Evidence map›Paper›PMID 24393492›Full record

ArticleComputers in biology and medicine2015

Clinicians' evaluation of computer-assisted medication summarization of electronic medical records.

Xinxin Zhu, James J Cimino

Open access · greenAbstract read
In one paragraph

Article in Computers in biology and medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 11% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
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

2 authors at 2 institutions in 1 country.

Xinxin ZhuIBM T.J. Watson Research Center, USA. Electronic address: zhux@us.ibm.com.
James J CiminoNational Institutes of Health, USA.
IBM (United States) · USNational Institutes of Health · US

Funding

Training in Biomedical Informatics at Columbia UniversityT15LM007079 · NLM · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI NOEMIE ELHADAD, GEORGE M HRIPCSAK · 1992 to 2026
$28.9M
NLM's Personal Health Record and Consumer Service R&DZIALM008925 · NLM · NATIONAL LIBRARY OF MEDICINE · PI MCDONALD, CLEMENT · 2009 to 2020
$11.8M
DISCOVERING AND APPLYING KNOWLEDGE IN CLINICAL DATABASESR01LM006910 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HRIPCSAK, GEORGE M · 2000 to 2023
$10.6M
NLM NIH HHS R01 LM006910NLM NIH HHS R01 LM06910NLM NIH HHS T15 LM007079NLM NIH HHS T15LM07079
6 · The paper itself

Abstract

Each year thousands of patients die of avoidable medication errors. When a patient is admitted to, transferred within, or discharged from a clinical facility, clinicians should review previous medication orders, current orders and future plans for care, and reconcile differences if there are any. If medication reconciliation is not accurate and systematic, medication errors such as omissions, duplications, dosing errors, or drug interactions may occur and cause harm. Computer-assisted medication applications showed promise as an intervention to reduce medication summarization inaccuracies and thus avoidable medication errors. In this study, a computer-assisted medication summarization application, designed to abstract and represent multi-source time-oriented medication data, was introduced to assist clinicians with their medication reconciliation processes. An evaluation study was carried out to assess clinical usefulness and analyze potential impact of such application. Both quantitative and qualitative methods were applied to measure clinicians' performance efficiency and inaccuracy in medication summarization process with and without the intervention of computer-assisted medication application. Clinicians' feedback indicated the feasibility of integrating such a medication summarization tool into clinical practice workflow as a complementary addition to existing electronic health record systems. The result of the study showed potential to improve efficiency and reduce inaccuracy in clinician performance of medication summarization, which could in turn improve care efficiency, quality of care, and patient safety.

Indexed as

Electronic Health RecordsHealth Information SystemsAgedAged, 80 and overFemaleHealth Services ResearchHumansMaleMedication ErrorsMedication ReconciliationMiddle AgedUser-Computer InterfaceElectronic health recordMedication errorMedication summarizationPerformance efficiencyPerformance inaccuracyTimeline

Identifiers

PMID24393492
PMCPMC4063892
OpenAlexW2003555839

What OpenQuestion holds

Textmetadata
LicenceTDM
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.