Evidence map›Paper›PMID 34245558›Full record

ArticleJMIR medical informatics2021

Classification of Electronic Health Record-Related Patient Safety Incidents: Development and Validation Study.

Sari Palojoki, Kaija Saranto, Elina Reponen, Noora Skants, Anne Vakkuri, Riikka Vuokko

Abstract read
In one paragraph

Article in JMIR medical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 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

6 authors.

Sari Palojoki *Department of Steering of Healthcare and Social Welfare, Ministry of Social Affairs and Health, Helsinki, Finland.ORCID https://orcid.org/0000-0003-3047-9713
Kaija Saranto *Faculty of Social Sciences and Business Studies, University of Eastern Finland, Kuopio, Finland.ORCID https://orcid.org/0000-0002-3195-1955
Elina Reponen *Department of Anesthesiology, Intensive Care and Pain Medicine, Peijas Hospital, Helsinki University Hospital, Vantaa, Finland.ORCID https://orcid.org/0000-0003-2974-9683
Noora Skants *Department of Anesthesiology, Intensive Care and Pain Medicine, Peijas Hospital, Helsinki University Hospital, Vantaa, Finland.ORCID https://orcid.org/0000-0002-1470-4397
Anne Vakkuri *Department of Anesthesiology, Intensive Care and Pain Medicine, Peijas Hospital, Helsinki University Hospital, Vantaa, Finland.ORCID https://orcid.org/0000-0003-4708-1779
Riikka Vuokko *Department of Steering of Healthcare and Social Welfare, Ministry of Social Affairs and Health, Helsinki, Finland.ORCID https://orcid.org/0000-0003-3495-2336

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt is assumed that the implementation of health information technology introduces new vulnerabilities within a complex sociotechnical health care system, but no international consensus exists on a standardized format for enhancing the collection, analysis, and interpretation of technology-induced errors.

objectiveThis study aims to develop a classification for patient safety incident reporting associated with the use of mature electronic health records (EHRs). It also aims to validate the classification by using a data set of incidents during a 6-month period immediately after the implementation of a new EHR system.

methodsThe starting point of the classification development was the Finnish Technology-Induced Error Risk Assessment Scale tool, based on research on commonly recognized error types. A multiprofessional research team used iterative tests on consensus building to develop a classification system. The final classification, with preliminary descriptions of classes, was validated by applying it to analyze EHR-related error incidents (n=428) during the implementation phase of a new EHR system and also to evaluate this classification's characteristics and applicability for reporting incidents. Interrater agreement was applied.

resultsThe number of EHR-related patient safety incidents during the implementation period (n=501) was five-fold when compared with the preimplementation period (n=82). The literature identified new error types that were added to the emerging classification. Error types were adapted iteratively after several test rounds to develop a classification for reporting patient safety incidents in the clinical use of a high-maturity EHR system. Of the 427 classified patient safety incidents, interface problems accounted for 96 (22.5%) incident reports, usability problems for 73 (17.1%), documentation problems for 60 (14.1%), and clinical workflow problems for 33 (7.7%). Altogether, 20.8% (89/427) of reports were related to medication section problems, and downtime problems were rare (n=8). During the classification work, 14.8% (74/501) of reports of the original sample were rejected because of insufficient information, even though the reports were deemed to be related to EHRs. The interrater agreement during the blinded review was 97.7%.

conclusionsThis study presents a new classification for EHR-related patient safety incidents applicable to mature EHRs. The number of EHR-related patient safety incidents during the implementation period may reflect patient safety challenges during the implementation of a new type of high-maturity EHR system. The results indicate that the types of errors previously identified in the literature change with the EHR development cycle.

Indexed as

classificationelectronic health recordshospitalsmedical informaticspatient safetyrisk

Identifiers

PMID34245558
PMCPMC8441612

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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.