How to use MedRec 2.0
- Start with your trusted medication list. Use the last known good medication list you believe is correct. This may be a current facility list, pharmacy list, patient portal list, discharge list already reviewed by a provider, or another list your care team trusts. This is your source of truth.
- Enter that list first. Paste the trusted baseline list into MedRec 2.0 as the medication list before the change.
- Enter the new list second. When you receive a new hospital discharge, pharmacy, portal, provider, or paper medication list, paste it as the new medication list.
- Review the comparison report. MedRec 2.0 highlights possible added, removed, changed, and unchanged medications, along with selected safety cautions for human review.
- Take changes to a trusted professional. If the report shows changes, bring or share it with your trusted provider, pharmacist, nurse, or care team before making medication decisions.
- Keep the reviewed report. After your care team confirms the correct medication list, save or print the report. Over time, keeping these reports can help create a history of medication changes.
- Use the confirmed list next time. Once a provider or care team confirms the current list, use that updated list as your new source of truth for the next comparison.
Medication orders only: do not enter names, dates of birth, medical record numbers, addresses, phone numbers, or other patient identifiers.
What the evidence supports
The evidence does not show that any single tool can replace medication reconciliation. It supports a safer workflow: collect the best available medication list, compare lists from multiple sources, identify possible discrepancies, and have a clinician, pharmacist, nurse, or care team review and resolve the differences. MedRec 2.0 is designed to support the comparison step by reducing manual scanning burden and making possible differences easier to review.
Phillips et al. (2022): 30-Day Readmission Reduction in a Skilled Facility Population Through Pharmacist-Driven Medication Reconciliation
Source: https://doi.org/10.1097/JHQ.0000000000000313
Key Takeaway:
Pharmacist-led medication reconciliation during hospital-to-SNF transitions was associated with high reconciliation completion and a 29.8% relative reduction in 30-day readmissions across the combined intervention cohorts. This supports the value of structured medication reconciliation during skilled nursing transitions, while MedRec 2.0 should still be described as a support tool rather than a proven readmission-reduction intervention.
Related: skilled nursing medication reconciliation workflow.
Vasilevskis et al. (2024): Medication discrepancies among older hospitalized adults discharged from post-acute care facilities to home
Source: https://doi.org/10.1016/j.jamda.2024.105017
Key Takeaway:
Older adults transitioning from post-acute care to home had a very high medication discrepancy burden, with 98% having at least one discrepancy and a median of 7 discrepancies at 7-day follow-up. This supports the need for patients, caregivers, and care teams to compare medication lists after transitions rather than assuming an imported list is complete or correct.
Related: personal medication source of truth.
Araya et al. (2023): Medication Reconciliation during Transitions of Care Across Institutions
Source: https://doi.org/10.1055/a-2178-0197
Key Takeaway:
Medication lists were highly similar within the same EHR system but far less similar across different EHR systems, even after RxNorm normalization. This directly supports MedRec 2.0's focus on comparing medication lists across different systems, formats, and sources.
Grauer et al. (2023): Examining medication ordering errors using AHRQ Network of Patient Safety Databases
Source: https://doi.org/10.1093/jamia/ocad007
Key Takeaway:
In a large analysis of medication ordering errors, incorrect dose and incorrect medication selection were among the most common reported error types. This supports prioritizing medication name, dose, route, frequency, and duration/order-detail review during medication reconciliation.
Related: complete medication order components.
AHRQ PSNet: Technology as a Tool for Improving Patient Safety
Source: https://psnet.ahrq.gov/perspective/technology-tool-improving-patient-safety
Key Takeaway:
Technology can improve standardization and safety, but poorly designed technology can also increase clinician burden and alert fatigue. MedRec 2.0 should therefore continue to keep alerts focused, explain its limits, and require human review.
Schnipper et al. (2022): Effects of a refined evidence-based toolkit and mentored implementation on medication reconciliation at 18 hospitals (MARQUIS2)
Source: https://doi.org/10.1136/bmjqs-2020-012709
Key Takeaway:
MARQUIS2 supports the idea that structured workflows, clear roles, feedback, and targeted interventions can improve medication reconciliation processes. MedRec 2.0 aligns with this evidence by supporting the comparison step, but final reconciliation decisions remain the responsibility of clinicians.
Mixon et al. (2019): Design of MARQUIS2
Source: https://doi.org/10.1186/s12913-019-4491-5
Key Takeaway:
The MARQUIS2 toolkit included best possible medication history, discharge medication reconciliation, role definition, risk stratification, health IT improvements, access to medication sources, and real-time discrepancy correction. This supports a workflow-based approach rather than relying on a person to visually scan long medication lists.
Related: MedRec 2.0 use cases.
Soeno et al. (2024): Development of novel OCR system to reduce recording time for vital signs and prescriptions
Source: https://doi.org/10.1371/journal.pone.0296319
Key Takeaway:
OCR reduced prescription recording time compared with manual typing in controlled testing, especially for medication lists. This supports OCR-assisted medication capture, but OCR text still needs verification because silent omissions or recognition errors can occur.
Related: OCR-copied medication text.
Ma et al. (2025): Development and evaluation of a patient-centric approach for accurate medication capture
Source: JAMIA Open / Oxford Academic
Key Takeaway:
A patient-centered medication capture app achieved high medication-entry accuracy, but EHR concordance remained low, especially because many OTC medications were missing from EHR records. This supports the idea that individuals and caregivers can help maintain a more complete medication list, including OTC products and supplements.
Related: personal medication list comparison.
Barnas & Ward (2022): Metacognitive judgements of change detection predict change blindness
Source: https://doi.org/10.1016/j.cognition.2022.105208
Key Takeaway:
People can miss meaningful changes when comparing visual information and may overestimate their ability to detect differences. This supports using structured medication list comparison instead of relying only on manual visual scanning.
Related: medication list comparison tool.
Pais et al. (2024): Large language models for preventing medication direction errors in online pharmacies
Source: https://doi.org/10.1038/s41591-024-02933-8
Key Takeaway:
Medication direction errors can create safety risk, and systems that extract core prescription components need domain-specific safeguards. This supports MedRec 2.0's emphasis on medication name, dose, route, frequency, and review by a qualified person.
Related: complete medication order.
Xu et al. (2025): Iterative Interventions to Improve Admission Medication Reconciliation Completion Rates and Reduce Medication Errors at Post-Acute Care Facilities
Source: https://doi.org/10.33940/001c.134045
Key Takeaway:
A standardized workflow, education, and feedback improved admission medication reconciliation completion in post-acute settings. This supports integrating MedRec 2.0 into a clear workflow rather than treating it as a stand-alone replacement for reconciliation.
Related: post-acute medication reconciliation.
Ciudad-Gutiérrez et al. (2025): ConciliaMed medication reconciliation tool
Source: https://doi.org/10.3390/healthcare13070778
Key Takeaway:
An electronic medication reconciliation tool was feasible and well received in a perioperative workflow and helped surface medication discrepancies. The setting differs from SNF and post-acute transitions, so this should be presented as supportive technology evidence, not direct proof for MedRec 2.0 outcomes.
Engstrom et al. (2023): TIME study, digital hospital transition and medication errors
Source: https://doi.org/10.1038/s41746-023-00877-w
Key Takeaway:
Digital medication workflows were associated with fewer medication incidents and prescribing errors after transition from paper-based processes. This supports the broader value of standardization and digital medication workflows, while still requiring local testing and monitoring.