Evidence map›Paper›PMID 10641963›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA

Assessing the quality of clinical data in a computer-based record for calculating the pneumonia severity index.

D Aronsky, P J Haug

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 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

33 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. Do N-terminal pro-brain natriuretic peptide levels determine the prognosis of community acquired pneumonia?Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia · 2019
    Article
  9. Article
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  11. A Review of Data Quality Assessment in Emergency Medical Services.The open medical informatics journal · 2018
    Review
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  17. Computerization of Mental Health Integration complexity scores at Intermountain Healthcare.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

D AronskyDepartment of Medical Informatics, LDS Hospital, University of Utah, Salt Lake City 84143, USA. lddarons@ihc.com
P J Haug

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study examined whether clinical data routinely available in a computerized patient record (CPR) can be used to drive a complex guideline that supports physicians in real time and at the point of care in assessing the risk of mortality for patients with community-acquired pneumonia.

settingEmergency department of a tertiary-care hospital.

designRetrospective analysis with medical chart review. PATIENTS: All 241 inpatients during a 17-month period (Jun 1995 to Nov 1996) who presented to the emergency department and had a primary discharge diagnosis of community-acquired pneumonia. METHODS/

main outcome measuresThe 20 guideline variables were extracted from the CPR (HELP System) and the paper chart. The risk score and the risk class of the Pneumonia Severity Index were computed using data from the CPR alone and from a reference standard of all data available in the paper chart and the CPR at the time of the emergency department encounters. Availability and concordance were quantified to determine data quality. The type and cause of errors were analyzed depending on the source and format of the clinical variables.

resultsOf the 20 guideline variables, 12 variables were required to be present for every computer-charted emergency department patient, seven variables were required for selected patients only, and one variable was not typically available in the HELP System during a patient's encounter. The risk class was identical for 86.7 percent of the patients. The majority of patients with different risk classes were assigned too low a risk class. The risk scores were identical for 72.1 percent of the patients. The average availability was 0.99 for the data elements that were required to be present and 0.79 for the data elements that were not required to be present. The average concordance was 0.98 when all a patient's variables were taken into account. The cause of error was attributed to the nurse charting in 77 percent of the cases and to the computerized evaluation in 23 percent. The type of error originated from the free-text fields in 64 percent, from coded fields in 21 percent, from vital signs in 14 percent, and from laboratory results in 1 percent.

conclusionFrom a clinical perspective, the current level of data quality in the HELP System supports the automation and the prospective evaluation of the Pneumonia Severity Index as a computerized decision support tool.

Indexed as

Decision Making, Computer-AssistedDecision Support Systems, ClinicalMedical Records Systems, ComputerizedSeverity of Illness IndexAlgorithmsCommunity-Acquired InfectionsEmergency Service, HospitalFemaleHumansMalePneumoniaPoint-of-Care SystemsPractice Guidelines as TopicPrognosisRetrospective StudiesRisk

Identifiers

PMID10641963
PMCPMC61455

What OpenQuestion holds

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Registered trials

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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.