Use the calculator as a planning aid, not as a replacement for validated study code.
Implementation Notes
Analysts should record each rule beside the exported file. This includes gap logic, inclusion rules, censor dates, and rounding choices. Clear notes make later macro validation easier, especially when teams compare outputs across different periods or study cohorts.
FAQs
What does persistence mean here?
Persistence means the share of eligible subjects who remain active at the analysis end point. It depends on your cohort rule, observation window, and allowed gap definition.
Is PDC the same as persistence?
No. PDC measures covered days divided by follow-up days. Persistence counts subjects who remain active. Both values can move differently when gaps or discontinuations occur.
Why is PDC capped at 100%?
PDC is commonly capped because covered days above the observation window should not create more than full coverage. The raw coverage value is also shown for review.
What is the allowed gap?
The allowed gap is the maximum interruption accepted before a subject is considered non-persistent, discontinued, or needing review under your study rule.
How is the persistence index created?
The index blends persistence rate, PDC, and remaining rate. It then subtracts a gap penalty. This gives one review score for quick screening.
Can this replace validated study code?
No. Use it for planning, checking, and documentation. Final regulatory, clinical, or financial analysis should use validated code and approved specifications.
What should I enter for follow-up days?
Enter the total eligible observation days across all subjects. It should match your index date, censor date, end date, and inclusion rules.
Why are CSV and PDF exports useful?
Exports preserve inputs, formulas, and results. They help reviewers compare assumptions, reproduce checks, and document how the macro logic was tested.