Evidence map›Paper›PMID 37726022›Full record

ArticleApplied clinical informatics2023

Medication Reconciliation during Transitions of Care Across Institutions: A Quantitative Analysis of Challenges and Opportunities.

Alejandro Araya, Logan R Thornton, Deukwoo Kwon, Gayla M Ferguson, Linda D Highfield, Kevin O Hwang, Holly M Holmes, Elmer V Bernstam

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Applied clinical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 40% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Alejandro ArayaD. Bradley McWilliams School of Biomedical Informatics, The University of Texas Health Science Center (UTHealth), Houston, Texas, United States.
Logan R ThorntonDivision of Population Health and Evidence-Based Practice, Healthcare Transformation Initiatives, The University of Texas Health Science Center at Houston (UTHealth) John P. and Kathrine G. McGovern Medical School, Houston, Texas, United States.
Deukwoo KwonDivision of Clinical and Translation Sciences, Department of Internal Medicine, The University of Texas Health Science Center at Houston (UTHealth) John P. and Kathrine G. McGovern Medical School, Houston, Texas, United States.
Gayla M FergusonDepartment of Management, Policy and Community Health, The University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Houston, Texas, United States.
Linda D HighfieldDepartment of Management, Policy and Community Health, The University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Houston, Texas, United States.
Kevin O HwangDivision of General Internal Medicine, Department of Internal Medicine, The University of Texas Health Science Center at Houston (UTHealth) John P. and Kathrine G. McGovern Medical School, Houston, Texas, United States.
Holly M HolmesDivision of Geriatrics, Department of Internal Medicine, The University of Texas Health Science Center at Houston (UTHealth) John P. and Kathrine G. McGovern Medical School, Houston, Texas, United States.
Elmer V BernstamD. Bradley McWilliams School of Biomedical Informatics, The University of Texas Health Science Center (UTHealth), Houston, Texas, United States.
The University of Texas Health Science Center at Houston · USThe University of Texas Health Science Center · USUniversity of Texas Health Science Center at Dallas · US

Funding

Convalescent Plasma to Limit Coronavirus Associated ComplicationsUL1TR003167 · NCATS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KARP, DANIEL D, MCPHERSON, DAVID D · 2019 to 2023
$45.3M
NCATS NIH HHS UL1 TR003167
6 · The paper itself

Abstract

objectiveMedication discrepancies between clinical systems may pose a patient safety hazard. In this paper, we identify challenges and quantify medication discrepancies across transitions of care.

methodsWe used structured clinical data and free-text hospital discharge summaries to compare active medications' lists at four time points: preadmission (outpatient), at-admission (inpatient), at-discharge (inpatient), and postdischarge (outpatient). Medication lists were normalized to RxNorm. RxNorm identifiers were further processed using the RxNav API to identify the ingredient. The specific drugs and ingredients from inpatient and outpatient medication lists were compared.

resultsUsing RxNorm drugs, the median percentage intersection when comparing active medication lists within the same electronic health record system ranged between 94.1 and 100% indicating substantial overlap. Similarly, when using RxNorm ingredients the median percentage intersection was 94.1 to 100%. In contrast, the median percentage intersection when comparing active medication lists across EHR systems was significantly lower (RxNorm drugs: 6.1-7.1%; RxNorm ingredients: 29.4-35.0%) indicating that the active medication lists were significantly less similar (

conclusionDespite the challenges to medication normalization, there are opportunities to identify and assist with medication reconciliation across transitions of care between institutions.

Indexed as

Medication ReconciliationPatient DischargeAftercareHospitalizationHumansVocabulary, Controlled

Identifiers

PMID37726022
PMCPMC10665121
OpenAlexW4386855052

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.