Recorded gaps around the prescribed interval and logging toleranceLive current inputs
Health & Fitness
Medication Interval Trend Calculator
Analyze six recorded administration gaps against a prescribed interval, quantify mean delay and variability, and overlay a generic half-life residual estimate without recommending schedule changes.
Mean recorded gap—
Mean difference from prescription—
Gap standard deviation—
Within entered tolerance—
Longest interval—
Shortest interval—
Generic residual range—
Trend boundary—
ADMINISTRATION GAP CONTROL VIEW
Recorded gaps around the prescribed interval and logging tolerance
A control-style chart displays each gap, the prescribed line, and a user-entered logging band; points outside it are highlighted without suggesting compensation.
GAP-BY-GAP AUDIT
Recorded timing, deviation, and modeled residual
Every entered gap remains visible with its own arithmetic.
| Gap | Recorded hours | Difference | Within tolerance | Modeled residual | Log note |
|---|
LOG REVIEW
Enter what happened, not what was intended
- Use actual elapsed gaps from a reliable log.
- Enter the prescription only as the reference line.
- Choose a tolerance for data review, not for clinical permission.
- Discuss missed or irregular doses using the medication-specific instructions.
ADHERENCE DESCRIPTION
Timing variation is evidence, not a self-correction rule
Mean delay can hide alternating early and late gaps, so the standard deviation and every point remain visible.
The generic residual range helps explain why long gaps differ mathematically, but it cannot determine safety, efficacy, or a catch-up response.
TIMING CONSISTENCY
Summarize the recorded gaps without rewriting the prescription
Descriptive statistics characterize the log. The residual fraction is a generic first-order context layer only.
Detailed calculation process and general formulas
Gap_bar = ΣG_i / nDelay_i = G_i - τ_prescribedSD = sqrt(Σ(G_i-Gap_bar)^2 / n)Within = count(|Delay_i| ≤ tolerance) / nResidual_i = 2^(-G_i/t_half)Symbols, meanings, and units
- Gi
- recorded administration gap ihours
- τ_prescribed
- prescribed reference intervalhours
- Delay_i
- timing difference from prescriptionhours
- SD
- population standard deviation of gapshours
- Residual_i
- generic first-order fraction after gap ifraction
LOG DIAGNOSTICS
Three ways to inspect timing consistency
The analysis avoids a single adherence score.
Central timing
—Mean gap shows the broad schedule center.
Variation
—Standard deviation exposes irregularity hidden by the mean.
Point-level review
—Tolerance counts preserve which gaps need discussion.
Decision takeaway: Use the log to ask better medication-specific questions; never shorten, double, or skip an interval from this display.
Applied decisions
Administration-log patterns
Correct mean, irregular gaps
Early and late administrations average to the prescribed interval.
What the result clarifies: The standard deviation and control chart reveal variation hidden by the mean.
One extended gap
Five gaps are close to schedule and one is much longer.
What the result clarifies: The outlier remains visible for medication-specific follow-up.
Worked default scenario
Current-input substitution and reconciliation
Method references
Evidence used to frame this specific model
Scope and limitations
Descriptive log analysis only. It does not judge adherence clinically or advise what to do after an early, late, or missed dose. Follow the label and contact a pharmacist or prescriber when uncertain.
Medication Interval Trend Calculator | Administration-Gap Consistency FAQ
Is the tolerance a safe window?
No. It is only a user-entered data-review band.
Can the mean gap hide problems?
Yes. Alternating early and late gaps may average correctly, which is why variability and individual points are shown.
Does modeled residual equal drug concentration?
No. It is a generic one-compartment fraction that omits absorption, distribution, and patient factors.
What should I do with an outlier gap?
Use the medication-specific label or contact the prescribing team; do not infer a correction here.