Evidence map›Paper›PMID 21303641›Full record

ReviewJournal of diabetes science and technology2011

Blood glucose testing in the hospital: error sources and risk management.

James H Nichols

Abstract readEvaluation StudyReview
In one paragraph

Review in Journal of diabetes science and technology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

  1. Pooled it
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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

1 author.

James H NicholsTufts University School of Medicine Boston, Massachusetts, USA. james.nichols@baystatehealth.org

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glucose testing in the hospital with point-of-care devices presents multiple opportunities for error. Any device can fail under the right conditions. For glucose monitoring in the hospital, with thousands of operators, hundreds of devices, and dozens of locations involved, there is ample opportunity for errors that can impact the quality of test results. Errors can occur in any phase of the testing process: preanalytic, analytic, or postanalytic. Common sources of meter error include patient or methodology interferences, operator mistakes, environmental exposure, and device malfunction. Early models of glucose meters had few internal checks or capability to warn the operator of meter problems. The latest generation of glucose monitors has a number of internal checks and controls engineered into the testing process to prevent serious errors or warn the operator by suppressing test results. Some of these control processes are built into the software and data management system of the meters, others require the hospital to do something, such as regularly clean the meter or analyze control samples of known glucose concentration, to verify meter performance. Hospitals need to be aware of the potential for errors by understanding weaknesses in the testing process that could lead to erroneous results and take steps to prevent errors from occurring or to minimize the harm to patients when errors do occur. The reliability of a glucose result will depend on the balance of internal control features available from manufacturers in conjunction with the liquid control analysis and other control processes (operator training, device validation, and maintenance) utilized by the hospitals.

Indexed as

HospitalsResearch DesignBlood GlucoseClinical Laboratory TechniquesHumansMedical StaffMonitoring, PhysiologicPatientsRisk ManagementBlood Glucose

Identifiers

PMID21303641
PMCPMC3045236

What OpenQuestion holds

Textmetadata
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.