01
The Problem
Across five Epic-based hospitals where I practiced as an RN, I repeatedly encountered a medication-administration workflow that required nurses to manually reconcile prior administrations, overlapping orders, and dosing intervals to determine when a medication was actually due.
The MAR displays medications at the order level, but bedside decisions often require understanding medication history across multiple orders, formulations, and phases of care.
As a result, nurses may need to search multiple locations, calculate next-dose eligibility manually, modify scheduled administration times, or rely on memory and handoff communication.
FIND
Search active, previous, and discontinued orders for prior administrations.
CALCULATE
Manually determine the next eligible administration time.
REMEMBER
Track future doses when the system does not create an actionable reminder.
02
What This Looks Like at the Bedside
Three scenarios, three medications, one underlying pattern.
SCENARIO A — POSTPARTUM ACETAMINOPHEN
08:30
Acetaminophen administered under vaginal-recovery orders
↓
Postpartum orders released
↓
09:00
New acetaminophen order appears due
↓
⚠
Patient received acetaminophen 30 minutes ago
Current RN workflow: Locate prior administration → recognize duplicate medication across order sets → calculate appropriate interval → manually adjust next due time.
The clinical decision is medication-centric, while the displayed workflow is order-centric.
SCENARIO B — GBS PROPHYLAXIS
10:00
2 g ampicillin loading dose administered
↓
14:00
1 g maintenance dose should be administered
RN MUST CREATE THE REMINDER
Current workarounds: Memory · handwritten notes · manually scheduling the MAR
I personally enter the next administration time into the maintenance order. Other nurses may rely on memory or written reminders, and I have observed delayed/missed doses.
Timely intrapartum antibiotic prophylaxis is clinically important. Requiring nurses to independently track subsequent doses introduces an avoidable opportunity for delayed or missed administration.
SCENARIO C — MINIMUM DOSING INTERVALS · FENTANYL, Q1H PRN
10:00
Last dose administered
↓
10:30
RN can initiate another administration without a meaningful timing warning
The nurse must recognize the previous administration and calculate elapsed time independently. I've observed the same pattern with other medications, such as q4h PRN misoprostol.
03
Why This Matters
CLINICAL
Potential opportunities for early, duplicate, delayed, or missed medication administration.
OPERATIONAL
Repeated investigation of medication history consumes nursing time across every patient and every shift.
COGNITIVE
The workflow requires nurses to maintain medication timing in working memory while managing competing clinical priorities.
PRODUCT
Stale or non-actionable overdue indicators can contribute to alert fatigue and reduce confidence in system-generated cues.
04
Current-State Workflow
Medication appears due
↓
Check last administration
↓
Was it given under this order?
↓ NO
Search other active orders
Search previous orders
Search discontinued orders
Check MAR report
↓
Identify last administration
↓
Calculate interval
↓
Determine actual eligibility
↓
Optionally update due time
↓
Administer
Every additional reconciliation step represents clinician time, cognitive load, and an opportunity for information to be missed.
05
Proposed Product Direction
I'm not proposing a redesign of Epic. Based on my clinical observations, this is the product direction I would investigate first.
Medication eligibility should follow the patient and medication — not the individual order.
Last administration
08:30 — 650 mg PO
Next eligible
14:30
Total administered
24-hr lookback
Source
Vaginal Recovery Order
⚠ Previous acetaminophen administration detected — last administered 30 minutes ago under another order.
Loading dose
✓ Administered 10:00
Next maintenance dose
14:00
Source
GBS Prophylaxis Order
✓ Maintenance reminder created automatically from the loading-dose administration — no manual tracking required.
06
How I Would Validate It
Before implementation, I'd validate the problem — not just the solution — through:
WORKFLOW OBSERVATION
Observe nurses managing scheduled and PRN medications across L&D/postpartum.
STAKEHOLDER INTERVIEWS
Nursing, pharmacy, clinical informatics, providers, and EHR analysts.
DATA ANALYSIS
Quantify rescheduled administrations, overdue medications, medication-timing events, duplicate orders, and relevant safety reports.
USABILITY TESTING
Test whether consolidated medication history reduces time-to-decision and improves correct identification of next-dose eligibility.
Success would look like:
↓ Time spent determining medication eligibility
↓ Delayed/missed doses
↓ Early administration attempts
↓ Non-actionable overdue alerts
↑ Nurse confidence in MAR timing
↑ Correct identification of next eligible dose
07
What I'd Do Next
This project is based on repeated frontline observations rather than access to Epic's underlying configuration or health-system data. Before pursuing implementation, I would partner with nursing, pharmacy, informatics, and EHR teams to validate the root cause, understand existing configuration capabilities, quantify the operational impact, and test potential interventions.
Why I Care
I've worked inside enough hospitals to know that clinicians are remarkably good at making imperfect systems work.
We remember what the software doesn't. We create workarounds. We double-check information across screens. We learn which alerts matter and which ones to ignore. We carry the cognitive burden of systems that weren't designed around the reality of providing care. Most of the time, the patient never knows how much invisible work happened behind the scenes.
I don't think we should accept that as the cost of working in healthcare.
Nurses and clinicians deserve technology that makes it easier to care for people, not technology they have to work around. Patients deserve healthcare systems that take advantage of what's possible today, rather than asking the people caring for them to keep compensating for what's outdated, fragmented, or unnecessarily difficult.
Working across multiple health systems has made me believe deeply in what thoughtful technology can change, especially when the people who actually deliver care have a voice in building it.
That's the work I want to be part of.