Evidence map›Paper›PMID 29945862›Full record

ArticleJMIR medical informatics2018

Nurses' Experience With Health Information Technology: Longitudinal Qualitative Study.

Inga M Zadvinskis, Jessica Garvey Smith, Po-Yin Yen

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Article in JMIR medical informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
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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

25 citing papers in PubMed, 1 synthesis or guideline 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

3 authors.

Inga M ZadvinskisRiverside Methodist Hospital, OhioHealth, Columbus, OH, United States.ORCID http://orcid.org/0000-0001-9504-1056
Jessica Garvey SmithDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, United States.ORCID http://orcid.org/0000-0002-9420-5327
Po-Yin YenDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, United States.ORCID http://orcid.org/0000-0002-7061-4185

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNurses are the largest group of health information technology (HIT) users. As such, nurses' adaptations are critical for HIT implementation success. However, longitudinal approaches to understanding nurses' perceptions of HIT remain underexplored. Previous studies of nurses' perceptions demonstrate that the progress and timing for acceptance of and adaptation to HIT varies.

objectiveThis study aimed to explore nurses' experience regarding implementation of HIT over time.

methodsA phenomenological approach was used for this longitudinal qualitative study to explore nurses' perceptions of HIT implementation over time, focusing on three time points (rounds) at 3, 9, and 18 months after implementation of electronic health records and bar code medication administration. The purposive sample was comprised of clinical nurses who worked on a medical-surgical unit in an academic center.

resultsMajor findings were categorized into 7 main themes with 54 subthemes. Nurses reported personal-level and organizational-level factors that facilitated HIT adaptation. We also generated network graphs to illustrate the occurrence of themes. Thematic interconnectivity differed due to nurses' concerns and satisfaction at different time points. Equipment and workflow were the most frequent themes across all three rounds. Nurses were the most dissatisfied approximately 9 months after HIT implementation. Eighteen months after HIT implementation, nurses' perceptions appeared more balanced.

conclusionsIt is recommended that organizations invest in equipment (ie, wireless barcode scanners), refine policies to reflect nursing practice, and improve systems to focus on patient safety. Future research is necessary to confirm patterns of nurses' adaptation to HIT in other samples.

Indexed as

adaptationbarcode medication administrationelectronic health recordhealth ITqualitative research

Identifiers

PMID29945862
PMCPMC6043728

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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.