Evidence map›Paper›PMID 31061618›Full record

ArticleSaudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society2019

Measuring the quality and completeness of medication-related information derived from hospital electronic health records database.

Monira Alwhaibi, Bander Balkhi, Thamir M Alshammari, Nasser AlQahtani, Mansour A Mahmoud, Mansour Almetwazi, Sondus Ata, Mada Basyoni, Tariq Alhawassi

Abstract read
In one paragraph

Article in Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Digital Health Data Quality Issues: Systematic Review.Journal of medical Internet research · 2023
    Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. National medicines policy development, Saudi Arabia.Bulletin of the World Health Organization · 2022
    Review
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  11. Article
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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

9 authors.

Monira AlwhaibiDepartment of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Bander BalkhiDepartment of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Thamir M AlshammariMedication Safety Research Chair, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Nasser AlQahtaniSaudi Food and Drug Authority, Riyadh, Saudi Arabia.
Mansour A MahmoudMedication Safety Research Chair, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Mansour AlmetwaziDepartment of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Sondus AtaPharmacy Care Services, King Saud University Medical City, Riyadh, Saudi Arabia.
Mada BasyoniSaudi Patient Safety Centre, Riyadh, Saudi Arabia.
Tariq AlhawassiDepartment of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveElectronic Health Records (EHRs) database is a great source for pharmacoepidemiological research as thousands of patients' clinical and medication information is stored in the database. However, the use of EHRs database for research purposes depends greatly on the accuracy and completeness of the data being used. This study mainly aimed to assess the completeness of EHRs patients' medication-related information.

designA retrospective cross-sectional study using data extracted from the EHRs database was conducted.

settingThe EHRs data was obtained from a single tertiary hospital in Saudi Arabia.

main outcome measuresThe completeness of data was measured considering if a patients' record contains all desired types of data (i.e., patients' demographics, clinical diagnosis, and medication-related information).

resultsA total of 23,411 unique individuals were identified after extracting the data from the EHRs. The study found that 89.9% of the patients had a complete data (i.e., age, gender, marital status, nationality, encounter type, and clinical diagnosis). Further, 83.1% of the patients had complete medication-related information. Subgroup analysis by the encounter type indicated that the data was 91.0% complete for outpatient encounter and 93.2% complete for inpatient encounter.

conclusionThe study findings indicate that the completeness of the data varies by the desired types of data. EHRs can be a potentially great resource to conduct research to assess medication use. Further studies focusing on the content and completeness of EHRs for a specific patient population and evaluate other dimensions of EHRs data quality are needed.

Indexed as

CompletenessElectronic Health RecordsMedicationSecondary data

Identifiers

PMID31061618
PMCPMC6488812

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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.