Evidence map›Paper›PMID 41917698›Full record

ArticleEndocrinology, diabetes & metabolism2026

Lost in Transcription: Frequency of Inaccurate Manually Documented Point-of-Care Blood Glucose and Ketone Measures in Hospital.

Ali Hazara, Rahul D Barmanray, Ray Wang, Mervyn Kyi, Spiros Fourlanos

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Article in Endocrinology, diabetes & metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ali HazaraDepartment of Diabetes and Endocrinology, The Royal Melbourne Hospital, Melbourne, Australia.ORCID https://orcid.org/0009-0001-9053-5142
Rahul D BarmanrayDepartment of Diabetes and Endocrinology, The Royal Melbourne Hospital, Melbourne, Australia.
Ray WangDepartment of Diabetes and Endocrinology, The Royal Melbourne Hospital, Melbourne, Australia.
Mervyn KyiDepartment of Diabetes and Endocrinology, The Royal Melbourne Hospital, Melbourne, Australia.ORCID https://orcid.org/0000-0002-4341-8250
Spiros FourlanosDepartment of Diabetes and Endocrinology, The Royal Melbourne Hospital, Melbourne, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOptimal inpatient diabetes management requires accurate blood glucose (BG) and ketone (BK) documentation. In 2019, Royal Melbourne Hospital implemented hospital-wide networked blood glucose monitoring (NBGM) (NovaBiomed StatStrip), which automatically uploads BG/BK values to point-of-care device software (Bioconnect). Until electronic health record (EHR) implementation in 2020, nurses manually recorded BG/BK data into paper-records, enabling blinded gold-standard accuracy assessment by digital software. This study evaluated the accuracy and potential clinical significance of inaccurate manual POC BG/BK values compared with NBGM records.

methodsDINGO POC, a sub-analysis of the Diabetes IN-hospital: Glucose and Outcomes (DINGO) study, audited paper-based glucose charts against NBGM-uploaded BG/BK values and BG time-stamps to identify manual transcription inaccuracies. Discrepancy rates, magnitude and potential clinical significance were analysed.

results4391 BG and 378 BK NBGM measures from 250 admissions over a two-month period were assessed. Of BG measures, 325 (7.4%) were not recorded in patient charts and 558 (13%) were inaccurate. 302 (54%) inaccurate BGs had potentially clinically significant discrepancies (≥ 0.4 mmol/L). 1570 (36%) BG time-stamps were recorded inaccurately, and 329 (7.5%) were not recorded. 524 (33%) inaccurate BG time-stamps had discrepancies > 15 min. Of BK measures, 153 (41%) were not recorded and 18 (8%) were transcribed inaccurately. Inaccuracy rates were similar across wards and patient groups.

conclusionManual transcription of POC BG/BK values and time-stamps, evaluated against blinded concurrent gold-standard digital software, was often inaccurate with potential for clinical harm. Implementation of hospital-wide NBGM systems with automated POC BG/BK upload to EHRs may mitigate manual transcription errors.

Indexed as

Blood GlucoseDiabetes MellitusDocumentationKetonesPoint-of-Care SystemsElectronic Health RecordsHumansBlood GlucoseKetonesglucoseketonemanual transcriptionpoint‐of‐care

Identifiers

PMID41917698
PMCPMC13580776

What Socratic holds

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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 Socratic graph.